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Zech HG, Reichert M, Ebner-Priemer UW, Tost H, Rapp MA, Heinz A, Dolan RJ, Smolka MN, Deserno L. Mobile Data Collection of Cognitive-Behavioral Tasks in Substance Use Disorders: Where Are We Now? Neuropsychobiology 2022; 81:438-450. [PMID: 35350031 DOI: 10.1159/000523697] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/11/2022] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. METHOD In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. RESULTS Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that - although more systematic studies are necessary - task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. CONCLUSION Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.
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Affiliation(s)
- Hilmar G Zech
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Markus Reichert
- Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr-Universität Bochum (RUB), Bochum, Germany.,Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Mental mHealth Lab, Karlsruhe, Germany.,Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Ulrich W Ebner-Priemer
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Mental mHealth Lab, Karlsruhe, Germany.,Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Heike Tost
- Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Michael A Rapp
- Department for Social and Preventive Medicine, University of Potsdam, Potsdam, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Lorenz Deserno
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany.,Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University of Würzburg, Würzburg, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Alcohol- and non-alcohol-related interference: An fMRI study of treatment-seeking adults with alcohol use disorder. Drug Alcohol Depend 2022; 235:109462. [PMID: 35462263 PMCID: PMC9106927 DOI: 10.1016/j.drugalcdep.2022.109462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND Individuals with alcohol use disorder (AUD) have difficulty diverting attention away from alcohol-related stimuli and towards non-alcohol-related goals (i.e., alcohol-related attention interference). It remains unclear whether regulatory brain function differs during alcohol and non-alcohol-related interference. This study compares brain reactivity during the alcohol and classic Stroop and whether such brain function relates to AUD severity. METHODS 46 participants with AUD completed alcohol and classic color-word Stroop tasks during fMRI. Brain activity was compared during alcohol and classic Stroop interference in the rostral and dorsal anterior cingulate cortices (rACC and dACC) and correlated with self-reported AUD severity. Exploratory whole-brain analyses were also conducted. RESULTS Behavioral interference (i.e., slower reaction times) was observed during alcohol and classic Stroop. rACC activity was significantly higher during the alcohol > neutral contrast versus the incongruent > congruent contrast. dACC activity did not differ between the Stroop tasks. dACC activity during incongruent > congruent was positively associated with AUD severity. CONCLUSIONS Activity in ACC subregions differed during alcohol and non-alcohol interference. Increased alcohol-related activity in the rACC, a region linked to emotional conflict resolution, suggests an interfering effect of self-relevant alcohol cues on non-alcohol-related processing. AUD severity was related to greater dACC reactivity during classic Stroop interference, suggesting that non-drug-related cognitive control impairments are more pronounced in those with more problematic alcohol use.
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