Expectancy Effects on Self-Reported Attention-Deficit/Hyperactivity Disorder Symptoms in Simulated Neurofeedback: A Pilot Study

Expectancy Effects on Self-Reported Attention-Deficit/Hyperactivity Disorder Symptoms in... Abstract Objective Expectancy is a psychological factor that can impact treatment effectiveness. Research on neurofeedback for attention-deficit/hyperactivity disorder (ADHD) suggests expectancy may contribute to treatment outcomes, though evidence for expectancy as an explanatory factor is sparse. This pilot study investigated the effects of expectancies on self-reported ADHD symptoms in simulated neurofeedback. Method Forty-six adults who were concerned that they had ADHD expected to receive active neurofeedback, but were randomly assigned to receive a placebo with false feedback indicating attentive (positive false feedback) or inattentive (negative false feedback) states. Effects of the expectancy manipulation were measured on an ADHD self-report scale. Results Large expectancy effects were found, such that individuals who received positive false feedback reported significant decreases in ADHD symptoms, whereas individuals who received negative false feedback reported significant increases in ADHD symptoms. Conclusions Findings suggest that expectancy should be considered as an explanatory mechanism for ADHD symptom change in response to neurofeedback. Attention-deficit/hyperactivity disorder, Electrophysiological studies, Attention, Clinical trials Introduction Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by core symptoms of inattention, hyperactivity, and impulsivity (American Psychiatric Association, 2013). Although stimulant medication is a common treatment for targeting these behavioral and neurocognitive dysfunctions, neurofeedback has emerged as an alternative nonpharmacological treatment (Antshel et al., 2011). Neurofeedback trains patients to self-regulate their brain activity patterns by providing reinforcements with real-time feedback of electrophysiological activity (Holtmann, Sonuga-Barke, Cortese & Brandeis, 2014). Significant ADHD symptom improvements after neurofeedback have been found in several randomized controlled trials, yet extant placebo-controlled studies have failed to show the superiority of neurofeedback over sham neurofeedback on symptom ratings and neuropsychological tests (Arns, Heinrich, & Strehl, 2014; Cortese et al., 2016). Because symptom improvements have been found in sham neurofeedback, it is necessary to examine placebo mechanisms as psychological factors that can influence treatment outcomes. Expectancy has been identified as a significant cognitive process underlying the placebo and nocebo effect in clinical research. Expectancy theory posits that expecting an outcome after treatment will likely result in corresponding behaviors that are directed toward producing that outcome (Kirsch, 1999). Thus, simply expecting symptom reduction after treatment (i.e., positive expectations) can lead to a genuine improvement in health status, even if the treatment is a placebo with no active properties (i.e., placebo effect; Benedetti, 2009). The opposite pertains to the nocebo effect. Expectancies have been shown to influence neuropsychological assessment, including symptom report and cognitive performance (Suhr & Wei, 2013). Some studies observed effects of both positive and negative expectancies on cognitive measures (e.g., Colagiuri, Livesey, & Harris, 2011), while others found effects of only one type of expectancy (Oken et al., 2008). Although these studies provide implications for clinical trials that utilize neuropsychological outcome measures, many did not examine expectancies specifically related to treatment effects. Even for neurofeedback, the few studies that evaluated expectancies regarding the nature and effectiveness of treatment did not test for whether these expectancies were directly related to symptom changes (e.g., Gevensleben et al., 2009; Perreau-Linck, Lessard, Levesque, & Beauregard, 2010; Vollebregt, van Dongen-Boomsma, Buitelaar, & Slaats-Willemse, 2014). In this pilot study, we investigated expectancy effects on self-reported ADHD symptoms in a simulation of neurofeedback. Participant expectancies were experimentally manipulated by giving positive or negative false feedback about their performance in sham neurofeedback. Consistent with other placebo studies and with the theoretical role of expectancies in explaining placebo effects, we hypothesized that there would be a relationship between false feedback and symptom report, such that positive false feedback would lead to decreased report of ADHD symptoms and negative false feedback would lead to increased report of ADHD symptoms. Methods Participants Forty-six undergraduate students (69.6% female, age range: 18–26) enrolled in introductory psychology courses were recruited for the present study. Participants responded to a study recruitment advertisement seeking individuals who were concerned that they had ADHD and offering to provide information about a potential alternative treatment to stimulant medication. Participants were randomly assigned to receive a placebo with positive false feedback (n = 23) or negative false feedback (n = 23). Two participants in the positive false feedback group and three participants in the negative false feedback group self-reported history of ADHD diagnosis. Exclusionary criteria included self-reported history of neurological disorders, visual or auditory impairments, previous experience receiving neurofeedback, and inability to fluently read and write in English. Participants taking stimulant medication (n = 2 from each group) were asked to refrain from taking the medication at least 24 hr prior to the study. Participants were also required to refrain from drinking caffeinated drinks, smoking, and drinking alcohol at least 12 hr before participating. Informed consent was obtained, and course credit was provided as compensation according to ethical standards of the university’s Institutional Review Board. Apparatus A brain sensing headband called the Muse (2014 edition, InteraXon Inc.) was used as a sham neurofeedback device. Muse is advertised as a tool that helps improve cognitive function, attention, and decrease stress. Muse contains seven calibrated sensors—two on the forehead, two behind the ears, and three reference sensors—that detect and measure brain activity primarily in the frontal lobe. The Muse electroencephalography software “MuseLab” was used to record electrophysiological activity while playing prerecorded false feedback during a five-minute simulated neurofeedback session. Although the duration of an actual neurofeedback session is longer than 5 min, the aim of the present study was to elicit an expectancy effect on outcomes within a neurofeedback treatment protocol. A five-minute session was selected based on prior research on biofeedback relaxation therapy, which demonstrated that even receiving biofeedback for five minutes yielded significant differences pre- and post-biofeedback for participants who received real feedback and for participants who received false feedback (Strunk, Sutton, & Burns, 2009). Measure The State Attention and Arousal Scale (SAAS), adapted from the Barkley Adult ADHD Rating Scale-IV Self-Report Current Symptoms scale (BAARS-IV; Barkley, 2011), was developed and used as a measure of self-reported current ADHD symptoms pre- and post-neurofeedback. The intention of the SAAS was to serve as a state measure of ADHD symptoms, rather than a clinical scale of ADHD symptoms experienced during the past 6 months. As such, 18 BAARS-IV self-report items, including seven Inattention items, three Hyperactivity items, and eight Sluggish Cognitive Tempo (SCT) items, were selected to describe attention and arousal states in the current moment, rather than during the past 6 months. For example, the BAARS-IV item, “fidget with hands or feet or squirm in seat” was modified to the SAAS item, “I feel fidgety”. Respondents were asked to indicate to what extent each statement best described their current experience of symptoms by responding on a four-point Likert scale, where 1 = not at all, 2 = mildly, 3 = moderately, and 4 = severely. A total ADHD symptom score of the SAAS items was calculated to test the main hypothesis. Subscale scores of Inattention, Hyperactivity, and SCT were calculated from the SAAS items for exploratory analyses. Procedure The present study was conducted in a university setting with approval from the university’s Institutional Review Board. After providing informed consent, participants who complied with the study’s preparatory instructions were randomly assigned to experimental conditions determined by an online random number generator. Participants allocated with even numbers were randomly assigned to receive positive false feedback, while those allocated with odd numbers were randomly assigned to receive negative false feedback. Participants were unaware of the group to which they were assigned. Pre-neurofeedback measurements of demographic information and current ADHD symptoms were collected. Then all participants were told that they would be receiving active neurofeedback that provided feedback contingent on their brain activity. Participants were instructed that if their attention was focused on their breathing, they would hear calm winds and birds chirping. However, if their attention was fluctuating, the winds would pick up and no bird sounds would be heard. The Muse headband was subsequently placed on the participant and calibrated. Calibration was immediately followed by a one-minute practice session during which participants received real-time feedback. Participants then underwent a five-minute simulated, sham neurofeedback session. Participants in the “negative false feedback” group heard a prerecorded session indicating low neurofeedback success (i.e., feedback of loud winds and no bird sounds) and received verbal feedback from the researcher stating that they were not concentrating well. Participants in the “positive false feedback” group heard a different prerecorded session indicating high neurofeedback success (i.e., feedback of calm winds and birds chirping) and received verbal feedback that they were concentrating very well. As participants removed the Muse headband, they were told that they reached a low state of concentration and their neurofeedback session was unsuccessful (for the “negative false feedback” group) or that they reached a high state of concentration and their neurofeedback session was very successful (for the “positive false feedback” group). All instructions and verbal feedback provided by the researcher were scripted. After the session, post-neurofeedback measurement of current ADHD symptoms was collected and then a debriefing was provided to participants. Results All 46 participants completed the study, but data from two participants were excluded from analyses. One participant reported previous experience with neurofeedback and another fell asleep during the neurofeedback session. Groups did not differ in demographics or on pre-neurofeedback measures (see Table 1). Table 1. Pre-neurofeedback participant characteristics Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Note: N = 44. M = mean; SD = standard deviation; SAAS = State Attention and Arousal Scale; ADHD = attention-deficit/hyperactivity disorder. Table 1. Pre-neurofeedback participant characteristics Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Note: N = 44. M = mean; SD = standard deviation; SAAS = State Attention and Arousal Scale; ADHD = attention-deficit/hyperactivity disorder. Mixed analyses of variance, with Group (positive vs. negative false feedback) as a between-subject factor and Time (pre- vs. post-neurofeedback) as a within-subject factor, were used to test expectancy effects on total self-reported ADHD symptoms. As expected, the total ADHD symptom score showed a significant Group by Time interaction. Simple effect analyses revealed groups did not differ in total ADHD symptoms pre-neurofeedback, but were different post-neurofeedback, F(1, 42) = 12.10, p = .001, ηp2=.22. Within-subjects analyses showed that participants given negative false feedback reported significant increases in total ADHD symptoms from pre- to post-neurofeedback, F(1, 21) = 7.99, p = .010, ηp2=.28, whereas participants given positive false feedback reported significant decreases in total ADHD symptoms, F(1, 21) = 21.85, p < .001, ηp2=.51 (see Table 2). Table 2. Results for self-reported symptoms of attention-deficit/hyperactivity disorder Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Note: N = 44. M = mean; SD = standard deviation; Pre-NFB = pre-neurofeedback; Post-NFB = post-neurofeedback; SAAS = State Attention and Arousal Scale; SCT = sluggish cognitive tempo. Table 2. Results for self-reported symptoms of attention-deficit/hyperactivity disorder Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Note: N = 44. M = mean; SD = standard deviation; Pre-NFB = pre-neurofeedback; Post-NFB = post-neurofeedback; SAAS = State Attention and Arousal Scale; SCT = sluggish cognitive tempo. The Inattention subscale score showed a similar pattern, with a significant Group by Time interaction, significant differences between groups post-neurofeedback, and significant changes in inattentive symptoms across time for both groups (see Table 2). Analyses for Hyperactivity and SCT subscale scores also indicated significant interactions and differences between groups post-neurofeedback. Participants given positive false feedback reported significant decreases in hyperactive symptoms, F(1, 21) = 13.31, p = .002, ηp2 = .39, and SCT symptoms, F(1, 21) = 8.29, p = .009, ηp2 = .28, but there was not a reliable change in Hyperactivity (p = .323) or SCT (p = .174) scores for participants given negative false feedback. Discussion The purpose of the present study was to examine expectancy effects on self-reported ADHD symptoms in sham neurofeedback. As expected, changes in self-reported symptoms occurred as a function of expectancies. Large effects of both positive and negative expectancy manipulations were found on total ADHD symptoms and inattentive symptoms, such that positive false feedback led to decreased symptom report and negative false feedback led to increased symptom report after sham neurofeedback. These findings are consistent with expectancy theory (Kirsch, 1999) and suggest that participants’ beliefs about neurofeedback activate expectancies that cause corresponding changes in behavior. Results for hyperactive and SCT symptoms showed effects of positive expectancies, but participants given negative false feedback did not report significant changes in these symptoms. While this finding could be related to the small number of Hyperactivity items included on the self-report measure, the lack of negative expectancy effects on the relatively larger number of SCT items suggests differential effects of positive and negative expectancies on ADHD symptom types. Unlike the specific impact of the nocebo effect on inattentive symptoms, the placebo effect appears to induce more generalized expectancies that affect multiple behavioral and neurocognitive dysfunctions. Findings from the present study call for researchers to account for both positive and negative expectancies when investigating the efficacy of neurofeedback for individuals diagnosed with ADHD or for those who are concerned that they may have ADHD. Unfortunately, randomized controlled studies to date often neglect the role of such higher cognitive processes in treatment outcomes (Gevensleben, Moll, Rothenberger, & Heinrich, 2014). This is concerning for evaluation of any treatment, but particularly one that is as time-consuming and expensive as neurofeedback for ADHD. Given that extant studies do not unanimously support neurofeedback as a treatment for ADHD, it is critical to elucidate what degree of symptom change is due to acquisition of self-regulation ability and what degree is due to expectancy effects. A few limitations to the present study warrant consideration. The study contained a small sample size and utilized self-report as a primary outcome measure. Although placebo effects have been consistently found in measures of subjective states (Stewart-Williams & Podd, 2004), cognitive performance may also be influenced by expectancies if experimental manipulations describe what the participants should expect. As such, the present findings will need to be replicated with a larger sample and with incorporation of objective measures in cognitive performance. Another potential limitation is that only two participants who received positive false feedback and three participants who received negative false feedback self-reported history of ADHD diagnosis. While the small percentage of clinical cases in the study sample precludes generalization to individuals diagnosed with ADHD, the sample is characterized by individuals seeking treatment of symptoms related to ADHD due to their concerns of having the disorder. Therefore, even with a sample of predominately healthy “treatment-seekers”, the study demonstrated significant effects of expectancies on a self-report outcome measure. In addition, it is difficult to determine if results from the simulated neurofeedback are generalizable to real neurofeedback. A simulated intervention enables control for threats to internal validity by incorporating random assignment, standardized procedures, scripted scenarios, and exclusion of participants who had prior experience with neurofeedback. However, these experimental controls may not translate to real clinical settings. Further, although use of an online random number generator allowed concealment of group assignment from participants, a double-blind design was not feasible for the study and therefore introduced potential for experimenter bias. Future research addressing these limitations is necessary to continue examining expectancy effects on ADHD symptoms and to determine whether there indeed is a differential impact of expectancy effects on symptom types. Taken together, these findings provide preliminary evidence that expectancy is a psychological factor that can impact the effectiveness of neurofeedback as a treatment for ADHD symptoms. A mere expectancy of symptom improvement or impairment, even without active properties of the treatment (i.e., sham neurofeedback), can lead to significant self-reported symptom changes. 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A. , van Dongen-Boomsma , M. , Buitelaar , J. K. , & Slaats-Willemse , D. ( 2014 ). Does EEG-neurofeedback improve neurocognitive functioning in children with attention-deficit/hyperactivity disorder? A systematic review and a double-blind placebo-controlled study . Journal of Child Psychology and Psychiatry, and Allied Disciplines , 55 , 460 – 472 . doi:10.1111/jcpp.12143 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Clinical Neuropsychology Oxford University Press

Expectancy Effects on Self-Reported Attention-Deficit/Hyperactivity Disorder Symptoms in Simulated Neurofeedback: A Pilot Study

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Abstract

Abstract Objective Expectancy is a psychological factor that can impact treatment effectiveness. Research on neurofeedback for attention-deficit/hyperactivity disorder (ADHD) suggests expectancy may contribute to treatment outcomes, though evidence for expectancy as an explanatory factor is sparse. This pilot study investigated the effects of expectancies on self-reported ADHD symptoms in simulated neurofeedback. Method Forty-six adults who were concerned that they had ADHD expected to receive active neurofeedback, but were randomly assigned to receive a placebo with false feedback indicating attentive (positive false feedback) or inattentive (negative false feedback) states. Effects of the expectancy manipulation were measured on an ADHD self-report scale. Results Large expectancy effects were found, such that individuals who received positive false feedback reported significant decreases in ADHD symptoms, whereas individuals who received negative false feedback reported significant increases in ADHD symptoms. Conclusions Findings suggest that expectancy should be considered as an explanatory mechanism for ADHD symptom change in response to neurofeedback. Attention-deficit/hyperactivity disorder, Electrophysiological studies, Attention, Clinical trials Introduction Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by core symptoms of inattention, hyperactivity, and impulsivity (American Psychiatric Association, 2013). Although stimulant medication is a common treatment for targeting these behavioral and neurocognitive dysfunctions, neurofeedback has emerged as an alternative nonpharmacological treatment (Antshel et al., 2011). Neurofeedback trains patients to self-regulate their brain activity patterns by providing reinforcements with real-time feedback of electrophysiological activity (Holtmann, Sonuga-Barke, Cortese & Brandeis, 2014). Significant ADHD symptom improvements after neurofeedback have been found in several randomized controlled trials, yet extant placebo-controlled studies have failed to show the superiority of neurofeedback over sham neurofeedback on symptom ratings and neuropsychological tests (Arns, Heinrich, & Strehl, 2014; Cortese et al., 2016). Because symptom improvements have been found in sham neurofeedback, it is necessary to examine placebo mechanisms as psychological factors that can influence treatment outcomes. Expectancy has been identified as a significant cognitive process underlying the placebo and nocebo effect in clinical research. Expectancy theory posits that expecting an outcome after treatment will likely result in corresponding behaviors that are directed toward producing that outcome (Kirsch, 1999). Thus, simply expecting symptom reduction after treatment (i.e., positive expectations) can lead to a genuine improvement in health status, even if the treatment is a placebo with no active properties (i.e., placebo effect; Benedetti, 2009). The opposite pertains to the nocebo effect. Expectancies have been shown to influence neuropsychological assessment, including symptom report and cognitive performance (Suhr & Wei, 2013). Some studies observed effects of both positive and negative expectancies on cognitive measures (e.g., Colagiuri, Livesey, & Harris, 2011), while others found effects of only one type of expectancy (Oken et al., 2008). Although these studies provide implications for clinical trials that utilize neuropsychological outcome measures, many did not examine expectancies specifically related to treatment effects. Even for neurofeedback, the few studies that evaluated expectancies regarding the nature and effectiveness of treatment did not test for whether these expectancies were directly related to symptom changes (e.g., Gevensleben et al., 2009; Perreau-Linck, Lessard, Levesque, & Beauregard, 2010; Vollebregt, van Dongen-Boomsma, Buitelaar, & Slaats-Willemse, 2014). In this pilot study, we investigated expectancy effects on self-reported ADHD symptoms in a simulation of neurofeedback. Participant expectancies were experimentally manipulated by giving positive or negative false feedback about their performance in sham neurofeedback. Consistent with other placebo studies and with the theoretical role of expectancies in explaining placebo effects, we hypothesized that there would be a relationship between false feedback and symptom report, such that positive false feedback would lead to decreased report of ADHD symptoms and negative false feedback would lead to increased report of ADHD symptoms. Methods Participants Forty-six undergraduate students (69.6% female, age range: 18–26) enrolled in introductory psychology courses were recruited for the present study. Participants responded to a study recruitment advertisement seeking individuals who were concerned that they had ADHD and offering to provide information about a potential alternative treatment to stimulant medication. Participants were randomly assigned to receive a placebo with positive false feedback (n = 23) or negative false feedback (n = 23). Two participants in the positive false feedback group and three participants in the negative false feedback group self-reported history of ADHD diagnosis. Exclusionary criteria included self-reported history of neurological disorders, visual or auditory impairments, previous experience receiving neurofeedback, and inability to fluently read and write in English. Participants taking stimulant medication (n = 2 from each group) were asked to refrain from taking the medication at least 24 hr prior to the study. Participants were also required to refrain from drinking caffeinated drinks, smoking, and drinking alcohol at least 12 hr before participating. Informed consent was obtained, and course credit was provided as compensation according to ethical standards of the university’s Institutional Review Board. Apparatus A brain sensing headband called the Muse (2014 edition, InteraXon Inc.) was used as a sham neurofeedback device. Muse is advertised as a tool that helps improve cognitive function, attention, and decrease stress. Muse contains seven calibrated sensors—two on the forehead, two behind the ears, and three reference sensors—that detect and measure brain activity primarily in the frontal lobe. The Muse electroencephalography software “MuseLab” was used to record electrophysiological activity while playing prerecorded false feedback during a five-minute simulated neurofeedback session. Although the duration of an actual neurofeedback session is longer than 5 min, the aim of the present study was to elicit an expectancy effect on outcomes within a neurofeedback treatment protocol. A five-minute session was selected based on prior research on biofeedback relaxation therapy, which demonstrated that even receiving biofeedback for five minutes yielded significant differences pre- and post-biofeedback for participants who received real feedback and for participants who received false feedback (Strunk, Sutton, & Burns, 2009). Measure The State Attention and Arousal Scale (SAAS), adapted from the Barkley Adult ADHD Rating Scale-IV Self-Report Current Symptoms scale (BAARS-IV; Barkley, 2011), was developed and used as a measure of self-reported current ADHD symptoms pre- and post-neurofeedback. The intention of the SAAS was to serve as a state measure of ADHD symptoms, rather than a clinical scale of ADHD symptoms experienced during the past 6 months. As such, 18 BAARS-IV self-report items, including seven Inattention items, three Hyperactivity items, and eight Sluggish Cognitive Tempo (SCT) items, were selected to describe attention and arousal states in the current moment, rather than during the past 6 months. For example, the BAARS-IV item, “fidget with hands or feet or squirm in seat” was modified to the SAAS item, “I feel fidgety”. Respondents were asked to indicate to what extent each statement best described their current experience of symptoms by responding on a four-point Likert scale, where 1 = not at all, 2 = mildly, 3 = moderately, and 4 = severely. A total ADHD symptom score of the SAAS items was calculated to test the main hypothesis. Subscale scores of Inattention, Hyperactivity, and SCT were calculated from the SAAS items for exploratory analyses. Procedure The present study was conducted in a university setting with approval from the university’s Institutional Review Board. After providing informed consent, participants who complied with the study’s preparatory instructions were randomly assigned to experimental conditions determined by an online random number generator. Participants allocated with even numbers were randomly assigned to receive positive false feedback, while those allocated with odd numbers were randomly assigned to receive negative false feedback. Participants were unaware of the group to which they were assigned. Pre-neurofeedback measurements of demographic information and current ADHD symptoms were collected. Then all participants were told that they would be receiving active neurofeedback that provided feedback contingent on their brain activity. Participants were instructed that if their attention was focused on their breathing, they would hear calm winds and birds chirping. However, if their attention was fluctuating, the winds would pick up and no bird sounds would be heard. The Muse headband was subsequently placed on the participant and calibrated. Calibration was immediately followed by a one-minute practice session during which participants received real-time feedback. Participants then underwent a five-minute simulated, sham neurofeedback session. Participants in the “negative false feedback” group heard a prerecorded session indicating low neurofeedback success (i.e., feedback of loud winds and no bird sounds) and received verbal feedback from the researcher stating that they were not concentrating well. Participants in the “positive false feedback” group heard a different prerecorded session indicating high neurofeedback success (i.e., feedback of calm winds and birds chirping) and received verbal feedback that they were concentrating very well. As participants removed the Muse headband, they were told that they reached a low state of concentration and their neurofeedback session was unsuccessful (for the “negative false feedback” group) or that they reached a high state of concentration and their neurofeedback session was very successful (for the “positive false feedback” group). All instructions and verbal feedback provided by the researcher were scripted. After the session, post-neurofeedback measurement of current ADHD symptoms was collected and then a debriefing was provided to participants. Results All 46 participants completed the study, but data from two participants were excluded from analyses. One participant reported previous experience with neurofeedback and another fell asleep during the neurofeedback session. Groups did not differ in demographics or on pre-neurofeedback measures (see Table 1). Table 1. Pre-neurofeedback participant characteristics Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Note: N = 44. M = mean; SD = standard deviation; SAAS = State Attention and Arousal Scale; ADHD = attention-deficit/hyperactivity disorder. Table 1. Pre-neurofeedback participant characteristics Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Variable Positive false Negative false Group comparisons feedback (n = 22) feedback (n = 22) M ± SD M ± SD F(1,42) p Age 19.36 ± 1.84 19.27 ± 1.42 .03 .86 Hours of sleep night prior 7.09 ± 1.49 7.23 ± 1.55 .09 .77 SAAS total score 31.36 ± 7.64 29.77 ± 8.42 .43 .52 n (%) n (%) χ2 (df) p Sex at birth .42 (1) .52  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 8 (36.4) Gender identity 1.21 (2) .55  Female 16 (72.7) 14 (63.6)  Male 6 (27.3) 7 (31.8)  Different identity 0 (0.0) 1 (4.5) Education 4.00 (3) .26  Freshman 16 (72.7) 16 (72.7)  Sophomore 4 (18.2) 2 (9.1)  Junior 0 (0.0) 3 (13.6)  Senior or higher 2 (9.1) 1 (4.5) Race/Ethnicity 2.36 (4) .67  Caucasian/White 19 (86.4) 18 (81.8)  African American 0 (0.0) 1 (4.5)  Hispanic/Latino 0 (0.0) 1 (4.5)  Asian American/Pacific Islander 2 (9.1) 1 (4.5)  Multiracial/other 1 (4.5) 1 (4.5) ADHD diagnosis 2 (9.1) 3 (13.6) .23 (1) .64 Other psychological diagnoses 0 (0.0) 3 (13.6) 3.22 (1) .07 Stimulant medication use 2 (9.1) 2 (9.1) .83 (1) .36 Smoking or other nicotine use 3 (13.6) 2 (9.1) .23 (1) .64 Caffeine use 15 (68.2) 17 (77.3) .46 (1) .50 Alcohol use 10 (45.5) 16 (72.7) 3.39 (1) .07 Drug use 2 (9.1) 4 (18.2) .77 (1) .38 Note: N = 44. M = mean; SD = standard deviation; SAAS = State Attention and Arousal Scale; ADHD = attention-deficit/hyperactivity disorder. Mixed analyses of variance, with Group (positive vs. negative false feedback) as a between-subject factor and Time (pre- vs. post-neurofeedback) as a within-subject factor, were used to test expectancy effects on total self-reported ADHD symptoms. As expected, the total ADHD symptom score showed a significant Group by Time interaction. Simple effect analyses revealed groups did not differ in total ADHD symptoms pre-neurofeedback, but were different post-neurofeedback, F(1, 42) = 12.10, p = .001, ηp2=.22. Within-subjects analyses showed that participants given negative false feedback reported significant increases in total ADHD symptoms from pre- to post-neurofeedback, F(1, 21) = 7.99, p = .010, ηp2=.28, whereas participants given positive false feedback reported significant decreases in total ADHD symptoms, F(1, 21) = 21.85, p < .001, ηp2=.51 (see Table 2). Table 2. Results for self-reported symptoms of attention-deficit/hyperactivity disorder Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Note: N = 44. M = mean; SD = standard deviation; Pre-NFB = pre-neurofeedback; Post-NFB = post-neurofeedback; SAAS = State Attention and Arousal Scale; SCT = sluggish cognitive tempo. Table 2. Results for self-reported symptoms of attention-deficit/hyperactivity disorder Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Measure n Pre-NFB M (SD) Post-NFB M(SD) Group by time effect Time effect F(1,42) p ηp2 F(1,21) p ηp2 SAAS  Total score 26.98 <.001 .391   Positive false feedback 22 31.36 (7.64) 25.14 (7.28) 21.85 <.001 .510   Negative false feedback 22 29.77 (8.42) 34.14 (9.71) 7.99 .010 .276  Inattention score 30.03 <.001 .417   Positive false feedback 22 13.91 (4.31) 10.59 (3.61) 16.80 .001 .444   Negative false feedback 22 12.64 (4.41) 15.55 (4.61) 13.31 .002 .388  Hyperactivity score 6.37 .015 .132   Positive false feedback 22 4.36 (1.18) 3.64 (0.85) 13.31 .002 .388   Negative false feedback 22 4.59 (2.15) 5.00 (2.37) 1.03 .323 .047  SCT score 9.25 .004 .180   Positive false feedback 22 13.09 (4.05) 10.91 (3.66) 8.29 .009 .283   Negative false feedback 22 12.55 (3.56) 13.59 (4.39) 1.98 .174 .086 Note: N = 44. M = mean; SD = standard deviation; Pre-NFB = pre-neurofeedback; Post-NFB = post-neurofeedback; SAAS = State Attention and Arousal Scale; SCT = sluggish cognitive tempo. The Inattention subscale score showed a similar pattern, with a significant Group by Time interaction, significant differences between groups post-neurofeedback, and significant changes in inattentive symptoms across time for both groups (see Table 2). Analyses for Hyperactivity and SCT subscale scores also indicated significant interactions and differences between groups post-neurofeedback. Participants given positive false feedback reported significant decreases in hyperactive symptoms, F(1, 21) = 13.31, p = .002, ηp2 = .39, and SCT symptoms, F(1, 21) = 8.29, p = .009, ηp2 = .28, but there was not a reliable change in Hyperactivity (p = .323) or SCT (p = .174) scores for participants given negative false feedback. Discussion The purpose of the present study was to examine expectancy effects on self-reported ADHD symptoms in sham neurofeedback. As expected, changes in self-reported symptoms occurred as a function of expectancies. Large effects of both positive and negative expectancy manipulations were found on total ADHD symptoms and inattentive symptoms, such that positive false feedback led to decreased symptom report and negative false feedback led to increased symptom report after sham neurofeedback. These findings are consistent with expectancy theory (Kirsch, 1999) and suggest that participants’ beliefs about neurofeedback activate expectancies that cause corresponding changes in behavior. Results for hyperactive and SCT symptoms showed effects of positive expectancies, but participants given negative false feedback did not report significant changes in these symptoms. While this finding could be related to the small number of Hyperactivity items included on the self-report measure, the lack of negative expectancy effects on the relatively larger number of SCT items suggests differential effects of positive and negative expectancies on ADHD symptom types. Unlike the specific impact of the nocebo effect on inattentive symptoms, the placebo effect appears to induce more generalized expectancies that affect multiple behavioral and neurocognitive dysfunctions. Findings from the present study call for researchers to account for both positive and negative expectancies when investigating the efficacy of neurofeedback for individuals diagnosed with ADHD or for those who are concerned that they may have ADHD. Unfortunately, randomized controlled studies to date often neglect the role of such higher cognitive processes in treatment outcomes (Gevensleben, Moll, Rothenberger, & Heinrich, 2014). This is concerning for evaluation of any treatment, but particularly one that is as time-consuming and expensive as neurofeedback for ADHD. Given that extant studies do not unanimously support neurofeedback as a treatment for ADHD, it is critical to elucidate what degree of symptom change is due to acquisition of self-regulation ability and what degree is due to expectancy effects. A few limitations to the present study warrant consideration. The study contained a small sample size and utilized self-report as a primary outcome measure. Although placebo effects have been consistently found in measures of subjective states (Stewart-Williams & Podd, 2004), cognitive performance may also be influenced by expectancies if experimental manipulations describe what the participants should expect. As such, the present findings will need to be replicated with a larger sample and with incorporation of objective measures in cognitive performance. Another potential limitation is that only two participants who received positive false feedback and three participants who received negative false feedback self-reported history of ADHD diagnosis. While the small percentage of clinical cases in the study sample precludes generalization to individuals diagnosed with ADHD, the sample is characterized by individuals seeking treatment of symptoms related to ADHD due to their concerns of having the disorder. Therefore, even with a sample of predominately healthy “treatment-seekers”, the study demonstrated significant effects of expectancies on a self-report outcome measure. In addition, it is difficult to determine if results from the simulated neurofeedback are generalizable to real neurofeedback. A simulated intervention enables control for threats to internal validity by incorporating random assignment, standardized procedures, scripted scenarios, and exclusion of participants who had prior experience with neurofeedback. However, these experimental controls may not translate to real clinical settings. Further, although use of an online random number generator allowed concealment of group assignment from participants, a double-blind design was not feasible for the study and therefore introduced potential for experimenter bias. Future research addressing these limitations is necessary to continue examining expectancy effects on ADHD symptoms and to determine whether there indeed is a differential impact of expectancy effects on symptom types. Taken together, these findings provide preliminary evidence that expectancy is a psychological factor that can impact the effectiveness of neurofeedback as a treatment for ADHD symptoms. A mere expectancy of symptom improvement or impairment, even without active properties of the treatment (i.e., sham neurofeedback), can lead to significant self-reported symptom changes. Therefore, expectancy should be considered as an explanatory mechanism for ADHD symptom change in response to neurofeedback. Accounting for expectancy effects will not only assist in accurately evaluating the efficacy of neurofeedback for ADHD, but will also provide approaches for maximizing positive outcomes and minimizing negative outcomes following treatment administration (Enck, Bingel, Schedlowski, & Rief, 2013). Conflict of interest None declared. References American Psychiatric Association . ( 2013 ). Diagnostic and statistical manual of mental disorders ( 5th edn ). Washington, DC : American Psychiatric Publishing . Antshel , K. M. , Hargrave , T. M. , Simonescu , M. , Kaul , P. , Hendricks , K. , & Faraone , S. V. ( 2011 ). Advances in understanding and treating ADHD . BMC Medicine , 9 , 72 . doi:10.1186/1741-7015-9-72 . Google Scholar CrossRef Search ADS PubMed Arns , M. , Heinrich , H. , & Strehl , U. ( 2014 ). 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A. , van Dongen-Boomsma , M. , Buitelaar , J. K. , & Slaats-Willemse , D. ( 2014 ). Does EEG-neurofeedback improve neurocognitive functioning in children with attention-deficit/hyperactivity disorder? A systematic review and a double-blind placebo-controlled study . Journal of Child Psychology and Psychiatry, and Allied Disciplines , 55 , 460 – 472 . doi:10.1111/jcpp.12143 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Archives of Clinical NeuropsychologyOxford University Press

Published: Mar 31, 2018

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