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- Furukawa, Toshi A., et al.
(author)
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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression : a systematic review and component network meta-analysis using individual data
- 2021
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In: Lancet psychiatry. - London, United Kingdom : Elsevier. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
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Research review (peer-reviewed)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
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| 2. |
- Karyotaki, Eirini, et al.
(author)
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Internet-Based Cognitive Behavioral Therapy for Depression : A Systematic Review and Individual Patient Data Network Meta-analysis
- 2021
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In: JAMA psychiatry. - : American Medical Association. - 2168-6238 .- 2168-622X. ; 78:4, s. 361-371
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Research review (peer-reviewed)abstract
- IMPORTANCE: Personalized treatment choices would increase the effectiveness of internet-based cognitive behavioral therapy (iCBT) for depression to the extent that patients differ in interventions that better suit them.OBJECTIVE: To provide personalized estimates of short-term and long-term relative efficacy of guided and unguided iCBT for depression using patient-level information.DATA SOURCES: We searched PubMed, Embase, PsycInfo, and Cochrane Library to identify randomized clinical trials (RCTs) published up to January 1, 2019.STUDY SELECTION: Eligible RCTs were those comparing guided or unguided iCBT against each other or against any control intervention in individuals with depression. Available individual patient data (IPD) was collected from all eligible studies. Depression symptom severity was assessed after treatment, 6 months, and 12 months after randomization.DATA EXTRACTION AND SYNTHESIS: We conducted a systematic review and IPD network meta-analysis and estimated relative treatment effect sizes across different patient characteristics through IPD network meta-regression.MAIN OUTCOMES AND MEASURES: Patient Health Questionnaire-9 (PHQ-9) scores.RESULTS: Of 42 eligible RCTs, 39 studies comprising 9751 participants with depression contributed IPD to the IPD network meta-analysis, of which 8107 IPD were synthesized. Overall, both guided and unguided iCBT were associated with more effectiveness as measured by PHQ-9 scores than control treatments over the short term and the long term. Guided iCBT was associated with more effectiveness than unguided iCBT (mean difference [MD] in posttreatment PHQ-9 scores, -0.8; 95% CI, -1.4 to -0.2), but we found no evidence of a difference at 6 or 12 months following randomization. Baseline depression was found to be the most important modifier of the relative association for efficacy of guided vs unguided iCBT. Differences between unguided and guided iCBT in people with baseline symptoms of subthreshold depression (PHQ-9 scores 5-9) were small, while guided iCBT was associated with overall better outcomes in patients with baseline PHQ-9 greater than 9.CONCLUSIONS AND RELEVANCE: In this network meta-analysis with IPD, guided iCBT was associated with more effectiveness than unguided iCBT for individuals with depression, benefits were more substantial in individuals with moderate to severe depression. Unguided iCBT was associated with similar effectiveness among individuals with symptoms of mild/subthreshold depression. Personalized treatment selection is entirely possible and necessary to ensure the best allocation of treatment resources for depression.
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| 3. |
- Phillips, S. P., et al.
(author)
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Systematic review of methods used to study the intersecting impact of sex and social locations on health outcomes
- 2020
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In: SSM - Population Health. - : Elsevier BV. - 2352-8273. ; 12
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Research review (peer-reviewed)abstract
- Purpose: Independent health impacts of sex or social circumstances are well-studied, particularly among older adults. Less theorized or examined is how combinations or intersections of these underpin differential health effects. Nevertheless, and often without naming it as such, an intersectional framework aligns with studies of social determinants of health, life-course epidemiology and eco-epidemiology. In this systematic review we examined and aimed to identify research methods used to operationalize, whether intentionally or inadvertently, interconnected effects of sex and social locations on health outcomes for 45+ year olds.Methods: Using broad search terms, numerous databases, and following Prisma guidelines, 732 of 9214 papers initially identified, met inclusion criteria for full review.Results: Of the 501 papers included after full review, methods used in considering intersections of sex and social circumstances/location(s) included regression (112 of 365 papers), growth curves (7 of 22), multilevel (15 of 25), decomposition (6 of 9), mediation (10 of 17), structural equation modelling (23 of 25), and other (2 of 3). Most (n = 157) approximated intersectional analyses by including interaction terms or sex-stratifying results.Discussion: Few authors used the inherent strength of some study methods to examine intersecting traits. As even fewer began with an intersectionality framework their subsequent failure to deliver cannot be faulted, despite many studies including data and methodologies that would support intersectional analyses. There appeared to be a gap, not in analytic potential but rather in theorizing that differential distributions of social locations describe heterogeneity within the categories 'men' and 'women' that can underlie differential, gendered effects on older adults' health. While SEM, mediation and decomposition analyses emerged as particularly robust methods, the unexpected outcome was finding how few researchers consider intersectionality as a potential predictor of health.
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