Clinical decision support systems in addiction and concurrent disorders: A systematic review and meta-analysis.

INTRODUCTION: This review aims to synthesise the literature on the efficacy, evolution, and challenges of implementing Clincian Decision Support Systems (CDSS) in the realm of mental health, addiction, and concurrent disorders. METHODS: Following PRISMA guidelines, a systematic review and meta-analysis were performed. Searches conducted in databases such as MEDLINE, Embase, CINAHL, PsycINFO, and Web of Science through 25 May 2023, yielded 27,344 records. After necessary exclusions, 69 records were allocated for detailed synthesis. In the examination of patient outcomes with a focus on metrics such as therapeutic efficacy, patient satisfaction, and treatment acceptance, meta-analytic techniques were employed to synthesise data from randomised controlled trials. RESULTS: A total of 69 studies were included, revealing a shift from knowledge-based models pre-2017 to a rise in data-driven models post-2017. The majority of models were found to be in Stage 2 or 4 of maturity. The meta-analysis showed an effect size of -0.11 for addiction-related outcomes and a stronger effect size of -0.50 for patient satisfaction and acceptance of CDSS. DISCUSSION: The results indicate a shift from knowledge-based to data-driven CDSS approaches, aligned with advances in machine learning and big data. Although the immediate impact on addiction outcomes is modest, higher patient satisfaction suggests promise for wider CDSS use. Identified challenges include alert fatigue and opaque AI models. CONCLUSION: CDSS shows promise in mental health and addiction treatment but requires a nuanced approach for effective and ethical implementation. The results emphasise the need for continued research to ensure optimised and equitable use in healthcare settings.

Autopsy rates and the misclassification of suicide and accident deaths.

Mortality statistics are critical to determine the burden of disease. Certain causes of death are prone to being misclassified on cause of death certificates. This poses a serious risk for public health and safety, as accurate death certificates form the basis for mortality statistics, which in turn are crucial for research, funding allocation and health interventions. This study uses generalised estimating equations and regression modelling to investigate for which cause of death categories suicide and accident deaths are misclassified as. National mortality statistics and autopsy rates from North America and Europe covering the past forty years were analysed to determine the associations between the different causes of death in cross-sectional and longitudinal models. We find that suicides and deaths by accidents are frequently mutually misclassified. We also find that suicides are frequently misclassified as drug use disorder deaths, in contrast to accident deaths, which are not misclassified as drug use disorder deaths. Furthermore, suicides do not seem to be misclassified as undetermined deaths or ill-defined deaths. The frequency of misclassification shows that the quality of death certificates should be improved, and autopsies may be used systematically to control the quality of death certificates.

E-learning as a tool of suicide prevention training: A meta-analysis and systematic review.

Suicide is a global health challenge. One prevention strategy is teaching individuals how to detect and respond to suicidality. These training have increasingly been delivered online. We searched WoS, Scopus, and PubMed from inception until the 20 September 2023 to evaluate e-learning efficacy as standardized mean changes and standardized mean differences. We synthesized main results using multilevel meta-analyses and subgroups using random-effects meta-analyses. Robins-I, RoB-II and trim-and-fill were used to assess the risk of bias. Of the 6516 initially screened articles, 26 were included. Overall, e-learning increased suicide prevention skills. Subgroups reported differing results: e-learning affected knowledge and self-efficacy more than behavior and attitudes. Efficacy, short duration, and low-cost suggest that e-learning may be feasible in teaching basic suicide prevention skills to lay people. However, current evidence suggests that health care professionals should not rely on e-learning as a training modality, except when no other form of training is available. Preregisteration: CRD42020218978.

The fearlessness about death scale's efficacy for differentiating suicide attempts from non-suicidal self-injury, a meta-analysis.

We used multivariate meta-analysis modeling variances and covariances of suicidal ideation, suicide attempts, and non-suicidal self-injury to investigate if the Fearlessness About Death scale differentiated between suicide attempts and non-suicidal self-injury. The systematic search yielded 27 studies that fulfilled the inclusion criteria. The association of suicidal ideation with suicide attempts was comparable to the association of suicidal ideation with non-suicidal self-injury. The Fearlessness About Death scale weakened both associations to a comparative degree. These results cast doubt on the clinical utility of the Fearlessness About Death scale, as well as the self-assessment of suicidal ideation, suicide attempts and non-suicidal self-injury.

Effectiveness of distance-based suicide interventions: multi-level meta-analysis and systematic review.

BACKGROUND: The use of distance-based interventions (DBIs) to reduce suicidal ideation and behaviours are an increasingly relevant form of intervention. DBIs are more affordable, scalable and available than traditional face-to-face interventions, helping to narrow the gap between needed and provided care. AIMS: To evaluate the overall effectiveness of DBIs against suicidal ideation and behaviours. METHOD: We systematically searched Web of Science, Scopus and PubMed for all DBIs primarily aimed at reducing suicidal ideation and behaviours. Data were analysed with a robust variance estimation corrected, multi-level meta-analysis. RESULTS: We found 38 studies, reporting 110 outcomes. Effectiveness in reducing suicidal ideation was low (standardised mean difference -0.174, 95% CI -0.238 to -0.110). DBIs were significantly less effective against suicidal behaviours than against suicidal ideation, although still effective (standardised mean difference -0.059, 95% CI -0.087 to -0.032). Human involvement had no significant effect on effectiveness. CONCLUSIONS: Despite low effectiveness, DBIs might play a role in large-scale prevention efforts against suicidal ideation within a stepped care approach. Further, DBIs may be helpful in expanding mental health services in low- and middle-income countries with otherwise limited access to mental healthcare. Although the evidence for DBIs efficacy is well grounded, the technical and scientific evaluation of DBIs regarding their set up, functionality and components needs to be addressed in future studies.