TY - GEN
T1 - Reviewing factors that contribute to substance use, anxiety and depressive disorders
AU - Brouwer, Marlies
AU - Wiers, Reinout
AU - van den Brand, Sofie
AU - Hofstee, Laura
AU - van de Schoot, Rens
AU - Bockting, Claudi
PY - 2021
Y1 - 2021
N2 - Review question What factors and interaction of factors contribute to the onset, maintenance and relapse of anxiety-, depressive-, and substance use disorders? Searches MEDLINE, PsycINFO, Embase, and Scopus. Types of study to be included Prospective, longitudinal, treatment or experiment (prospective), pre-post design with time-element (prospective), ecological momentary assessment/experience sampling method, epidemiological studies Condition or domain being studied Anxiety, depressive, and substance use disorders. The search strategy includes terms relating to (1) the three disorders; (2) risk factors and protective factors; and (3) disorder outcomes (eg. relapse, onset, maintenance, recovery). The search terms are adapted for use with other bibliographic databases in combination with database-specific filters for human, English language, and original article (not review). No date restrictions are applied. Based on citation information and recent reviews, recently published studies will be retrieved for inclusion before finalizing the paper. Participants/population We include articles with 1) Participants at risk, with a history, or current anxiety, depressive, and/or substance use disorder (DSM-5 definitions); 2) a prospective and longitudinal design, including experiments and trials; 3) risk or protective factor(s) is/are assessed before the onset, maintenance, or relapse/recurrence of the mental disorder; 4) the outcome of the disorder is assessed. Exclusion: Other disorders (including bipolar disorder, post-stroke MDD, schizophrenia, PTSD, OCD), theoretical papers without human subjects, animal-only studies, cross-sectional, retrospective, case-control, meta-analyses, reviews, other non-prospective or non-longitudinal designs. Intervention(s), exposure(s) Factors, interaction of factors and mechanisms of change in relation to the three mental disorders. Comparator(s)/control This is dependent on the articles. Most frequently, individuals that had an onset, continuation of symptoms, relapse/recurrence of one of the three disorders will be compared with individuals that did not. All other relevant comparisons are included (eg. exposed vs non-exposed). Main outcome(s) Dependent on the articles, main outcomes include odds ratios, hazard ratios, group differences, regression coefficients for prediction, correlations, changes in scores, in relation to the outcome of (symptoms of) the anxiety, depressive, and/or substance use disorder. All formats of reporting will be included. Measures of effect Risk factors or protective factors need to be measured prior to the outcome of (symptoms of) the anxiety, depressive, and/or substance use disorder. Additional outcome(s) Not pre-specified, but includes study characteristics, baseline symptoms, type of trial, type of participants, etc. Data extraction (selection and coding) The studies will be selected by screeners using an open source machine learning-aided pipeline applying active learning: ASReview (see van de Schoot, R., Bruin, J.D., Schram, R., Zahedi, P., Boer, J.D., Weijdema, F., Kramer, B., Huijts, M., Hoogerwerf, M., Ferdinands, G., Harkema, A., Willemsen, J., Ma, Y., Fang, Q., Hindriks, S. Tummers, L., & Oberski, D. (2020). An open source machine learning framework for efficient and transparent systematic reviews. Nat Mach Intell (2021). DOI: 10.1038/s42256-020-00287-7). ASReview increases the efficiency to screen title and abstract by determining prioritization with active learning. With help of ASReview, the number of abstracts and potentially full-texts which have to be screened by the reviewer will be reduced to only approximately 10% of all identified records. Any disagreement over the eligibility of particular studies will be resolved by discussion with a third reviewer until consensus is reached. All identified articles from ASReview will be checked by another screener. Extracted information will include: Participant demographics and baseline characteristics; diagnostic instrument utilized (self-report vs. clinical interview); outcomes and timing of measurement; factor assessment; information for assessment of the risk of bias. Data will be extracted by one researcher and checked by a second researcher. Missing data will be requested from study authors. Risk of bias (quality) assessment Depending on the design of the included study, risk of bias will be assessed using the RoB 2.0 or ROBINS-I. Strength and certainty of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Strategy for data synthesis Meta-analyses will be performed using Comprehensive Meta-Analysis (CMA; www.meta-analysis.com version 3.0 Biostat, Englewood, NJ), when 3 or more studies are included using a similar modality of assessment. Effect sizes are preferentially calculated based on correlation values, group differences, hazard ratios, regression coefficients, or odds ratios. Heterogeneity and publication bias are assessed using CMA. If methodology between studies is too heterogeneous to conduct a meta-analysis, results will be systematically reviewed in a narrative manner. Moderator analysis will be performed if enough similar studies are included. Potential moderators are baseline symptom severity, age, gender, and follow-up time. Publication bias will be assessed using Egger's test for asymmetry of the funnel plot and Duval and Tweedie's trim and fill procedure. Analysis of subgroups or subsets If applicable, subgroup analyses can be conducted by comparing subgroups with at least 3 similar studies, for example on baseline symptom severity, age, gender, and follow-up time. Subgroup analyses will be conducted using a mixed-effects analysis. Alternatively, meta-regression can be conducted on a minimum of 10 similar studies.
AB - Review question What factors and interaction of factors contribute to the onset, maintenance and relapse of anxiety-, depressive-, and substance use disorders? Searches MEDLINE, PsycINFO, Embase, and Scopus. Types of study to be included Prospective, longitudinal, treatment or experiment (prospective), pre-post design with time-element (prospective), ecological momentary assessment/experience sampling method, epidemiological studies Condition or domain being studied Anxiety, depressive, and substance use disorders. The search strategy includes terms relating to (1) the three disorders; (2) risk factors and protective factors; and (3) disorder outcomes (eg. relapse, onset, maintenance, recovery). The search terms are adapted for use with other bibliographic databases in combination with database-specific filters for human, English language, and original article (not review). No date restrictions are applied. Based on citation information and recent reviews, recently published studies will be retrieved for inclusion before finalizing the paper. Participants/population We include articles with 1) Participants at risk, with a history, or current anxiety, depressive, and/or substance use disorder (DSM-5 definitions); 2) a prospective and longitudinal design, including experiments and trials; 3) risk or protective factor(s) is/are assessed before the onset, maintenance, or relapse/recurrence of the mental disorder; 4) the outcome of the disorder is assessed. Exclusion: Other disorders (including bipolar disorder, post-stroke MDD, schizophrenia, PTSD, OCD), theoretical papers without human subjects, animal-only studies, cross-sectional, retrospective, case-control, meta-analyses, reviews, other non-prospective or non-longitudinal designs. Intervention(s), exposure(s) Factors, interaction of factors and mechanisms of change in relation to the three mental disorders. Comparator(s)/control This is dependent on the articles. Most frequently, individuals that had an onset, continuation of symptoms, relapse/recurrence of one of the three disorders will be compared with individuals that did not. All other relevant comparisons are included (eg. exposed vs non-exposed). Main outcome(s) Dependent on the articles, main outcomes include odds ratios, hazard ratios, group differences, regression coefficients for prediction, correlations, changes in scores, in relation to the outcome of (symptoms of) the anxiety, depressive, and/or substance use disorder. All formats of reporting will be included. Measures of effect Risk factors or protective factors need to be measured prior to the outcome of (symptoms of) the anxiety, depressive, and/or substance use disorder. Additional outcome(s) Not pre-specified, but includes study characteristics, baseline symptoms, type of trial, type of participants, etc. Data extraction (selection and coding) The studies will be selected by screeners using an open source machine learning-aided pipeline applying active learning: ASReview (see van de Schoot, R., Bruin, J.D., Schram, R., Zahedi, P., Boer, J.D., Weijdema, F., Kramer, B., Huijts, M., Hoogerwerf, M., Ferdinands, G., Harkema, A., Willemsen, J., Ma, Y., Fang, Q., Hindriks, S. Tummers, L., & Oberski, D. (2020). An open source machine learning framework for efficient and transparent systematic reviews. Nat Mach Intell (2021). DOI: 10.1038/s42256-020-00287-7). ASReview increases the efficiency to screen title and abstract by determining prioritization with active learning. With help of ASReview, the number of abstracts and potentially full-texts which have to be screened by the reviewer will be reduced to only approximately 10% of all identified records. Any disagreement over the eligibility of particular studies will be resolved by discussion with a third reviewer until consensus is reached. All identified articles from ASReview will be checked by another screener. Extracted information will include: Participant demographics and baseline characteristics; diagnostic instrument utilized (self-report vs. clinical interview); outcomes and timing of measurement; factor assessment; information for assessment of the risk of bias. Data will be extracted by one researcher and checked by a second researcher. Missing data will be requested from study authors. Risk of bias (quality) assessment Depending on the design of the included study, risk of bias will be assessed using the RoB 2.0 or ROBINS-I. Strength and certainty of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Strategy for data synthesis Meta-analyses will be performed using Comprehensive Meta-Analysis (CMA; www.meta-analysis.com version 3.0 Biostat, Englewood, NJ), when 3 or more studies are included using a similar modality of assessment. Effect sizes are preferentially calculated based on correlation values, group differences, hazard ratios, regression coefficients, or odds ratios. Heterogeneity and publication bias are assessed using CMA. If methodology between studies is too heterogeneous to conduct a meta-analysis, results will be systematically reviewed in a narrative manner. Moderator analysis will be performed if enough similar studies are included. Potential moderators are baseline symptom severity, age, gender, and follow-up time. Publication bias will be assessed using Egger's test for asymmetry of the funnel plot and Duval and Tweedie's trim and fill procedure. Analysis of subgroups or subsets If applicable, subgroup analyses can be conducted by comparing subgroups with at least 3 similar studies, for example on baseline symptom severity, age, gender, and follow-up time. Subgroup analyses will be conducted using a mixed-effects analysis. Alternatively, meta-regression can be conducted on a minimum of 10 similar studies.
M3 - Other contribution
PB - PROSPERO: International Prospective Register of Systematic Reviews
ER -