Project description:BackgroundSmartphone-delivered attentional bias modification training (ABMT) intervention has gained popularity as a remote solution for alleviating symptoms of mental health problems. However, the existing literature presents mixed results indicating both significant and insignificant effects of smartphone-delivered interventions.ObjectiveThis systematic review and meta-analysis aims to assess the impact of smartphone-delivered ABMT on attentional bias and symptoms of mental health problems. Specifically, we examined different design approaches and methods of administration, focusing on common mental health issues, such as anxiety and depression, and design elements, including gamification and stimulus types.MethodsOur search spanned from 2014 to 2023 and encompassed 4 major databases: MEDLINE, PsycINFO, PubMed, and Scopus. Study selection, data extraction, and critical appraisal were performed independently by 3 authors using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. When necessary, we pooled the standardized mean difference with a 95% CI. In addition, we conducted sensitivity, subgroup, and meta-regression analyses to explore moderator variables of active and placebo ABMT interventions on reducing symptoms of mental health problems and attentional bias.ResultsOur review included 12 papers, involving a total of 24,503 participants, and we were able to conduct a meta-analysis on 20 different study samples from 11 papers. Active ABMT exhibited an effect size (Hedges g) of -0.18 (P=.03) in reducing symptoms of mental health problems, while the overall effect remained significant. Similarly, placebo ABMT showed an effect size of -0.38 (P=.008) in reducing symptoms of mental health problems. In addition, active ABMT (Hedges g -0.17; P=.004) had significant effects on reducing attentional bias, while placebo ABMT did not significantly alter attentional bias (Hedges g -0.04; P=.66).ConclusionsOur understanding of smartphone-delivered ABMT's potential highlights the value of both active and placebo interventions in mental health care. The insights from the moderator analysis also showed that tailoring smartphone-delivered ABMT interventions to specific threat stimuli and considering exposure duration are crucial for optimizing their efficacy. This research underscores the need for personalized approaches in ABMT to effectively reduce attentional bias and symptoms of mental health problems.Trial registrationPROSPERO CRD42023460749; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=460749.

Project description:Background: Interpreters often play a crucial role in the health care of refugees. Although interpreters working with refugees are regularly confronted with emotionally stressful content, little is known about their work-related stress and psychological well-being. Primarily qualitative studies indicate increased emotional stress in interpreters, and difficulties in handling the traumatic content from their clients. Additionally, the working conditions of interpreters appear to be demanding, due to low payment and a lack of supervision or adequate preparation. Objective: The presented systematic review aimed to identify and summarise quantitative and qualitative research on the mental health of interpreters in the mental health care of refugees. Method: A systematic search was performed in five databases, and specific interpreting journals were searched. After removal of duplicates, 6,920 hits remained. Eligible studies included quantitative, qualitative, and mixed-methods studies as well as case studies and grey literature. The studies aimed to examine mental health aspects or work experiences of spoken language interpreters in mental health care settings for adult refugees. Results: Altogether, 25 studies were identified, including six quantitative and 19 qualitative studies. Studies were analysed and presented narratively. In the analysis of the qualitative studies, three themes emerged: "Emotions, behaviour, and coping strategies," "Working in a triad," and "Working environment." In the quantitative studies, interpreters showed heightened levels of emotional stress and anxiety, and secondary traumatic stress reactions. In several qualitative studies, interpreters described a devaluing health care system and stressful working conditions with a lack of support structures. Conclusion: Overall, the results indicate a high level of stress among interpreters working with refugees. Quantitative data are sparse, and studies employ heterogeneous assessments in diverse study settings. Therefore, future quantitative research is necessary to consistently investigate interpreters' mental health in different mental health care settings. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42019117948.

Project description:BackgroundConnected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management.ObjectiveThe aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness.MethodsA systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted.ResultsAfter final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients' preferring traditional therapy, were reported in studies addressing patients with specific physical health issues.ConclusionsThe use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

Project description:BackgroundConversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials.ObjectiveThis review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition.MethodsWe searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings.ResultsThe systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition.ConclusionsOur results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

Project description:Children in foster care have high rates of adverse childhood experiences and are at risk for mental health problems. These problems can be difficult to ameliorate, creating a need for rigorous intervention research. Previous research suggests that intervening with children in foster care can be challenging for several reasons, including the severity and complexity of their mental health problems, and challenges engaging this often transitory population in mental health services. The goal of this article was to systematically review the intervention research that has been conducted with children in foster care, and to identify future research directions. This review was conducted on mental health interventions for children, ages 0 to 12, in foster care, using ERIC, CINAHL, PsycINFO, PubMed, ProQuest's Dissertation and Theses Database, Social Services Abstracts, and Social Work Abstracts. It was restricted to interventions that are at least "possibly efficacious" (i.e., supported by evidence from at least one randomized controlled trial). Studies were evaluated for risk of bias. Ten interventions were identified, with diverse outcomes, including mental health and physiological. Six interventions were developed for children in foster care. Interventions not developed for children in foster care were typically adapted to the foster context. Most interventions have yet to be rigorously evaluated in community-based settings with children in foster care. Little research has been conducted on child and family engagement within these interventions, and there is a need for more research on moderators of intervention outcomes and subgroups that benefit most from these interventions. In addition, there is not consensus regarding how to adapt interventions to this population. Future research should focus on developing and testing more interventions with this population, rigorously evaluating their effectiveness in community-based settings, determining necessary adaptations, and identifying which interventions work best for whom.

Project description:ObjectivesProviding adequate access to mental health services is a global challenge. Smartphone apps offer a potentially cost-effective, available and accessible solution for monitoring, supporting and treating mental health conditions. This systematic review describes and evaluates the usage of smartphone apps across a wide range of mental health disorders in terms of clinical effectiveness, feasibility and acceptability.DesignThis is a systematic review of studies examining treatment, self-monitoring and multipurpose smartphone apps for mental health disorders.Data sourcesStudies were identified through a comprehensive search of the Ovid and PubMed databases. Articles published up to 14 January 2024 were included based on predefined criteria.Eligibility criteriaWe included randomised controlled trials that compared mental health apps (single- or multipurpose) with treatment-as-usual or no treatment for clinical populations with mental health disorders. Studies were excluded if they focused on web-based interventions, combined apps with non-TAU treatments or targeted physical health apps.Data extraction and synthesisTwo independent reviewers screened and selected studies, with a third reviewer resolving inconsistencies. Extracted data included study details, participant characteristics, app information and outcome measures related to effectiveness, feasibility and acceptability. A risk-of-bias assessment for each study was conducted.ResultsOut of 4153 non-duplicate articles screened, 31 studies met full-text eligibility criteria. These included 6 studies on treatment apps, 4 on self-monitoring apps and 21 on multipurpose apps for a range of mental health disorders. Fifteen were identified as having between some and high concern on the risk-of-bias assessment. While smartphone apps were generally effective and acceptable, their feasibility appeared to decline over time.ConclusionsSmartphone apps are promising tools for mental healthcare, demonstrating effectiveness and acceptability. However, challenges such as reduced feasibility over time, potential biases and underrepresented demographics require further research. This review proposes five recommendations for improving clinical translation in future studies.

Dataset Information

Smartphone-delivered mental health care interventions for refugees: A systematic review of the literature.

Publications

Smartphone-delivered mental health care interventions for refugees: A systematic review of the literature.

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