Psychological interventions for adults with bipolar disorder: a systematic review and meta-analysis

Background Psychological interventions may be beneficial for bipolar disorder. Aims Efficacy evaluation of psychological interventions for adults with bipolar disorder. Methods A systematic review of randomised controlled trials.. Outcomes were meta-analysed using RevMan and confidence assessed using the GRADE-method. Results We included 55 trials with 6010 participants. Moderate quality evidence associated individual psychological interventions with reduced relapses at post-treatment and follow-up, and collaborative care with a reduction in hospitalisations. . Low quality evidence associated group interventions with fewer depression relapses at post-treatment and follow-up, and family psycho-education with reduced symptoms of depression and mania at post-treatment. Conclusions There is evidence that psychological interventions are effective for people with bipolar disorder. Limits were the very low quality of much of the evidence and therefore inconclusive. Further research should identify the most (cost)-effective interventions for each phase of this disorder

Changes in social functioning over the course of psychotic disorders:A meta-analysis

In this meta-analysis we investigated changes in social functioning and its moderators in patients with a psychotic disorder but different durations of illness at baseline. We included longitudinal studies assessing the course of five domains of social functioning in patients with a psychotic disorder. Effect sizes of change between baseline and follow-up within these domains were analyzed in four subgroups based on durations of psychotic disorder at baseline: less than 2 years, between 2 and 5 years, between 5 and 10 years, and more than 10 years. The influence of baseline confounders was analyzed using meta-regression and sensitivity analysis. We included 84 studies analyzing 33,456 participants. We found a medium improvement (d = 0.60) in overall social functioning over time, with a greater improvement for studies investigating patients with a duration of illness of less than 5 years. We found minor improvement in specific domains of social functioning, such as vocational functioning (d = 0.31), prosocial behavior (d = 0.36), activities (d = 0.15), and independence (d = 0.25). Improvement in social functioning was associated with lower baseline levels of negative symptoms, higher baseline levels of quality of life, and, specifically, improved vocational functioning, with rehabilitation and combined treatment. Social functioning in patients with psychotic disorders improves over time, especially for patients with shorter illness durations. Reduction of negative symptoms and improving quality of life might reinforce improvement of social functioning

Implementing a stepped-care approach in primary care: results of a qualitative study

Contains fulltext : 108260.pdf (publisher's version ) (Open Access)BACKGROUND: Since 2004, 'stepped-care models' have been adopted in several international evidence-based clinical guidelines to guide clinicians in the organisation of depression care. To enhance the adoption of this new treatment approach, a Quality Improvement Collaborative (QIC) was initiated in the Netherlands. METHODS: Alongside the QIC, an intervention study using a controlled before-and-after design was performed. Part of the study was a process evaluation, utilizing semi-structured group interviews, to provide insight into the perceptions of the participating clinicians on the implementation of stepped care for depression into their daily routines. Participants were primary care clinicians, specialist clinicians, and other healthcare staff from eight regions in the Netherlands. Analysis was supported by the Normalisation Process Theory (NPT). RESULTS: The introduction of a stepped-care model for depression to primary care teams within the context of a depression QIC was generally well received by participating clinicians. All three elements of the proposed stepped-care model (patient differentiation, stepped-care treatment, and outcome monitoring), were translated and introduced locally. Clinicians reported changes in terms of learning how to differentiate between patient groups and different levels of care, changing antidepressant prescribing routines as a consequence of having a broader treatment package to offer to their patients, and better working relationships with patients and colleagues. A complex range of factors influenced the implementation process. Facilitating factors were the stepped-care model itself, the structured team meetings (part of the QIC method), and the positive reaction from patients to stepped care. The differing views of depression and depression care within multidisciplinary health teams, lack of resources, and poor information systems hindered the rapid introduction of the stepped-care model. The NPT constructs 'coherence' and 'cognitive participation' appeared to be crucial drivers in the initial stage of the process. CONCLUSIONS: Stepped care for depression is received positively in primary care. While it is difficult for the implementation of a full stepped-care approach to occur within a short time frame, clinicians can make progress towards achieving a stepped-care approach, particularly within the context of a QIC. Creating a shared understanding within multidisciplinary teams of what constitutes depression, reaching a consensus about the content of depression care, and the division of tasks are important when addressing the implementation process

Scripts, data and output to reproduce "Addressing the Challenges of Reconstructing Systematic Reviews Datasets: A Case Study and a Noisy Label Filter Procedure"

Here you can find the scripts, data and output to reproduce our study "Addressing the Challenges of Reconstructing Systematic Reviews Datasets: A Case Study and Decision Tree". In this study, we reconstructed a database to perform a simulation study in ASReview. A solution for the problems faced is presented: the NLF procedure (noisy label filter)

Taking steps towards deinstitutionalizing mental health care within a low and middle-income country:A cross-sectional study of service user needs in the Republic of Moldova

Aim: The current research was conducted in the context of an ongoing reform of mental health services in the Republic of Moldova since 2014, where efforts have been devoted to creating community-based mental health services. This article presents a snapshot of the needs of mental health service users in the Republic of Moldova and helps to understand how and with which services their needs can be addressed. Methods: This cross-sectional study compared the levels of needs (CANSAS scale), quality of life (EQ-5D 3L), mental health status (MINI for psychotic disorders) and functioning (WHO-DAS) among mental health service users in the psychiatric hospital in Chisinau, Moldova. All service users resided in districts where community mental health services were being developed. Correlations between quality of life, functioning and unmet need were explored. Results: Of 83 participants, one third had a psychotic or a mood disorder. On average, participants reported needs in 9.41 domains (SD = 4.41), of which 4.29 were unmet (SD = 3.63). Most unmet needs related to intimacy and relation to others. The level of functioning and quality of life were reported. We found strong, negative associations between the number of unmet needs and level of functioning, as well as the quality of life. We also found that higher functioning levels were positively associated with higher quality of life. Conclusion: There were a high number of unmet needs among this inpatient population, particularly social needs and service-related needs. A continuum of inpatient and outpatient care and individual treatment plans can help address the different needs of different patients. Individual treatment plans for patients and the choice of the appropriate treatment for patients could be guided by an assessment of service users’ (unmet) needs of care and level of functioning

Addressing the challenges of reconstructing systematic reviews datasets: a case study and a noisy label filter procedure

Abstract Systematic reviews and meta-analyses typically require significant time and effort. Machine learning models have the potential to enhance screening efficiency in these processes. To effectively evaluate such models, fully labeled datasets—detailing all records screened by humans and their labeling decisions—are imperative. This paper presents the creation of a comprehensive dataset for a systematic review of treatments for Borderline Personality Disorder, as reported by Oud et al. (2018) for running a simulation study. The authors adhered to the PRISMA guidelines and published both the search query and the list of included records, but the complete dataset with all labels was not disclosed. We replicated their search and, facing the absence of initial screening data, introduced a Noisy Label Filter (NLF) procedure using active learning to validate noisy labels. Following the NLF application, no further relevant records were found. A simulation study employing the reconstructed dataset demonstrated that active learning could reduce screening time by 82.30% compared to random reading. The paper discusses potential causes for discrepancies, provides recommendations, and introduces a decision tree to assist in reconstructing datasets for the purpose of running simulation studies