Interventions for reducing self-stigma in people with mental illnesses: a systematic review of randomized controlled trials

Background: Self-stigma occurs when people with mental illnesses internalize negative stereotypes and prejudices about their condition. It can reduce help-seeking behaviour and treatment adherence. The effectiveness of interventions aimed at reducing self-stigma in people with mental illness is systematically reviewed. Results are discussed in the context of a logic model of the broader social context of mental illness stigma. Methods: Medline, Embase, PsycINFO, ERIC, and CENTRAL were searched for randomized controlled trials in November 2013. Studies were assessed with the Cochrane risk of bias tool.Results: Five trials were eligible for inclusion, four of which provided data for statistical analyses. Four studies had a high risk of bias. The quality of evidence was very low for each set of interventions and outcomes. The interventions studied included various group based anti-stigma interventions and an anti-stigma booklet. The intensity and fidelity of most interventions was high. Two studies were considered to be sufficiently homogeneous to be pooled for the outcome self-stigma. The meta-analysis did not find a statistically significant effect at 3 months: –0.26 [–0.64, 0.12], I=0%, n=108). None of the individual studies found sustainable effects on other outcomes, including recovery, help-seeking behaviour and self-stigma.Conclusions: The effectiveness of interventions against self-stigma is uncertain. Previous studies lacked statistical power, used questionable outcome measures and had a high risk of bias. Future studies should be based on robust methods and consider practical implications regarding intervention development (relevance, implementability, and placement in routine services)

Reporting of methods to prepare, pilot and perform data extraction in systematic reviews: analysis of a sample of 152 Cochrane and non-Cochrane reviews

Background!#!Previous research on data extraction methods in systematic reviews has focused on single aspects of the process. We aimed to provide a deeper insight into these methods by analysing a current sample of reviews.!##!Methods!#!We included systematic reviews of health interventions in humans published in English. We analysed 75 Cochrane reviews from May and June 2020 and a random sample of non-Cochrane reviews published in the same period and retrieved from Medline. We linked reviews with protocols and study registrations. We collected information on preparing, piloting, and performing data extraction and on use of software to assist review conduct (automation tools). Data were extracted by one author, with 20% extracted in duplicate. Data were analysed descriptively.!##!Results!#!Of the 152 included reviews, 77 reported use of a standardized extraction form (51%); 42 provided information on the type of form used (28%); 24 on piloting (16%); 58 on what data was collected (38%); 133 on the extraction method (88%); 107 on resolving disagreements (70%); 103 on methods to obtain additional data or information (68%); 52 on procedures to avoid data errors (34%); and 47 on methods to deal with multiple study reports (31%). Items were more frequently reported in Cochrane than non-Cochrane reviews. The data extraction form used was published in 10 reviews (7%). Use of software was rarely reported except for statistical analysis software and use of RevMan and GRADEpro GDT in Cochrane reviews. Covidence was the most frequent automation tool used: 18 reviews used it for study selection (12%) and 9 for data extraction (6%).!##!Conclusions!#!Reporting of data extraction methods in systematic reviews is limited, especially in non-Cochrane reviews. This includes core items of data extraction such as methods used to manage disagreements. Few reviews currently use software to assist data extraction and review conduct. Our results can serve as a baseline to assess the uptake of such tools in future analyses

Development, testing and use of data extraction forms in systematic reviews: a review of methodological guidance

Background!#!Data extraction forms link systematic reviews with primary research and provide the foundation for appraising, analysing, summarising and interpreting a body of evidence. This makes their development, pilot testing and use a crucial part of the systematic reviews process. Several studies have shown that data extraction errors are frequent in systematic reviews, especially regarding outcome data.!##!Methods!#!We reviewed guidance on the development and pilot testing of data extraction forms and the data extraction process. We reviewed four types of sources: 1) methodological handbooks of systematic review organisations (SRO); 2) textbooks on conducting systematic reviews; 3) method documents from health technology assessment (HTA) agencies and 4) journal articles. HTA documents were retrieved in February 2019 and database searches conducted in December 2019. One author extracted the recommendations and a second author checked them for accuracy. Results are presented descriptively.!##!Results!#!Our analysis includes recommendations from 25 documents: 4 SRO handbooks, 11 textbooks, 5 HTA method documents and 5 journal articles. Across these sources the most common recommendations on form development are to use customized or adapted standardised extraction forms (14/25); provide detailed instructions on their use (10/25); ensure clear and consistent coding and response options (9/25); plan in advance which data are needed (9/25); obtain additional data if required (8/25); and link multiple reports of the same study (8/25). The most frequent recommendations on piloting extractions forms are that forms should be piloted on a sample of studies (18/25); and that data extractors should be trained in the use of the forms (7/25). The most frequent recommendations on data extraction are that extraction should be conducted by at least two people (17/25); that independent parallel extraction should be used (11/25); and that procedures to resolve disagreements between data extractors should be in place (14/25).!##!Conclusions!#!Overall, our results suggest a lack of comprehensiveness of recommendations. This may be particularly problematic for less experienced reviewers. Limitations of our method are the scoping nature of the review and that we did not analyse internal documents of health technology agencies

Quality ratings of reviews in overviews: a comparison of reviews with and without dual (co-)authorship

Abstract Background Previous research shows that many authors of Cochrane overviews were also involved in some of the included systematic reviews (SRs). This type of dual (co-)authorship (DCA) may be a conflict of interest and a potential source of bias. Our objectives were to (1) additionally investigate DCA in non-Cochrane overviews; (2) investigate whether there is an association between DCA and quality assessments of SRs in Cochrane and non-Cochrane overviews. Methods We selected a sample of Cochrane (n = 20) and non-Cochrane (n = 78) overviews for analysis. We extracted data on the number of reviews affected by DCA and whether quality assessment of included reviews was conducted independently. Differences in mean quality scores between SRs with and without DCA were calculated in each overview. These differences were standardized (using the standardized mean difference (SMD)) and meta-analyzed using a random effects model. Results Forty out of 78 non-Cochrane overviews (51%) and 18 out of 20 Cochrane overviews (90%) had included at least one SR with DCA. For Cochrane overviews, a median of 5 [interquartile range (IQR) 2.5 to 7] SRs were affected by DCA (median of included reviews 10). For non-Cochrane overviews a median of 1 [IQR 0 to 2] of the included SRs were affected (median of included reviews 14). The meta-analysis showed a SMD of 0.58 (95% confidence interval (CI) 0.27 to 0.90) indicating higher quality scores in reviews with overlapping authors. The test for subgroup differences shows no evidence of a difference between Cochrane (SMD 0.44; 95% CI 0.07 to 0.81) and non-Cochrane overviews (SMD 0.62; 95% CI 0.06 to 1.17). Conclusions Many authors of overviews also often have an authorship on one or more of the underlying reviews. Our analysis shows that, on average, authors of overviews give higher quality ratings to SRs in which they were involved themselves than to other SRs. Conflict of interest is one explanation, but there are several others such as reviewer expertise. Independent and blinded reassessments of the reviews would provide more robust evidence on potential bias arising from DCA

Epidemiology and reporting characteristics of overviews of reviews of healthcare interventions published 2012–2016: protocol for a systematic review

Abstract Background Overviews of systematic reviews (overviews) attempt to systematically retrieve and summarize the results of multiple systematic reviews (SRs) for a given condition or public health problem. Two prior descriptive analyses of overviews found substantial variation in the methodological approaches used in overviews, and deficiencies in reporting of key methodological steps. Since then, new methods have been developed so it is timely to update the prior descriptive analyses. The objectives are to: (1) investigate the epidemiological, descriptive, and reporting characteristics of a random sample of 100 overviews published from 2012 to 2016 and (2) compare these recently published overviews (2012–2016) to those published prior to 2012 (based on the prior descriptive analyses). Methods Medline, EMBASE, and CDSR will be searched for overviews published 2012–2016, using a validated search filter for overviews. Only overviews written in English will be included. All titles and abstracts will be screened by one review author; those deemed not relevant will be verified by a second person for exclusion. Full-texts will be assessed for inclusion by two reviewers independently. Of those deemed relevant, a random sample of 100 overviews will be selected for inclusion. Data extraction will be either performed by one reviewer with verification by a second reviewer or by one reviewer only depending on the complexity of the item. Discrepancies at any stage will be resolved by consensus or consulting a third person. Data will be extracted on the epidemiological, descriptive, and reporting characteristics of each overview. Data will be analyzed descriptively. When data are available for both time points (up to 2011 vs. 2012–2016), we will compare characteristics by calculating risk ratios or applying the Mann-Whitney test. Discussion Overviews are becoming increasingly valuable evidence syntheses, and the number of published overviews is increasing. However, former analyses found limitations in the conduct and reporting of overviews. This update of a recent sample of overviews will inform whether this has changed, while also identifying areas for further improvement. Systematic review registration The review will not be registered in PROSPERO as it does not meet the eligibility criterion of dealing with health-related outcomes