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Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

ABSTRACT: Implicit self-associations are theorized to be rigidly and excessively negative in affective disorders like depression. Such information processing patterns may be useful as an approach to parsing heterogeneous etiologies, substrates, and treatment outcomes within the broad syndrome of depression. However, there is a lack of sufficient data on the psychometric, neural, and computational substrates of Implicit Association Test (IAT) performance in patient populations. In a treatment-seeking, clinically depressed sample (n = 122), we administered five variants of the IAT-a dominant paradigm used in hundreds of studies of implicit cognition to date-at two repeated sessions (outside and inside a functional MRI scanner). We examined reliability, clinical correlates, and neural and computational substrates of IAT performance. IAT scores showed adequate (.67-.81) split-half reliability and convergent validity with one another and with relevant explicit symptom measures. Test-retest correlations (in vs. outside the functional MRI scanner) were present but modest (.15-.55). In depressed patients, on average, negative implicit self-representations appeared to be weaker or less efficiently processed relative to positive self-representations; elicited greater recruitment of frontoparietal task network regions; and, according to computational modeling of trial-by-trial data, were driven primarily by differential efficiency of information accumulation for negative and positive attributes. Greater degree of discrepancy between implicit and explicit self-worth predicted depression severity. Overall, these IATs show potential utility in understanding heterogeneous substrates of depression but leave substantial room for improvement. The observed clinical, neural, and computational correlates of implicit self-associations offer novel insights into a simple computer-administered task in a clinical population and point toward heterogeneous depression mechanisms and treatment targets. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

SUBMITTER: Price RB

PROVIDER: S-EPMC8201635 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: The goal of the Depression Inventory Development (DID) project is to develop a comprehensive and psychometrically sound rating scale for major depressive disorder (MDD) that reflects current diagnostic criteria and conceptualizations of depression. We report here the evaluation of the current DID item bank using Classical Test Theory (CTT), Item Response Theory (IRT) and Rasch Measurement Theory (RMT). Methods: The present study was part of a larger multisite, open-label study conducted by the Canadian Biomarker Integration Network in Depression (ClinicalTrials.gov: NCT01655706). Trained raters administered the 32 DID items at each of two visits (MDD: baseline, n=211 and Week 8, n=177; healthy participants: baseline, n=112 and Week 8, n=104). The DID's "grid" structure operationalizes intensity and frequency of each item, with clear symptom definitions and a structured interview guide, with the current iteration assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain, and appetite. Participants were also administered the Montgomery- Åsberg Depression Rating Scale (MADRS) and Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) that allowed DID items to be evaluated against existing "benchmark" items. CTT was used to assess data quality/reliability (i.e., missing data, skewness, scoring frequency, internal consistency), IRT to assess individual item performance by modelling an item's ability to discriminate levels of depressive severity (as assessed by the MADRS), and RMT to assess how the items perform together as a scale to capture a range of depressive severity (item targeting). These analyses together provided empirical evidence to base decisions on which DID items to remove, modify, or advance. Results: Of the 32 DID items evaluated, eight items were identified by CTT as problematic, displaying low variability in the range of responses, floor effects, and/or skewness; and four items were identified by IRT to show poor discriminative properties that would limit their clinical utility. Five additional items were deemed to be redundant. The remaining 15 DID items all fit the Rasch model, with person and item difficulty estimates indicating satisfactory item targeting, with lower precision in participants with mild levels of depression. These 15 DID items also showed good internal consistency (alpha=0.95 and inter-item correlations ranging from r=0.49 to r=0.84) and all items were sensitive to change following antidepressant treatment (baseline vs. Week 8). RMT revealed problematic item targeting for the MADRS and QIDSSR, including an absence of MADRS items targeting participants with mild/moderate depression and an absence of QIDS-SR items targeting participants with mild or severe depression. Conclusion: The present study applied CTT, IRT, and RMT to assess the measurement properties of the DID items and identify those that should be advanced, modified, or removed. Of the 32 items evaluated, 15 items showed good measurement properties. These items (along with previously evaluated items) will provide the basis for validation of a penultimate DID scale assessing anhedonia, cognitive slowing, concentration, executive function, recent memory, drive, emotional fatigue, guilt, self-esteem, hopelessness, tension, rumination, irritability, reduced appetite, insomnia, sadness, worry, suicidality, and depressed mood. The strategies adopted by the DID process provide a framework for rating scale development and validation.

Project description:Aims: This study compared the psychometric properties of two self-efficacy instruments related to physical activity. Factorial validity, cross-group and longitudinal invariance, and composite reliability were examined. Methods: Secondary analysis was conducted on data from a group randomized controlled trial investigating the effect of a 17-week intervention on increasing moderate to vigorous physical activity among 5th-8th grade girls (N = 1,012). Participants completed a 6-item Physical Activity Self-Efficacy Scale (PASE) and a 7-item Self-Efficacy for Exercise Behaviors Scale (SEEB) at baseline and post-intervention. Confirmatory factor analyses for intervention and control groups were conducted with Mplus Version 7.4 using robust weighted least squares estimation. Model fit was evaluated with the chi-square index, comparative fit index, and root mean square error of approximation. Composite reliability for latent factors with ordinal indicators was computed from Mplus output using SAS 9.3. Results: Mean age of the girls was 12.2 years (SD = 0.96). One-third of the girls were obese. Girls represented a diverse sample with over 50% indicating black race and an additional 19% identifying as mixed or other race. Both instruments demonstrated configural invariance for simultaneous analysis of cross-group and longitudinal invariance based on alternative fit indices. However, simultaneous metric invariance was not met for the PASE or the SEEB instruments. Partial metric invariance for the simultaneous analysis was achieved for the PASE with one factor loading identified as non-invariant. Partial metric invariance was not met for the SEEB. Longitudinal scalar invariance was achieved for both instruments in the control group but not the intervention group. Composite reliability for the PASE ranged from 0.772 to 0.842. Reliability for the SEEB ranged from 0.719 to 0.800 indicating higher reliability for the PASE. Reliability was more stable over time in the control group for both instruments. Conclusions: Results suggest that the intervention influenced how girls responded to indicator items. Neither of the instruments achieved simultaneous metric invariance making it difficult to assess mean differences in PA self-efficacy between groups.

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Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

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