Digital Tools to Facilitate the Detection and Treatment of Bipolar Disorder: Key Developments and Future Directions.

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.

Evidence of factors influencing delays in the diagnosis and treatment of bipolar disorder in adolescents and young adults. Protocol for a systematic scoping review.

BACKGROUND: Bipolar Disorder (BD) is a complex psychiatric condition that typically manifests during late adolescence and early adulthood. Over the past two decades, international studies have reported that BD often goes unrecognized and untreated for several years, which can lead to negative clinical and functional outcomes. However, the components of delay in the diagnosis and treatment of BD and various factors influencing those components have not been systematically explored. OBJECTIVES: The scoping review described in this protocol aims to map the existing literature on potential factors that influence delays in the treatment of BD in adolescents and young adults, in order to identify the knowledge gaps and future research and policy priorities. METHODS: This protocol for a systematic scoping review will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline (PRISMA-ScR). We will search the electronic databases of MEDLINE (OVID), EMBASE, PsycINFO and CINAHL for peer-reviewed primary research articles published in academic journals. Grey literature will not be explored due to resource limitations. A conceptual framework based on the Model of Pathways to Treatment by Scott and colleagues was used as a foundation for our search and extraction strategy to ensure all components of delay and potential factors influencing each component are explored. Two independent reviewers will screen the references retrieved by the literature search and select relevant studies based on our inclusion criteria. The data from included studies will be synthesized into a narrative summary, and implications for future research, practice and policy will be discussed. DISCUSSION: To the best of our knowledge, this will be the first scoping review to explore the potential factors that influence delays in the treatment of BD in adolescents and young adults. We intend to disseminate the review results through academic conferences and publication in a peer-reviewed journal.

Machine Learning Prediction of Quality of Life Improvement During Antidepressant Treatment of Patients With Major Depressive Disorder: A STAR*D and CAN-BIND-1 Report.

Background: Quality of life (QoL) is an important patient-centric outcome to evaluate in treatment of major depressive disorder (MDD). This work sought to investigate the performance of several machine learning methods to predict a return to normative QoL in patients with MDD after antidepressant treatment.Methods: Several binary classification algorithms were trained on data from the first 2 weeks of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (n = 651, conducted from 2001 to 2006) to predict week 9 normative QoL (score ≥ 67, based on a community normative sample, on the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form [Q-LES-Q-SF]) after treatment with citalopram. Internal validation was performed using a STAR*D holdout dataset, and external validation was performed using the Canadian Biomarker Integration Network in Depression-1 (CAN-BIND-1) dataset (n = 175, study conducted from 2012 to 2017) after treatment with escitalopram. Feature importance was calculated using SHapley Additive exPlanations (SHAP).Results: Random Forest performed most consistently on internal and external validation, with balanced accuracy (area under the receiver operator curve) of 71% (0.81) on the STAR*D dataset and 69% (0.75) on the CAN-BIND-1 dataset. Random Forest Classifiers trained on Q-LES-Q-SF and Quick Inventory of Depressive Symptomatology-Self-Rated variables had similar performance on both internal and external validation. Important predictive variables came from psychological, physical, and socioeconomic domains.Conclusions: Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility.Trial Registration: ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.

Using EMPOWER in daily life: a qualitative investigation of implementation experiences.

BACKGROUND: Digital self-management tools blended with clinical triage and peer support have the potential to improve access to early warning signs (EWS) based relapse prevention in schizophrenia care. However, the implementation of digital interventions in psychosis can be poor. Traditionally, research focused on understanding how people implement interventions has focused on the perspectives of mental health staff. Digital interventions are becoming more commonly used by patients within the context of daily life, which means there is a need to understand implementation from the perspectives of patients and carers. METHODS: Semi-structured one-on-one interviews with 16 patients who had access to the EMPOWER digital self-management intervention during their participation in a feasibility trial, six mental health staff members who supported the patients and were enrolled in the trial, and one carer participant. Interviews focused on understanding implementation, including barriers and facilitators. Data were coded using thematic analysis. RESULTS: The intervention was well implemented, and EMPOWER was typically perceived positively by patients, mental health staff and the carer we spoke to. However, some patients reported negative views and reported ideas for intervention improvement. Patients reported valuing that the app afforded them access to things like information or increased social contact from peer support workers that went above and beyond that offered in routine care. Patients seemed motivated to continue implementing EMPOWER in daily life when they perceived it was creating positive change to their wellbeing, but seemed less motivated if this did not occur. Mental health staff and carer views suggest they developed increased confidence patients could self-manage and valued using the fact that people they support were using the EMPOWER intervention to open up conversations about self-management and wellbeing. CONCLUSIONS: The findings from this study suggest peer worker supported digital self-management like EMPOWER has the potential to be implemented. Further evaluations of these interventions are warranted, and conducting qualitative research on the feasibility gives insight into implementation barriers and facilitators, improving the likelihood of interventions being usable. In particular, the views of patients who demonstrated low usage levels would be valuable.

Barriers to and facilitators of success for early and Mid-Career professionals focused on bipolar disorder: A global needs survey by the International Society for Bipolar Disorders.

INTRODUCTION: The International Society for Bipolar Disorders created the Early Mid-Career Committee (EMCC) to support career development of the next generation of researchers and clinicians specializing in bipolar disorder (BD). To develop new infrastructure and initiatives, the EMCC completed a Needs Survey of the current limitations and gaps that restrict recruitment and retention of researchers and clinicians focused on BD. METHODS: The EMCC Needs Survey was developed through an iterative process, relying on literature and content expertise of workgroup members. The survey included 8 domains: navigating transitional career stages, creating and fostering mentorship, research activities, raising academic profile, clinical-research balance, networking and collaboration, community engagement, work-life balance. The final survey was deployed from May to August 2022 and was available in English, Spanish, Portuguese, Italian, and Chinese. RESULTS: Three hundred participants across six continents completed the Needs Survey. Half of the participants self-identified as belonging to an underrepresented group in health-related sciences (i.e., from certain gender, racial, ethnic, cultural, or disadvantaged backgrounds including individuals with disabilities). Quantitative results and qualitative content analysis revealed key barriers to pursuing a research career focused on BD with unique challenges specific to scientific writing and grant funding. Participants highlighted mentorship as a key facilitator of success in research and clinical work. CONCLUSION: The results of the Needs Survey are a call to action to support early- and midcareer professionals pursuing a career in BD. Interventions required to address the identified barriers will take coordination, creativity, and resources to develop, implement, and encourage uptake but will have long-lasting benefits for research, clinical practice, and ultimately those affected by BD.

Engaging diverse patients in a diverse world: the development and preliminary evaluation of educational modules to support diversity in patient engagement research.

BACKGROUND: Current practices for engaging patients in patient-oriented research (POR) result in a narrow pool of patient perspectives being reflected in POR. This project aims to address gaps in methodological knowledge to foster diversity in POR, through the co-design and evaluation of a series of educational modules for health researchers in British Columbia, Canada. METHODS: Modules were co-created by a team of academic researchers and patient partners from hardly-reached communities. The modules are presented using the Tapestry Tool, an interactive, online educational platform. Our evaluation framework focused on engagement, content quality, and predicted behavior change. The User Engagement Scale short form (UES-SF) measured participants' level of engagement with the modules. Survey evaluation items assessed the content within the modules and participants' perceptions of how the modules will impact their behavior. Evaluation items modeled on the theory of planned behavior, administered before and after viewing the modules, assessed the impact of the modules on participants' perceptions of diversity in POR. RESULTS: Seventy-four health researchers evaluated the modules. Researchers' engagement and ratings of module content were high. Subjective behavioral control over fostering diversity in POR increased significantly after viewing the modules. CONCLUSIONS: Our results suggest the modules may be an engaging way to provide health researchers with tools and knowledge to increase diversity in health research. Future studies are needed to investigate best practices for engaging with communities not represented in this pilot project, such as children and youth, Indigenous Peoples, and Black communities. While educational interventions represent one route to increasing diversity in POR, individual efforts must occur in tandem with high-level changes that address systemic barriers to engagement.

Patient-Oriented research (POR) recognizes patients as partners in the research process, contributing valuable knowledge and lived experience to improve health outcomes and research translation. Unfortunately, POR presently does not represent all patients: patient partners involved in research tend to be white, middle-class women. Limited diversity in POR may limit research impact, in part because health research is not fully inclusive of the people requiring healthcare services and support. Although they recognize the need for diversity, many health researchers do not understand how to foster this. To empower health researchers with tools and knowledge to foster diversity in POR, we coordinated teams that co-created a set of educational modules. These teams included academic researchers and patient partners from seldom-heard communities in health research. The modules were built using the Tapestry Tool, an interactive, educational platform. We evaluated the modules using online surveys of 74 health researchers for three things: quality of module content, how engaging they were, and how they impacted health researchers' views on diversity in POR. Our results show that the modules' content was high quality and engaging. After viewing the modules, health researchers were more likely to feel like they had a role in engaging with more diverse people in their research, and felt that they had the tools, knowledge, and ability to do so. Education and knowledge for health researchers are a first step to increasing diversity in POR settings, but systemic barriers to inclusion also need attention.

Risks and benefits of psilocybin use in people with bipolar disorder: An international web-based survey on experiences of 'magic mushroom' consumption.

BACKGROUND: Psilocybin, the primary psychoactive component of psychedelic 'magic mushrooms', may have potential for treating depressive symptoms, and consequent applications for bipolar disorder (BD). Knowledge of the risks and benefits of psilocybin in BD is limited to case studies. AIM: To support the design of clinical trials, we surveyed experiences of psilocybin use in people with BD. METHODS: An international web-based survey was used to explore experiences of psilocybin use in people with a self-reported diagnosis of BD. Quantitative findings were summarised using descriptive statistics. Qualitative content analysis was used to investigate free-text responses, with a focus on positive experiences of psilocybin use. RESULTS: A total of 541 people completed the survey (46.4% female, mean 34.1 years old). One-third (32.2%; n = 174) of respondents described new/increasing symptoms after psilocybin trips, prominently manic symptoms, difficulties sleeping and anxiety. No differences in rates of adverse events overall were observed between individuals with BD I compared to BD II. Use of emergency medical services was rare (n = 18; 3.3%), and respondents (even those who experienced adverse effects) indicated that psilocybin use was more helpful than harmful. Quantitative findings elaborated on perceived benefits, as well as the potential for psilocybin trips to contain both positively and negatively received elements. CONCLUSIONS: The subjective benefits of psilocybin use for mental health symptoms reported by survey participants encourage further investigation of psilocybin-based treatments for BD. Clinical trials should incorporate careful monitoring of symptoms, as data suggest that BD symptoms may emerge or intensify following psilocybin use.

"A sense of the bigger picture:" A qualitative analysis of follow-up interviews with people with bipolar disorder who self-reported psilocybin use.

OBJECTIVES: People with bipolar disorder (BD) spend more time depressed than manic/hypomanic, and depression is associated with greater impairments in psychosocial functioning and quality of life than mania/hypomania. Emerging evidence suggests psilocybin, the psychoactive compound in "magic mushrooms," is a promising treatment for unipolar depression. Clinical trials of psilocybin therapy have excluded people with BD as a precaution against possible adverse effects (e.g., mania). Our study centered the experiences of adults living with BD who consumed psilocybin-containing mushrooms, and aimed to (1) understand its subjective impacts on BD symptoms, (2) deepen understanding of Phase I survey results, and (3) elucidate specific contextual factors associated with adverse reactions in naturalistic settings. METHODS: Following an international survey (Phase I), follow-up interviews were conducted with 15 respondents (Phase II) to further understand psilocybin use among adults with BD. As part of a larger mixed-methods explanatory sequential design study, reflexive thematic analysis was used to elaborate findings. RESULTS: Three major themes containing sub-themes were developed. (1) Mental Health Improvements: (1.1) decreased impact and severity of depression, (1.2) increased emotion processing, (1.3) development of new perspectives, and (1.4) greater relaxation and sleep. (2) Undesired Mental Health Impacts: (2.1) changes in sleep, (2.2) increased mania severity, (2.3) hospitalization, and (2.4) distressing sensory experiences. (3) Salient Contextual Factors for psilocybin use included: (3.1) poly-substance use and psilocybin dose, (3.2) solo versus social experiences, and (3.3) pre-psilocybin sleep deprivation. CONCLUSION: Our findings demonstrate both benefits and risks of psilocybin use in this population. Carefully designed clinical trials focused on safety and preliminary efficacy are warranted.

Supporting Self-management and Quality of Life in Bipolar Disorder With the PolarUs App (Alpha): Protocol for a Mixed Methods Study.

BACKGROUND: Quality of life (QoL) is increasingly being recognized as a key outcome of interventions for bipolar disorder (BD). Mobile phone apps can increase access to evidence-based self-management strategies and provide real-time support. However, although individuals with lived experiences desire support with monitoring and improving broader health domains, existing BD apps largely target mood symptoms only. Further, evidence from the broader mobile health (mHealth) literature has shown that the desires and goals of end users are not adequately considered during app development, and as a result, engagement with mental health apps is suboptimal. To capitalize on the potential of apps to optimize wellness in BD, there is a need for interventions developed in consultation with real-world users designed to support QoL self-monitoring and self-management. OBJECTIVE: This mixed methods pilot study was designed to evaluate the alpha version of the newly developed PolarUs app, developed to support QoL self-monitoring and self-management in people with BD. Co-designed using a community-based participatory research framework, the PolarUs app builds on the web-based adaptation of a BD-specific QoL self-assessment measure and integrates material from a web-based portal providing information on evidence-informed self-management strategies in BD. The primary objectives of this project were to evaluate PolarUs app feasibility (via behavioral use metrics), the impact of PolarUs (via the Brief Quality of Life in Bipolar Disorder scale, our primary outcome measure), and explore engagement with the PolarUs app (via quantitative and qualitative methods). METHODS: Participants will be residents of North America (N=150), aged >18 years, with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision diagnosis of BD type 1, BD type 2, or BD not otherwise specified as assessed by structured diagnostic interview. An embedded mixed methods research design will be adopted; qualitative interviews with a purposefully selected subsample (approximately, n=30) of participants will be conducted to explore in more depth feasibility, impact, and engagement with the PolarUs app over the 12-week study period. RESULTS: At the time of publication of this protocol, the development of the alpha version of the PolarUs app was complete. Participant enrollment has begun in June 2022. Data collection is expected to be completed by December 2022. CONCLUSIONS: Beyond contributing knowledge on the feasibility and impact of a novel app to support QoL and self-management in BD, this study will also provide new insights related to engagement with mHealth apps. Furthermore, it will function as a case study of successful co-design between people with BD, health care providers, and BD researchers, providing a template for the future use of community-based participatory research frameworks in mHealth intervention development. The results will be used to further refine the PolarUs app and inform the design of a larger clinical trial. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/36213.

The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia.

BACKGROUND: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. METHODS: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). FINDINGS: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Aug 8, 2018; 73 were randomised (42 [58%] to EMPOWER and 31 [42%] to treatment as usual). There were 37 (51%) men and 36 (49%) women. At 12 months, main outcomes were collected for 32 (76%) of service users in the EMPOWER group and 30 (97%) of service users in the treatment as usual group. Of those randomised to EMPOWER, 30 (71%) met our a priori criterion of more than 33% adherence to daily monitoring that assumed feasibility. Median time to discontinuation of these participants was 31·5 weeks (SD 14·5). There were 29 adverse events in the EMPOWER group and 25 adverse events in the treatment as usual group. There were 13 app-related adverse events, affecting 11 people, one of which was serious. Fear of relapse was lower in the EMPOWER group than in the treatment as usual group at 12 months (mean difference -7·53 (95% CI -14·45 to 0·60; Cohen's d -0·53). INTERPRETATION: A trial of digital technology to monitor early warning signs blended with peer support and clinical triage to detect and prevent relapse appears to be feasible, safe, and acceptable. A further main trial is merited. FUNDING: UK National Institute for Health Research Health Technology Assessment programme and the Australian National Health and Medical Research Council.

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT.

BACKGROUND: Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse. OBJECTIVE: How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? DESIGN: A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up. SETTINGS: Glasgow, UK, and Melbourne, Australia. PARTICIPANTS: Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user. INTERVENTIONS: The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted. MAIN OUTCOME MEASURES: The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse. RESULTS: We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference -4.29, 95% confidence interval -7.29 to -1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained. LIMITATIONS: This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness. CONCLUSIONS: A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible. FUTURE WORK: A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3-0.4). TRIAL REGISTRATION: This trial is registered as ISRCTN99559262. FUNDING: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879).

WHAT WAS THE PROBLEM?: Relapse is a considerable problem for people with a diagnosis of schizophrenia. Relapse can be predicted by early warning signs that are unique to the person. They include withdrawal, fear and paranoia. WHAT WAS THE QUESTION?: Is it possible to investigate the effectiveness of an intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse? WHAT DID WE DO?: We spoke with 88 mental health staff, 40 carers and 21 service users before we designed a system that used a mobile phone to help people monitor early warning signs. We included peer support to help people using the system reflect on their experiences. We hoped the overall system, called EMPOWER, would help people to be more in charge of their mental health. After consenting 86 people to the study, we were able to randomly assign 73 people either to use the EMPOWER system (42 people) or to receive their normal treatment alone (31 people). We used research measures over 1 year to help us better understand people's experiences. We also involved carers (for example family or friends) and mental health service providers in the research. WHAT DID WE FIND?: We found that it was possible to recruit people to the study and to gather research data. We also found that people used the EMPOWER system and found it acceptable. We found that those who used EMPOWER had a lower rate of relapse over 12 months than people who did not. They were also less likely to be fearful of relapse. We found that EMPOWER was likely to be cost-effective. WHAT DOES THIS MEAN?: This means that a study to investigate the effectiveness of a system to recognise and respond to early warning signs of relapse in schizophrenia is possible.

Evaluating the quality, safety, and functionality of commonly used smartphone apps for bipolar disorder mood and sleep self-management.

BACKGROUND: Individuals with bipolar disorder (BD) are increasingly turning to smartphone applications (apps) for health information and self-management support. While reviews have raised concerns regarding the effectiveness and safety of publicly available apps for BD, apps surveyed may not reflect what individuals with BD are using. The present study had two aims: first, to characterize the use of health apps to support mood and sleep amongst people with BD, and second, to evaluate the quality, safety and functionality of the most commonly used self-management apps. METHODS: A web-based survey was conducted to explore which apps people with BD reported using to support self-management of mood and sleep. The characteristics of the most commonly nominated apps were described using a standardized framework, including their privacy policy, clinical foundations, and functionality. RESULTS: Respondents (n = 919) were 77.9% female with a mean age of 36.9 years. 41.6% of participants (n = 382) reported using a self-management app to support mood or sleep. 110 unique apps were nominated in relation to mood, and 104 unique apps nominated in relation to sleep; however, most apps were only mentioned once. The nine most frequently nominated apps related to mood and sleep were subject to further evaluation. All reviewed apps offered a privacy policy, however user control over data was limited and the complexity of privacy policies was high. Only one app was developed for BD populations. Half of reviewed apps had published peer-reviewed evidence to support their claims of efficacy, but little research was specific to BD. CONCLUSION: Findings illustrate the potential of smartphone apps to increase the reach of psychosocial interventions amongst people with BD. Apps were largely created by commercial developers and designed for the general population, highlighting a gap in the development and dissemination of evidence-informed apps for BD. There may be risks in using generic health apps for BD self-management; clinicians should enquire about patients' app use to foster conversations about their particular benefits and limitations.

"Supporting Wellness": A depression and bipolar support alliance mixed-methods investigation of lived experience perspectives and priorities for mood disorder treatment.

BACKGROUND: The lived experience of people with mood disorders may be leveraged to inform priorities for research, define key treatment outcomes, and support decision-making in clinical care. The aim of this mixed-methods project was to provide insight into how people with depression and bipolar disorder experience the impact of symptoms, their treatment preferences, and their definitions of wellness. METHODS: The project was implemented in two phases. In Phase 1, community-based participatory research was used to develop a web-based survey enquiring about living with a mood disorder, treatment experiences, and wellness priorities. In Phase 2, a series of focus groups were conducted to explore aspects of wellness in greater detail. RESULTS: Respondents (n= 6153) described the symptoms of mood disorders as having a significant, chronic impact on their lives. A holistic approach to treatment was desired by participants, but not necessarily experienced. Qualitative findings were used to further describe four highly ranked wellness priorities identified in the survey: ability to act independently or according to my own will; purpose in life; getting through the day; and contentment. LIMITATIONS: Experience of a mood disorder was self-reported, and no formal confirmation of diagnosis occurred. Although the survey could not incorporate all possible wellness definitions, this was supplemented by qualitative focus groups. CONCLUSION: The present findings provide important insights from the perspectives of individuals with lived experience of mood disorders. Implications of this for research and clinical practice are discussed, particularly with regards to measurement-based care and use of wellness-oriented clinical outcome assessments.

Functional outcomes with bright light in monotherapy and combined with fluoxetine in patients with major depressive disorder: Results from the LIFE-D trial.

BACKGROUND: Bright light therapy has been shown to improve depressive symptoms in patients with nonseasonal major depressive disorder (MDD) but there are few studies examining functional outcomes. METHODS: We examined secondary functional outcomes in the 8-week randomized, placebo-sham-controlled LIFE-D trial comparing light therapy, fluoxetine, and the combination in patients with nonseasonal MDD. Functional assessments included the Sheehan Disability Scale (SDS) and, for employed participants, the Lam Employment Absence and Productivity Scale (LEAPS). Analysis of covariance (ANCOVA) was conducted with SDS and LEAPS change scores from baseline to week 8 as dependent variables, treatment modality (light, fluoxetine) as an independent variable, and baseline SDS and LEAPS scores as covariates. RESULTS: Of 122 randomized participants, SDS data were available for 105 and LEAPS data for 70. For the SDS, there were no interaction effects, but there was a significant small- to medium-sized main effect of light treatment on total SDS scores with corresponding significant effects in the Social Life and Family Life domains, but not in the Work/Study domain. There were no significant interaction or main effects with LEAPS scores. CONCLUSION: Light therapy significantly improved social and family life functioning in patients with MDD. However, work functioning was not significantly improved despite large effect sizes; these results were limited by low statistical power because of small sample sizes. Future studies should use longer treatment durations and be powered to detect clinically relevant differences in functional outcomes.

Association between discrepancy in objective and subjective cognitive abilities and treatment response in patients with major depressive disorder: A CAN-BIND-1 study report.

BACKGROUND: Major Depressive Disorder (MDD) is characterized by objective and subjective cognitive deficits. Discrepancies between objective and subjective cognitive performance can reflect under- to over-estimations of cognitive abilities, and these discrepancies are referred to as cognitive self-appraisals. Despite evidence that low self-appraisals are associated with depression, the modifiability of self-appraisals and their association with treatment outcome remains unclear. The current study examined whether self-appraisals change following antidepressant treatment. Furthermore, we investigated the association of self-appraisals with treatment outcome. METHODS: As part of the CAN-BIND-1 clinical trial, 154 patients with MDD completed measures of objective and subjective cognitive abilities, depressive symptoms, and functional outcomes (work productivity, psychosocial functioning, and quality of life) at baseline and post-escitalopram treatment. Self-appraisals were calculated based on discrepancies between objective and subjective cognitive abilities, with higher scores indicating overestimation of cognitive abilities. RESULTS: Baseline self-appraisals were not predictive of treatment outcomes. However, self-appraisals increased from pre- to post-treatment. Moreover, pre-post treatment increases in self-appraisals were associated with positive treatment response and remission, decreases in depressive symptoms, and improvements in work productivity, psychosocial functioning, and quality of life. LIMITATIONS: The pre-post intervention design precluded examining the temporal precedence of change in self-appraisals versus depressive symptoms and functional outcomes. CONCLUSIONS: Findings are the first to demonstrate that self-appraisals are treatment-sensitive and are associated with treatment outcomes and recovery from MDD. Cognitive self-appraisals may represent a key marker of treatment response and a valuable target for assessment and intervention, as well as a potential mechanism underlying risk and recovery.