Prospective Memory in Depression: Review of an Emerging Field

Prospective Memory in Depression: Review of an Emerging Field Abstract Depressive disorders have been linked to a variety of neuropsychological deficits, including in the areas of processing speed, memory, and executive functioning. These neurocognitive disturbances may contribute to the impairments in daily functioning often experienced by those suffering with depression. Prospective memory (PM), which refers to remembering to execute a previously formed intention at some point in the future, has been shown to play a critical role in daily functioning and may be particularly relevant in the context of depression. In this review, we synthesize the literature on PM and its relation to depression. We also put forth a new five-phase model of PM through which we frame our discussion of the existing literature on PM and depression. The results of this review reveal that PM deficits emerge in those tasks that place the greatest demands on executive functioning (e.g., monitoring for a PM cue, maintaining an intention over a delay). We conclude the review by highlighting the potential clinical relevance of these findings and proposing directions for future research. Depression, Learning and memory, Executive functions, Everyday functioning, Rehabilitation Introduction Clinically significant depression is a common mental health concern, with epidemiological estimates suggesting that 20% of the U.S. population will experience major depressive disorder at some point in their lifetime (Kessler & Wang, 2009). In addition to encompassing emotional and behavioral symptoms, depression is also often associated with significant impairments of daily functioning, adversely affecting quality of life. Neurocognitive disturbance may serve as a significant source of functional impairment in individuals suffering with depression, as depression is associated with deficits in processing speed, memory, and executive function (McDermott & Ebmeier, 2009). Such deficits have been shown to contribute to both psychosocial impairment (McIntyre et al., 2013) and poor long-term functional outcome (Jaeger, Berns, Uzelac, & Davis-Conway, 2006). Memory deficits may be a particularly important precipitant of functional impairment in depression. Memory functioning may be categorized into retrospective memory (the ability to recall information from the past) and prospective memory (PM: the ability to carry out previously formed intentions in the future). Although functional impairment is commonly thought of in reference to retrospective memory, PM is also particularly relevant to daily functioning (Smits, Deeg, & Jonker, 1997; Vedhara et al., 2004), adversely affecting activities ranging from maintaining relationships to remaining compliant with medication and non-pharmacological treatment regimens (e.g., difficulties completing homework assigned as part of psychosocial interventions). A number of depression-related deficits in retrospective memory have been documented (Gotlib & Joorman, 2010); however, less is known about PM deficits and depression. A recently emerging body of literature indicates that individuals experiencing depression may be less likely to successfully execute PM tasks. The goals of the present review are to synthesize the growing body of research into the associations of depression with PM, to interpret those findings in the context of a newly proposed model of PM, to highlight potential clinical applications of published findings, and to identify directions for future research. Neuropsychology of Depressive Disorders Depressive disorders have been associated with structural and functional brain abnormalities, including volumetric reductions in the prefrontal cortex (Bremner et al., 2002), hippocampus (Hickie et al., 2005), and cingulate cortex (Davidson, Pizzagalli, Nitschke, & Putnam, 2002). Additionally, clinically significant depression and depressive symptoms have been associated with abnormalities in several neurotransmitter systems, including seretonergic, dopaminergic, and cholinergic systems (Drevets, Price, & Furey, 2008). Such neural abnormalities are in turn purported to be associated with neuropsychological deficits in individuals diagnosed with depression. Although depression is associated with a wide range of deficits including attention (e.g., Cohen, Lohr, Paul, & Boland, 2001; Lampe, Sitskoorn, & Heeren, 2004), and retrospective memory (Burt, Zembar, & Niederehe, 1995; Simons et al., 2009; Vythilingham, et al., 2004), depression-related executive deficits (Austin, Mitchell, & Goodwin, 2001; Castaneda, Tuulio-Henriksson, Marttunen, Suvisaari, & Lönnqvist, 2008), as described in subsequent sections, may be particularly germane to PM. For example, consistent with reports of prefrontal cortex dysfunction in imaging studies among individuals with depressive disorders (Bremner et al., 2002), impairments associated with depression have been identified in planning and problem-solving (Andersson, Lövdahl, & Malt, 2010; Naismith et al., 2003), working memory (Gotlib & Joorman, 2010; Harvey et al. 2004; Rose & Ebmeier, 2006), inhibition (Gohier et al., 2009; Joorman, 2010), and task-switching (Lo & Allen, 2011; Murphy, Michael, & Sahakian, 2012). Furthermore, mood-related impairments are often most prominent on tasks that require more effortful engagement (Austin et al. 2001; Hammar, Isaksen, Schmid, Årdal & Strand, 2011), self-initiation (Hertel, 1997), or strategic cognitive control (Henry & Crawford, 2005; Langenecker et al., 2005). Finally, an emerging area of research has linked depression with reduced ability to simulate or imagine future events (Holmes, Lange, Moulds, & Steele, 2008; King, MacDougall, Ferris, Herdman, & McKinnon, 2011), which engages a number of cognitive processes reliant upon the prefrontal cortex in addition to medial temporal lobe structures (Hach, Tippet, & Addis, 2014). Together, the executive functioning deficits observed in depression implicate a distributed “executive control system” involving frontal and parietal regions of the brain. Neuropsychology of PM Successful PM performance depends upon distributed networks that include prefrontal cortices, the hippocampal complex, parietal regions, and subcortical structures. Several imaging studies have identified prefrontal regions, especially BA 10, as critically involved in successful PM (Burgess, Quayle, & Frith, 2001; Burgess, Scott, & Frith, 2003; Costa et al., 2011; Simons, Scholvinck, Gilbert, Frith, & Burgess, 2006). More recently, McDaniel, LaMontagne, Beck, Scullin, and Braver (2013) revealed that successful PM can be achieved via sustained attention or “top-down” control reliant upon a dorsal frontoparietal network, including anterior prefrontal cortex (e.g., BA 10), or by transient “bottom-up” processing that relies upon ventral parietal and cingulo-opercular regions. Similarly, Cona, Bisiacchi, and Moscovitch (2014) revealed sustained frontoparietal activation related to ongoing monitoring in a PM task. In line with the structures and regions involved, PM depends upon intact retrospective memory (i.e., failure to recall an intention will result in PM failure), along with cognitive processes that depend upon intact executive functioning (Fuster, 1997, 2008; Stuss & Benson, 1984). Although retrospective memory contributes to successful PM, the majority of PM studies have focused on the role of executive processes in PM, with several behavioral studies revealing relations between deficits in executive functioning and impaired PM performance (Burgess, Veitch, de Lacy Costello, & Shallice, 2000; McDaniel, Glisky, Rubin, Guynn, & Routhieaux, 1999; McFarland & Glisky, 2009). Specifically, poor PM has been linked to impaired planning, (Shum, Cahill, Hohaus, O’Gorman, & Chan, 2013), working memory (Arnold, Bayen, & Smith, 2015; Rose, Rendell, McDaniel, Aberle, & Kliegel, 2010), and inhibition and task switching (Schnitzspahn, Stahl, Zeintl, Kaller, & Kliegel, 2013). PM deficits, therefore, could be anticipated in the context of depression given the shared neuroanatomical structures and neuropsychological processes that have been implicated in depression and that provide for successful PM. Additionally, PM is inherently a future-oriented form of memory and is dependent upon more general prospection abilities, which are often affected in the context of depression (Roepke & Seligman, 2016). Measuring PM To understand the relations between depression and PM, it is first necessary to be familiar with the paradigms that assess PM. PM tasks are frequently of two kinds: event-based and time-based. An example of an event-based task in daily life is remembering to send an email when arriving at your desk, in which case the desk serves as an environmental cue or event to signal the appropriateness of sending the email. An example from daily life of a time-based task is remembering to leave a seminar at 1:45 p.m. so that you can arrive at a 2:00 p.m. meeting on time. In this scenario, there is no environmental cue or event, but rather the arrival of a particular time serves as the impetus for action. To simulate everyday PM tasks, studies of PM typically incorporate an ongoing task (e.g., answering trivia questions), which is intended to capture the cognitive demands and goal-directed behavior of everyday life, and within this ongoing activity a PM task with a separate, embedded goal (e.g., press the “6” key whenever a word belonging to the category “animal” appears). Prior PM investigations have identified factors that influence PM task difficulty. Critical factors include the nature of the PM task itself and the circumstances under which the task can be completed. Both event-and time-based PM tasks frequently place greater demands on self-initiated processing than do tasks of retrospective memory. For example, unlike retrospective memory tasks in which participants are explicitly asked to recall previously learned information, PM tasks provide no such support. Instead, participants must on their own recall or recognize a PM cue without any prompting, disengage from an ongoing task, and execute the previously formed intention. Furthermore, time-based tasks require participants to monitor the passage of time, which is typically unrelated to the execution of ongoing activity (e.g. monitoring the clock on the back wall of the classroom is not directly related to an ongoing goal of attending to a lecture), and therefore requires greater self-initiated processing than event-based tasks (Einstein, McDaniel, Richardson, Guynn, & Cunfer, 1995). A second factor affecting PM performance pertains to the “focality” of the cue in an event-based task. “Focality” refers to the degree to which the ongoing activity fosters processing of the environmental cue as it was processed at the time the intention was formed. An example of a focal PM task would be if your commute home required you to pass the bakery, a prominent landmark at the end of your street. The site of the bakery would remind you to stop and get cinnamon bread for making French toast that weekend. In contrast, the presence of a new construction project that required traffic to converge to a single lane would demand your attention the first time you encountered it. In this scenario, the bakery (and other typically focal landmarks at the intersection) would no longer be a focal cue, but rather becomes non-focal, despite the fact that you still drive past it. Laboratory investigations of focal cues often rely on a lexical decision task in which the respondent must execute an intention when a particular word is encountered (e.g., “animal”). In contrast, a non-focal PM task may require respondents to execute an intention when a particular syllable appears in a lexical decision task (e.g., “pel”). It has been argued that focal cues promote relatively automatic identification of cues, without need for the type of controlled monitoring processes required in non-focal PM tasks (Brewer, Knight, Marsh, & Unsworth, 2010; McDaniel & Einstein, 2000, 2007; Scullin, McDaniel, & Einstein, 2010). In other words, focal cues simply “pop out” and may remind you to follow through with a delayed plan, whereas non-focal cues do not. Therefore, the type of PM task (i.e., event- vs. time-based) and the nature of cues (focal vs. non-focal) are important considerations when considering the conditions under which PM failure may occur, as well as the populations that are likely to experience greater difficulty with such tasks. Five-Phase Model of PM To clarify the cognitive mechanisms that underlie successful PM, we propose a five-phase model of PM (see also Ellis, 1996; Kliegel, Martin, McDaniel, & Einstein, 2002 for alternative models). The model reflects the view that numerous cognitive processes are required for successful PM and that those processes may contribute to PM in at least one of five phases of task execution. Our model of PM (Fig. 1) includes the following five phases: development, maintenance/monitoring, retrieval, inhibition, and execution. Our five-phase model of PM is similar to that of Kliegel and colleagues (2002) in that it emphasizes the coordination of multiple cognitive processes in the execution of PM tasks, including forming an intention, retaining the intention over a delay interval, retrieving the intention at the appropriate time, and executing the intention. However, our model also highlights the role of additional cognitive processes (e.g., monitoring, inhibition, switching), without which PM task completion is less likely to occur. Additionally, this model specifies the neural correlates of the individual cognitive processes that underlie PM (e.g., frontal–parietal cognitive control network vs. medial temporal lobe involvement). By specifying the full range of cognitive processes that may support successful PM and delineating breakdowns that may lead to PM failure, we hope that this model will be an effective tool for developing targeted interventions aimed at improving PM. The proposed model will be applied to depression in the current paper; however, it can be applied to a wide range of clinical populations and presentations. Fig. 1. View largeDownload slide Executive control system. Fig. 1. View largeDownload slide Executive control system. Each phase of the model places differing demands on the medial temporal lobe (MTL) declarative memory system, which includes the hippocampal formation along with entorhinal, perirhinal, and parahippocampal cortices, and on a frontoparietal executive control system. In the first phase, the development phase, the executive control system is critical to developing an intention and devising a plan for completing that intention. Of note, intention formation and planning are not synonymous (i.e., it is possible to develop an intention without developing a plan to execute that intention.). Though the development phase relies to some extent on retrospective memory (e.g., to recall or know what needs to be done and to recognize or recall a future situation in which an intention could be executed), planning how and when to execute an intention (e.g., how can I remember to send the rent check tomorrow?) likely plays the most critical role during this phase. While planning to execute a task, an associative link between the intention and a future cue may be created by the MTL system. The strength of this associative link will influence the degree to which MTL or frontoparietal executive control processes are required in later phases. In the maintenance/monitoring phase, the processing burden may be more equally shared between MTL and frontoparietal executive control. In this phase, relevant cues must be retained by the MTL system while one is engaged in an ongoing, unrelated activity. Depending on a number of factors, including individual and task characteristics, the allocation of attentional resources may also be critical in this phase (Smith, 2003, 2010; but see, Einstein et al., 2005; McDaniel & Einstein, 2000). For instance, the frontoparietal executive control system may be engaged in rehearsing the intention and monitoring the environment for intention–relevant cues while one continues to devote cognitive resources to the current, ongoing task. The retrieval phase is heavily dependent upon the MTL system, which provides for recognition of a cue (e.g., the correct situation or time) and the spontaneous retrieval of the intention in the appropriate context. The frontoparietal executive control system may also be implicated in this phase, depending upon the strength of the associative link between cue and intention that was previously established by the MTL system. That is, a strong link established by the MTL system would obviate the need for the frontoparietal executive control system to be engaged, as the intention would “pop into mind” when the intention–relevant cue is encountered. Alternatively, if the PM cue or context is recognized, but the intention is not spontaneously retrieved due to a weak associative link between intention and cue, the frontoparietal executive control system will be recruited as one engages in an effortful, perhaps strategic, search for the related intention. Once the cue and intention are recognized and retrieved (either spontaneously or strategically), one must disengage from the ongoing activity to execute the PM task. The inhibition phase is driven entirely by the frontoparietal executive control system, which allows for inhibition of, or disengagement from, the ongoing activity. Finally, in the execution phase, the ongoing task has already been successfully inhibited and attentional resources must now be allocated to the PM task. Thus, the frontoparietal executive control system is called upon to switch from the ongoing task and initiate the actions necessary to complete the PM task. Impairments of processes involved in one or more of the five phases of the model can be anticipated in a host of clinical populations in which neuropsychological deficits are known to occur. The likelihood that PM impairments emerge will depend upon a combination of factors, including those associated with age (e.g., reduced working memory), and type and degree of severity of illness or disease (e.g., Parkinson's disease). Additional factors include those that are specific to the ongoing and PM tasks, such as ongoing task difficulty, cue type (event- or time-based), cue focality (focal or non-focal), and perceived importance of the PM task. The specific phase in which a breakdown occurs that leads to PM failure will often depend on an interaction between these person-specific and task-specific characteristics. Review Methods To identify relevant articles, PsychInfo, PubMed, and Web of Science databases were searched using a combination of the following terms: “mood,” “depression,” “depressive,” “sad,” “dysphoria,” “anhedonia,” “dysthymia,” “adjustment disorder with depressed mood,” “prospective memory,” and “delayed intention,” along with the names of prospective memory tests, including “MIST,” “RBMT,” “CAMPROMPT,” and “Virtual Week.” Additionally, we reviewed the bibliography of articles identified through those searches for other, related work. In the current review, because this area of research is relatively new we include clinically diagnosed depression, sub-threshold depressive symptomatology, and experimentally induced sad mood in our conceptualization of depressive disorders. PM in Depressive Disorders To date, 19 studies have been published that were designed to examine associations between depressive symptoms and PM performance. Eleven of those papers have been published in the last 5 years, reflecting the growing interest in this area of PM research. The eighteen published studies differed methodologically in several ways. Five studies investigated time-based PM (Jeong & Cranney, 2009; Kliegel et al., 2005; Li, Weinborn, Loft, & Maybery, 2014; Rude, Hertel, Jarrold, Covich, & Hedlund, 1999; Schnitzspahn et al., 2013) and four others investigated both time- and event-based PM (Albiński, Kliegel, Sędek, & Kleszczewska-Albiński, 2012; Griffiths et al., 2012; Lee et al., 2010; Li, Weinborn, Loft, & Maybery, 2013). The remaining 10 studies investigated event-based PM only. Only one study employed a naturalistic (i.e., non-laboratory) paradigm (Jeong & Cranney, 2009). In the following section, we describe the results of event-based PM studies, followed by those of time-based PM. Within both the event-based and time-based sections, studies are organized into those that included clinical samples, those with non-clinical samples, and finally mood induction studies with non-clinical samples. For the purposes of this review, our definition of clinical samples includes individuals receiving inpatient treatment for depression and/or individuals who reported moderate or severe levels of depressive symptoms on self-report measures (e.g., BDI-II > 20). Non-clinical samples include participants with mild self-reported depressive symptoms (e.g., BDI-II < 20). Please refer to Table 1 for full participant and task details of each study. Table 2 lists studies based upon their relevance to our five-phase model of PM. Table 1. Summary of PM studies in depression with sample, methodology, and results Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Note: DASS-21 = Depression Anxiety Stress Scales 21 (Lovibond & Lovibond, 1995); SCID = Structured Clinical Interview for DSM-III-R (Spitzer, Williams, & Gibbon, 1987); BDI = Beck Depression Inventory (Beck & Steer, 1987); CPRS = Comprehensive Psychopathological Rating Scale (Åsberg, Montgomery, Perris, Schalling, & Sedval, 1978); OCI = Obsessive-Compulsive Inventory; HAM-D = Hamilton Depression Rating Scale (Hamilton, 1960); GDS = Geriatric Depression Scale (Yesavage et al., 1983); SAMI = Self-Assessment Manikin Inventory (Bradley & Lang, 1994); HADS = Hospital Anxiety and Depression Scale (Zigmond and Snaith, 1983). Table 1. Summary of PM studies in depression with sample, methodology, and results Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Note: DASS-21 = Depression Anxiety Stress Scales 21 (Lovibond & Lovibond, 1995); SCID = Structured Clinical Interview for DSM-III-R (Spitzer, Williams, & Gibbon, 1987); BDI = Beck Depression Inventory (Beck & Steer, 1987); CPRS = Comprehensive Psychopathological Rating Scale (Åsberg, Montgomery, Perris, Schalling, & Sedval, 1978); OCI = Obsessive-Compulsive Inventory; HAM-D = Hamilton Depression Rating Scale (Hamilton, 1960); GDS = Geriatric Depression Scale (Yesavage et al., 1983); SAMI = Self-Assessment Manikin Inventory (Bradley & Lang, 1994); HADS = Hospital Anxiety and Depression Scale (Zigmond and Snaith, 1983). Table 2. Summary of depression-related deficits in PM in relation to the five-phase model Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Table 2. Summary of depression-related deficits in PM in relation to the five-phase model Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Event-based PM Clinical Samples The first four studies in this section investigated aspects of self-initiated processing and attentional control and its relation to PM in the context of depression. These studies are followed by the only study to have used a standardized clinical neuropsychological measure in the investigation of event-based PM. In the first investigation of event-based PM among clinically depressed participants, Altgassen, Kliegel, and Martin (2009) compared the performance of depressed with non-depressed older adults and manipulated the demand placed on self-initiated processing by including half focal and half non-focal cues. As hypothesized, all participants performed more accurately on focal than on non-focal trials, and non-depressed participants outperformed depressed participants. Importantly, there was a group by focality interaction, such that relative to non-depressed participants, depressed participants performed less proficiently only on non-focal tasks. Although no group differences emerged in neuropsychological tasks of short-term memory, working memory, and inhibition, findings indicated that the depressed group was slower to respond to ongoing task trials than the non-depressed group. There exist three possible explanations for the longer reaction times of the depressed group. First, depressed participants may have found the ongoing task more difficult than non-depressed participants and thus, responded more slowly. This hypothesis is unlikely to explain the group differences, however, given the easy nature of the ongoing task (i.e., deciding which of two words contains more vowels) and the equivalent accuracy in performance between groups on the ongoing task. Alternatively, the longer reaction times of the depressed group may have been driven by slower information processing speed, which often accompanies depressive states (Snyder, 2013). However, that there were no group differences in inhibition renders this possibility less convincing as well, as a processing speed deficit would have been expected to also negatively affect performance on the inhibition task. The most plausible account of the group differences in non-focal PM performance pertains instead to monitoring abilities and suggests a breakdown in the maintenance/monitoring phase of the model. Reaction times to ongoing task trials are often thought to reflect monitoring activity for the presence or occurrence of a PM cue, as maintaining a PM intention frequently entails a cost in the form of slower reaction times in the performance of the ongoing task. Although group differences in the cost associated with the non-focal PM task (i.e., longer reaction times in the ongoing task) did not reach significance, the depressed group exhibited a numerical tendency towards less cost. This pattern suggests that the depressed group experienced difficulty maintaining active monitoring, which resulted in the completion of fewer PM tasks relative to the non-depressed group. Based on the study of Altgassen and colleagues (2009), which implicated deficient self-initiated processing in the reduced PM performance of depressed participants, Altgassen, Henry, Bürgler, and Kliegel (2011) sought to further examine the role of self-initiated processing by including salient, emotional PM cues. Thus, they examined the relations between emotional cue valence and PM in depressed and non-depressed individuals. Target words varied in emotional valence and consisted of three positive (love, beauty, happiness), three negative (sadness, tiredness, sorrow), and three neutral words (apple, rabbit, surfboard). Results indicated that non-depressed participants executed more PM intentions than depressed participants. However, group differences were only observed for positively–valenced target words, for which non-depressed participants demonstrated enhanced performance relative to other word types. These findings suggest that for non-depressed participants, positive valence increased the salience of target words resulting in improved PM. On the other hand, for depressed participants emotionally–valenced items were no more salient than neutral items, and therefore did not reduce self-initiated processing demands. Although accuracy of ongoing task performance did not differ between groups, reaction time data were not reported, limiting the conclusions regarding monitoring behavior. Overall, these results lend partial support to a mood congruence effect in PM (Eich, Macauley, & Ryan, 1994), in that the absence of a positivity effect could be interpreted as congruent with anhedonic aspects of depression. However, the lack of an effect of negative words among depressed participants was somewhat surprising. Following up on the two studies by Altgassen and colleagues, Chen, Zhou, Cui, and Chen (2013) used behavioral and eye tracking measures to examine the relation between depressive symptoms and the attentional control required to strategically monitor the environment for PM cues. Participants were individuals seeking treatment for depression in the psychology division of a hospital. The ongoing task consisted of a visual search task during which a single “target” word was displayed (e.g., “balloon”), followed immediately by four line drawings of objects. Participants were instructed to press the “1” key if a target word was depicted among the four objects, and the “2” if it was not present. Focal PM cues, to which participants were to press the “3”, were images of fruit (e.g., grapes) and appeared as one of the four line drawings on eight occasions. Half of the PM cues were presented with target images and half were presented without target images, with the goal of assessing participants’ ability to shift attention from the ongoing task to the PM task. Results revealed a main effect of depression on PM performance, as non-depressed participants outperformed depressed participants in both accuracy and reaction time. Additionally, the depressed participants completed fewer PM tasks in the target-plus-cue condition than in the cue-only condition. With regard to eye movement, depressed participants tended to fixate on targets and had difficulty shifting their attention (i.e., gaze) to PM cues. The authors interpreted the eye tracking data to suggest that depressed participants needed to exert greater cognitive control in the form of increased focused (rather than divided) attention to process the displays. Though these results imply decreased monitoring among depressed participants and suggest a breakdown in the maintenance/monitoring phase, the poorer performance of the depressed group on target-plus-cue trials also implicates the inhibition phase of the five-phase model and raises important questions regarding the role that inhibition and task-switching abilities may play in monitoring behavior and subsequent PM performance. In a subsequent investigation of the attentional control capacity of individuals with depression, Li, Loft, Weinborn, and Mayberry (2014) manipulated the perceived importance of an ongoing lexical decision task versus a PM task to see whether individuals with depression are capable of prioritizing attentional resources. When the ongoing task was emphasized as the more important task, there were no group differences in either PM or ongoing task performance, or in performance cost (i.e., reaction times to ongoing lexical decision task relative to a baseline condition), suggesting that participants with higher levels of depressive symptoms are capable of successfully completing a focal event-based task. When the importance of the PM task was stressed over the ongoing task, however, the PM performance of the low depressive symptoms group improved, whereas the performance of the high depressive symptoms group did not. Performance costs increased for both groups. The equivalent PM performance when the ongoing task was emphasized suggests that individuals with high levels of depressive symptoms may be capable of completing resource-demanding event-based tasks (e.g., high retrospective memory load). However, participants with relatively greater depressive symptoms were unable to benefit from the increased importance placed on the PM task, suggesting that they may have had difficulty allocating attentional resources in an efficient or consistent manner. These results are consistent with difficulties during the maintenance/monitoring phase. Lending some support for this idea, the high depressive symptom group reported experiencing greater distractibility during the task, which may have resulted in less persistent monitoring. Self-reported distractibility, however, was not significantly correlated with PM performance. Li and colleagues (2013) investigated the possibility that PM deficits in depression may vary as a function of cue type (event- vs. time-based). Whereas the studies reviewed thus far employed classic experimental laboratory tasks, used a clinical neuropsychological measure to investigate the relation between depression and event- and time-based PM among undergraduate students. The research version of the Memory for Intentions Screening Test (MIST; Raskin, Buckheit, & Sherrod, 2010) consists of four event-based tasks (e.g., “When I hand you a postcard, write the name of the city and country we are located in.”) and four time-based tasks (e.g., “In 15 minutes, use that paper to write down your age.”), occurring at delays of 2 and 15 min. Although there was no main effect of depression on event-based PM, a significant group × delay interval interaction was revealed, indicating that the performance difference between depressed and non-depressed participants was greater at 15-min delays than at 2-min delays. This finding suggests that as the delay interval increased from 2 to 15 min, depressed participants were less able to sustain the monitoring activity necessary for successful PM. Increasing a delay interval has been shown to exert negative effects on PM (Martin, Brown, & Hicks, 2011), but the exact mechanisms of this effect are unclear. One possible mechanism explaining the effect of delay in this study is that the 15-min delay interval required a level of sustained attention and monitoring that the depressed participants were not able to achieve. Although this interpretation would seem to fit given the non-focal nature of the event-based tasks, the highly salient nature of the cues in the MIST (e.g., “when I hand you a red pen, sign your name on your paper”) likely offset the self-initiated processing typically required in non-focal tasks and thereby reduced the need for active monitoring. Instead, the reduced event-based performance at the 15-min delay would seem to stem more from a retrospective memory failure, as suggested by the authors. That is, participants did not need to monitor the environment for the appearance of a red pen or a postcard, but did need to maintain and recall the associated intention or action. This pattern implicates the maintenance/monitoring phase and the retrieval phase and is consistent with imaging results in which medial temporal lobe activity has been shown to underlie performance on focal event-based tasks (Martin et al., 2007). Although the results of a recognition test conducted at the conclusion of the MIST revealed that depressed participants were just as likely as non-depressed to successfully recognize the PM tasks they were to complete, the possibility remains that they were unable to actively search for and freely recall the intention. In summary, studies that have included clinically depressed participants suggest that individuals with depression have difficulty on tasks that require self-initiated processing and implicate the maintenance/monitoring phase. Although not all of these studies have revealed deficits in event-based PM, they each suggest that individuals with depression are less able to allocate attentional resources in a manner that will facilitate PM performance. Non-clinical Samples Three studies have been conducted to investigate the relations between mild depressive symptoms and PM. Given findings that indicate that depression does not always result in cognitive deficits (and that depressive symptoms may reduce or enhance cognitive functioning depending on the severity of those symptoms (von Helversen, Wilke, Johnson, & Schmid, 2011)), Abliński and colleagues (2012) examined the possibility that mild depressive symptoms may in fact facilitate event- and time-based PM in younger and older adults. The results of the event-based task will be described here, whereas those of the time-based task will be reviewed in the Time-based PM section. The ongoing task required participants to complete a linear orders task, in which they had to learn relationships between three people (e.g., Mike is taller than Ben. Tom is taller than Mike) and answer true/false statements about those relationships. In the PM condition, participants were instructed to press the “Q” key whenever they encountered a word written in bold red font. Results revealed that younger adults executed more PM intentions than older adults. There was no main effect of mood or interactions between mood and age on PM performance. The failure to detect a significant association between depressive symptoms and focal PM performance is consistent with Altgassen and colleagues (2009). However, the comparable PM performance between mildly depressed and non-depressed in this study could have been a product of the highly salient PM cues (i.e., words printed in bold, red font), which would have fostered automatic processing and would not have required the type of self-initiated processing thought to occur in the maintenance/monitoring phase. This was particularly true for the younger adults for whom a ceiling effect emerged. To further investigate the role of strategic monitoring in an event-based task, Albiński, Sędek, and Kliegel (2012) used the linear orders task described previously. Participants were classified as “monitorers” and “non-monitorers” based on changes in reaction time between an ongoing task only condition and an ongoing task plus PM condition (i.e., PM performance cost). Results revealed that young and middle-aged adults outperformed older adults on the PM task. Additionally, “monitorers” outperformed “non-monitorers.” Although the relation between depressive symptoms and PM performance was not analyzed directly, results indicated that among young adults, greater depressive symptoms were associated with non-monitoring. These results implicate the maintenance/monitoring phase of the model. However, although performance cost is a widely accepted means of inferring monitoring activity, the possibility remains that increased reaction times in the presence of a PM task reflect something other than active monitoring. For example, it could simply reflect less efficient processing under dual task demands. Most recently, Arnold, Bayen, and Böhm (2015) used a multinomial processing approach designed to isolate the prospective and retrospective components of a PM task to determine which component might better account for any observed PM impairments associated with depression and anxiety among undergraduate students. In the ongoing task, participants were presented with four colored rectangles one at a time, followed by a colored word and were required to indicate whether the color of the word matched the color of either of the four rectangles that preceded it. The PM task required that participants press the space bar any time one of five previously studied words was presented. Results indicated that depressive symptoms were not significantly correlated with event-based PM performance. Anxiety symptoms, however, was significantly negatively correlated with PM performance. One major limitation of the results pertains to the sample. Although a relatively large sample was obtained (N = 129), scores on both the BDI-II and the HADS indicated mean depression levels in the mild range, with only 10 participants from the total sample endorsing symptoms consistent with moderate to severe depression. Thus, the results suggest that non-focal event-based PM performance can be unaffected in the context of mild depressive symptoms. However, no conclusions can be drawn regarding the relation between moderate or more severe depressive symptoms and PM. Although not a primary focus, additional studies have investigated the relations between depressive symptoms and event-based PM. Livner, Berger, Karlsson, and Bäckman (2008) reported no relation between depression and PM among older adults, but a negative relation between depression and retrospective memory. They concluded that any PM deficits among individuals with depression were likely related to the effects of depression on retrospective memory. Harris and Menzies (1999) also found no relation between depression and PM among undergraduates. Instead, the results of a regression analysis revealed that PM was uniquely associated with anxiety. In a study of sub-clinical obsessive-compulsive symptoms and PM, Marsh and colleagues (2009) found that participants with mild depressive symptoms completed just as many PM tasks as did a group of healthy control participants. Similarly, in an investigation of bipolar disorder and PM Lee and colleagues (2010) found no relation between depression symptoms and event-based PM. Finally, no relation was observed between depression symptoms and event-based PM in a study of alcohol dependence (Griffiths et al., 2012). In summary, studies of event-based PM among non-clinical samples have revealed little relation between mild depressive symptoms and PM. However, it is possible that methodological features (e.g., highly salient cues) contribute to the pattern of findings. Mood Induction Studies Among Non-clinical Samples In the only study of event-based PM to employ a mood induction technique, Rummel, Hepp, Klein, and Silberleitner (2012) tested a resource allocation model (Ellis & Ashbrook, 1988) against an affective-regulation-of-processing model (Gasper & Clore, 2002; Storbeck & Clore, 2007) and administered a non-focal PM task to undergraduate students. Participants were randomly assigned to view sad, neutral, or happy films prior to completing the lexical decision task with the embedded PM cues. Participants then viewed and rated a second film of the same emotional content as the first, to refresh mood induction prior to completing a second block of the lexical decision task. To explore mood congruent effects on PM performance, the emotional valence of PM cues varied such that four words were sad, four were neutral, and four were happy. There were no differences in ongoing task performance between groups, either in accuracy or reaction time. With regard to PM performance, positive cues were identified more than negative cues, which were detected more than neutral cues. A main effect of mood was revealed, with participants in whom a happy mood was induced completing fewer PM tasks than participants in whom a sad mood was induced. A linear trend analysis revealed that as mood became more positive across groups, PM performance declined, confirming that PM performance was significantly lower in the happy group. The PM performance of the neutral group fell between that of the sad and happy groups, but did not differ from either. Despite the presence of a main effect of cue valence on PM performance, there was no evidence of a mood congruent effect, as cue valence did not interact with mood condition. It is important to highlight, however, that the PM performance of the sad group did not differ from that of the neutral group, but only from that of the happy group. With this in mind, it is possible that the effect of mood on PM in this study resulted from more general, less focused, processing in the happy group, and a more focused, item-specific analysis among the sad group, consistent with processing accounts (Storbeck & Clore, 2007). This finding is also in line with the results of Albiński and colleagues (2012), in which depressed participants outperformed non-depressed participants on an ongoing linear orders task. With regard to the five-phase model, these results suggest that a happy mood may result in reduced processing in the maintenance/monitoring phase. Thus, the lone published mood induction study of event-based PM suggests that a negative mood state may result in enhanced PM performance relative to a positive mood state, perhaps by encouraging a more focused, analytic approach to PM task performance. Summary of Event-based Studies To date, 13 studies have investigated event-based PM. Of those, five have revealed a negative relation between depressive symptoms and event-based PM, and one more approached significance. Although the lack of a relation between depression and PM performance in eight studies would seem to suggest that event-based PM might be intact in the context of depression, greater depression severity is associated with reduced PM. Those studies in which poor PM was associated with depressive symptoms most consistently implicate the maintenance/monitoring phase of the five-phase model. Time-based PM Clinical Samples In the first study of time-based PM, Rude and colleagues (1999) hypothesized that the considerable self-initiated processing required in time-based PM would result in depression-related impairment. The PM task required participants to press a particular button every 5 min while engaged in an ongoing general knowledge test. By pressing a second button, participants could view and track the elapsed time. Results indicated that depressed participants completed fewer PM button presses. Importantly, they also checked the clock fewer times than did their non-depressed counterparts and did not increase the frequency with which they monitored the time in the moments just prior to the target time. Notably, no group differences emerged in tests of retrospective memory selected from the Wechsler Memory Scales – Revised. This pattern suggests that the poorer performance of the depressed group resulted from a breakdown in the maintenance/monitoring phase, which depends heavily upon self-initiated processing. One limitation of this study was that the depressed and non-depressed participants differed in their performance of the ongoing general knowledge test, with non-depressed participants answering more questions correctly. There was also a marginally significant group difference in scores on a modified WAIS Vocabulary test. These performance disparities raise the possibility that the depressed group may have been less engaged or experienced more fatigue while completing experimental tasks, or that lower general intellectual potential could account for PM performance differences. As noted in the “Event-Based PM” section, Li and colleagues (2013) investigated the relations between depression and PM as a function of cue type among undergraduate students. A main effect of depression was revealed on time-based tasks of the Memory for Intentions Screening Test (Raskin et al. 2010; Weinborn, Woods, Nulsen, & Park, 2011), with non-depressed participants completing more time-based PM tasks than depressed participants. As was the case regarding event-based task performance, depressed participants were differentially affected by longer delay intervals and completed significantly fewer time-based PM tasks following a 15-min delay interval than non-depressed participants. The group × delay interval interaction observed for time-based PM performance could have been driven by retrospective memory difficulties as was likely true for the same pattern for event-based cues. However, it is also possible that the impaired performance on time-based tasks involving a 15-min delay resulted from difficulty maintaining the intention and reduced active monitoring. Unfortunately, it is not possible to confidently disentangle these alternatives as the MIST includes only a recognition test (rather than free recall) and does not incorporate a measure of monitoring behavior. Therefore, the performance of the depressed group on time-based tasks following a 15-min delay suggests either a breakdown in the maintenance/monitoring phase or in the retrieval phase. Regardless of the mechanisms that underlie poorer performance among depressed participants, these results raise important questions about the affect that increasing delays may have on individuals with depression. Following up on these studies, Li and colleagues (2014) further investigated the role of strategic monitoring and cognitive control in time-based PM among undergraduate students. Participants were classified as possessing elevated depressive symptoms (HDS) or minimal depressive symptoms (LDS) and were engaged in a lexical decision task. To date, this is the only study of time-based PM to have included a no-PM baseline condition to allow for comparison of cost effects (i.e., changes in ongoing task performance with embedded PM task). Participants completed two blocks, one involving only the lexical decision task, the other including the PM task embedded within the lexical decision task. The PM task required participants to press the “F1” key at 4, 8, and 12 min into the task. Results revealed a main effect of depressive symptoms, with HDS participants completing significantly fewer PM tasks than LDS participants. Though there was not a main effect of depressive symptoms on clock checking, a trend was revealed in which LDS participants checked the clock numerically more than HDS participants, including in the final, critical minute preceding target times. Importantly, clock checking correlated with PM performance in both groups, suggesting that monitoring behavior was relevant to PM performance. There was no effect of depressive symptoms on ongoing task accuracy, but there was a group by block interaction, such that the LDS participants experienced greater cost on the ongoing task (in reaction time) associated with the addition of the PM task. This finding along with the trend that HDS participants checked the clock less frequently, including in the critical minute preceding the PM target time suggests that the poorer PM performance of the HDS was likely due, at least in part, to reduced processing in the maintenance/monitoring phase. In summary, time-based studies reveal reduced PM performance among people with clinically significant depression. The poor PM performance appears to be driven by reduced monitoring ability and would therefore implicate the maintenance/monitoring phase. However, only one of the three studies directly assessed monitoring performance. Non-clinical Samples Three studies have investigated the relation between mild depressive symptoms and time-based PM. Using a naturalistic paradigm, Jeong and Cranney (2009) investigated motivation and PM. They also explored the relation between depression severity and PM through correlational analyses. Undergraduate students were required to send text messages at a particular time 3 and 6 days after meeting with the researchers to initiate their involvement in the study. They were also required to record in a diary all the instances in which they retrieved the intention to send the text messages. The study revealed a negative correlation between depression severity and time-based PM, such that more severe depression symptoms were related to poorer PM task performance, but only in terms of timeliness. There were no significant associations of PM with self-reported anxiety or stress, or a computer-based task of working memory. Although no significant relation was observed between PM performance and the total number of times an intention was retrieved, a negative trend emerged between the number of retrievals on the specific day a task was to be completed and PM performance. This raises the possibility that depression resulted in decreased processing in the maintenance/monitoring phase of the five-phase model. In a study designed primarily to investigate the relations between bipolar disorder and PM, Lee and colleagues (2010) also explored the relations between depressive symptoms and PM. That study revealed a negative relation between the presence of depressive symptoms and performance on the time-based PM tasks of the Cambridge PM Test (CAMPROMPT; Wilson et al., 2005). The time-based tasks in the CAMPROMPT are to be performed at 7-, 13-, and 20-min delays. It is possible that the negative correlation between depressive symptoms and PM resulted from a breakdown in the maintenance/monitoring phase or in the retrieval phase. Although no additional information regarding the relation between depressive symptoms and PM was included (e.g., types of errors), given the two longer delay intervals, it is possible that the results of this study were similar to those of Li and colleagues (2013), in which impaired performance was observed only at longer delay intervals. Most recently, Abliński and colleagues (2012) investigated the possibility that mild depressive symptoms might facilitate event- and time-based PM among young and older adults. (The event-based portion of this study was described above.) The ongoing task required participants to read short stories, each of which contained three key elements (e.g., people, places, animals) and relationships between them. After reading each story, participants responded true or false to three statements about each story. The PM task required participants to stop reading the stories and classifying statements after 4 min had elapsed. Participants monitored the time by checking a stopwatch that was placed on the table beside them. This represented the sole time-based PM task. Analyses of the time-based PM data revealed a main effect of age, with more young adults completing the PM task than older adults. There was also a main effect of depressive symptoms, with more mildly depressed participants completing the PM task than non-depressed participants. With regard to time monitoring performance, the mildly depressed group checked the clock more frequently during the critical 60-s period preceding the target time but did not differ from the non-depressed group with regard to ongoing task performance. This was the first published finding of a positive effect of depressive symptoms on time-based PM. However, the reliance upon only a single PM trial raises concerns about the reliability of the findings. Perhaps more importantly, to exclude the possibility of retrospective memory failure influencing PM task performance, data analyses included only those participants who monitored the time at least once, resulting in five young adults and 11 older adults being excluded from analyses. Exclusion of participants who did not monitor the time, however, limited interpretation of the relations between depressive symptoms, monitoring behavior and PM. The authors note that the inclusion of all participants, regardless of monitoring behavior, resulted in a non-significant effect of depression (p = .11). This raises the possibility that mild depressive symptoms facilitated monitoring behavior and led to increased PM performance for some participants, but may have had a negative affect on monitoring and PM performance for others. To summarize, studies of mild depressive symptoms and time-based PM have produced equivocal results, with some findings suggesting a positive relation between depressive symptoms and PM and others a negative relation. Mood Induction Studies Among Non-clinical Samples Two studies have experimentally induced sad mood in an attempt to investigate the potential affect of a negative emotional state on PM performance. Kliegel and colleagues (2005) used brief films to induce sad or neutral mood states in undergraduate students prior to a time-based PM task. The ongoing task was an n-back working memory task in which the names of animals appeared on the computer screen for 4 s, followed by a 1 s pause before the next word appeared. Participants were required to press a “yes” key if the current word was identical to the word presented two words before. The time-based PM task required participants to press a specific key at 1-min intervals. Participants could monitor the time by pressing the “space” key, which revealed the time that had elapsed since the start of the experiment. The n-back task lasted 10 min and 10 s, allowing for 10 PM target times. For all analyses, the ongoing and PM tasks were divided into two 5 min and 5 s halves. Analyses revealed no main effect of mood group on the performance of the n-back task, indicating that the sad and neutral groups did not differ in terms of working memory performance. With regard to PM performance, there was no main effect of mood. The dissipating effects of the induction over time likely drove the lack of an overall main effect of sad mood. This interpretation is supported by the presence of a significant mood by task half interaction, by which the sad group completed significantly fewer PM tasks than the neutral group in the first half of the task. Additional analyses revealed that there was no difference in the number of PM button presses made by the sad and neutral groups in the first half of the study, but that the PM responses made by the sad group were slightly less timely than those made by the neutral group, coming either before or after the 3 s window. Similarly, with regard to clock monitoring, a mood by task half interaction revealed that the sad group checked the clock non-significantly less often than the neutral group during the first half of the task. Overall, clock monitoring was positively correlated with PM performance. These results suggest that sadness may affect PM via the timeliness of task execution. However, that the time-based task was to be executed at 1-min intervals likely reduced the executive demands of the task, thereby limiting the ability to detect PM differences. For instance, a 3- or 5-min interval would have required greater self-initiated processing to actively maintain the intention and to strategically monitor the passage of time, either of which may have led to group differences in PM performance. Additionally, although n-back tasks engage working memory, the 4 s presentation of each stimulus in this study may have made for a less demanding ongoing n-back task than had the stimuli been presented for only 2 s. This could have allowed for greater resources to be devoted to the PM task. Despite the absence of depression-related impairment in the number of PM tasks completed, the less timely responses of the sad group raise the possibility of reduced processing in the maintenance/monitoring phase. Schnitzspahn and colleagues (2014) broadened the study of mood and PM and examined whether mood and age interact to influence PM performance. Specifically, they sought to determine whether mood might differentially affect PM among younger and older adults and induced sad, neutral, or positive moods. The ongoing task was an n-back task in which animal words were displayed one at a time on a computer screen and participants were required to press a “yes” key if the current word was the same as the word that was presented two positions before. The PM task required participants to press a target key at 1-min intervals. Pressing the “space” bar revealed the elapsed time and provided a measure of monitoring. Results revealed a significant effect of age, wherein younger adults outperformed older adults on the PM task, regardless of mood condition. There was also a main effect of mood that was qualified by a significant interaction with age, such that among younger adults PM performance was best in the neutral condition, and negative and positive conditions did not differ from one another. For older adults, there were no significant PM or ongoing task performance differences between mood conditions. With regard to time monitoring, a main effect of age was revealed, but no main effect of mood. A simple main effect of mood was revealed among younger adults, but not older adults, such that younger adults in the neutral condition checked the clock more frequently than those in the negative and positive mood conditions. Mediation analyses revealed that decreased time monitoring mediated the effect of both negative and positive mood on PM performance among younger adults, suggesting that the poorer performance of both the positive and negative mood induction groups was driven by decreased processing at the maintenance/monitoring phase. These results are somewhat consistent with the findings of Kliegel and colleagues (2005), who also used a time-based task with younger adults, but contrary to those of Rummel and colleagues (2012), who found a positive effect of sad mood (relative to happy mood) in an event-based PM task among younger adults. A key methodological difference between this and the Kliegel et al. study that may have contributed to the discrepant findings pertains to stimuli presentation. Whereas in the Kliegel et al. study the n-back stimuli were presented for 4 s, stimuli were presented for only 2 s in this study, which likely required greater cognitive resources be devoted to the ongoing task at the expense of the PM task. This may have been particularly important among older adults in whom no mood differences emerged. As the authors point out, one potential explanation of the lack of mood induction effects among older adults is that the overall task was more challenging for older adults, regardless of induction, which contributed to poor performance across groups. The difficulty of the task may also have reduced the older adults ability to maintain a mood state throughout the task. Finally, although a simple main effect of mood was observed in young adults, the 1-min interval between time-based PM tasks in this study may have limited the ability to detect differences across mood inductions (e.g., positive vs. negative among young). The results of the Li and colleagues (2013) study, in which time-based PM performance suffered at longer delay intervals lend support for this notion. Summary of Time-based Studies All but one of the six time-based studies revealed a negative relation between depressive symptoms and time-based PM. Of the two mood induction studies, one found no main effect of mood and the other revealed reduced PM performance in both positive and negative relative to neutral mood states. In all of these studies, poorer PM performance among depressed or sad participants resulted from breakdowns in the maintenance/monitoring phase and or in the retrieval phase of the five-phase model. Discussion Until recently, little had been known about the relations between depression and PM. Although research on PM in depression remains somewhat limited at this time, a few key themes have begun to emerge. First, depression appears to be associated with poorer performance on PM tasks that place significant demands on executive functioning. Depression-related impairments have been revealed in event-based PM tasks that incorporate non-focal cues (Altgassen et al., 2009) and time-based PM tasks (Jeong & Cranney, 2009; Kliegel et al., 2005; Lee et al., 2010; Li et al., 2013, 2014; Rude et al., 1999; but see, Albiński et al. 2012), those tasks that require the greatest self-initiated processing. This pattern of results is not surprising given the considerable body of research that implicates depression in executive functioning deficits (Austin et al. 2001; Castaneda et al. 2008). Although it is possible that impairment of non-executive cognitive processes (e.g., retrospective memory) contribute to PM failure in the context of depression, the most prominent sources of impoverished PM performance appear to be deficits in those frontally mediated processes that allow for cognitive control (e.g., monitoring, inhibiting, and task switching). From a neuropsychological perspective, findings of impaired PM in the context of depression fit with work that has revealed depression-related deficits in tasks of executive functioning (Snyder, 2013), including planning and problem-solving (Andersson et al. 2010), working memory (Joorman & Gotlib, 2008), inhibition (Gohier et al., 2009), and task switching (Murphy et al. 2012), each of which could contribute to PM failure. Furthermore, many of the cognitive deficits that have been associated with depression have been linked to dysfunction of prefrontal regions, including dorsolateral, ventrolateral, and anterior cingulate cortices (Bremner et al., 2002; Menzies et al., 2007). These prefrontal regions have also been implicated in PM-relevant processes as planning, monitoring the environment, inhibiting an ongoing activity, and maintaining and retrieving an intention (Burgess et al., 2001, 2003; Costa et al., 2011; Simons et al. 2006). One aim of the current paper was to highlight the various factors that contribute to PM failures and to anchor those in our Five-phase model of PM. To date, the majority of depression-related PM impairments appear to be driven by failure at the maintenance/monitoring and/or retrieval phases. Critical processes required during the maintenance/monitoring phase include retaining and updating one's intention, and actively monitoring the environment for the presence of a PM cue or the arrival of the appropriate time to complete an intended action. The retrieval phase is characterized by recalling the previously formed intention, which may occur spontaneously when a strong associative link was established between a PM cue and an intention. Alternatively, retrieval may require more strategic or effortful attempts to recall the intention that was associated with a PM cue. The one study that examined the role of inhibition in PM among depressed participants revealed a depression-related deficit in PM performance that implicates the inhibition phase (Chen et al., 2013). Although no studies have attempted to isolate the relation between planning and PM in depression, established findings of reduced planning ability in individuals with depression (Andersson et al. 2010) and research that highlights the importance of planning in successful PM (Shum et al. 2013), suggests that it is likely that depressive symptoms culminate in PM impairment due to poor planning in the development phase. It is also quite possible that future work in the area of depression and PM will reveal PM impairments that are secondary to breakdowns in the execution phases of our model, though failures at that stage of the model may be associated only with more severe depression. From a clinical perspective, current knowledge regarding the relations between depression and PM represents an opportunity to identify possible cognitive constraints upon the effectiveness of therapeutic interventions. Increased understanding among therapists and other healthcare providers of the cognitive mechanisms that underlie PM failures may lead to improvements in patient care and treatment outcomes. For example, whereas for some patients a failure to complete homework exercises might be indicative of resistance to change or a lack of motivation, for others the problem might be one of reduced executive functioning abilities, which results in PM failures related to the completion of the exercises. Limitations It is important to enumerate key limitations to the interpretation of the findings described above. First, compared to the vast body of research into retrospective memory, relatively little is known about PM and even less is understood about the nature of PM in depression. Inconsistencies in the extant literature regarding the relations between depressive symptoms and PM may be related to several factors. These factors include methodological differences, including differences in the type of PM task examined (i.e., event- vs. time-based), the nature of PM cues (e.g., focal vs. non-focal), the cognitive demands of ongoing tasks, and the methods and measures used to classify participants as depressed (e.g., clinical interview, BDI-II, Geriatric Depression Scale, etc.). Additionally, we decided to include mood induction studies because we believe they can provide valuable insight into the aspects of depression that may affect PM. However, mood induction studies are not proxies for the broad clinical manifestation of depression. Future Directions In addition to further clarifying the basic relations between depressive disorders and PM, future studies would benefit from further examination of the mechanism(s) responsible for PM failure among individuals with depression. If, as hypothesized, executive functioning deficits are responsible for poor PM among people with depression, it will be important to understand the role that monitoring, inhibition, or task-switching difficulties may play. One glaring omission in the extant literature is investigation of the role that planning may play in the relation between depressive symptoms and PM. Planning may be a critical link in the chain of processes that must be engaged to successfully complete a PM task, and has been shown to be impaired in depression (Andersson et al. 2010). Future work would benefit from continued investigation of the role of prefrontal cortical functions and their affect on PM performance among individuals with depression. The field could benefit from more naturalistic studies. Thus far, only one study has investigated the relation between depression and PM performance outside the laboratory (Jeong & Cranney, 2009). Although lab-based paradigms are developed with real-world implications in mind, subtle, but critical differences may emerge between lab-based findings and those of naturalistic paradigms, as has been observed in studies of PM and aging (Phillips, Henry, & Martin, 2008; Rendell & Craik, 2000). Implementation of ecologically valid, naturalistic paradigms in individuals with depressive disorders could only serve to deepen our understanding of the real-world implications of PM deficits. Understanding of the relations between depressive symptoms and PM would also benefit from investigating the role that rumination may play. Rumination, which is characterized by repetitive focus on the causes and potential effects of current distress (Nolen-Hoeksema, 1991), has been associated with impairments in a range of executive functions, including performance deficits in working memory (Watkins & Brown, 2002), inhibition (Philippot & Brutoux, 2008; Whitmer & Banich, 2007), and task switching (Davis & Nolen-Hoeksema, 2000). In depression, it is possible that rumination could occupy attentional resources at the expense of PM-relevant environmental cues or events. Critically, recent work suggests that rumination may moderate the relation between depression and cognitive impairment (Whitmer & Gotlib, 2012). Thus, the study of rumination may provide a critical avenue by which to better understand the relations between depression and PM. Finally, it will be important to investigate the effectiveness of interventions aimed at improving PM. Several strategies have been shown to improve PM among other populations, including the use of visual imagery (Grilli & McFarland, 2011; McFarland & Glisky, 2012) and implementation intentions (i.e., verbal “if, then” statements; Gollwitzer, 1993, 1996, 1999), both of which appear to increase the spontaneous recognition of PM cues and the associated strength of cue-intention pairing and subsequently reduce demands on self-initiated processing both in terms of maintenance/monitoring and retrieval. Promising results have also been reported by Fish and colleagues, who have attempted to improve PM among brain-injured individuals using “content-free” cueing (Fish et al., 2007), which appears to act on the maintenance/monitoring phase, and errorless learning (Fish, Manly, Kopelman, & Morris, 2015), which likely targets the development and retrieval phases. 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This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Clinical Neuropsychology Oxford University Press

Prospective Memory in Depression: Review of an Emerging Field

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Abstract

Abstract Depressive disorders have been linked to a variety of neuropsychological deficits, including in the areas of processing speed, memory, and executive functioning. These neurocognitive disturbances may contribute to the impairments in daily functioning often experienced by those suffering with depression. Prospective memory (PM), which refers to remembering to execute a previously formed intention at some point in the future, has been shown to play a critical role in daily functioning and may be particularly relevant in the context of depression. In this review, we synthesize the literature on PM and its relation to depression. We also put forth a new five-phase model of PM through which we frame our discussion of the existing literature on PM and depression. The results of this review reveal that PM deficits emerge in those tasks that place the greatest demands on executive functioning (e.g., monitoring for a PM cue, maintaining an intention over a delay). We conclude the review by highlighting the potential clinical relevance of these findings and proposing directions for future research. Depression, Learning and memory, Executive functions, Everyday functioning, Rehabilitation Introduction Clinically significant depression is a common mental health concern, with epidemiological estimates suggesting that 20% of the U.S. population will experience major depressive disorder at some point in their lifetime (Kessler & Wang, 2009). In addition to encompassing emotional and behavioral symptoms, depression is also often associated with significant impairments of daily functioning, adversely affecting quality of life. Neurocognitive disturbance may serve as a significant source of functional impairment in individuals suffering with depression, as depression is associated with deficits in processing speed, memory, and executive function (McDermott & Ebmeier, 2009). Such deficits have been shown to contribute to both psychosocial impairment (McIntyre et al., 2013) and poor long-term functional outcome (Jaeger, Berns, Uzelac, & Davis-Conway, 2006). Memory deficits may be a particularly important precipitant of functional impairment in depression. Memory functioning may be categorized into retrospective memory (the ability to recall information from the past) and prospective memory (PM: the ability to carry out previously formed intentions in the future). Although functional impairment is commonly thought of in reference to retrospective memory, PM is also particularly relevant to daily functioning (Smits, Deeg, & Jonker, 1997; Vedhara et al., 2004), adversely affecting activities ranging from maintaining relationships to remaining compliant with medication and non-pharmacological treatment regimens (e.g., difficulties completing homework assigned as part of psychosocial interventions). A number of depression-related deficits in retrospective memory have been documented (Gotlib & Joorman, 2010); however, less is known about PM deficits and depression. A recently emerging body of literature indicates that individuals experiencing depression may be less likely to successfully execute PM tasks. The goals of the present review are to synthesize the growing body of research into the associations of depression with PM, to interpret those findings in the context of a newly proposed model of PM, to highlight potential clinical applications of published findings, and to identify directions for future research. Neuropsychology of Depressive Disorders Depressive disorders have been associated with structural and functional brain abnormalities, including volumetric reductions in the prefrontal cortex (Bremner et al., 2002), hippocampus (Hickie et al., 2005), and cingulate cortex (Davidson, Pizzagalli, Nitschke, & Putnam, 2002). Additionally, clinically significant depression and depressive symptoms have been associated with abnormalities in several neurotransmitter systems, including seretonergic, dopaminergic, and cholinergic systems (Drevets, Price, & Furey, 2008). Such neural abnormalities are in turn purported to be associated with neuropsychological deficits in individuals diagnosed with depression. Although depression is associated with a wide range of deficits including attention (e.g., Cohen, Lohr, Paul, & Boland, 2001; Lampe, Sitskoorn, & Heeren, 2004), and retrospective memory (Burt, Zembar, & Niederehe, 1995; Simons et al., 2009; Vythilingham, et al., 2004), depression-related executive deficits (Austin, Mitchell, & Goodwin, 2001; Castaneda, Tuulio-Henriksson, Marttunen, Suvisaari, & Lönnqvist, 2008), as described in subsequent sections, may be particularly germane to PM. For example, consistent with reports of prefrontal cortex dysfunction in imaging studies among individuals with depressive disorders (Bremner et al., 2002), impairments associated with depression have been identified in planning and problem-solving (Andersson, Lövdahl, & Malt, 2010; Naismith et al., 2003), working memory (Gotlib & Joorman, 2010; Harvey et al. 2004; Rose & Ebmeier, 2006), inhibition (Gohier et al., 2009; Joorman, 2010), and task-switching (Lo & Allen, 2011; Murphy, Michael, & Sahakian, 2012). Furthermore, mood-related impairments are often most prominent on tasks that require more effortful engagement (Austin et al. 2001; Hammar, Isaksen, Schmid, Årdal & Strand, 2011), self-initiation (Hertel, 1997), or strategic cognitive control (Henry & Crawford, 2005; Langenecker et al., 2005). Finally, an emerging area of research has linked depression with reduced ability to simulate or imagine future events (Holmes, Lange, Moulds, & Steele, 2008; King, MacDougall, Ferris, Herdman, & McKinnon, 2011), which engages a number of cognitive processes reliant upon the prefrontal cortex in addition to medial temporal lobe structures (Hach, Tippet, & Addis, 2014). Together, the executive functioning deficits observed in depression implicate a distributed “executive control system” involving frontal and parietal regions of the brain. Neuropsychology of PM Successful PM performance depends upon distributed networks that include prefrontal cortices, the hippocampal complex, parietal regions, and subcortical structures. Several imaging studies have identified prefrontal regions, especially BA 10, as critically involved in successful PM (Burgess, Quayle, & Frith, 2001; Burgess, Scott, & Frith, 2003; Costa et al., 2011; Simons, Scholvinck, Gilbert, Frith, & Burgess, 2006). More recently, McDaniel, LaMontagne, Beck, Scullin, and Braver (2013) revealed that successful PM can be achieved via sustained attention or “top-down” control reliant upon a dorsal frontoparietal network, including anterior prefrontal cortex (e.g., BA 10), or by transient “bottom-up” processing that relies upon ventral parietal and cingulo-opercular regions. Similarly, Cona, Bisiacchi, and Moscovitch (2014) revealed sustained frontoparietal activation related to ongoing monitoring in a PM task. In line with the structures and regions involved, PM depends upon intact retrospective memory (i.e., failure to recall an intention will result in PM failure), along with cognitive processes that depend upon intact executive functioning (Fuster, 1997, 2008; Stuss & Benson, 1984). Although retrospective memory contributes to successful PM, the majority of PM studies have focused on the role of executive processes in PM, with several behavioral studies revealing relations between deficits in executive functioning and impaired PM performance (Burgess, Veitch, de Lacy Costello, & Shallice, 2000; McDaniel, Glisky, Rubin, Guynn, & Routhieaux, 1999; McFarland & Glisky, 2009). Specifically, poor PM has been linked to impaired planning, (Shum, Cahill, Hohaus, O’Gorman, & Chan, 2013), working memory (Arnold, Bayen, & Smith, 2015; Rose, Rendell, McDaniel, Aberle, & Kliegel, 2010), and inhibition and task switching (Schnitzspahn, Stahl, Zeintl, Kaller, & Kliegel, 2013). PM deficits, therefore, could be anticipated in the context of depression given the shared neuroanatomical structures and neuropsychological processes that have been implicated in depression and that provide for successful PM. Additionally, PM is inherently a future-oriented form of memory and is dependent upon more general prospection abilities, which are often affected in the context of depression (Roepke & Seligman, 2016). Measuring PM To understand the relations between depression and PM, it is first necessary to be familiar with the paradigms that assess PM. PM tasks are frequently of two kinds: event-based and time-based. An example of an event-based task in daily life is remembering to send an email when arriving at your desk, in which case the desk serves as an environmental cue or event to signal the appropriateness of sending the email. An example from daily life of a time-based task is remembering to leave a seminar at 1:45 p.m. so that you can arrive at a 2:00 p.m. meeting on time. In this scenario, there is no environmental cue or event, but rather the arrival of a particular time serves as the impetus for action. To simulate everyday PM tasks, studies of PM typically incorporate an ongoing task (e.g., answering trivia questions), which is intended to capture the cognitive demands and goal-directed behavior of everyday life, and within this ongoing activity a PM task with a separate, embedded goal (e.g., press the “6” key whenever a word belonging to the category “animal” appears). Prior PM investigations have identified factors that influence PM task difficulty. Critical factors include the nature of the PM task itself and the circumstances under which the task can be completed. Both event-and time-based PM tasks frequently place greater demands on self-initiated processing than do tasks of retrospective memory. For example, unlike retrospective memory tasks in which participants are explicitly asked to recall previously learned information, PM tasks provide no such support. Instead, participants must on their own recall or recognize a PM cue without any prompting, disengage from an ongoing task, and execute the previously formed intention. Furthermore, time-based tasks require participants to monitor the passage of time, which is typically unrelated to the execution of ongoing activity (e.g. monitoring the clock on the back wall of the classroom is not directly related to an ongoing goal of attending to a lecture), and therefore requires greater self-initiated processing than event-based tasks (Einstein, McDaniel, Richardson, Guynn, & Cunfer, 1995). A second factor affecting PM performance pertains to the “focality” of the cue in an event-based task. “Focality” refers to the degree to which the ongoing activity fosters processing of the environmental cue as it was processed at the time the intention was formed. An example of a focal PM task would be if your commute home required you to pass the bakery, a prominent landmark at the end of your street. The site of the bakery would remind you to stop and get cinnamon bread for making French toast that weekend. In contrast, the presence of a new construction project that required traffic to converge to a single lane would demand your attention the first time you encountered it. In this scenario, the bakery (and other typically focal landmarks at the intersection) would no longer be a focal cue, but rather becomes non-focal, despite the fact that you still drive past it. Laboratory investigations of focal cues often rely on a lexical decision task in which the respondent must execute an intention when a particular word is encountered (e.g., “animal”). In contrast, a non-focal PM task may require respondents to execute an intention when a particular syllable appears in a lexical decision task (e.g., “pel”). It has been argued that focal cues promote relatively automatic identification of cues, without need for the type of controlled monitoring processes required in non-focal PM tasks (Brewer, Knight, Marsh, & Unsworth, 2010; McDaniel & Einstein, 2000, 2007; Scullin, McDaniel, & Einstein, 2010). In other words, focal cues simply “pop out” and may remind you to follow through with a delayed plan, whereas non-focal cues do not. Therefore, the type of PM task (i.e., event- vs. time-based) and the nature of cues (focal vs. non-focal) are important considerations when considering the conditions under which PM failure may occur, as well as the populations that are likely to experience greater difficulty with such tasks. Five-Phase Model of PM To clarify the cognitive mechanisms that underlie successful PM, we propose a five-phase model of PM (see also Ellis, 1996; Kliegel, Martin, McDaniel, & Einstein, 2002 for alternative models). The model reflects the view that numerous cognitive processes are required for successful PM and that those processes may contribute to PM in at least one of five phases of task execution. Our model of PM (Fig. 1) includes the following five phases: development, maintenance/monitoring, retrieval, inhibition, and execution. Our five-phase model of PM is similar to that of Kliegel and colleagues (2002) in that it emphasizes the coordination of multiple cognitive processes in the execution of PM tasks, including forming an intention, retaining the intention over a delay interval, retrieving the intention at the appropriate time, and executing the intention. However, our model also highlights the role of additional cognitive processes (e.g., monitoring, inhibition, switching), without which PM task completion is less likely to occur. Additionally, this model specifies the neural correlates of the individual cognitive processes that underlie PM (e.g., frontal–parietal cognitive control network vs. medial temporal lobe involvement). By specifying the full range of cognitive processes that may support successful PM and delineating breakdowns that may lead to PM failure, we hope that this model will be an effective tool for developing targeted interventions aimed at improving PM. The proposed model will be applied to depression in the current paper; however, it can be applied to a wide range of clinical populations and presentations. Fig. 1. View largeDownload slide Executive control system. Fig. 1. View largeDownload slide Executive control system. Each phase of the model places differing demands on the medial temporal lobe (MTL) declarative memory system, which includes the hippocampal formation along with entorhinal, perirhinal, and parahippocampal cortices, and on a frontoparietal executive control system. In the first phase, the development phase, the executive control system is critical to developing an intention and devising a plan for completing that intention. Of note, intention formation and planning are not synonymous (i.e., it is possible to develop an intention without developing a plan to execute that intention.). Though the development phase relies to some extent on retrospective memory (e.g., to recall or know what needs to be done and to recognize or recall a future situation in which an intention could be executed), planning how and when to execute an intention (e.g., how can I remember to send the rent check tomorrow?) likely plays the most critical role during this phase. While planning to execute a task, an associative link between the intention and a future cue may be created by the MTL system. The strength of this associative link will influence the degree to which MTL or frontoparietal executive control processes are required in later phases. In the maintenance/monitoring phase, the processing burden may be more equally shared between MTL and frontoparietal executive control. In this phase, relevant cues must be retained by the MTL system while one is engaged in an ongoing, unrelated activity. Depending on a number of factors, including individual and task characteristics, the allocation of attentional resources may also be critical in this phase (Smith, 2003, 2010; but see, Einstein et al., 2005; McDaniel & Einstein, 2000). For instance, the frontoparietal executive control system may be engaged in rehearsing the intention and monitoring the environment for intention–relevant cues while one continues to devote cognitive resources to the current, ongoing task. The retrieval phase is heavily dependent upon the MTL system, which provides for recognition of a cue (e.g., the correct situation or time) and the spontaneous retrieval of the intention in the appropriate context. The frontoparietal executive control system may also be implicated in this phase, depending upon the strength of the associative link between cue and intention that was previously established by the MTL system. That is, a strong link established by the MTL system would obviate the need for the frontoparietal executive control system to be engaged, as the intention would “pop into mind” when the intention–relevant cue is encountered. Alternatively, if the PM cue or context is recognized, but the intention is not spontaneously retrieved due to a weak associative link between intention and cue, the frontoparietal executive control system will be recruited as one engages in an effortful, perhaps strategic, search for the related intention. Once the cue and intention are recognized and retrieved (either spontaneously or strategically), one must disengage from the ongoing activity to execute the PM task. The inhibition phase is driven entirely by the frontoparietal executive control system, which allows for inhibition of, or disengagement from, the ongoing activity. Finally, in the execution phase, the ongoing task has already been successfully inhibited and attentional resources must now be allocated to the PM task. Thus, the frontoparietal executive control system is called upon to switch from the ongoing task and initiate the actions necessary to complete the PM task. Impairments of processes involved in one or more of the five phases of the model can be anticipated in a host of clinical populations in which neuropsychological deficits are known to occur. The likelihood that PM impairments emerge will depend upon a combination of factors, including those associated with age (e.g., reduced working memory), and type and degree of severity of illness or disease (e.g., Parkinson's disease). Additional factors include those that are specific to the ongoing and PM tasks, such as ongoing task difficulty, cue type (event- or time-based), cue focality (focal or non-focal), and perceived importance of the PM task. The specific phase in which a breakdown occurs that leads to PM failure will often depend on an interaction between these person-specific and task-specific characteristics. Review Methods To identify relevant articles, PsychInfo, PubMed, and Web of Science databases were searched using a combination of the following terms: “mood,” “depression,” “depressive,” “sad,” “dysphoria,” “anhedonia,” “dysthymia,” “adjustment disorder with depressed mood,” “prospective memory,” and “delayed intention,” along with the names of prospective memory tests, including “MIST,” “RBMT,” “CAMPROMPT,” and “Virtual Week.” Additionally, we reviewed the bibliography of articles identified through those searches for other, related work. In the current review, because this area of research is relatively new we include clinically diagnosed depression, sub-threshold depressive symptomatology, and experimentally induced sad mood in our conceptualization of depressive disorders. PM in Depressive Disorders To date, 19 studies have been published that were designed to examine associations between depressive symptoms and PM performance. Eleven of those papers have been published in the last 5 years, reflecting the growing interest in this area of PM research. The eighteen published studies differed methodologically in several ways. Five studies investigated time-based PM (Jeong & Cranney, 2009; Kliegel et al., 2005; Li, Weinborn, Loft, & Maybery, 2014; Rude, Hertel, Jarrold, Covich, & Hedlund, 1999; Schnitzspahn et al., 2013) and four others investigated both time- and event-based PM (Albiński, Kliegel, Sędek, & Kleszczewska-Albiński, 2012; Griffiths et al., 2012; Lee et al., 2010; Li, Weinborn, Loft, & Maybery, 2013). The remaining 10 studies investigated event-based PM only. Only one study employed a naturalistic (i.e., non-laboratory) paradigm (Jeong & Cranney, 2009). In the following section, we describe the results of event-based PM studies, followed by those of time-based PM. Within both the event-based and time-based sections, studies are organized into those that included clinical samples, those with non-clinical samples, and finally mood induction studies with non-clinical samples. For the purposes of this review, our definition of clinical samples includes individuals receiving inpatient treatment for depression and/or individuals who reported moderate or severe levels of depressive symptoms on self-report measures (e.g., BDI-II > 20). Non-clinical samples include participants with mild self-reported depressive symptoms (e.g., BDI-II < 20). Please refer to Table 1 for full participant and task details of each study. Table 2 lists studies based upon their relevance to our five-phase model of PM. Table 1. Summary of PM studies in depression with sample, methodology, and results Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Note: DASS-21 = Depression Anxiety Stress Scales 21 (Lovibond & Lovibond, 1995); SCID = Structured Clinical Interview for DSM-III-R (Spitzer, Williams, & Gibbon, 1987); BDI = Beck Depression Inventory (Beck & Steer, 1987); CPRS = Comprehensive Psychopathological Rating Scale (Åsberg, Montgomery, Perris, Schalling, & Sedval, 1978); OCI = Obsessive-Compulsive Inventory; HAM-D = Hamilton Depression Rating Scale (Hamilton, 1960); GDS = Geriatric Depression Scale (Yesavage et al., 1983); SAMI = Self-Assessment Manikin Inventory (Bradley & Lang, 1994); HADS = Hospital Anxiety and Depression Scale (Zigmond and Snaith, 1983). Table 1. Summary of PM studies in depression with sample, methodology, and results Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Authors Sample Characterization PM test/manipulation PM type Ongoing task Results Harris & Menzies (1999) 101 undergraduates DASS-21 Experimental Event non-focal Semantic generation Depression approached significance (p = .07) Rude et al. (1999) Community sample 20 depressed 3 inpatient 20 non-depressed SCID; BDI Experimental Time General knowledge Non-depressed > depressed (p < .02) Depressed monitored time less often Non-depressed > depressed in ongoing task Kliegel et al. (2005) 61 undergraduates Experimental/Mood induction (sad; neutral) Time Working memory No main effect of mood on PM (F < 1) Sad group was non-significantly less timely in responding (p = .154) Livner et al. (2008) 404 OAs > 75 y.o. 14 MDD; 6 dysthymia; 275 w/ symptoms 109 w/o symptoms CPRS Experimental Event non-focal Cognitive tasks No relation between depression and PM (p = .38) Depression was related to impaired RM (p < . 01) Altgassen et al. (2009) Community sample 28 depressed 32 non-depressed BDI Experimental/Cue focality Event ½ focal ½ non-focal Vowel counting Group x focality interaction (ŋ2 = .08) Depressed completed fewer non-focal PM tasks (p < .002) Jeong & Cranney (2009) 40 undergraduates 20 depressed 20 non-depressed DASS-21 Send text message/Motivation Naturalistic Time N/A Depression related to impaired PM (p < .05) Motivation related to better PM (p < .05) Marsh et al. (2009) 75 undergraduates 25 depressed 25 o.c. washers 25 non-depressed BDI-II; OCI Experimental Event non-focal Lexical decision No relation between depression and PM (t(24) < 1) Lee et al. (2010) 40 patients with bipolar disorder; 40 healthy controls HAM-D Experimental/CAMPROMPT Event 1 focal 2 non-focal Time Puzzles No relation between depressive symptoms and PM (p = .09) Depressive symptoms negatively correlated with PM (p < .001) Altgassen et al. (2011) Inpatient sample 30 depressed; Community sample 28 non-depressed BDI Experimental/Emotional targets Event focal Word categorization Main effect of group on PM (p < .05) Non-depressed outperformed depressed only for positive target words (p < .01) Abliński et al. (2012) 60 undergraduates; 30 depressed; 30 non-depressed; 60 older adults; 27 depressed; 33 non-depressed BDI; GDS Experimental Event Linear orders No relation between depression and PM (p = .49) focal Young outperformed older adults (p < .05) Time Modified linear orders Depressed outperformed non-depressed (p < .05) Young outperformed older adults (p < .01) Albiński et al. (2012) 63 undergraduates (19–26); 28 middle-aged (42–50); 47 older adults (65–78) BDI; GDS Experimental Event focal Linear orders Young and middle-aged outperformed older adults (p < .001) Monitorers outperformed non-monitorers Young: (p < .001); Middle aged/older adults (p < .05) Non-monitorers reported more depressive symptoms Young: (p < .05) Rummel et al. (2012) 140 undergraduates SAMI Experimental/Mood induction (happy; sad); Emotional targets Event focal Lexical decision Sad outperformed happy on PM (p = .02) Positive cues were identified more than negative (p = .002) Li et al. (2013) 64 undergraduates; 32 mod to severe symptoms; 32 no or mild symptoms DASS-21; BDI-II (day of testing) Experimental/MIST Event Word search No relation between depression and PM (p = .42)  non-focal Time Non-depressed > depressed (p < .01) Delay interval Task type × delay interaction: non-depressed > depressed at longer delay (15 m) (p = .03) Chen et al. (2013) Outpatient sample 19 depressed; 19 non-depressed HAM-D; BDI-II (day of testing) Experimental/Eye tracking Event focal Visual search Non-depressed outperformed depressed (p = .001) Eye tracking: depressed demonstrated greater number of Fixations (p < .00001), average (p = .03) and total (p < .00001) fixation duration Li et al. (2014) 64 undergraduates; 32 high depressive (BDI-II > 13); 32 low depressive (BDI-II < 13) BDI-II Experimental/Task emphasis Ongoing task PM task Event focal Lexical decision No group difference when ongoing task was emphasized (p = .47) High depressive outperformed low when PM task was emphasized (p = .002) Li et al. (2014) 62 undergraduates; 31 mod to severe symptoms; 31 no or mild symptoms BDI-II Experimental Time Lexical decision Non-depressed outperformed depressed (p = .02) Clock-checking: trend with depressed checking less frequently (p = .10) Schnitzspahn et al. (2014) 121 adults; 64 young; 57 older HADS Experimental/Mood induction (happy; neutral; sad) Time n-back Young outperformed older (p < .001) Y: neutral > positive (p < .001) = negative (p < .01) Time monitoring mediated effect of happy and sad mood on PM O: neutral = positive = negative Arnold, Bayen, et al. (2015) 129 undergraduates BDI-II; HADS Experimental Event non-focal Color matching No relation between depression and PM (p's > .35) Note: DASS-21 = Depression Anxiety Stress Scales 21 (Lovibond & Lovibond, 1995); SCID = Structured Clinical Interview for DSM-III-R (Spitzer, Williams, & Gibbon, 1987); BDI = Beck Depression Inventory (Beck & Steer, 1987); CPRS = Comprehensive Psychopathological Rating Scale (Åsberg, Montgomery, Perris, Schalling, & Sedval, 1978); OCI = Obsessive-Compulsive Inventory; HAM-D = Hamilton Depression Rating Scale (Hamilton, 1960); GDS = Geriatric Depression Scale (Yesavage et al., 1983); SAMI = Self-Assessment Manikin Inventory (Bradley & Lang, 1994); HADS = Hospital Anxiety and Depression Scale (Zigmond and Snaith, 1983). Table 2. Summary of depression-related deficits in PM in relation to the five-phase model Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Table 2. Summary of depression-related deficits in PM in relation to the five-phase model Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Development Maintenance/Monitoring Retrieval Inhibition Execution Albiński et al. (2012)  Event X Altgassen et al. (2009)  Event (non-focal) X Altgassen et al. (2011)  Event (positive cue) X Chen et al. (2013)  Event X X Jeong and Cranney (2009)  Time X Kliegel et al. (2005)  Time X Lee et al. (2010) X X  Time Li et al. (2013)  Time X X Li et al. (2014)  Event X Li et al. (2014)  Time X Rude et al. (1999)  Time X Rummel et al. (2012)  Event X Schnitzspahn et al. (2014)  Time X Event-based PM Clinical Samples The first four studies in this section investigated aspects of self-initiated processing and attentional control and its relation to PM in the context of depression. These studies are followed by the only study to have used a standardized clinical neuropsychological measure in the investigation of event-based PM. In the first investigation of event-based PM among clinically depressed participants, Altgassen, Kliegel, and Martin (2009) compared the performance of depressed with non-depressed older adults and manipulated the demand placed on self-initiated processing by including half focal and half non-focal cues. As hypothesized, all participants performed more accurately on focal than on non-focal trials, and non-depressed participants outperformed depressed participants. Importantly, there was a group by focality interaction, such that relative to non-depressed participants, depressed participants performed less proficiently only on non-focal tasks. Although no group differences emerged in neuropsychological tasks of short-term memory, working memory, and inhibition, findings indicated that the depressed group was slower to respond to ongoing task trials than the non-depressed group. There exist three possible explanations for the longer reaction times of the depressed group. First, depressed participants may have found the ongoing task more difficult than non-depressed participants and thus, responded more slowly. This hypothesis is unlikely to explain the group differences, however, given the easy nature of the ongoing task (i.e., deciding which of two words contains more vowels) and the equivalent accuracy in performance between groups on the ongoing task. Alternatively, the longer reaction times of the depressed group may have been driven by slower information processing speed, which often accompanies depressive states (Snyder, 2013). However, that there were no group differences in inhibition renders this possibility less convincing as well, as a processing speed deficit would have been expected to also negatively affect performance on the inhibition task. The most plausible account of the group differences in non-focal PM performance pertains instead to monitoring abilities and suggests a breakdown in the maintenance/monitoring phase of the model. Reaction times to ongoing task trials are often thought to reflect monitoring activity for the presence or occurrence of a PM cue, as maintaining a PM intention frequently entails a cost in the form of slower reaction times in the performance of the ongoing task. Although group differences in the cost associated with the non-focal PM task (i.e., longer reaction times in the ongoing task) did not reach significance, the depressed group exhibited a numerical tendency towards less cost. This pattern suggests that the depressed group experienced difficulty maintaining active monitoring, which resulted in the completion of fewer PM tasks relative to the non-depressed group. Based on the study of Altgassen and colleagues (2009), which implicated deficient self-initiated processing in the reduced PM performance of depressed participants, Altgassen, Henry, Bürgler, and Kliegel (2011) sought to further examine the role of self-initiated processing by including salient, emotional PM cues. Thus, they examined the relations between emotional cue valence and PM in depressed and non-depressed individuals. Target words varied in emotional valence and consisted of three positive (love, beauty, happiness), three negative (sadness, tiredness, sorrow), and three neutral words (apple, rabbit, surfboard). Results indicated that non-depressed participants executed more PM intentions than depressed participants. However, group differences were only observed for positively–valenced target words, for which non-depressed participants demonstrated enhanced performance relative to other word types. These findings suggest that for non-depressed participants, positive valence increased the salience of target words resulting in improved PM. On the other hand, for depressed participants emotionally–valenced items were no more salient than neutral items, and therefore did not reduce self-initiated processing demands. Although accuracy of ongoing task performance did not differ between groups, reaction time data were not reported, limiting the conclusions regarding monitoring behavior. Overall, these results lend partial support to a mood congruence effect in PM (Eich, Macauley, & Ryan, 1994), in that the absence of a positivity effect could be interpreted as congruent with anhedonic aspects of depression. However, the lack of an effect of negative words among depressed participants was somewhat surprising. Following up on the two studies by Altgassen and colleagues, Chen, Zhou, Cui, and Chen (2013) used behavioral and eye tracking measures to examine the relation between depressive symptoms and the attentional control required to strategically monitor the environment for PM cues. Participants were individuals seeking treatment for depression in the psychology division of a hospital. The ongoing task consisted of a visual search task during which a single “target” word was displayed (e.g., “balloon”), followed immediately by four line drawings of objects. Participants were instructed to press the “1” key if a target word was depicted among the four objects, and the “2” if it was not present. Focal PM cues, to which participants were to press the “3”, were images of fruit (e.g., grapes) and appeared as one of the four line drawings on eight occasions. Half of the PM cues were presented with target images and half were presented without target images, with the goal of assessing participants’ ability to shift attention from the ongoing task to the PM task. Results revealed a main effect of depression on PM performance, as non-depressed participants outperformed depressed participants in both accuracy and reaction time. Additionally, the depressed participants completed fewer PM tasks in the target-plus-cue condition than in the cue-only condition. With regard to eye movement, depressed participants tended to fixate on targets and had difficulty shifting their attention (i.e., gaze) to PM cues. The authors interpreted the eye tracking data to suggest that depressed participants needed to exert greater cognitive control in the form of increased focused (rather than divided) attention to process the displays. Though these results imply decreased monitoring among depressed participants and suggest a breakdown in the maintenance/monitoring phase, the poorer performance of the depressed group on target-plus-cue trials also implicates the inhibition phase of the five-phase model and raises important questions regarding the role that inhibition and task-switching abilities may play in monitoring behavior and subsequent PM performance. In a subsequent investigation of the attentional control capacity of individuals with depression, Li, Loft, Weinborn, and Mayberry (2014) manipulated the perceived importance of an ongoing lexical decision task versus a PM task to see whether individuals with depression are capable of prioritizing attentional resources. When the ongoing task was emphasized as the more important task, there were no group differences in either PM or ongoing task performance, or in performance cost (i.e., reaction times to ongoing lexical decision task relative to a baseline condition), suggesting that participants with higher levels of depressive symptoms are capable of successfully completing a focal event-based task. When the importance of the PM task was stressed over the ongoing task, however, the PM performance of the low depressive symptoms group improved, whereas the performance of the high depressive symptoms group did not. Performance costs increased for both groups. The equivalent PM performance when the ongoing task was emphasized suggests that individuals with high levels of depressive symptoms may be capable of completing resource-demanding event-based tasks (e.g., high retrospective memory load). However, participants with relatively greater depressive symptoms were unable to benefit from the increased importance placed on the PM task, suggesting that they may have had difficulty allocating attentional resources in an efficient or consistent manner. These results are consistent with difficulties during the maintenance/monitoring phase. Lending some support for this idea, the high depressive symptom group reported experiencing greater distractibility during the task, which may have resulted in less persistent monitoring. Self-reported distractibility, however, was not significantly correlated with PM performance. Li and colleagues (2013) investigated the possibility that PM deficits in depression may vary as a function of cue type (event- vs. time-based). Whereas the studies reviewed thus far employed classic experimental laboratory tasks, used a clinical neuropsychological measure to investigate the relation between depression and event- and time-based PM among undergraduate students. The research version of the Memory for Intentions Screening Test (MIST; Raskin, Buckheit, & Sherrod, 2010) consists of four event-based tasks (e.g., “When I hand you a postcard, write the name of the city and country we are located in.”) and four time-based tasks (e.g., “In 15 minutes, use that paper to write down your age.”), occurring at delays of 2 and 15 min. Although there was no main effect of depression on event-based PM, a significant group × delay interval interaction was revealed, indicating that the performance difference between depressed and non-depressed participants was greater at 15-min delays than at 2-min delays. This finding suggests that as the delay interval increased from 2 to 15 min, depressed participants were less able to sustain the monitoring activity necessary for successful PM. Increasing a delay interval has been shown to exert negative effects on PM (Martin, Brown, & Hicks, 2011), but the exact mechanisms of this effect are unclear. One possible mechanism explaining the effect of delay in this study is that the 15-min delay interval required a level of sustained attention and monitoring that the depressed participants were not able to achieve. Although this interpretation would seem to fit given the non-focal nature of the event-based tasks, the highly salient nature of the cues in the MIST (e.g., “when I hand you a red pen, sign your name on your paper”) likely offset the self-initiated processing typically required in non-focal tasks and thereby reduced the need for active monitoring. Instead, the reduced event-based performance at the 15-min delay would seem to stem more from a retrospective memory failure, as suggested by the authors. That is, participants did not need to monitor the environment for the appearance of a red pen or a postcard, but did need to maintain and recall the associated intention or action. This pattern implicates the maintenance/monitoring phase and the retrieval phase and is consistent with imaging results in which medial temporal lobe activity has been shown to underlie performance on focal event-based tasks (Martin et al., 2007). Although the results of a recognition test conducted at the conclusion of the MIST revealed that depressed participants were just as likely as non-depressed to successfully recognize the PM tasks they were to complete, the possibility remains that they were unable to actively search for and freely recall the intention. In summary, studies that have included clinically depressed participants suggest that individuals with depression have difficulty on tasks that require self-initiated processing and implicate the maintenance/monitoring phase. Although not all of these studies have revealed deficits in event-based PM, they each suggest that individuals with depression are less able to allocate attentional resources in a manner that will facilitate PM performance. Non-clinical Samples Three studies have been conducted to investigate the relations between mild depressive symptoms and PM. Given findings that indicate that depression does not always result in cognitive deficits (and that depressive symptoms may reduce or enhance cognitive functioning depending on the severity of those symptoms (von Helversen, Wilke, Johnson, & Schmid, 2011)), Abliński and colleagues (2012) examined the possibility that mild depressive symptoms may in fact facilitate event- and time-based PM in younger and older adults. The results of the event-based task will be described here, whereas those of the time-based task will be reviewed in the Time-based PM section. The ongoing task required participants to complete a linear orders task, in which they had to learn relationships between three people (e.g., Mike is taller than Ben. Tom is taller than Mike) and answer true/false statements about those relationships. In the PM condition, participants were instructed to press the “Q” key whenever they encountered a word written in bold red font. Results revealed that younger adults executed more PM intentions than older adults. There was no main effect of mood or interactions between mood and age on PM performance. The failure to detect a significant association between depressive symptoms and focal PM performance is consistent with Altgassen and colleagues (2009). However, the comparable PM performance between mildly depressed and non-depressed in this study could have been a product of the highly salient PM cues (i.e., words printed in bold, red font), which would have fostered automatic processing and would not have required the type of self-initiated processing thought to occur in the maintenance/monitoring phase. This was particularly true for the younger adults for whom a ceiling effect emerged. To further investigate the role of strategic monitoring in an event-based task, Albiński, Sędek, and Kliegel (2012) used the linear orders task described previously. Participants were classified as “monitorers” and “non-monitorers” based on changes in reaction time between an ongoing task only condition and an ongoing task plus PM condition (i.e., PM performance cost). Results revealed that young and middle-aged adults outperformed older adults on the PM task. Additionally, “monitorers” outperformed “non-monitorers.” Although the relation between depressive symptoms and PM performance was not analyzed directly, results indicated that among young adults, greater depressive symptoms were associated with non-monitoring. These results implicate the maintenance/monitoring phase of the model. However, although performance cost is a widely accepted means of inferring monitoring activity, the possibility remains that increased reaction times in the presence of a PM task reflect something other than active monitoring. For example, it could simply reflect less efficient processing under dual task demands. Most recently, Arnold, Bayen, and Böhm (2015) used a multinomial processing approach designed to isolate the prospective and retrospective components of a PM task to determine which component might better account for any observed PM impairments associated with depression and anxiety among undergraduate students. In the ongoing task, participants were presented with four colored rectangles one at a time, followed by a colored word and were required to indicate whether the color of the word matched the color of either of the four rectangles that preceded it. The PM task required that participants press the space bar any time one of five previously studied words was presented. Results indicated that depressive symptoms were not significantly correlated with event-based PM performance. Anxiety symptoms, however, was significantly negatively correlated with PM performance. One major limitation of the results pertains to the sample. Although a relatively large sample was obtained (N = 129), scores on both the BDI-II and the HADS indicated mean depression levels in the mild range, with only 10 participants from the total sample endorsing symptoms consistent with moderate to severe depression. Thus, the results suggest that non-focal event-based PM performance can be unaffected in the context of mild depressive symptoms. However, no conclusions can be drawn regarding the relation between moderate or more severe depressive symptoms and PM. Although not a primary focus, additional studies have investigated the relations between depressive symptoms and event-based PM. Livner, Berger, Karlsson, and Bäckman (2008) reported no relation between depression and PM among older adults, but a negative relation between depression and retrospective memory. They concluded that any PM deficits among individuals with depression were likely related to the effects of depression on retrospective memory. Harris and Menzies (1999) also found no relation between depression and PM among undergraduates. Instead, the results of a regression analysis revealed that PM was uniquely associated with anxiety. In a study of sub-clinical obsessive-compulsive symptoms and PM, Marsh and colleagues (2009) found that participants with mild depressive symptoms completed just as many PM tasks as did a group of healthy control participants. Similarly, in an investigation of bipolar disorder and PM Lee and colleagues (2010) found no relation between depression symptoms and event-based PM. Finally, no relation was observed between depression symptoms and event-based PM in a study of alcohol dependence (Griffiths et al., 2012). In summary, studies of event-based PM among non-clinical samples have revealed little relation between mild depressive symptoms and PM. However, it is possible that methodological features (e.g., highly salient cues) contribute to the pattern of findings. Mood Induction Studies Among Non-clinical Samples In the only study of event-based PM to employ a mood induction technique, Rummel, Hepp, Klein, and Silberleitner (2012) tested a resource allocation model (Ellis & Ashbrook, 1988) against an affective-regulation-of-processing model (Gasper & Clore, 2002; Storbeck & Clore, 2007) and administered a non-focal PM task to undergraduate students. Participants were randomly assigned to view sad, neutral, or happy films prior to completing the lexical decision task with the embedded PM cues. Participants then viewed and rated a second film of the same emotional content as the first, to refresh mood induction prior to completing a second block of the lexical decision task. To explore mood congruent effects on PM performance, the emotional valence of PM cues varied such that four words were sad, four were neutral, and four were happy. There were no differences in ongoing task performance between groups, either in accuracy or reaction time. With regard to PM performance, positive cues were identified more than negative cues, which were detected more than neutral cues. A main effect of mood was revealed, with participants in whom a happy mood was induced completing fewer PM tasks than participants in whom a sad mood was induced. A linear trend analysis revealed that as mood became more positive across groups, PM performance declined, confirming that PM performance was significantly lower in the happy group. The PM performance of the neutral group fell between that of the sad and happy groups, but did not differ from either. Despite the presence of a main effect of cue valence on PM performance, there was no evidence of a mood congruent effect, as cue valence did not interact with mood condition. It is important to highlight, however, that the PM performance of the sad group did not differ from that of the neutral group, but only from that of the happy group. With this in mind, it is possible that the effect of mood on PM in this study resulted from more general, less focused, processing in the happy group, and a more focused, item-specific analysis among the sad group, consistent with processing accounts (Storbeck & Clore, 2007). This finding is also in line with the results of Albiński and colleagues (2012), in which depressed participants outperformed non-depressed participants on an ongoing linear orders task. With regard to the five-phase model, these results suggest that a happy mood may result in reduced processing in the maintenance/monitoring phase. Thus, the lone published mood induction study of event-based PM suggests that a negative mood state may result in enhanced PM performance relative to a positive mood state, perhaps by encouraging a more focused, analytic approach to PM task performance. Summary of Event-based Studies To date, 13 studies have investigated event-based PM. Of those, five have revealed a negative relation between depressive symptoms and event-based PM, and one more approached significance. Although the lack of a relation between depression and PM performance in eight studies would seem to suggest that event-based PM might be intact in the context of depression, greater depression severity is associated with reduced PM. Those studies in which poor PM was associated with depressive symptoms most consistently implicate the maintenance/monitoring phase of the five-phase model. Time-based PM Clinical Samples In the first study of time-based PM, Rude and colleagues (1999) hypothesized that the considerable self-initiated processing required in time-based PM would result in depression-related impairment. The PM task required participants to press a particular button every 5 min while engaged in an ongoing general knowledge test. By pressing a second button, participants could view and track the elapsed time. Results indicated that depressed participants completed fewer PM button presses. Importantly, they also checked the clock fewer times than did their non-depressed counterparts and did not increase the frequency with which they monitored the time in the moments just prior to the target time. Notably, no group differences emerged in tests of retrospective memory selected from the Wechsler Memory Scales – Revised. This pattern suggests that the poorer performance of the depressed group resulted from a breakdown in the maintenance/monitoring phase, which depends heavily upon self-initiated processing. One limitation of this study was that the depressed and non-depressed participants differed in their performance of the ongoing general knowledge test, with non-depressed participants answering more questions correctly. There was also a marginally significant group difference in scores on a modified WAIS Vocabulary test. These performance disparities raise the possibility that the depressed group may have been less engaged or experienced more fatigue while completing experimental tasks, or that lower general intellectual potential could account for PM performance differences. As noted in the “Event-Based PM” section, Li and colleagues (2013) investigated the relations between depression and PM as a function of cue type among undergraduate students. A main effect of depression was revealed on time-based tasks of the Memory for Intentions Screening Test (Raskin et al. 2010; Weinborn, Woods, Nulsen, & Park, 2011), with non-depressed participants completing more time-based PM tasks than depressed participants. As was the case regarding event-based task performance, depressed participants were differentially affected by longer delay intervals and completed significantly fewer time-based PM tasks following a 15-min delay interval than non-depressed participants. The group × delay interval interaction observed for time-based PM performance could have been driven by retrospective memory difficulties as was likely true for the same pattern for event-based cues. However, it is also possible that the impaired performance on time-based tasks involving a 15-min delay resulted from difficulty maintaining the intention and reduced active monitoring. Unfortunately, it is not possible to confidently disentangle these alternatives as the MIST includes only a recognition test (rather than free recall) and does not incorporate a measure of monitoring behavior. Therefore, the performance of the depressed group on time-based tasks following a 15-min delay suggests either a breakdown in the maintenance/monitoring phase or in the retrieval phase. Regardless of the mechanisms that underlie poorer performance among depressed participants, these results raise important questions about the affect that increasing delays may have on individuals with depression. Following up on these studies, Li and colleagues (2014) further investigated the role of strategic monitoring and cognitive control in time-based PM among undergraduate students. Participants were classified as possessing elevated depressive symptoms (HDS) or minimal depressive symptoms (LDS) and were engaged in a lexical decision task. To date, this is the only study of time-based PM to have included a no-PM baseline condition to allow for comparison of cost effects (i.e., changes in ongoing task performance with embedded PM task). Participants completed two blocks, one involving only the lexical decision task, the other including the PM task embedded within the lexical decision task. The PM task required participants to press the “F1” key at 4, 8, and 12 min into the task. Results revealed a main effect of depressive symptoms, with HDS participants completing significantly fewer PM tasks than LDS participants. Though there was not a main effect of depressive symptoms on clock checking, a trend was revealed in which LDS participants checked the clock numerically more than HDS participants, including in the final, critical minute preceding target times. Importantly, clock checking correlated with PM performance in both groups, suggesting that monitoring behavior was relevant to PM performance. There was no effect of depressive symptoms on ongoing task accuracy, but there was a group by block interaction, such that the LDS participants experienced greater cost on the ongoing task (in reaction time) associated with the addition of the PM task. This finding along with the trend that HDS participants checked the clock less frequently, including in the critical minute preceding the PM target time suggests that the poorer PM performance of the HDS was likely due, at least in part, to reduced processing in the maintenance/monitoring phase. In summary, time-based studies reveal reduced PM performance among people with clinically significant depression. The poor PM performance appears to be driven by reduced monitoring ability and would therefore implicate the maintenance/monitoring phase. However, only one of the three studies directly assessed monitoring performance. Non-clinical Samples Three studies have investigated the relation between mild depressive symptoms and time-based PM. Using a naturalistic paradigm, Jeong and Cranney (2009) investigated motivation and PM. They also explored the relation between depression severity and PM through correlational analyses. Undergraduate students were required to send text messages at a particular time 3 and 6 days after meeting with the researchers to initiate their involvement in the study. They were also required to record in a diary all the instances in which they retrieved the intention to send the text messages. The study revealed a negative correlation between depression severity and time-based PM, such that more severe depression symptoms were related to poorer PM task performance, but only in terms of timeliness. There were no significant associations of PM with self-reported anxiety or stress, or a computer-based task of working memory. Although no significant relation was observed between PM performance and the total number of times an intention was retrieved, a negative trend emerged between the number of retrievals on the specific day a task was to be completed and PM performance. This raises the possibility that depression resulted in decreased processing in the maintenance/monitoring phase of the five-phase model. In a study designed primarily to investigate the relations between bipolar disorder and PM, Lee and colleagues (2010) also explored the relations between depressive symptoms and PM. That study revealed a negative relation between the presence of depressive symptoms and performance on the time-based PM tasks of the Cambridge PM Test (CAMPROMPT; Wilson et al., 2005). The time-based tasks in the CAMPROMPT are to be performed at 7-, 13-, and 20-min delays. It is possible that the negative correlation between depressive symptoms and PM resulted from a breakdown in the maintenance/monitoring phase or in the retrieval phase. Although no additional information regarding the relation between depressive symptoms and PM was included (e.g., types of errors), given the two longer delay intervals, it is possible that the results of this study were similar to those of Li and colleagues (2013), in which impaired performance was observed only at longer delay intervals. Most recently, Abliński and colleagues (2012) investigated the possibility that mild depressive symptoms might facilitate event- and time-based PM among young and older adults. (The event-based portion of this study was described above.) The ongoing task required participants to read short stories, each of which contained three key elements (e.g., people, places, animals) and relationships between them. After reading each story, participants responded true or false to three statements about each story. The PM task required participants to stop reading the stories and classifying statements after 4 min had elapsed. Participants monitored the time by checking a stopwatch that was placed on the table beside them. This represented the sole time-based PM task. Analyses of the time-based PM data revealed a main effect of age, with more young adults completing the PM task than older adults. There was also a main effect of depressive symptoms, with more mildly depressed participants completing the PM task than non-depressed participants. With regard to time monitoring performance, the mildly depressed group checked the clock more frequently during the critical 60-s period preceding the target time but did not differ from the non-depressed group with regard to ongoing task performance. This was the first published finding of a positive effect of depressive symptoms on time-based PM. However, the reliance upon only a single PM trial raises concerns about the reliability of the findings. Perhaps more importantly, to exclude the possibility of retrospective memory failure influencing PM task performance, data analyses included only those participants who monitored the time at least once, resulting in five young adults and 11 older adults being excluded from analyses. Exclusion of participants who did not monitor the time, however, limited interpretation of the relations between depressive symptoms, monitoring behavior and PM. The authors note that the inclusion of all participants, regardless of monitoring behavior, resulted in a non-significant effect of depression (p = .11). This raises the possibility that mild depressive symptoms facilitated monitoring behavior and led to increased PM performance for some participants, but may have had a negative affect on monitoring and PM performance for others. To summarize, studies of mild depressive symptoms and time-based PM have produced equivocal results, with some findings suggesting a positive relation between depressive symptoms and PM and others a negative relation. Mood Induction Studies Among Non-clinical Samples Two studies have experimentally induced sad mood in an attempt to investigate the potential affect of a negative emotional state on PM performance. Kliegel and colleagues (2005) used brief films to induce sad or neutral mood states in undergraduate students prior to a time-based PM task. The ongoing task was an n-back working memory task in which the names of animals appeared on the computer screen for 4 s, followed by a 1 s pause before the next word appeared. Participants were required to press a “yes” key if the current word was identical to the word presented two words before. The time-based PM task required participants to press a specific key at 1-min intervals. Participants could monitor the time by pressing the “space” key, which revealed the time that had elapsed since the start of the experiment. The n-back task lasted 10 min and 10 s, allowing for 10 PM target times. For all analyses, the ongoing and PM tasks were divided into two 5 min and 5 s halves. Analyses revealed no main effect of mood group on the performance of the n-back task, indicating that the sad and neutral groups did not differ in terms of working memory performance. With regard to PM performance, there was no main effect of mood. The dissipating effects of the induction over time likely drove the lack of an overall main effect of sad mood. This interpretation is supported by the presence of a significant mood by task half interaction, by which the sad group completed significantly fewer PM tasks than the neutral group in the first half of the task. Additional analyses revealed that there was no difference in the number of PM button presses made by the sad and neutral groups in the first half of the study, but that the PM responses made by the sad group were slightly less timely than those made by the neutral group, coming either before or after the 3 s window. Similarly, with regard to clock monitoring, a mood by task half interaction revealed that the sad group checked the clock non-significantly less often than the neutral group during the first half of the task. Overall, clock monitoring was positively correlated with PM performance. These results suggest that sadness may affect PM via the timeliness of task execution. However, that the time-based task was to be executed at 1-min intervals likely reduced the executive demands of the task, thereby limiting the ability to detect PM differences. For instance, a 3- or 5-min interval would have required greater self-initiated processing to actively maintain the intention and to strategically monitor the passage of time, either of which may have led to group differences in PM performance. Additionally, although n-back tasks engage working memory, the 4 s presentation of each stimulus in this study may have made for a less demanding ongoing n-back task than had the stimuli been presented for only 2 s. This could have allowed for greater resources to be devoted to the PM task. Despite the absence of depression-related impairment in the number of PM tasks completed, the less timely responses of the sad group raise the possibility of reduced processing in the maintenance/monitoring phase. Schnitzspahn and colleagues (2014) broadened the study of mood and PM and examined whether mood and age interact to influence PM performance. Specifically, they sought to determine whether mood might differentially affect PM among younger and older adults and induced sad, neutral, or positive moods. The ongoing task was an n-back task in which animal words were displayed one at a time on a computer screen and participants were required to press a “yes” key if the current word was the same as the word that was presented two positions before. The PM task required participants to press a target key at 1-min intervals. Pressing the “space” bar revealed the elapsed time and provided a measure of monitoring. Results revealed a significant effect of age, wherein younger adults outperformed older adults on the PM task, regardless of mood condition. There was also a main effect of mood that was qualified by a significant interaction with age, such that among younger adults PM performance was best in the neutral condition, and negative and positive conditions did not differ from one another. For older adults, there were no significant PM or ongoing task performance differences between mood conditions. With regard to time monitoring, a main effect of age was revealed, but no main effect of mood. A simple main effect of mood was revealed among younger adults, but not older adults, such that younger adults in the neutral condition checked the clock more frequently than those in the negative and positive mood conditions. Mediation analyses revealed that decreased time monitoring mediated the effect of both negative and positive mood on PM performance among younger adults, suggesting that the poorer performance of both the positive and negative mood induction groups was driven by decreased processing at the maintenance/monitoring phase. These results are somewhat consistent with the findings of Kliegel and colleagues (2005), who also used a time-based task with younger adults, but contrary to those of Rummel and colleagues (2012), who found a positive effect of sad mood (relative to happy mood) in an event-based PM task among younger adults. A key methodological difference between this and the Kliegel et al. study that may have contributed to the discrepant findings pertains to stimuli presentation. Whereas in the Kliegel et al. study the n-back stimuli were presented for 4 s, stimuli were presented for only 2 s in this study, which likely required greater cognitive resources be devoted to the ongoing task at the expense of the PM task. This may have been particularly important among older adults in whom no mood differences emerged. As the authors point out, one potential explanation of the lack of mood induction effects among older adults is that the overall task was more challenging for older adults, regardless of induction, which contributed to poor performance across groups. The difficulty of the task may also have reduced the older adults ability to maintain a mood state throughout the task. Finally, although a simple main effect of mood was observed in young adults, the 1-min interval between time-based PM tasks in this study may have limited the ability to detect differences across mood inductions (e.g., positive vs. negative among young). The results of the Li and colleagues (2013) study, in which time-based PM performance suffered at longer delay intervals lend support for this notion. Summary of Time-based Studies All but one of the six time-based studies revealed a negative relation between depressive symptoms and time-based PM. Of the two mood induction studies, one found no main effect of mood and the other revealed reduced PM performance in both positive and negative relative to neutral mood states. In all of these studies, poorer PM performance among depressed or sad participants resulted from breakdowns in the maintenance/monitoring phase and or in the retrieval phase of the five-phase model. Discussion Until recently, little had been known about the relations between depression and PM. Although research on PM in depression remains somewhat limited at this time, a few key themes have begun to emerge. First, depression appears to be associated with poorer performance on PM tasks that place significant demands on executive functioning. Depression-related impairments have been revealed in event-based PM tasks that incorporate non-focal cues (Altgassen et al., 2009) and time-based PM tasks (Jeong & Cranney, 2009; Kliegel et al., 2005; Lee et al., 2010; Li et al., 2013, 2014; Rude et al., 1999; but see, Albiński et al. 2012), those tasks that require the greatest self-initiated processing. This pattern of results is not surprising given the considerable body of research that implicates depression in executive functioning deficits (Austin et al. 2001; Castaneda et al. 2008). Although it is possible that impairment of non-executive cognitive processes (e.g., retrospective memory) contribute to PM failure in the context of depression, the most prominent sources of impoverished PM performance appear to be deficits in those frontally mediated processes that allow for cognitive control (e.g., monitoring, inhibiting, and task switching). From a neuropsychological perspective, findings of impaired PM in the context of depression fit with work that has revealed depression-related deficits in tasks of executive functioning (Snyder, 2013), including planning and problem-solving (Andersson et al. 2010), working memory (Joorman & Gotlib, 2008), inhibition (Gohier et al., 2009), and task switching (Murphy et al. 2012), each of which could contribute to PM failure. Furthermore, many of the cognitive deficits that have been associated with depression have been linked to dysfunction of prefrontal regions, including dorsolateral, ventrolateral, and anterior cingulate cortices (Bremner et al., 2002; Menzies et al., 2007). These prefrontal regions have also been implicated in PM-relevant processes as planning, monitoring the environment, inhibiting an ongoing activity, and maintaining and retrieving an intention (Burgess et al., 2001, 2003; Costa et al., 2011; Simons et al. 2006). One aim of the current paper was to highlight the various factors that contribute to PM failures and to anchor those in our Five-phase model of PM. To date, the majority of depression-related PM impairments appear to be driven by failure at the maintenance/monitoring and/or retrieval phases. Critical processes required during the maintenance/monitoring phase include retaining and updating one's intention, and actively monitoring the environment for the presence of a PM cue or the arrival of the appropriate time to complete an intended action. The retrieval phase is characterized by recalling the previously formed intention, which may occur spontaneously when a strong associative link was established between a PM cue and an intention. Alternatively, retrieval may require more strategic or effortful attempts to recall the intention that was associated with a PM cue. The one study that examined the role of inhibition in PM among depressed participants revealed a depression-related deficit in PM performance that implicates the inhibition phase (Chen et al., 2013). Although no studies have attempted to isolate the relation between planning and PM in depression, established findings of reduced planning ability in individuals with depression (Andersson et al. 2010) and research that highlights the importance of planning in successful PM (Shum et al. 2013), suggests that it is likely that depressive symptoms culminate in PM impairment due to poor planning in the development phase. It is also quite possible that future work in the area of depression and PM will reveal PM impairments that are secondary to breakdowns in the execution phases of our model, though failures at that stage of the model may be associated only with more severe depression. From a clinical perspective, current knowledge regarding the relations between depression and PM represents an opportunity to identify possible cognitive constraints upon the effectiveness of therapeutic interventions. Increased understanding among therapists and other healthcare providers of the cognitive mechanisms that underlie PM failures may lead to improvements in patient care and treatment outcomes. For example, whereas for some patients a failure to complete homework exercises might be indicative of resistance to change or a lack of motivation, for others the problem might be one of reduced executive functioning abilities, which results in PM failures related to the completion of the exercises. Limitations It is important to enumerate key limitations to the interpretation of the findings described above. First, compared to the vast body of research into retrospective memory, relatively little is known about PM and even less is understood about the nature of PM in depression. Inconsistencies in the extant literature regarding the relations between depressive symptoms and PM may be related to several factors. These factors include methodological differences, including differences in the type of PM task examined (i.e., event- vs. time-based), the nature of PM cues (e.g., focal vs. non-focal), the cognitive demands of ongoing tasks, and the methods and measures used to classify participants as depressed (e.g., clinical interview, BDI-II, Geriatric Depression Scale, etc.). Additionally, we decided to include mood induction studies because we believe they can provide valuable insight into the aspects of depression that may affect PM. However, mood induction studies are not proxies for the broad clinical manifestation of depression. Future Directions In addition to further clarifying the basic relations between depressive disorders and PM, future studies would benefit from further examination of the mechanism(s) responsible for PM failure among individuals with depression. If, as hypothesized, executive functioning deficits are responsible for poor PM among people with depression, it will be important to understand the role that monitoring, inhibition, or task-switching difficulties may play. One glaring omission in the extant literature is investigation of the role that planning may play in the relation between depressive symptoms and PM. Planning may be a critical link in the chain of processes that must be engaged to successfully complete a PM task, and has been shown to be impaired in depression (Andersson et al. 2010). Future work would benefit from continued investigation of the role of prefrontal cortical functions and their affect on PM performance among individuals with depression. The field could benefit from more naturalistic studies. Thus far, only one study has investigated the relation between depression and PM performance outside the laboratory (Jeong & Cranney, 2009). Although lab-based paradigms are developed with real-world implications in mind, subtle, but critical differences may emerge between lab-based findings and those of naturalistic paradigms, as has been observed in studies of PM and aging (Phillips, Henry, & Martin, 2008; Rendell & Craik, 2000). Implementation of ecologically valid, naturalistic paradigms in individuals with depressive disorders could only serve to deepen our understanding of the real-world implications of PM deficits. Understanding of the relations between depressive symptoms and PM would also benefit from investigating the role that rumination may play. Rumination, which is characterized by repetitive focus on the causes and potential effects of current distress (Nolen-Hoeksema, 1991), has been associated with impairments in a range of executive functions, including performance deficits in working memory (Watkins & Brown, 2002), inhibition (Philippot & Brutoux, 2008; Whitmer & Banich, 2007), and task switching (Davis & Nolen-Hoeksema, 2000). In depression, it is possible that rumination could occupy attentional resources at the expense of PM-relevant environmental cues or events. Critically, recent work suggests that rumination may moderate the relation between depression and cognitive impairment (Whitmer & Gotlib, 2012). Thus, the study of rumination may provide a critical avenue by which to better understand the relations between depression and PM. Finally, it will be important to investigate the effectiveness of interventions aimed at improving PM. Several strategies have been shown to improve PM among other populations, including the use of visual imagery (Grilli & McFarland, 2011; McFarland & Glisky, 2012) and implementation intentions (i.e., verbal “if, then” statements; Gollwitzer, 1993, 1996, 1999), both of which appear to increase the spontaneous recognition of PM cues and the associated strength of cue-intention pairing and subsequently reduce demands on self-initiated processing both in terms of maintenance/monitoring and retrieval. Promising results have also been reported by Fish and colleagues, who have attempted to improve PM among brain-injured individuals using “content-free” cueing (Fish et al., 2007), which appears to act on the maintenance/monitoring phase, and errorless learning (Fish, Manly, Kopelman, & Morris, 2015), which likely targets the development and retrieval phases. 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Journal

Archives of Clinical NeuropsychologyOxford University Press

Published: Nov 1, 2018

References

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