The Role of Apathy and Depression on Verbal Learning and Memory Performance After Stroke

The Role of Apathy and Depression on Verbal Learning and Memory Performance After Stroke Abstract Objective Psychiatric symptoms, including depression and apathy, may significantly impede functional and cognitive capabilities following a cerebrovascular event. This study examined the role of apathy and depression on learning and memory performance in stroke patients. Method Stroke patients (n = 140 [119 ischemic, 21 hemorrhagic], mean age = 60.6 [SD = 15.1]) completed the Apathy Evaluation Scale (AES), the Center for Epidemiologic Studies Depression Scale (CES-D), and the California Verbal Learning Test-Second Edition (CVLT-II). Results Using a 2 × 2 MANOVA with depression (CESD ≥ 16) and apathy (AES ≥ 34) as the independent variables and cognitive performance (i.e., verbal acquisition, short-term free recall, and long-term free recall) as the dependent variables, we found a main effect for apathy (F[3,134] = 2.98, p = .034), such that apathetic stroke patients (n = 24) performed significantly worse on verbal acquisition (F[1,136] = 6.44; p = .012), short-term free recall (F[1,136] = 7.86; p = .006), and long-term free recall (F[1,136] = 8.37; p = .004) than nonapathetic stroke patients (n = 116). There was no main effect of depression on cognitive performance (F[1,136] = 1.72, p = .155). Conclusions These results suggest that apathy, not depression, is related to verbal memory performance in stroke patients. Future research should explore whether treatment of apathy (e.g., improving motivation) could be a novel target for improving cognition after stroke. Researchers should also examine whether this model can be applied to other aspects of cognition, including executive function and other areas of memory including autobiographical and working memory. Learning and memory, Apathy, motivation, Cerebrovascular disease/accident and stroke, Cognition, Depression Apathy, meaning “lack of passion,” is characterized by diminished goal-directed behavior (e.g., lack of effort), decreased goal-directed cognition (e.g., lack of interest in learning/pursuing new experiences), and blunted emotion (e.g., unchanging affect; Marin, 1991). It has been shown to negatively impact various aspects of an individual’s life, including one’s functional status, social activity, and physical ability (Kaufer et al., 1998; Starkstein, Federoff, Price, Leiguarda, & Robinson, 1993). Apathy has been found to occur in clinical and non-clinical populations, including stroke, Parkinson’s disease, dementia, depression, and healthy adult populations (Adams, 2001; Lyketsos et al., 2002; Okada, Kobayashi, Yamagata, Takahashi, & Yamaguchi, 1997). Apathy is related to depression and is also a symptom of dysexecutive syndromes (Levy & Dubois, 2006). In contrast to apathy, depression is characterized by feelings of sadness, low mood, and helplessness (American Psychiatric Association, 2013). Accompanying symptoms may include guilt, suicidal ideation, sleep irregularities, and appetite abnormalities (American Psychiatric Association, 2013). Individuals with either apathy or depression may also experience a reduction in interest, energy, or insight. Although depression and apathy are related to each other, they can occur separately from one another (Brodaty et al., 2005; Starkstein et al., 1992). Psychiatric symptoms, including depression and apathy, may seriously impede an individual’s functional and cognitive capabilities following a vascular event (Hosking, Marsh, & Friedman, 2000). Apathy is present in approximately 20%–50% of individuals after experiencing a stroke (Brodaty et al., 2005; Van Reekum, Stuss, & Ostrander, 2005). Similarly, approximately 33% of stroke survivors exhibit depressive symptoms after a stroke (Hackett, Yapa, Parag, & Anderson, 2005). Furthermore, meta-analyses posit that apathy occurs nearly as frequently as depression in neurological disorders, although apathy has only gained attention over the past few decades as an important neuropsychiatric construct (Caeiro, Ferro, & Costa, 2013; Van Dalen, Moll van Charante, Nederkoorn, van Gool, & Richard, 2013). Both apathy and depression have been related to cognitive impairment after stroke, but in different studies. Cognitive impairment is three times more frequent in stroke patients with apathy than without apathy (Hama et al., 2007; Yamagata, Yamaguchi, & Kobayashi, 2004). Deficits in attention, working memory, reasoning, and processing speed have been commonly observed in apathetic stroke patients (Caeiro et al., 2013; Withall, Brodaty, Altendorf, & Sachdev, 2011). Stroke patients with apathy had lower memory performance than individuals without apathy (Hama, Yamashita, Yamawaki, & Kurishu, 2011). Impairments in verbal fluency (Fishman et al., 2017; Yamagata et al., 2004) and executive dysfunction (Feil, Razani, Boone, & Lesser, 2003; Withall, Brodaty, Altendorf, & Sachdev, 2011) have been correlated with greater apathy scores. A similar relationship exists between post-stroke depression (PSD) and cognitive impairment (Andersen, Vestergaard, Ingemann-Nielsen, & Lauritzen, 1995; Bour et al., 2010; Donnellan et al., 2016; Kauhanen et al., 1999). Memory, attention, and psychomotor speed are the domains most commonly affected among patients with PSD (Kauhanen et al., 1999). Additionally, stroke patients with executive dysfunction are more depressed than stroke patients without executive dysfunction (Bour et al., 2010). Apathy is also a feature of dysexecutive syndromes (Ardila, 2013). Dysexecutive syndrome encompasses difficulties with planning, organizing, problem solving, initiating, and completing tasks (Levy & Dubois, 2006). Damage to the frontal lobes and frontal subcortical circuits commonly cause dysexecutive syndromes, which may include emotional and behavioral changes in individuals (Repoves & Baddeley, 2006). Impairments in the frontal-subcortical circuit have frequently been associated with apathy (Bonelli & Cummings, 2007; Van Dalen et al. 2013). Additionally, although memory consolidation is dependent on the medial temporal lobe (e.g., hippocampus, entorhinal cortex, perirhinal cortex; Achim, Bertrand, Montoya, Malla, & Lepage, 2007), the prefrontal cortex is believed to underlie memory encoding and retrieval (Alvarez & Squire, 1994). Research has shown that the prefrontal cortex is activated by memory recall tasks (Badre & Wagner, 2007). Specifically, the dorsolateral prefrontal cortex (dlPFC; Blumenfeld & Ranganath, 2006) and ventrolateral prefrontal cortex (vlPFC; Badre & Wagner, 2007) have been found to contribute to memory performance, and these regions are essential to frontal-subcortical circuitry. The ACC and dlPFC are also functionally interconnected (Sallet et al., 2011). Lesions or damage to ACC and/or dlPFC frontal-subcortical circuits (which involve projections to the caudate nucleus) have been found to impact motivational control (Bonelli & Cummings, 2007; Tekin & Cummings, 2002), and cause severe apathy (Kumral, Evyapan, & Balkir, 1999). Researchers have posited that apathy may impact learning and memory regardless of depression (Pluck & Brown, 2002). In support of this notion, Butterfield, Cimino, Oelke, Hauser, and Sanchez-Ramos (2010) reported that after controlling for depressive symptoms, apathy accounted for marginally significant impairment in short-term memory, whereas after controlling for apathy, depression did not predict memory impairment in patients with Parkinson’s disease. Scheurich et al. (2008) and Benitez, Horner, and Bachman (2011) also found that individuals with depression who either used goal-setting techniques or provided adequate effort did not perform worse on neurocognitive tests than non-depressed individuals. Additionally, Santangelo et al. (2009) and Cohen, Weingartner, Smallberg, Pickar, and Murphy (1982) did not find a significant effect of depression on any neuropsychological tests, and found that apathy alone was sufficient in predicting cognitive dysfunction in individuals with Parkinson’s disease and depression, respectively. These studies suggest a greater role of apathy than depression on memory performance, but in a different population. Although studies have examined the role of depression and apathy on cognition in stroke patients, few studies have examined these constructs in the same study. As a result, specific mood–memory relationships remain understudied and underappreciated in vascular populations. Many studies have also used small sample sizes (Hochstenbach, Mulder, van Limbeek, Rogier, & Schoonderwaldt, 1998) or assessed learning and memory impairment in very specific types of stroke (Van der Werf et al., 2003). Additionally, the association between apathy and cognitive function may be confounded by age, education, or other medical conditions (e.g., diabetes; Clarke, Ko, Lyketsos, Rebok, & Eaton, 2010; Mayo, Fellows, Scott, Cameron, & Wood-Dauphinee, 2009). The current study aimed to help clarify the roles of apathy and depression on verbal learning and memory performance in stroke patients by examining these constructs together, including a substantially larger sample size, by taking into account the age and education of participants, as well as other potential medical confounds. Given the role of apathy as a symptom of dysexecutive syndromes and a construct that may overlap with depression, apathetic stroke patients may exhibit deficits in learning and memory regardless of depression diagnosis. We hypothesized that apathetic stroke patients (Apathy Evaluation Scale ([Marin, 1991]) ≥34, consistent with Andersson, Krogstad, and Finset ([1999]), and Kant, Duffy, and Pivovarnik ([1998])) would have impaired cognitive performance (measured by memory acquisition, short-term free recall, and long-term free recall on the California Verbal Learning Test-II; Delis, Kramer, Kaplan & Ober, 2000) after scaling scores by age and years of education, regardless of depression (as measured by the Center for Epidemiologic Studies Depression Scale ([Radloff, 1977]) ≥16, consistent with Lewinsohn, Seeley, Roberts, and Allen ([1997])). Methods This research project was conducted as part of the “Depression, Obstructive Sleep Apnea, and Cognitive Impairment” Study, which examined the use of a brief screening tool to assess patients for common post-stroke comorbidities (Swartz et al., 2017). All testing took place at the Secondary Stroke Prevention Clinic at Sunnybrook Health Sciences Centre in Toronto, Canada. The Institute’s ethics board approved all study procedures. The research was completed in accordance with the Helsinki Declaration. Participants Participants were individuals with stroke at the Secondary Stroke Prevention Clinic in Toronto. One hundred fifty-eight non-aphasic, English speaking stroke patients without motor/visual impairments consented to complete a neuropsychological examination. Multivariate outliers (n = 2) and participants with over 80% of missing data for the tests related to this study (n = 11) were excluded from analysis. Participants who did not complete any memory testing were also excluded (n = 5). In total, 140 stroke patients participated in this study. The study took place between April 23, 2012 and April 30, 2014. The mean age of study participants (N = 140) was 60.50 (SD = 15.3, range = 17–95) years and 44.3% (n = 63) were female. Participants reported on average 15.5 years (SD = 4.4, range = 5–30) of education. Forty-one participants were classified as “depressed,” consistent with the cut-off score of greater than or equal to 16 (Lewinsohn et al., 1997) on the CES-D (Radloff, 1977). Twenty-four participants were classified as “apathetic,” consistent with the cut-off score of greater than or equal to 34 (Andersson et al. 1999; Kant et al. 1998; Sagen et al., 2010) on the AES (Marin, 1991). Seventeen individuals were both apathetic and depressed, seven individuals were only apathetic, 24 individuals were only depressed, and 92 individuals were neither apathetic nor depressed. Of the 140 stroke patients, 119 (83.8%) had ischemic events and 23 (16.2%) had hemorrhagic events. There were no differences in age, sex, years of education, or medical diagnoses (e.g., diabetes, history of vascular disease) between individuals with ischemic versus hemorrhagic strokes, There were no differences in verbal acquisition (F = 1.96, p = .16), short-term free recall (F = 1.10, p = .29), long-term free recall (F = .82, p = .37), education (F = 3.73, p = .06), sex (F = 1.56, p = .21), or age (F = 1.93, p = .167) for individuals with ischemic versus hemorrhagic strokes. Additionally, there were no differences in verbal acquisition (F = .02, p = .88), short-term free recall (F = .68, p = .41), long-term free recall (F = .06, p = .81), education (F = 3.73, p = .06), sex (F = 1.56, p = .21), or age (F = 1.93, p = .167) for individuals with left- versus right-hemisphere strokes. There were significantly more depressed (CES-D ≥ 16) apathetic stroke patients than nonapathetic stroke patients, χ2 = 23.97, p < .001. Participants did not differ from excluded participants (n = 18) in terms of age, years of education, location of cerebrovascular event, type of stroke, smoking status, family history of cerebrovascular disease, or diabetes/autoimmune disease/obstructive sleep apnea diagnosis. Additional participant information is included in Table 1. Table 1. Participant characteristics Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 aThere were 80 cases missing. bThere were 28 cases missing. cThere were 38 cases missing. Table 1. Participant characteristics Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 aThere were 80 cases missing. bThere were 28 cases missing. cThere were 38 cases missing. Materials DOC Case Report Form (DOC-CRF). The DOC-CRF extracted information on demographic status and prior medical history, including previous cerebrovascular disease risk factors, alcohol intake, BMI, diagnosis, smoker status, as well as other diagnoses (e.g., cancer, diabetes). Apathy Evaluation Scale (AES; Marin, 1991). Participants answered 18 questions regarding participants’ interest in learning and having new experiences, taking initiative, being motivated, and putting effort into tasks. They responded to these statements using a Likert-type scale ranging from 1 (Not at all) to 4 (A lot). AES scores range from 18 to 60, with higher scores indicating greater apathy. Cronbach’s alpha for the AES was .87 in this study. Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977). The CES-D is a 20-item questionnaire that measures depressive symptomatology over the past week (Radloff, 1977). Participants were asked questions about their sleep patterns, appetite, as well as feelings of fear, loneliness, and hopelessness. Participants responded to statements using a Likert-type scale ranging from 0 (Rarely or none of the time) to 3 (Most or almost all of the time). CES-D scores range from 0 to 60, with higher scores indicating greater depressive symptomatology. Cronbach’s alpha for the CES-D was .90 in this study. California Verbal Learning Test-Second Edition (CVLT-II; Delis et al. 2000). The CVLT-II is a frequently used neuropsychological measure that assesses auditory-verbal learning, recall, and recognition of words. The word list was created from four unrelated semantic categories; furniture, modes of transportation, animals, and vegetables (Delis et al., 2000). In the current study, only verbal acquisition, short-term free recall, and long-term free recall scores were utilized for analysis. Procedure Participants at the Secondary Stroke Prevention Clinic completed a 5-min, brief screen for depression, obstructive sleep apnea, and cognitive impairment (“DOC” screen), as part of clinical standard of care. Patients were approached by research assistants, nurses, or doctors and asked to consent to participate in more detailed neuropsychological assessments at a time suitable for the participant. Research assistants obtained informed consent from all participants. Out of the larger battery, for the purposes of this study, participants completed the CES-D, AES, and CVLT-II. Data Analysis SPSS version 21, 64-bit edition, was used for data analysis. Of the patients retained for analysis, there were 24 (.5%) missing cells from the AES, and 51 (.9%) missing cells from the CES-D. This missing data was handled using expectation maximization. The results of Little’s MCAR test indicated that the data were missing completely at random, χ2 = 584.89, df = 519, p = .824. Scores for memory acquisition, short-term free recall, and long-term free recall were scaled according to age, sex, and years of education (Delis et al., 2000). We conducted a 2 × 2 MANOVA to examine whether apathy and depression (two independent variables) impacted (1) verbal memory acquisition (i.e., word learning), (2) short-term free recall, and (3) long-term free recall in stroke patients. Depression (CESD ≥ 16) and apathy (AES ≥34) were entered into the MANOVA as independent variables, and verbal acquisition, short-term free recall, and long-term free recall were entered into the MANOVA as dependent variables. A 2 × 2 MANCOVA was also conducted to control for potential medical confounds, including past stroke, family history of cardiovascular disease, diabetes, smoking status, alcohol use, obstructive sleep apnea, past stroke, and time since stroke. Results A two-way MANOVA revealed a significant multivariate main effect for apathy, Wilks’ λ = .94, F(3,134) = 2.98, p = .034, partial η2 = .063. There was no significant multivariate main effect for depression (p = .155). The interaction between apathy and depression on cognitive performance was also not significant (p = .622; see Table 2). Table 2. Multivariate analysis of variance (MANOVA) for the role of apathy and depression on cognitive performance Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 *p < .05. Table 2. Multivariate analysis of variance (MANOVA) for the role of apathy and depression on cognitive performance Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 *p < .05. Significant univariate main effects for apathy were found for verbal acquisition (F[1,136] = 6.44, p = .012), short-term free recall (F[1,136] = 7.86, p = .006), and long-term free recall (F[1,136] = 8.37, p = .004), such that apathetic stroke patients performed significantly worse than nonapathetic stroke patients on these tasks. These results remained significant after implementing a Bonferroni correction (0.05/3 = .016). Specifically, apathetic stroke patients (verbal acquisition: M = −.46, SD = 1.21; short-term free recall: M = −.88, SD = 1.28; long-term free recall: M = −1.02, SD = 1.30) had significantly worse learning and memory than nonapathetic stroke patients (verbal acquisition: M = −.06, SD = 1.05; short-term free recall: M = −.27, SD = 1.12; long-term free recall: M = −.43, SD = 1.09; see Fig. 1). The results did not change after controlling for depression (CES-D ≥ 16). Fig. 1. View largeDownload slide Main effect of apathy on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Fig. 1. View largeDownload slide Main effect of apathy on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). The univariate post-hoc analyses for depression revealed a main effect of depression on verbal acquisition, such that depressed stroke patients (M = .04, SD = 1.01) had significant better verbal acquisition scores than non-depressed stroke patients (M = −.20, SD = 1.11), F(1,136) = 5.37, p = .022 (see Fig. 2). However, this effect did not remain statistically significant when the Bonferroni correction (.05/3 = .016) was applied. No significant effects were observed for depression on short-term (p = .108) or long-term (p = .085) recall. Fig. 2. View largeDownload slide Main effect of depression on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Fig. 2. View largeDownload slide Main effect of depression on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Medical Confounds A 2 × 2 MANCOVA was also conducted to examine whether these findings could be accounted for by other medical considerations associated with cognitive functioning in stroke patients, including diabetes diagnosis, family history of cardiovascular disease, past stroke, time since most recent stroke, alcohol use, smoking status, and obstructive sleep apnea. As shown in Table 3, none of the covariates were significant in the model. In addition, the results did not change after controlling for these variables, as there was a significant main effect of apathy on cognitive performance (Wilks’ λ = .89, F(3,101) = 4.35, p = .006, partial η2 = .12). Table 3. Multivariate analysis of covariance (MANCOVA) for the role of apathy and depression on cognitive performancea Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 *p ≤ .05. a26 cases missing. Table 3. Multivariate analysis of covariance (MANCOVA) for the role of apathy and depression on cognitive performancea Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 *p ≤ .05. a26 cases missing. Discussion In this study, 140 stroke patients from a Secondary Stroke Prevention Clinic underwent neuropsychological testing to examine the role of apathy and depression on verbal learning and memory performance. Memory acquisition, short-term free recall, and long-term free recall were assessed using the CVLT-II (Delis et al., 2000). Using a 2 × 2 MANOVA and a 2 × 2 MANCOVA, we found a main effect of apathy on memory performance, such that apathetic stroke patients performed significantly worse than nonapathetic stroke patients on verbal acquisition, short-term free recall, and long-term free recall on the CVLT-II, regardless of depression. There was no difference in memory performance on the CVLT-II between depressed versus non-depressed individuals, apart from verbal acquisition (i.e., depressed individuals performed superior to non-depressed individuals). However, this effect was no longer significant after applying the Bonferroni correction. Therefore, this result should be interpreted with reservations. These results provide support that apathy is a separate construct from depression, and that apathy may play a more pivotal role in learning and memory performance than depression in stroke patients. Researchers have suggested that the relationship between depression and memory performance is largely due to a deficiency in motivation. Motivation, defined as “the ability to initiate appropriate activity either spontaneously or in response to environmental cues” (Lezak, 1995), is the crucial component of apathy (Marin, 1991). As such, apathy, which encompasses decreases in goal-oriented behavior/cognition and increases in emotional indifference, may be the key link between depression and cognitive performance (Lezak, 1995; Santangelo et al., 2009; Scheurich et al., 2008). This theory complements the results of our study. Scheurich et al. (2008) found that goal-setting significantly improved verbal memory performance in patients with depression when compared with standard instructions. When these goal-setting strategies were utilized, depressed patients performed similarly on memory measures as healthy controls (Scheurich et al., 2008). Another study found that depressed individuals performed significantly worse than non-depressed individuals on immediate memory, language, delayed memory, and attention (Benitez et al. 2011). However, when individuals were excluded who did not provide adequate effort, there were no group differences in cognitive performance, regardless of depression diagnosis (Benitez et al. 2011). These results support that cognition may be more affected by symptoms of apathy than symptoms of depression. The results of this study exemplify a link between apathy and cognitive performance in stroke patients, but not between depression and cognitive performance. The stronger ties between apathy and memory, rather than depression and memory, have been previously reported in Parkinson’s disease (Pluck & Brown, 2002; Varanese, Perfetti, Ghilardi, & Di Rocco, 2011). Santangelo et al. (2009) and Cohen and colleagues (1982) did not find a significant effect of depression on any neuropsychological tests, and found that apathetic patients were more cognitively impaired than nonapathetic patients with Parkinson’s disease and depression, respectively. These studies support our findings that apathy impacts cognitive performance, regardless of (and after controlling for) depression (CES-D ≥ 16), and is consistent with our findings that apathy and cognitive performance are also linked in stroke populations. Apathy may be a better indicator of impaired learning and memory (due to low motivational resources) than depression in stroke patients. It is also important to distinguish between depression and apathy in order to optimize treatment outcomes. Widely prescribed antidepressant medications for treatment of depressive disorders include selective serotonin reuptake inhibitors (SSRIs; e.g., citalopram, escitalopram, fluoxetine, sertraline; De Lima & Hotopf, 2003). However, SSRIs are associated with increased behavioral and affective indifference (Barnhart, Makela, & Latocha, 2004; Lee & Keltner, 2005; Wongpakaran, Van Reekum, Wongpakaran, & Clarke, 2007). Qualitative studies have reported decreases in emotional expression and reduced motivation in individuals taking SSRIs (Garland & Baerg, 2004). Wongpakaran et al. (2007) reported that individuals being treated for depression with SSRIs described more apathetic symptoms than individuals being treated with non-SSRIs, although they experienced a decrease in depressive symptoms. Medication-induced apathetic symptoms were also found with serotonin-noradrenaline reuptake inhibitors and mood stabilizers (Price, Cole, & Goodwin, 2009). However, brain-injured individuals who were prescribed dopamine stimulants (bromocriptine and amantadine) reported decreases in apathy symptoms and improved cognitive function (Kraus & Maki, 1997; Powell, Al-Adawi, Morgan, & Greenwood, 1996). No changes in depressive or anxiety symptoms were observed using bromocriptine treatment (Powell et al., 1996). As such, improperly identifying neuropsychiatric symptoms may detrimentally affect treatment outcomes and, in turn, may further impair cognitive functioning (Powell et al., 1996; Price et al., 2009; Wongpakaran et al., 2007). Limitations to this study include the self-report nature of assessing apathy. Given that apathetic individuals may have poor insight into their symptoms, rates of apathy may have been underestimated, as observed in Njomboro and Deb’s (2012) study. In addition, individuals were classified as apathetic if their AES score was equal to or greater than 34, consistent with Andersson and colleagues (1999), Kant and colleagues (1998), and Sagen et al. (2010). Individuals were identified as depressed when their CES-D score was greater than or equal to 16, consistent with Lewinsohn and colleagues (1997). Although these cutoffs have excellent sensitivity and specificity (e.g., Beekman et al., 1997), a clinical interview, such as the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), may reduce the rate of potential false positives (American Psychiatric Association, 2013). Given the larger variability in CVLT-II acquisition, short-term recall, and long-term free recall performance (which may be expected with a range of brain damage severity), future studies should focus on replicating these findings in order to strengthen the study’s conclusions and implications. Lastly, there were missing cases regarding stroke laterality and the degree of anterior cerebrovascular damage, which may affect depression prevalence (Narushima, Kosier, & Robinson, 2003). Despite these limitations, there are a number of strengths to the current study. To our knowledge, this is one of few studies that has examined the impact of apathy and depression on learning and memory performance in the same study in a stroke sample. Other studies have either ignored the role of apathy (Donnellan et al., 2016) or depression (Mayo, Fellows, Scott, Cameron & Wood-Dauphinee, 2009) in neuropsychological evaluations. We also controlled for a range of potential medical confounders, including diabetes, past stroke, days since most recent stroke, family history of cardiovascular disease, obstructive sleep apnea, smoking status, and alcohol use, which did not impact the results of the study. The results of this study offer preliminary support for the role of apathy, and not depression, in verbal learning and memory in stroke patients. As both an important feature of dysexecutive syndromes (Ardila, 2013) and a construct related to depression, these results suggest that apathy may potentially better indicate difficulties with verbal learning and memory than depression. However, additional research should continue to explore the role of apathy in cognitive functioning. Future research should also examine whether this model can be applied to other populations and other aspects of learning and memory, such as autobiographical memory and working memory. Additionally, given that emotional indifference is a hallmark symptom of apathy, and apathetic individuals experience greater difficulty with emotional recognition (Hanby, 2014), it may be of interest to examine apathy’s role in emotional verbal memory test performance (e.g., Emotional Verbal Learning Test; Strauss & Allen, 2013). These studies would allow researchers to further explore the emotion–cognition interaction. Given its prevalence across neurodegenerative diseases, acquired brain injuries, psychiatric disorders, and healthy adults, as well as its detrimental impact on social and physical ability, functional recovery, and treatment optimization, it is surprising that apathy has not received more attention in the literature (Kaufer et al., 1998; Starkstein et al., 1993). There is a need to better understand the unique effect of apathy, to appropriately identify symptoms of apathy, and to improve neuropsychological models of their effects in patients with vascular pathology. Future work may then determine whether treatments targeting apathy could serve as a novel approach to improving cognitive outcomes and to enhance patient and caregiver quality of life after stroke. Funding This work was supported by the Heart and Stroke Foundation of Ontario (Grant number 000392 to R.H.S.); and the Canadian Institutes of Health Research (Grant number 1012404 to R.H.S.); and an Alexander Graham Bell Natural Sciences and Engineering Research Council of Canada (NSERC) Graduate Scholarship (K.N.F.). R.H.S. receives salary support from a New Investigator Award and the HJ Barnett Award from the Heart and Stroke Foundation of Canada, the Canadian Partnership for Stroke Recovery, the Department of Medicine (Sunnybrook Health Sciences Centre and University of Toronto), and the Brill Chair in Neurology at Sunnybrook Health Sciences Centre. Conflicts of interest There are no conflicts of interest to disclose. References Achim , A. M. , Bertrand , M. 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The Role of Apathy and Depression on Verbal Learning and Memory Performance After Stroke

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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0887-6177
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1873-5843
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10.1093/arclin/acy044
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Abstract

Abstract Objective Psychiatric symptoms, including depression and apathy, may significantly impede functional and cognitive capabilities following a cerebrovascular event. This study examined the role of apathy and depression on learning and memory performance in stroke patients. Method Stroke patients (n = 140 [119 ischemic, 21 hemorrhagic], mean age = 60.6 [SD = 15.1]) completed the Apathy Evaluation Scale (AES), the Center for Epidemiologic Studies Depression Scale (CES-D), and the California Verbal Learning Test-Second Edition (CVLT-II). Results Using a 2 × 2 MANOVA with depression (CESD ≥ 16) and apathy (AES ≥ 34) as the independent variables and cognitive performance (i.e., verbal acquisition, short-term free recall, and long-term free recall) as the dependent variables, we found a main effect for apathy (F[3,134] = 2.98, p = .034), such that apathetic stroke patients (n = 24) performed significantly worse on verbal acquisition (F[1,136] = 6.44; p = .012), short-term free recall (F[1,136] = 7.86; p = .006), and long-term free recall (F[1,136] = 8.37; p = .004) than nonapathetic stroke patients (n = 116). There was no main effect of depression on cognitive performance (F[1,136] = 1.72, p = .155). Conclusions These results suggest that apathy, not depression, is related to verbal memory performance in stroke patients. Future research should explore whether treatment of apathy (e.g., improving motivation) could be a novel target for improving cognition after stroke. Researchers should also examine whether this model can be applied to other aspects of cognition, including executive function and other areas of memory including autobiographical and working memory. Learning and memory, Apathy, motivation, Cerebrovascular disease/accident and stroke, Cognition, Depression Apathy, meaning “lack of passion,” is characterized by diminished goal-directed behavior (e.g., lack of effort), decreased goal-directed cognition (e.g., lack of interest in learning/pursuing new experiences), and blunted emotion (e.g., unchanging affect; Marin, 1991). It has been shown to negatively impact various aspects of an individual’s life, including one’s functional status, social activity, and physical ability (Kaufer et al., 1998; Starkstein, Federoff, Price, Leiguarda, & Robinson, 1993). Apathy has been found to occur in clinical and non-clinical populations, including stroke, Parkinson’s disease, dementia, depression, and healthy adult populations (Adams, 2001; Lyketsos et al., 2002; Okada, Kobayashi, Yamagata, Takahashi, & Yamaguchi, 1997). Apathy is related to depression and is also a symptom of dysexecutive syndromes (Levy & Dubois, 2006). In contrast to apathy, depression is characterized by feelings of sadness, low mood, and helplessness (American Psychiatric Association, 2013). Accompanying symptoms may include guilt, suicidal ideation, sleep irregularities, and appetite abnormalities (American Psychiatric Association, 2013). Individuals with either apathy or depression may also experience a reduction in interest, energy, or insight. Although depression and apathy are related to each other, they can occur separately from one another (Brodaty et al., 2005; Starkstein et al., 1992). Psychiatric symptoms, including depression and apathy, may seriously impede an individual’s functional and cognitive capabilities following a vascular event (Hosking, Marsh, & Friedman, 2000). Apathy is present in approximately 20%–50% of individuals after experiencing a stroke (Brodaty et al., 2005; Van Reekum, Stuss, & Ostrander, 2005). Similarly, approximately 33% of stroke survivors exhibit depressive symptoms after a stroke (Hackett, Yapa, Parag, & Anderson, 2005). Furthermore, meta-analyses posit that apathy occurs nearly as frequently as depression in neurological disorders, although apathy has only gained attention over the past few decades as an important neuropsychiatric construct (Caeiro, Ferro, & Costa, 2013; Van Dalen, Moll van Charante, Nederkoorn, van Gool, & Richard, 2013). Both apathy and depression have been related to cognitive impairment after stroke, but in different studies. Cognitive impairment is three times more frequent in stroke patients with apathy than without apathy (Hama et al., 2007; Yamagata, Yamaguchi, & Kobayashi, 2004). Deficits in attention, working memory, reasoning, and processing speed have been commonly observed in apathetic stroke patients (Caeiro et al., 2013; Withall, Brodaty, Altendorf, & Sachdev, 2011). Stroke patients with apathy had lower memory performance than individuals without apathy (Hama, Yamashita, Yamawaki, & Kurishu, 2011). Impairments in verbal fluency (Fishman et al., 2017; Yamagata et al., 2004) and executive dysfunction (Feil, Razani, Boone, & Lesser, 2003; Withall, Brodaty, Altendorf, & Sachdev, 2011) have been correlated with greater apathy scores. A similar relationship exists between post-stroke depression (PSD) and cognitive impairment (Andersen, Vestergaard, Ingemann-Nielsen, & Lauritzen, 1995; Bour et al., 2010; Donnellan et al., 2016; Kauhanen et al., 1999). Memory, attention, and psychomotor speed are the domains most commonly affected among patients with PSD (Kauhanen et al., 1999). Additionally, stroke patients with executive dysfunction are more depressed than stroke patients without executive dysfunction (Bour et al., 2010). Apathy is also a feature of dysexecutive syndromes (Ardila, 2013). Dysexecutive syndrome encompasses difficulties with planning, organizing, problem solving, initiating, and completing tasks (Levy & Dubois, 2006). Damage to the frontal lobes and frontal subcortical circuits commonly cause dysexecutive syndromes, which may include emotional and behavioral changes in individuals (Repoves & Baddeley, 2006). Impairments in the frontal-subcortical circuit have frequently been associated with apathy (Bonelli & Cummings, 2007; Van Dalen et al. 2013). Additionally, although memory consolidation is dependent on the medial temporal lobe (e.g., hippocampus, entorhinal cortex, perirhinal cortex; Achim, Bertrand, Montoya, Malla, & Lepage, 2007), the prefrontal cortex is believed to underlie memory encoding and retrieval (Alvarez & Squire, 1994). Research has shown that the prefrontal cortex is activated by memory recall tasks (Badre & Wagner, 2007). Specifically, the dorsolateral prefrontal cortex (dlPFC; Blumenfeld & Ranganath, 2006) and ventrolateral prefrontal cortex (vlPFC; Badre & Wagner, 2007) have been found to contribute to memory performance, and these regions are essential to frontal-subcortical circuitry. The ACC and dlPFC are also functionally interconnected (Sallet et al., 2011). Lesions or damage to ACC and/or dlPFC frontal-subcortical circuits (which involve projections to the caudate nucleus) have been found to impact motivational control (Bonelli & Cummings, 2007; Tekin & Cummings, 2002), and cause severe apathy (Kumral, Evyapan, & Balkir, 1999). Researchers have posited that apathy may impact learning and memory regardless of depression (Pluck & Brown, 2002). In support of this notion, Butterfield, Cimino, Oelke, Hauser, and Sanchez-Ramos (2010) reported that after controlling for depressive symptoms, apathy accounted for marginally significant impairment in short-term memory, whereas after controlling for apathy, depression did not predict memory impairment in patients with Parkinson’s disease. Scheurich et al. (2008) and Benitez, Horner, and Bachman (2011) also found that individuals with depression who either used goal-setting techniques or provided adequate effort did not perform worse on neurocognitive tests than non-depressed individuals. Additionally, Santangelo et al. (2009) and Cohen, Weingartner, Smallberg, Pickar, and Murphy (1982) did not find a significant effect of depression on any neuropsychological tests, and found that apathy alone was sufficient in predicting cognitive dysfunction in individuals with Parkinson’s disease and depression, respectively. These studies suggest a greater role of apathy than depression on memory performance, but in a different population. Although studies have examined the role of depression and apathy on cognition in stroke patients, few studies have examined these constructs in the same study. As a result, specific mood–memory relationships remain understudied and underappreciated in vascular populations. Many studies have also used small sample sizes (Hochstenbach, Mulder, van Limbeek, Rogier, & Schoonderwaldt, 1998) or assessed learning and memory impairment in very specific types of stroke (Van der Werf et al., 2003). Additionally, the association between apathy and cognitive function may be confounded by age, education, or other medical conditions (e.g., diabetes; Clarke, Ko, Lyketsos, Rebok, & Eaton, 2010; Mayo, Fellows, Scott, Cameron, & Wood-Dauphinee, 2009). The current study aimed to help clarify the roles of apathy and depression on verbal learning and memory performance in stroke patients by examining these constructs together, including a substantially larger sample size, by taking into account the age and education of participants, as well as other potential medical confounds. Given the role of apathy as a symptom of dysexecutive syndromes and a construct that may overlap with depression, apathetic stroke patients may exhibit deficits in learning and memory regardless of depression diagnosis. We hypothesized that apathetic stroke patients (Apathy Evaluation Scale ([Marin, 1991]) ≥34, consistent with Andersson, Krogstad, and Finset ([1999]), and Kant, Duffy, and Pivovarnik ([1998])) would have impaired cognitive performance (measured by memory acquisition, short-term free recall, and long-term free recall on the California Verbal Learning Test-II; Delis, Kramer, Kaplan & Ober, 2000) after scaling scores by age and years of education, regardless of depression (as measured by the Center for Epidemiologic Studies Depression Scale ([Radloff, 1977]) ≥16, consistent with Lewinsohn, Seeley, Roberts, and Allen ([1997])). Methods This research project was conducted as part of the “Depression, Obstructive Sleep Apnea, and Cognitive Impairment” Study, which examined the use of a brief screening tool to assess patients for common post-stroke comorbidities (Swartz et al., 2017). All testing took place at the Secondary Stroke Prevention Clinic at Sunnybrook Health Sciences Centre in Toronto, Canada. The Institute’s ethics board approved all study procedures. The research was completed in accordance with the Helsinki Declaration. Participants Participants were individuals with stroke at the Secondary Stroke Prevention Clinic in Toronto. One hundred fifty-eight non-aphasic, English speaking stroke patients without motor/visual impairments consented to complete a neuropsychological examination. Multivariate outliers (n = 2) and participants with over 80% of missing data for the tests related to this study (n = 11) were excluded from analysis. Participants who did not complete any memory testing were also excluded (n = 5). In total, 140 stroke patients participated in this study. The study took place between April 23, 2012 and April 30, 2014. The mean age of study participants (N = 140) was 60.50 (SD = 15.3, range = 17–95) years and 44.3% (n = 63) were female. Participants reported on average 15.5 years (SD = 4.4, range = 5–30) of education. Forty-one participants were classified as “depressed,” consistent with the cut-off score of greater than or equal to 16 (Lewinsohn et al., 1997) on the CES-D (Radloff, 1977). Twenty-four participants were classified as “apathetic,” consistent with the cut-off score of greater than or equal to 34 (Andersson et al. 1999; Kant et al. 1998; Sagen et al., 2010) on the AES (Marin, 1991). Seventeen individuals were both apathetic and depressed, seven individuals were only apathetic, 24 individuals were only depressed, and 92 individuals were neither apathetic nor depressed. Of the 140 stroke patients, 119 (83.8%) had ischemic events and 23 (16.2%) had hemorrhagic events. There were no differences in age, sex, years of education, or medical diagnoses (e.g., diabetes, history of vascular disease) between individuals with ischemic versus hemorrhagic strokes, There were no differences in verbal acquisition (F = 1.96, p = .16), short-term free recall (F = 1.10, p = .29), long-term free recall (F = .82, p = .37), education (F = 3.73, p = .06), sex (F = 1.56, p = .21), or age (F = 1.93, p = .167) for individuals with ischemic versus hemorrhagic strokes. Additionally, there were no differences in verbal acquisition (F = .02, p = .88), short-term free recall (F = .68, p = .41), long-term free recall (F = .06, p = .81), education (F = 3.73, p = .06), sex (F = 1.56, p = .21), or age (F = 1.93, p = .167) for individuals with left- versus right-hemisphere strokes. There were significantly more depressed (CES-D ≥ 16) apathetic stroke patients than nonapathetic stroke patients, χ2 = 23.97, p < .001. Participants did not differ from excluded participants (n = 18) in terms of age, years of education, location of cerebrovascular event, type of stroke, smoking status, family history of cerebrovascular disease, or diabetes/autoimmune disease/obstructive sleep apnea diagnosis. Additional participant information is included in Table 1. Table 1. Participant characteristics Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 aThere were 80 cases missing. bThere were 28 cases missing. cThere were 38 cases missing. Table 1. Participant characteristics Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 Stroke patients (N = 140) Apathetic (n = 24) Not apathetic (n= 116) Statistical difference Age M = 60.6 (SD = 15.1), range 17–95 M = 61.3 (SD = 14.6), range 21–87 M = 57.3 (SD = 17.6), range 17–95 t(138) = 1.19, p = .238 Women:men 62:78 (44.3% female) 13:11 49:67 χ2 = 1.14, p = .286 Years of education M = 15.5 (SD = 4.4), range 5–30 M = 15.7 (SD = 5.2), range 7–30 M = 15.6 (SD = 3.7), range 5-26 t(138) = −.08, p = .936 Location of eventa  Left hemisphere 58 (55.8%) 8 (57.1%) 50 (55.6%) χ2 = .01, p = .931  Right hemisphere 39 (37.5%) 5 (35.7%) 34 (37.8%)  Bilateral 7 (6.7%) 1 (7.1%) 6 (6.7%) Type of Stroke χ2 = .74, p = .391  Ischemic 118 (85.0%) 19 (79.2%) 99 (86.1%)  Hemorrhagic 21 (15.0%) 5 (20.8%) 16 (14.0%) Smoking statusb χ2 = 7.24, p = .007  Current 15 (11.7%) 3 (15.0%) 12 (11.1%)  Reformed 11 (8.6%) 6 (30.0%) 5 (4.6%)  Non-smoker 102 (79.7%) 11 (55.0%) 91 (84.3%) Family history of cardiovascular diseasec 37 (26.4%) 5 (20.8%) 32 (27.6%) χ2 = .46, p = .496 Diabetes (diagnosed)c 25 (17.9%) 4 (16.7%) 21 (18.1%) χ2 = .03, p = .868 Autoimmune diseasec 5 (3.6%) 2 (8.3%) 3 (2.6%) χ2 = 1.89, p = .169 Alcohol usec   >2 drinks/day 8 (6.7%) 2 (11.1%) 6 (5.9%) χ2 = 1.90, p = .168   <2 drinks/day 15 (12.5%) 0 15 (14.7%)  Rare/social 61 (50.8%) 8 (44.4%) 53 (52.0%)  Never/not currently 36 (30.0%) 8 (44.4%) 28 (27.5%) Obstructive sleep apnea (diagnosed) 18 (12.9%) 1 (4.2%) 17 (14.7%) χ2 = 1.94, p = .164 CES-D score M = 11.9 (SD = 10.1), range 0–49 χ2 = 23.97, p < .001 # depressed 41 17 24 AES score M = 28.3 (SD = 8.1), range 18–56 # apathetic 24 CVLT acquisition score scaled M = −.12 (SD = 1.1), range −3.5–2.4 CVLT short-term recall score scaled M = −.36 (SD = 1.2), range −3.0–3.0 CVLT long-term recall score scaled M = −.52 (1.2), range −3.0–2.5 aThere were 80 cases missing. bThere were 28 cases missing. cThere were 38 cases missing. Materials DOC Case Report Form (DOC-CRF). The DOC-CRF extracted information on demographic status and prior medical history, including previous cerebrovascular disease risk factors, alcohol intake, BMI, diagnosis, smoker status, as well as other diagnoses (e.g., cancer, diabetes). Apathy Evaluation Scale (AES; Marin, 1991). Participants answered 18 questions regarding participants’ interest in learning and having new experiences, taking initiative, being motivated, and putting effort into tasks. They responded to these statements using a Likert-type scale ranging from 1 (Not at all) to 4 (A lot). AES scores range from 18 to 60, with higher scores indicating greater apathy. Cronbach’s alpha for the AES was .87 in this study. Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977). The CES-D is a 20-item questionnaire that measures depressive symptomatology over the past week (Radloff, 1977). Participants were asked questions about their sleep patterns, appetite, as well as feelings of fear, loneliness, and hopelessness. Participants responded to statements using a Likert-type scale ranging from 0 (Rarely or none of the time) to 3 (Most or almost all of the time). CES-D scores range from 0 to 60, with higher scores indicating greater depressive symptomatology. Cronbach’s alpha for the CES-D was .90 in this study. California Verbal Learning Test-Second Edition (CVLT-II; Delis et al. 2000). The CVLT-II is a frequently used neuropsychological measure that assesses auditory-verbal learning, recall, and recognition of words. The word list was created from four unrelated semantic categories; furniture, modes of transportation, animals, and vegetables (Delis et al., 2000). In the current study, only verbal acquisition, short-term free recall, and long-term free recall scores were utilized for analysis. Procedure Participants at the Secondary Stroke Prevention Clinic completed a 5-min, brief screen for depression, obstructive sleep apnea, and cognitive impairment (“DOC” screen), as part of clinical standard of care. Patients were approached by research assistants, nurses, or doctors and asked to consent to participate in more detailed neuropsychological assessments at a time suitable for the participant. Research assistants obtained informed consent from all participants. Out of the larger battery, for the purposes of this study, participants completed the CES-D, AES, and CVLT-II. Data Analysis SPSS version 21, 64-bit edition, was used for data analysis. Of the patients retained for analysis, there were 24 (.5%) missing cells from the AES, and 51 (.9%) missing cells from the CES-D. This missing data was handled using expectation maximization. The results of Little’s MCAR test indicated that the data were missing completely at random, χ2 = 584.89, df = 519, p = .824. Scores for memory acquisition, short-term free recall, and long-term free recall were scaled according to age, sex, and years of education (Delis et al., 2000). We conducted a 2 × 2 MANOVA to examine whether apathy and depression (two independent variables) impacted (1) verbal memory acquisition (i.e., word learning), (2) short-term free recall, and (3) long-term free recall in stroke patients. Depression (CESD ≥ 16) and apathy (AES ≥34) were entered into the MANOVA as independent variables, and verbal acquisition, short-term free recall, and long-term free recall were entered into the MANOVA as dependent variables. A 2 × 2 MANCOVA was also conducted to control for potential medical confounds, including past stroke, family history of cardiovascular disease, diabetes, smoking status, alcohol use, obstructive sleep apnea, past stroke, and time since stroke. Results A two-way MANOVA revealed a significant multivariate main effect for apathy, Wilks’ λ = .94, F(3,134) = 2.98, p = .034, partial η2 = .063. There was no significant multivariate main effect for depression (p = .155). The interaction between apathy and depression on cognitive performance was also not significant (p = .622; see Table 2). Table 2. Multivariate analysis of variance (MANOVA) for the role of apathy and depression on cognitive performance Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 *p < .05. Table 2. Multivariate analysis of variance (MANOVA) for the role of apathy and depression on cognitive performance Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 Wilks’ λ F df p Partial η2 Apathy .94 2.98 3, 134 .034* .063 Depression .96 1.77 3, 134 .155 .038 Apathy × Depression .99 0.59 3, 134 .622 .013 *p < .05. Significant univariate main effects for apathy were found for verbal acquisition (F[1,136] = 6.44, p = .012), short-term free recall (F[1,136] = 7.86, p = .006), and long-term free recall (F[1,136] = 8.37, p = .004), such that apathetic stroke patients performed significantly worse than nonapathetic stroke patients on these tasks. These results remained significant after implementing a Bonferroni correction (0.05/3 = .016). Specifically, apathetic stroke patients (verbal acquisition: M = −.46, SD = 1.21; short-term free recall: M = −.88, SD = 1.28; long-term free recall: M = −1.02, SD = 1.30) had significantly worse learning and memory than nonapathetic stroke patients (verbal acquisition: M = −.06, SD = 1.05; short-term free recall: M = −.27, SD = 1.12; long-term free recall: M = −.43, SD = 1.09; see Fig. 1). The results did not change after controlling for depression (CES-D ≥ 16). Fig. 1. View largeDownload slide Main effect of apathy on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Fig. 1. View largeDownload slide Main effect of apathy on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). The univariate post-hoc analyses for depression revealed a main effect of depression on verbal acquisition, such that depressed stroke patients (M = .04, SD = 1.01) had significant better verbal acquisition scores than non-depressed stroke patients (M = −.20, SD = 1.11), F(1,136) = 5.37, p = .022 (see Fig. 2). However, this effect did not remain statistically significant when the Bonferroni correction (.05/3 = .016) was applied. No significant effects were observed for depression on short-term (p = .108) or long-term (p = .085) recall. Fig. 2. View largeDownload slide Main effect of depression on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Fig. 2. View largeDownload slide Main effect of depression on verbal acquisition, short-term free recall, and long-term free recall in stroke patients. *Raw scores were scaled by age and years of education (Delis et al., 2000). Medical Confounds A 2 × 2 MANCOVA was also conducted to examine whether these findings could be accounted for by other medical considerations associated with cognitive functioning in stroke patients, including diabetes diagnosis, family history of cardiovascular disease, past stroke, time since most recent stroke, alcohol use, smoking status, and obstructive sleep apnea. As shown in Table 3, none of the covariates were significant in the model. In addition, the results did not change after controlling for these variables, as there was a significant main effect of apathy on cognitive performance (Wilks’ λ = .89, F(3,101) = 4.35, p = .006, partial η2 = .12). Table 3. Multivariate analysis of covariance (MANCOVA) for the role of apathy and depression on cognitive performancea Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 *p ≤ .05. a26 cases missing. Table 3. Multivariate analysis of covariance (MANCOVA) for the role of apathy and depression on cognitive performancea Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 Wilks’ λ F df p Partial η2 Diabetes .96 1.37 3, 101 .256 .04 Family history of cardiovascular issues .98 0.69 .558 .02 Past stroke .96 1.25 .296 .04 Days since most recent stroke .95 1.44 .235 .04 Smoking .98 0.78 .507 .02 Obstructive sleep apnea .97 0.95 .418 .03 Alcohol use .99 0.45 .721 .01 Apathy .89 4.35 .006* .12 Depression .95 1.92 .132 .05 Apathy × Depression .98 0.80 .493 .02 *p ≤ .05. a26 cases missing. Discussion In this study, 140 stroke patients from a Secondary Stroke Prevention Clinic underwent neuropsychological testing to examine the role of apathy and depression on verbal learning and memory performance. Memory acquisition, short-term free recall, and long-term free recall were assessed using the CVLT-II (Delis et al., 2000). Using a 2 × 2 MANOVA and a 2 × 2 MANCOVA, we found a main effect of apathy on memory performance, such that apathetic stroke patients performed significantly worse than nonapathetic stroke patients on verbal acquisition, short-term free recall, and long-term free recall on the CVLT-II, regardless of depression. There was no difference in memory performance on the CVLT-II between depressed versus non-depressed individuals, apart from verbal acquisition (i.e., depressed individuals performed superior to non-depressed individuals). However, this effect was no longer significant after applying the Bonferroni correction. Therefore, this result should be interpreted with reservations. These results provide support that apathy is a separate construct from depression, and that apathy may play a more pivotal role in learning and memory performance than depression in stroke patients. Researchers have suggested that the relationship between depression and memory performance is largely due to a deficiency in motivation. Motivation, defined as “the ability to initiate appropriate activity either spontaneously or in response to environmental cues” (Lezak, 1995), is the crucial component of apathy (Marin, 1991). As such, apathy, which encompasses decreases in goal-oriented behavior/cognition and increases in emotional indifference, may be the key link between depression and cognitive performance (Lezak, 1995; Santangelo et al., 2009; Scheurich et al., 2008). This theory complements the results of our study. Scheurich et al. (2008) found that goal-setting significantly improved verbal memory performance in patients with depression when compared with standard instructions. When these goal-setting strategies were utilized, depressed patients performed similarly on memory measures as healthy controls (Scheurich et al., 2008). Another study found that depressed individuals performed significantly worse than non-depressed individuals on immediate memory, language, delayed memory, and attention (Benitez et al. 2011). However, when individuals were excluded who did not provide adequate effort, there were no group differences in cognitive performance, regardless of depression diagnosis (Benitez et al. 2011). These results support that cognition may be more affected by symptoms of apathy than symptoms of depression. The results of this study exemplify a link between apathy and cognitive performance in stroke patients, but not between depression and cognitive performance. The stronger ties between apathy and memory, rather than depression and memory, have been previously reported in Parkinson’s disease (Pluck & Brown, 2002; Varanese, Perfetti, Ghilardi, & Di Rocco, 2011). Santangelo et al. (2009) and Cohen and colleagues (1982) did not find a significant effect of depression on any neuropsychological tests, and found that apathetic patients were more cognitively impaired than nonapathetic patients with Parkinson’s disease and depression, respectively. These studies support our findings that apathy impacts cognitive performance, regardless of (and after controlling for) depression (CES-D ≥ 16), and is consistent with our findings that apathy and cognitive performance are also linked in stroke populations. Apathy may be a better indicator of impaired learning and memory (due to low motivational resources) than depression in stroke patients. It is also important to distinguish between depression and apathy in order to optimize treatment outcomes. Widely prescribed antidepressant medications for treatment of depressive disorders include selective serotonin reuptake inhibitors (SSRIs; e.g., citalopram, escitalopram, fluoxetine, sertraline; De Lima & Hotopf, 2003). However, SSRIs are associated with increased behavioral and affective indifference (Barnhart, Makela, & Latocha, 2004; Lee & Keltner, 2005; Wongpakaran, Van Reekum, Wongpakaran, & Clarke, 2007). Qualitative studies have reported decreases in emotional expression and reduced motivation in individuals taking SSRIs (Garland & Baerg, 2004). Wongpakaran et al. (2007) reported that individuals being treated for depression with SSRIs described more apathetic symptoms than individuals being treated with non-SSRIs, although they experienced a decrease in depressive symptoms. Medication-induced apathetic symptoms were also found with serotonin-noradrenaline reuptake inhibitors and mood stabilizers (Price, Cole, & Goodwin, 2009). However, brain-injured individuals who were prescribed dopamine stimulants (bromocriptine and amantadine) reported decreases in apathy symptoms and improved cognitive function (Kraus & Maki, 1997; Powell, Al-Adawi, Morgan, & Greenwood, 1996). No changes in depressive or anxiety symptoms were observed using bromocriptine treatment (Powell et al., 1996). As such, improperly identifying neuropsychiatric symptoms may detrimentally affect treatment outcomes and, in turn, may further impair cognitive functioning (Powell et al., 1996; Price et al., 2009; Wongpakaran et al., 2007). Limitations to this study include the self-report nature of assessing apathy. Given that apathetic individuals may have poor insight into their symptoms, rates of apathy may have been underestimated, as observed in Njomboro and Deb’s (2012) study. In addition, individuals were classified as apathetic if their AES score was equal to or greater than 34, consistent with Andersson and colleagues (1999), Kant and colleagues (1998), and Sagen et al. (2010). Individuals were identified as depressed when their CES-D score was greater than or equal to 16, consistent with Lewinsohn and colleagues (1997). Although these cutoffs have excellent sensitivity and specificity (e.g., Beekman et al., 1997), a clinical interview, such as the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), may reduce the rate of potential false positives (American Psychiatric Association, 2013). Given the larger variability in CVLT-II acquisition, short-term recall, and long-term free recall performance (which may be expected with a range of brain damage severity), future studies should focus on replicating these findings in order to strengthen the study’s conclusions and implications. Lastly, there were missing cases regarding stroke laterality and the degree of anterior cerebrovascular damage, which may affect depression prevalence (Narushima, Kosier, & Robinson, 2003). Despite these limitations, there are a number of strengths to the current study. To our knowledge, this is one of few studies that has examined the impact of apathy and depression on learning and memory performance in the same study in a stroke sample. Other studies have either ignored the role of apathy (Donnellan et al., 2016) or depression (Mayo, Fellows, Scott, Cameron & Wood-Dauphinee, 2009) in neuropsychological evaluations. We also controlled for a range of potential medical confounders, including diabetes, past stroke, days since most recent stroke, family history of cardiovascular disease, obstructive sleep apnea, smoking status, and alcohol use, which did not impact the results of the study. The results of this study offer preliminary support for the role of apathy, and not depression, in verbal learning and memory in stroke patients. As both an important feature of dysexecutive syndromes (Ardila, 2013) and a construct related to depression, these results suggest that apathy may potentially better indicate difficulties with verbal learning and memory than depression. However, additional research should continue to explore the role of apathy in cognitive functioning. Future research should also examine whether this model can be applied to other populations and other aspects of learning and memory, such as autobiographical memory and working memory. Additionally, given that emotional indifference is a hallmark symptom of apathy, and apathetic individuals experience greater difficulty with emotional recognition (Hanby, 2014), it may be of interest to examine apathy’s role in emotional verbal memory test performance (e.g., Emotional Verbal Learning Test; Strauss & Allen, 2013). These studies would allow researchers to further explore the emotion–cognition interaction. Given its prevalence across neurodegenerative diseases, acquired brain injuries, psychiatric disorders, and healthy adults, as well as its detrimental impact on social and physical ability, functional recovery, and treatment optimization, it is surprising that apathy has not received more attention in the literature (Kaufer et al., 1998; Starkstein et al., 1993). There is a need to better understand the unique effect of apathy, to appropriately identify symptoms of apathy, and to improve neuropsychological models of their effects in patients with vascular pathology. Future work may then determine whether treatments targeting apathy could serve as a novel approach to improving cognitive outcomes and to enhance patient and caregiver quality of life after stroke. Funding This work was supported by the Heart and Stroke Foundation of Ontario (Grant number 000392 to R.H.S.); and the Canadian Institutes of Health Research (Grant number 1012404 to R.H.S.); and an Alexander Graham Bell Natural Sciences and Engineering Research Council of Canada (NSERC) Graduate Scholarship (K.N.F.). R.H.S. receives salary support from a New Investigator Award and the HJ Barnett Award from the Heart and Stroke Foundation of Canada, the Canadian Partnership for Stroke Recovery, the Department of Medicine (Sunnybrook Health Sciences Centre and University of Toronto), and the Brill Chair in Neurology at Sunnybrook Health Sciences Centre. Conflicts of interest There are no conflicts of interest to disclose. References Achim , A. M. , Bertrand , M. 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Archives of Clinical NeuropsychologyOxford University Press

Published: May 18, 2018

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