The digital revolution and its impact on mental health care

Examining technology use and mental health among parents with newborns in the intensive care unit during the COVID-19 pandemic: A cross-sectional study

Objectives

To investigate the relationship between pandemic-related stressors, mental health, and technology use among parents of hospitalized infants during the COVID-19 pandemic.

Methods

A cross-sectional study of 47 participants who had an infant in the Neonatal Intensive Care Unit (NICU) during the pandemic was completed. Participants ranked several statements on a Likert scale to assess mental health, technology use, and COVID-19-related stress during their infant's stay in the NICU.

Results

Mental health wellness scores were negatively associated with COVID-19-related stress (rs - 0.40, p = .015). The most prevalent stressor was hospital visitation restriction. Higher COVID-19-related stress was associated with greater use of text and video chat [(rs0.35, p = 0.016) and (rs0.33, p = .025)]. Enjoyment of technology use and access to technology were positively associated with higher mental health wellness scores [(rs0.42, p = .003) and (rs0.38, p = .009)].

Conclusions

Social uses of technology were valuable in a cohort of parents with infants hospitalized during the COVID-19 pandemic.

Innovation

Technology is a tool that can help parents cope with the stress of having a hospitalized infant. Digital literacy and technology access should be promoted in the post-pandemic landscape to help parents of infants in the NICU attain more benefit from these resources.

Who benefits from digital interventions for bipolar disorder? Stage of illness characteristics as predictors of changes in quality of life

OBJECTIVES

This study explored the potential role of stage-related variables in intervention outcomes in bipolar disorder (BD). Specifically, we aimed to identify which subgroups of individuals were most likely to experience improved quality of life following digitally delivered psychosocial interventions for BD.

METHODS

The study involved a secondary analysis of combined data from two randomised control trials (RCTs). Each trial assessed the effectiveness of digitally delivered interventions for improving quality of life, in late-stage (ORBIT RCT) or early-stage (BETTER RCT) BD. Three iterations of cluster analyses were performed, identifying subgroups of individuals based on (i) current phenomenology, (ii) course of illness and (iii) medication response. The resultant subgroups were compared with regard to changes in quality of life pre-post intervention, via repeated measures ANOVAs.

RESULTS

In each cluster analysis, two clusters were found. The current phenomenology clusters reflected two impairment levels, 'moderate impairment' and 'low impairment'. The course of illness clusters reflected 'more chronicity' and 'less chronicity' and the medication response clusters reflected 'good medication response' and 'poor medication response'. Differences in changes in quality of life over time were observed between the two current phenomenology clusters and between the medication response clusters, while the course of illness subgroups did not respond differently.

CONCLUSIONS

There are at least two distinct groups of treatment-seeking individuals with established BD, based on illness features with previously established links to different illness stages. Clusters within the current phenomenology and medication response domains demonstrated significantly different trajectories of QoL change over time in the context of our interventions, highlighting potential implications for treatment selection aligned with precision psychiatry.

Reduced speech coherence in psychosis-related social media forum posts

The extraction of linguistic markers from social media posts, which are indicative of the onset and course of mental disorders, offers great potential for mental healthcare. In the present study, we extracted over one million posts from the popular social media platform Reddit to analyze speech coherence, which reflects formal thought disorder and is a characteristic feature of schizophrenia and associated psychotic disorders. Natural language processing (NLP) models were used to perform an automated quantification of speech coherence. We could demonstrate that users who are active on forums geared towards disorders with a higher degree of psychotic symptoms tend to show a lower level of coherence. The lowest coherence scores were found in users of forums on dissociative identity disorder, schizophrenia, and bipolar disorder. In contrast, a relatively high level of coherence was detected in users of forums related to obsessive-compulsive disorder, anxiety, and depression. Users of forums on posttraumatic stress disorder, autism, and attention-deficit hyperactivity disorder exhibited medium-level coherence. Our findings provide promising first evidence for the possible utility of NLP-based coherence analyses for the early detection and prevention of psychosis on the basis of posts gathered from publicly available social media data. This opens new avenues for large-scale prevention programs aimed at high-risk populations.

Digitally Enhanced Psychological Assessment and Treatment of Paranoia: A Systematic Review

BACKGROUND

Paranoia is relatively common but can lead to significant distress, impairment and need for care. Digital technologies offer a valuable extension to service provision and are increasingly being integrated into healthcare. This systematic review evaluated feasibility, acceptability, and effectiveness of digitally enhanced psychological assessments and treatments for paranoia across the paranoia continuum (PROSPERO: CRD42023393257).

METHODS

Databases PsychINFO, EMBASE, MEDLINE and Web of Science were searched until 12 June 2023; the Effective Public Health Practice Project (EPHPP) quality assessment tool evaluated studies; and a narrative synthesis was conducted.

RESULTS

Twenty-seven studies met inclusion criteria (n = 3457, 23 assessment and 4 treatment, 2005-2023, most in Europe). Technologies included virtual reality (VR, n = 23), experience sampling methodology (ESM, n = 2), an app (n = 1) and a combination of VR and ESM (n = 1). Assessments involved monitoring paranoia under various virtual conditions or in everyday life. Treatments were generally integrated with Cognitive Behaviour Therapy (CBT), which involved using VR to test out threat beliefs and drop safety behaviours or using an app to support slowing down paranoid thinking. EPHPP ratings were strong (n = 8), moderate (n = 12) and weak (n = 7).

CONCLUSIONS

Digitally enhanced assessments and treatments showed promising acceptability, feasibility and treatment effectiveness. Limitations of studies include small sample sizes, lack of comparison groups and long-term data and limited randomised controlled trials. Results support the potential future integration of VR in the assessment of paranoia and show promise for treatments such as CBT, although further clinical trials are required. Investigation of other technologies is limited.

A Digital Microintervention Supporting Evidence-Based Parenting Skills: Development Study Using the Agile Scrum Methodology

BACKGROUND

Conduct disorder increases risks of educational dropout, future mental illness, and incarceration if untreated. First-line treatment of conduct disorder involves evidence-based parenting skills programs. Time-outs, a frequent tool in these programs, can be effective at improving behavior, and recent apps have been developed to aid this process. However, these apps promote the use of time-outs in inconsistent or developmentally inappropriate ways, potentially worsening behavior problems. Digital microinterventions like these apps could guide parents through high-quality time-outs in the moment, but current time-out apps lack features promoting adherence to the evidence-based best practice. Agile scrum is a respected approach in the software development industry.

OBJECTIVE

We aimed to explore the feasibility of using the agile scrum approach to build a digital microintervention to help parents deliver an evidence-based time-out.

METHODS

The agile scrum methodology was used. Four sprints were conducted. Figma software was used for app design and wireframing. Insights from 42 expert stakeholders were used during 3 sprint reviews. We consulted experts who were identified from councils around the Midlands region of the United Kingdom and charities through personal contacts and a snowballing approach.

RESULTS

Over 4 development sprints from August 2022 to March 2023, the app was iteratively designed and refined based on consultation with a diverse group of 42 experts who shared their knowledge about the content of common parenting programs and the challenges parents commonly face. Modifications made throughout the process resulted in significant app enhancements, including tailored timer algorithms and enhanced readability, as well as an onboarding zone, mindfulness module, and pictorial information to increase inclusivity. By the end of the fourth sprint, the app was deemed ready for home use by stakeholders, demonstrating the effectiveness of our agile scrum development approach.

CONCLUSIONS

We developed an app to support parents to use the evidence-based time-out technique. We recommend the agile scrum approach to create mobile health apps. Our experience highlights the valuable role that frontline health and social care professionals, particularly those working with vulnerable families, can play as experts in scrum reviews. There is a need for research to both evaluate the impact of digital microinterventions on child behavioral change and also create digital microinterventions that cater to non-English speakers and individuals who participate in parenting programs in settings outside the United Kingdom.

Can Artificial Intelligence Chatbots Improve Mental Health?: A Scoping Review

BACKGROUND AND OBJECTIVES

Mental health disorders, including anxiety and depression, are the leading causes of global health-related burden and have increased dramatically since the 1990s. Delivering mental healthcare using artificial intelligence chatbots may be one option for closing the gaps in mental healthcare access. The overall aim of this scoping review was to describe the use, efficacy, and advantages/disadvantages of using an artificial intelligence chatbot for mental healthcare (stress, anxiety, depression).

METHODS

PubMed, PsycINFO, CINAHL, and Web of Science databases were searched. When possible, Medical Subject Headings terms were searched in combination with keywords. Two independent reviewers reviewed a total of 5768 abstracts.

RESULTS

Fifty-four articles were chosen for further review, with 10 articles included in the final analysis. Regarding quality assessment, the overall quality of the evidence was lower than expected. Overall, most studies showed positive trends in improving anxiety, stress, and depression.

DISCUSSION

Overall, using an artificial intelligence chatbot for mental health has some promising effects. However, many studies were done using rudimentary versions of artificial intelligence chatbots. In addition, lack of guardrails and privacy issues were identified. More research is needed to determine the effectiveness of artificial intelligence chatbots and to describe undesirable effects.

Genetics providers' perspectives on the use of digital tools in clinical practice

PURPOSE

Digital tools are increasingly incorporated into genetics practice to address challenges with the current model of care. Yet, genetics providers' perspectives on digital tool use are not well characterized.

METHODS

Genetics providers across Canada were recruited. Semistructured interviews were conducted to ascertain their perspectives on digital tool use and the clinical practice factors that might inform digital tool integration. A qualitative interpretive description approach was used for analysis.

RESULTS

Thirty-three genetics providers across 5 provinces were interviewed. Participants had favorable attitudes toward digital tool use. They were open to using digital tools in the pretest phase of the genetic testing pathway and for some posttest tasks or in a hybrid model of care. Participants expressed that digital tools could enhance efficiency and allow providers to spend more time practicing at the top of scope. Providers also described the need for careful consideration of the potential impact of digitalization on the clinician-patient dynamic, access to and equity of care, and unintended digital burden on providers.

CONCLUSION

Genetics providers considered digital tools to represent a viable solution for improving access, efficiency, and quality of care in genetics practice. Successful use of digital tools in practice will require careful consideration of their potential unintended impacts.

Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies

OBJECTIVE

Suicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the prediction of suicide attempts.

METHOD

A systematic review was performed using PubMed, Scopus, Web of Science and SID databases. We aim to evaluate the performance of ML algorithms and summarize their effects, gather relevant and reliable information to synthesize existing evidence, identify knowledge gaps, and provide a comprehensive list of the suicide risk factors using mixed method approach.

RESULTS

Forty-one studies published between 2011 and 2022, which matched inclusion criteria, were chosen as suitable. We included studies aimed at predicting the suicide risk by machine learning algorithms except natural language processing (NLP) and image processing. The neural network (NN) algorithm exhibited the lowest accuracy at 0.70, whereas the random forest demonstrated the highest accuracy, reaching 0.94. The study assessed the COX and random forest models and observed a minimum area under the curve (AUC) value of 0.54. In contrast, the XGBoost classifier yielded the highest AUC value, reaching 0.97. These specific AUC values emphasize the algorithm-specific performance in capturing the trade-off between sensitivity and specificity for suicide risk prediction. Furthermore, our investigation identified several common suicide risk factors, including age, gender, substance abuse, depression, anxiety, alcohol consumption, marital status, income, education, and occupation. This comprehensive analysis contributes valuable insights into the multifaceted nature of suicide risk, providing a foundation for targeted preventive strategies and intervention efforts.

CONCLUSIONS

The effectiveness of ML algorithms and their application in predicting suicide risk has been controversial. There is a need for more studies on these algorithms in clinical settings, and the related ethical concerns require further clarification.

Leveraging Implementation Science to Integrate Digital Mental Health Interventions as part of Routine Care in a Practice Research Network

The supply / demand issue in behavioral health care is a well-established fact, and the mental health toll of the COVID-19 pandemic continues to add challenges to an already taxed system. Existing healthcare models are not set up to adequately address the increasing mental health related needs. As such, innovative models are needed to provide patients with access to appropriate, evidence-based behavioral health care within routine clinical care. This paper introduces Precision Behavioral Health (PBH) as an example of such a model. PBH is an innovative, digital first care delivery model that provides an ecosystem of evidence-based digital mental health interventions to patients as a frontline behavioral health treatment within routine care in a large multispecialty group medical center in the United States. This paper describes the implementation of PBH within a practice research network set-up as part of an integrated behavioral health department. We will present how our team leveraged the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance; "What is RE-AIM?," n.d.) implementation science framework, which emphasizes the design, dissemination, and implementation processes at the individual, staff, and organizational levels, to prioritize key implementation constructs to enhance the successful integration of PBH within routine care. We describe how each of these constructs were operationalized to aid data gathering for rapid evaluation and lessons learned. We discuss the benefits of these types of initiatives across multiple stakeholders including patients, providers, organizations, payers, and digital intervention vendors.

Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study

BACKGROUND

Access to high-quality mental healthcare remains challenging for people with psychosis globally, including China. Smartphone-based symptom monitoring has the potential to support scalable mental healthcare. However, no such tool, until now, has been developed and evaluated for people with psychosis in China. This study investigated the acceptability and the experience of using a symptom self-monitoring smartphone app (YouXin) specifically developed for people with psychosis in China.

METHODS

Semi-structured interviews were conducted with 10 participants with psychosis to explore the acceptability of YouXin. Participants were recruited from the non-randomised feasibility study that tested the validity, feasibility, acceptability and safety of the YouXin app. Data analysis was guided by the theoretical framework of acceptability.

RESULTS

Most participants felt the app was acceptable and easy to use, and no unbearable burdens or opportunity costs were reported. Participants found completing the self-monitoring app rewarding and experienced a sense of achievement. Privacy and data security were not major concerns for participants, largely due to trust in their treating hospital around data protection. Participants found the app easy to use and attributed this to the training provided at the beginning of the study. A few participants said they had built some form of relationship with the app and would miss the app when the study finished.

CONCLUSIONS

The YouXin app is acceptable for symptom self-monitoring in people with experience of psychosis in China. Participants gained greater insights about their symptoms by using the YouXin app. As we only collected retrospective acceptability in this study, future studies are warranted to assess hypothetical acceptability before the commencement of study to provide a more comprehensive understanding of implementation.

College student interest in teletherapy and self-guided mental health supports during the COVID-19 pandemic

Objective The COVID-19 pandemic has worsened college students' mental health while simultaneously creating new barriers to traditional in-person care. Teletherapy and online self-guided mental health supports are two potential avenues for addressing unmet mental health needs when face-to-face services are less accessible, but little is known about factors that shape interest in these supports. Participants: 1,224 U.S. undergraduate students (mean age = 20.7; 73% female; 40% White) participated. Methods: Students completed an online questionnaire assessing interest in teletherapy and self-guided supports. Predictors included age, sex, race/ethnicity, sexual minority status, and anxiety and depression symptomatology. Results: Interest rates were 20% and 25% for at-cost supports (teletherapy and online self-help, respectively) and 70% and 72% for free supports (teletherapy and online self-help, respectively). Patterns emerged by age, anxiety symptom severity, and race/ethnicity. Conclusions: Results may inform universities' efforts to optimize students' engagement with nontraditional, digital mental health supports, including teletherapy and self-guided programs.

The SARS-CoV2 (COVID-19) pandemic has taken a severe toll on public health, with effects reaching far beyond unprecedented illness and mortality. Levels of mental health difficulties appear to be rising broadly as the pandemic has progressed, both in the general U.S. population and among college students specifically.1,2 The COVID-19 pandemic and its repercussions may undermine college student mental health in myriad ways.2 Concurrently, students now face the potential for serious illness, loss of loved ones, financial strain, social isolation, loss of on-campus resources, and sudden disruption of routines-creating a "perfect storm" for the emergence or exacerbation of psychological distress.

Benchmarking Mental Health Status Using Passive Sensor Data: Protocol for a Prospective Observational Study

BACKGROUND

Computational psychiatry has the potential to advance the diagnosis, mechanistic understanding, and treatment of mental health conditions. Promising results from clinical samples have led to calls to extend these methods to mental health risk assessment in the general public; however, data typically used with clinical samples are neither available nor scalable for research in the general population. Digital phenotyping addresses this by capitalizing on the multimodal and widely available data created by sensors embedded in personal digital devices (eg, smartphones) and is a promising approach to extending computational psychiatry methods to improve mental health risk assessment in the general population.

OBJECTIVE

Building on recommendations from existing computational psychiatry and digital phenotyping work, we aim to create the first computational psychiatry data set that is tailored to studying mental health risk in the general population; includes multimodal, sensor-based behavioral features; and is designed to be widely shared across academia, industry, and government using gold standard methods for privacy, confidentiality, and data integrity.

METHODS

We are using a stratified, random sampling design with 2 crossed factors (difficulties with emotion regulation and perceived life stress) to recruit a sample of 400 community-dwelling adults balanced across high- and low-risk for episodic mental health conditions. Participants first complete self-report questionnaires assessing current and lifetime psychiatric and medical diagnoses and treatment, and current psychosocial functioning. Participants then complete a 7-day in situ data collection phase that includes providing daily audio recordings, passive sensor data collected from smartphones, self-reports of daily mood and significant events, and a verbal description of the significant daily events during a nightly phone call. Participants complete the same baseline questionnaires 6 and 12 months after this phase. Self-report questionnaires will be scored using standard methods. Raw audio and passive sensor data will be processed to create a suite of daily summary features (eg, time spent at home).

RESULTS

Data collection began in June 2022 and is expected to conclude by July 2024. To date, 310 participants have consented to the study; 149 have completed the baseline questionnaire and 7-day intensive data collection phase; and 61 and 31 have completed the 6- and 12-month follow-up questionnaires, respectively. Once completed, the proposed data set will be made available to academic researchers, industry, and the government using a stepped approach to maximize data privacy.

CONCLUSIONS

This data set is designed as a complementary approach to current computational psychiatry and digital phenotyping research, with the goal of advancing mental health risk assessment within the general population. This data set aims to support the field's move away from siloed research laboratories collecting proprietary data and toward interdisciplinary collaborations that incorporate clinical, technical, and quantitative expertise at all stages of the research process.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53857.

Assessment of the feasibility of a community-based mental health training programme for persons with disabilities by non-specialists from different stakeholders' perspectives in Bangladesh

INTRODUCTION

Bangladesh is a developing country where 11% of the population has at least one disability, but no community-level mental health service is available. There is limited evidence of the burden of mental health issues and health-seeking behaviour among this population. This study assessed the feasibility of a training intervention for persons with disabilities, where peer support providers provided community-based disability-inclusive mental health services.

METHODS

Four stakeholder groups participated in this qualitative study: peer responders (trained persons with disabilities), trainers, representatives of organisations of persons with disabilities and disability-specific organisations, and officials of international and national non-governmental organisations. Two types of qualitative interviews were used to collect data, and thematic analysis techniques were utilised.

RESULT

Stakeholders perceived the peer responder training programme as acceptable for persons with disabilities to develop themselves as peer support providers, with potential benefits including increased mental health literacy, ensuring accessible mental health services, and improving the well-being of persons with disabilities. Potential challenges included receiving training and delivering services. Increased training duration, more fieldwork, supervision opportunities, and refresher training were recommended to mitigate training challenges. Financial support and formal community recognition were deemed necessary for training delivery.

CONCLUSION

The peer responder training programme was feasible to ensure accessible mental health services for persons with disabilities, build a workforce to screen for mental health conditions, and provide appropriate referrals. A multi-sectoral collaboration of government and non-governmental institutions is recommended to policy advocates to expand the peer responder training programme in the mainstream mental healthcare system.

What methods are used to examine representation of mental ill-health on social media? A systematic review

There has been an increasing number of papers which explore the representation of mental health on social media using various social media platforms and methodologies. It is timely to review methodologies employed in this growing body of research in order to understand their strengths and weaknesses. This systematic literature review provides a comprehensive overview and evaluation of the methods used to investigate the representation of mental ill-health on social media, shedding light on the current state of this field. Seven databases were searched with keywords related to social media, mental health, and aspects of representation (e.g., trivialisation or stigma). Of the 36 studies which met inclusion criteria, the most frequently selected social media platforms for data collection were Twitter (n = 22, 61.1%), Sina Weibo (n = 5, 13.9%) and YouTube (n = 4, 11.1%). The vast majority of studies analysed social media data using manual content analysis (n = 24, 66.7%), with limited studies employing more contemporary data analysis techniques, such as machine learning (n = 5, 13.9%). Few studies analysed visual data (n = 7, 19.4%). To enable a more complete understanding of mental ill-health representation on social media, further research is needed focussing on popular and influential image and video-based platforms, moving beyond text-based data like Twitter. Future research in this field should also employ a combination of both manual and computer-assisted approaches for analysis.

Co-producing an online patient public community research hub: a qualitative study exploring the perspectives of national institute for health research (NIHR) research champions in England

BACKGROUND

Patient and Public Involvement and Engagement (PPIE) should be embedded as part of researchers' everyday practice. However, this can be challenging. Creating a digital presence for PPIE as part of Higher Education Institutes' (HEIs) infrastructure may be one way of supporting this. This can support how information is made available to patients and members of the public, but relatively little is known about how HEIs can best do this. Our aim was to develop a university website for patients and members of the public to learn about ways to get actively involved in research and be able to access the results of health and social care research.

METHODS

This project involved working as partners with five National Institute for Health and Care Research (NIHR) Research Champions. NIHR Research Champions are volunteers who raise awareness and share experiences about health and social care research. Content of a prototype Patient Public Community Research Hub website was co-produced with the Research Champions, and then 15 NIHR Research Champions from across England were asked for their views about the website.

FINDINGS

The information collected told us that the Patient Public Community Research Hub was viewed as being beneficial for increasing visibility of PPIE opportunities and sharing the findings of studies though needs further work: to make the information more user-friendly; to improve the methods for directing people to the site and to create new ways of connecting with people. It provides a foundation for further co-development and evaluation. A set of recommendations has been developed that may be of benefit to other HEIs and organisations who are committed to working with patients and members of the public.

A qualitative interview study of patients' attitudes towards and intention to use digital interventions for depressive disorders on prescription

Background

Depressive disorders are an emerging public health topic. Due to their increasing prevalence, patients with depressive disorders suffer from the lack of therapeutic treatment. Digital health interventions may offer an opportunity to bridge waiting times, supplement, or even substitute in-person treatment. Among others, the Unified Theory of Acceptance and Use of Technology (UTAUT) explains that actual technology use is affected by users' behavioural intention. However, patients' perspectives on digital interventions are rarely discussed within the specific context of primary care provided by general practitioners (GP) and need further exploration.

Method

A qualitative study design with semi-structured interviews was used to explore DTx-acceptance of patients with mild or moderate depression (n = 17). The audio-recorded interviews were transcribed verbatim, coded, and thematically analysed by qualitative content analysis.

Results

Patients' performance expectancies reveal that DTx are not perceived as a substitute for face-to-face treatment. Effort expectancies include potential advantages and efforts concerning technical, motivational, and skill-based aspects. Moreover, we identified health status and experience with depressive disorders as other determinants and potential barriers to patients' DTx acceptance: Difficult stages of depression or long-time experience are perceived hurdles for DTx use. GPs' recommendations were just partly relevant for patients and varied according to patients' consultancy preferences. But still, GPs have a crucial role for access due to prescription. GPs' influence on patients' DTx acceptance varies between three situations: (1) pre-use for consultation, (2) pre-use for access and (3) during DTx-use. Further, GPs' guidance could be especially relevant for patients during DTx-use in routine care.

Discussion

The UTAUT-based exploration suggests that acceptance determinants should be considered independently and embedded in personal and situational aspects. DTx require a healthcare professional to prescribe or diagnose the disease, unlike other digital offerings. We identified prescription- and depression-related determinants, exceeding existing theoretical constructs. GPs' guidance can compensate for some barriers to DTx use e.g., by increasing commitment and motivational support to strengthen patients' acceptance.

Conclusion

We argue for a multidimensional integration of acceptance determinants for further development of health technology acceptance research. Future research should specify how DTx can be integrated into routine care to strengthen user acceptance.

Best practice for integrating digital interventions into clinical care for young people at risk of suicide: a Delphi study

BACKGROUND

Digital tools have the capacity to complement and enhance clinical care for young people at risk of suicide. Despite the rapid rise of digital tools, their rate of integration into clinical practice remains low. The poor uptake of digital tools may be in part due to the lack of best-practice guidelines for clinicians and services to safely apply them with this population.

METHODS

A Delphi study was conducted to produce a set of best-practice guidelines for clinicians and services on integrating digital tools into clinical care for young people at risk of suicide. First, a questionnaire was developed incorporating action items derived from peer-reviewed and grey literature, and stakeholder interviews with 17 participants. Next, two independent expert panels comprising professionals (academics and clinical staff; n = 20) and young people with lived experience of using digital technology for support with suicidal thoughts and behaviours (n = 29) rated items across two consensus rounds. Items reaching consensus (rated as "essential" or "important" by at least 80% of panel members) at the end of round two were collated into a set of guidelines.

RESULTS

Out of 326 individual items rated by the panels, 188 (57.7%) reached consensus for inclusion in the guidelines. The endorsed items provide guidance on important topics when working with young people, including when and for whom digital tools should be used, how to select a digital tool and identify potentially harmful content, and identifying and managing suicide risk conveyed via digital tools. Several items directed at services (rather than individual clinicians) were also endorsed.

CONCLUSIONS

This study offers world-first evidence-informed guidelines for clinicians and services to integrate digital tools into clinical care for young people at risk of suicide. Implementation of the guidelines is an important next step and will hopefully lead to improved uptake of potentially helpful digital tools in clinical practice.

Evaluation of the benefits of neutral bicarbonate ionized water baths in an open-label, randomized, crossover trial

We previously demonstrated that neutral bicarbonate ionized water (NBIW) bathing enhances blood flow by bicarbonate ions and described the underlying mechanism. However, additional clinical investigation was warranted to investigate the efficacy of NBIW bathing. Hence, we performed a randomized, open-label, crossover trial to examine the effects of NBIW bathing on mental stress, sleep, and immune function. Participants who regularly felt stressed were randomly assigned to NBIW or regular bathing for 4 weeks. Mental stress was assessed with the Brief Job Stress Questionnaire (BJSQ) and the Profile of Mood States Second Edition; sleep quality, with the Pittsburgh Sleep Quality Index Japanese version (PSQI-J) and actigraphy; and immune function, with laboratory tests. PSQI-J scores and actigraphy sleep latency and bed out latency improved significantly more with NBIW bathing than with regular bathing (p < 0.05). Furthermore, NBIW bathing reduced both stress-induced fluctuations in CD4+ and CD8+ T cell counts and fluctuations in the naive to memory T cell ratio and neutrophil phagocytosis, indicating improved immune function. These findings suggest that daily NBIW bathing could improve mental stress, sleep quality, and immune function and bring about positive health effects in those who experience stress in their daily lives.

Digitally managing depression: A fully remote randomised attention-placebo controlled trial

Background

Depression is a common and disabling condition. Digital apps may augment or facilitate care, particularly in under-served populations. We tested the efficacy of juli, a digital self-management app for depression in a fully remote randomised controlled trial.

Methods

A pragmatic randomised controlled trial that included participants aged > 18 who self-identified as having depression and scored > 5 on the Patient Health Questionnaire-8. Participants were randomly assigned (1:1) to receive juli for 8 weeks or a limited attention-placebo control app. Our primary outcome was the difference in Patient Health Questionnaire-8 scores at 8 weeks. Secondary outcomes were remission, minimal clinically important difference, worsening of depression, and health-related quality of life. Analyses were per-protocol (primary), and modified and full intention-to-treat (secondary). The trial was registered at ISRCTN (ISRCTN12329547).

Results

Between May 2021 and January 2023, we randomised 908 participants. 662 completed the week 2 outcome assessment and were included in the modified intention-to-treat analysis, and 456 completed the week 8 outcome assessments (per-protocol). In the per-protocol analysis, the juli group had a greater reduction in Patient Health Questionnaire-8 score (10.78, standard deviation 6.26) than the control group (11.88, standard deviation 5.73) by week 8 (baseline adjusted β-coefficient -0.94, 95% CI: -1.87 to -0.22, p = 0.045). Achieving remission and a minimal clinically important difference was more likely in the juli group at 8 weeks (adjusted odds ratios 2.22, 95% CI: 1.45-3.39, p < 0.001 and 1.56, 95% CI: 1.08-2.27, p = 0.018, respectively). There were no between-group differences in health-related quality of life or worsening of depression. Modified and full intention-to-treat analyses found similar results, but the primary outcome was non-significant.

Conclusion

The use of juli for 8 weeks resulted in a small reduction in symptoms of depression compared with an attention-placebo control. The juli app is a digital self-management tool that could increase the accessibility of evidence-based depression treatments.

Smartphone-based safety plan for suicidal crisis: The SmartCrisis 2.0 pilot study

Here we present the findings of the pilot phase of the SmartCrisis 2.0 Randomized Clinical Trial. This pilot study aimed to explore the feasibility and acceptability of a safety plan contained in a smartphone app. Our sample consisted patients with a history of recent suicidal behaviour who installed a smartphone-based safety plan. To explore the satisfaction with of the safety plan, two patient satisfaction surveys were conducted: one qualitative and one quantitative. To explore the objective use of the safety plan, we gained access to texts contained in the safety plans completed by the patients. Participation rate was 77%, while 48.9% patients completed both satisfaction surveys at the end of the pilot phase. N = 105 successfully installed the safety plan. In a scale from 1 to 10, users rated the usefulness of the security plan at 7.4, the usability at 8.9, the degree to which they would recommend it to others at 8.6 and the overall satisfaction with the project including evaluations at 9.6. The most widely completed tab was warning signs. Feeling sad or lonely was the warning sign most commonly reported by patients. The second most completed tab was internal coping strategies. Walking or practicing any other exercise was the strategy most commonly resorted to. Our smartphone-based safety plan appears to be a feasible intervention. Data obtained from this pilot study showed high participation rates and high acceptability by patients. This, together with the general satisfaction with the project, supports its implementation in the clinical practice.

Co-producing digital mental health interventions: A systematic review

Objective

Smartphone apps (apps) are widely recognised as promising tools for improving access to mental healthcare. However, a key challenge is the development of digital interventions that are acceptable to end users. Co-production with providers and stakeholders is increasingly positioned as the gold standard for improving uptake, engagement, and healthcare outcomes. Nevertheless, clear guidance around the process of co-production is lacking. The objectives of this review were to: (i) present an overview of the methods and approaches to co-production when designing, producing, and evaluating digital mental health interventions; and (ii) explore the barriers and facilitators affecting co-production in this context.

Methods

A pre-registered (CRD42023414007) systematic review was completed in accordance with The Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Five databases were searched. A co-produced bespoke quality appraisal tool was developed with an expert by experience to assess the quality of the co-production methods and approaches. A narrative synthesis was conducted.

Results

Twenty-six studies across 24 digital mental health interventions met inclusion criteria. App interventions were rarely co-produced with end users throughout all stages of design, development, and evaluation. Co-producing digital mental health interventions added value by creating culturally sensitive and acceptable interventions. Reported challenges included resource issues exacerbated by the digital nature of the intervention, variability across stakeholder suggestions, and power imbalances between stakeholders and researchers.

Conclusions

Variation in approaches to co-producing digital mental health interventions is evident, with inconsistencies between stakeholder groups involved, stage of involvement, stakeholders' roles and methods employed.

Evaluating a treatment selection approach for online single-session interventions for adolescent depression

BACKGROUND

The question 'what works for whom' is essential to mental health research, as matching individuals to the treatment best suited to their needs has the potential to maximize the effectiveness of existing approaches. Digitally administered single-session interventions (SSIs) are effective means of reducing depressive symptoms in adolescence, with potential for rapid, large-scale implementation. However, little is known about which SSIs work best for different adolescents.

OBJECTIVE

We created and tested a treatment selection algorithm for use with two SSIs targeting depression in high-symptom adolescents from across the United States.

METHODS

Using data from a large-scale RCT comparing two evidence-based SSIs (N = 996; ClinicalTrials.gov: NCT04634903), we utilized a Personalized Advantage Index approach to create and evaluate a treatment-matching algorithm for these interventions. The two interventions were Project Personality (PP; N = 482), an intervention teaching that traits and symptoms are malleable (a 'growth mindset'), and the Action Brings Change Project (ABC; N = 514), a behavioral activation intervention.

RESULTS

Results indicated no significant difference in 3-month depression outcomes between participants assigned to their matched intervention and those assigned to their nonmatched intervention. The relationship between predicted response to intervention (RTI) and observed RTI was weak for both interventions (r = .39 for PP, r = .24 for ABC). Moreover, the correlation between a participants' predicted RTI for PP and their predicted RTI for ABC was very high (r = .79).

CONCLUSIONS

The utility of treatment selection approaches for SSIs targeting adolescent depression appears limited. Results suggest that both (a) predicting RTI for SSIs is relatively challenging, and (b) the factors that predict RTI for SSIs are similar regardless of the content of the intervention. Given their overall effectiveness and their low-intensity, low-cost nature, increasing youths' access to both digital SSIs may carry more public health utility than additional treatment-matching efforts.

German Version of the Mobile Agnew Relationship Measure: Translation and Validation Study

BACKGROUND

The mobile Agnew Relationship Measure (mARM) is a self-report questionnaire for the evaluation of digital mental health interventions and their interactions with users. With the global increase in digital mental health intervention research, translated measures are required to conduct research with local populations.

OBJECTIVE

The aim of this study was to translate and validate the original English version of the mARM into a German version (mARM-G).

METHODS

A total of 2 native German speakers who spoke English as their second language conducted forward translation of the original items. This version was then back translated by 2 native German speakers with a fluent knowledge of English. An independent bilingual reviewer then compared these drafts and created a final German version. The mARM-G was validated by 15 experts in the field of mobile app development and 15 nonexperts for content validity and face validity; 144 participants were recruited to conduct reliability testing as well as confirmatory factor analysis.

RESULTS

The content validity index of the mARM-G was 0.90 (expert ratings) and 0.79 (nonexperts). The face validity index was 0.89 (experts) and 0.86 (nonexperts). Internal consistency for the entire scale was Cronbach α=.91. Confirmatory factor analysis results were as follows: the chi-square statistic to df ratio was 1.66. Comparative Fit Index was 0.87 and the Tucker-Lewis Index was 0.86. The root mean square error of approximation was 0.07.

CONCLUSIONS

The mARM-G is a valid and reliable tool that can be used for future studies in German-speaking countries.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial)

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

Feasibility and acceptability of an online mental health intervention for pregnant women and their partners: a mixed method study with a pilot randomized control trial

BACKGROUND

Untreated perinatal mood and anxiety disorders (PMAD) have short- and long-term health and social consequences; online cognitive behavioral therapy (CBT) interventions can reduce symptoms. Despite partner support being protective online interventions rarely target couples. This study builds on research on an existing CBT-based intervention, the Mothers and Babies Online Course (eMB), by testing its feasibility with prenatal couples.

METHODS

We conducted a pilot, randomized, controlled feasibility trial using a 1:1 parallel design. To be eligible, participant dyads were pregnant people (between 13-30 weeks gestation and with a score of 10 or greater on either the GAD-7 or PHQ-9 scale indicating elevated symptoms of anxiety or depression) and their cohabitating partners, living in Missouri, with access to the internet; both in the dyad consented to participate. Recruitment occurred via Facebook ads, flyers, and a snowball approach. The intervention group received eMB, and the control group received a list of community resources. We examined retention and adherence data extracted from eMB analytics and study databases. All participants were given depression and anxiety scales at baseline, 4 and 8 weeks to test preliminary efficacy; satisfaction and acceptability were measured at trial end (i.e., eight weeks) and via interview.

RESULTS

There were 441 people who responded to recruitment materials, 74 pregnant people were screened; 19 partners did not complete enrolment, and 25 dyads were ineligible. There were 15 dyads per group (N = 30) who enrolled; all completed the study. The survey response rate was 90% but partners required nearly twice the number of reminders. No participant completed all lessons. Mean depression and anxiety scores dropped over time for dyads in control (M = -1.99, -1.53) and intervention (M = -4.80, -1.99). Intervention pregnant people's anxiety significantly decreased (M = -4.05; 95% CI [0.82, 7.27]) at time two compared to control. Twelve pregnant people and four partners participated in post-intervention interviews and suggested improvements for eMB.

CONCLUSION

Online dyadic interventions can potentially reduce PMAD symptoms. However, to feasibly study eMB with couples, strategies to increase program adherence are necessary. Tailoring interventions to overtly include partners may be advantageous.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05867680, 19/05/2023.

"Our Job is to be so Temporary": Designing Digital Tools that Meet the Needs of Care Managers and their Patients with Mental Health Concerns

Digital tools have potential to support collaborative management of mental health conditions, but we need to better understand how to integrate them in routine healthcare, particularly for patients with both physical and mental health needs. We therefore conducted interviews and design workshops with 1) a group of care managers who support patients with complex health needs, and 2) their patients whose health needs include mental health concerns. We investigate both groups' views of potential applications of digital tools within care management. Findings suggest that care managers felt underprepared to play an ongoing role in addressing mental health issues and had concerns about the burden and ambiguity of providing support through new digital channels. In contrast, patients envisioned benefiting from ongoing mental health support from care managers, including support in using digital tools. Patients' and care managers' needs may diverge such that meeting both through the same tools presents a significant challenge. We discuss how successful design and integration of digital tools into care management would require reconceptualizing these professionals' roles in mental health support.

Longitudinal Patterns of Engagement and Clinical Outcomes: Results From a Therapist-Supported Digital Mental Health Intervention

OBJECTIVE

Digital mental health interventions (DMHIs) are an effective treatment modality for common mental disorders like depression and anxiety; however, the role of intervention engagement as a longitudinal "dosing" factor is poorly understood in relation to clinical outcomes.

METHODS

We studied 4978 participants in a 12-week therapist-supported DMHI (June 2020-December 2021), applying a longitudinal agglomerative hierarchical cluster analysis to the number of days per week of intervention engagement. The proportion of people demonstrating remission in depression and anxiety symptoms during the intervention was calculated for each cluster. Multivariable logistic regression models were fit to examine associations between the engagement clusters and symptom remission, adjusting for demographic and clinical characteristics.

RESULTS

Based on clinical interpretability and stopping rules, four clusters were derived from the hierarchical cluster analysis (in descending order): a) sustained high engagers (45.0%), b) late disengagers (24.1%), c) early disengagers (22.5%), and d) immediate disengagers (8.4%). Bivariate and multivariate analyses supported a dose-response relationship between engagement and depression symptom remission, whereas the pattern was partially evident for anxiety symptom remission. In multivariable logistic regression models, older age groups, male participants, and Asians had increased odds of achieving depression and anxiety symptom remission, whereas higher odds of anxiety symptom remission were observed among gender-expansive individuals.

CONCLUSIONS

Segmentation based on the frequency of engagement performs well in discerning timing of intervention disengagement and a dose-response relationship with clinical outcomes. The findings among the demographic subpopulations indicate that therapist-supported DMHIs may be effective in addressing mental health problems among patients who disproportionately experience stigma and structural barriers to care. Machine learning models can enable precision care by delineating how heterogeneous patterns of engagement over time relate to clinical outcomes. This empirical identification may help clinicians personalize and optimize interventions to prevent premature disengagement.

An App to Support Fathers' Mental Health and Well-Being: User-Centered Development Study

BACKGROUND

Numerous studies describe the popularity and usefulness of parenting programs. In particular, parenting programs are generally viewed as effective for supporting parents' mental well-being during key transition periods. However, the evidence base for fathers is limited owing to their lack of involvement in parenting programs and scarcity of tailored support.

OBJECTIVE

This paper aimed to describe the co-design process for a universal digital intervention for fathers (fatherli) and the outline of a logic model with its expected outcomes.

METHODS

Following established guidelines for co-designing and developing complex interventions, we conducted a nonsystematic review of the available literature to gather key information, developed market surveys to assess fathers' needs and interests, consulted with key stakeholders to obtain expert opinions, and engaged in a rapid iterative prototyping process with app developers. Each step was summarized, and the information was collated and integrated to inform a logic model and the features of the resulting intervention.

RESULTS

The steps in the co-design process confirmed a need for and interest in a digital intervention for fathers. In response to this finding, fatherli was developed, consisting of 5 key features: a discussion forum for anyone to post information about various topics (the forum), a socializing platform for fathers to create and engage with others in small groups about topics or points of shared interest (dad hub), a tool for fathers to find other fathers with shared interests or within the same geographic location (dad finder), a resource for fathers to access up-to-date information about topics that interest them (dad wiki), and a portal to book sessions with coaches who specialize in different topics (dad coaching space). The evidence-based logic model proposes that if fatherli is successfully implemented, important outcomes such as increased parental efficacy and mental health help-seeking behaviors may be observed.

CONCLUSIONS

We documented the co-design and development process of fatherli, which confirmed that it is possible to use input from end users and experts, integrated with theory and research evidence, to create suitable digital well-being interventions for fathers. In general, the key findings suggest that an app that facilitates connection, communication, and psychoeducation may appeal to fathers. Further studies will now focus on acceptability, feasibility, and effectiveness. Feedback gathered during pilot-testing will inform any further developments in the app to increase its applicability to fathers and its usability.

Opportunities for the Implementation of a Digital Mental Health Assessment Tool in the United Kingdom: Exploratory Survey Study

BACKGROUND

Every year, one-fourth of the people in the United Kingdom experience diagnosable mental health concerns, yet only a proportion receive a timely diagnosis and treatment. With novel developments in digital technologies, the potential to increase access to mental health assessments and triage is promising.

OBJECTIVE

This study aimed to investigate the current state of mental health provision in the United Kingdom and understand the utility of, and interest in, digital mental health technologies.

METHODS

A web-based survey was generated using Qualtrics XM. Participants were recruited via social media. Data were explored using descriptive statistics.

RESULTS

The majority of the respondents (555/618, 89.8%) had discussed their mental health with a general practitioner. More than three-fourths (503/618, 81.4%) of the respondents had been diagnosed with a mental health disorder, with the most common diagnoses being depression and generalized anxiety disorder. Diagnostic waiting times from first contact with a health care professional varied by diagnosis. Neurodevelopmental disorders (30/56, 54%), bipolar disorder (25/52, 48%), and personality disorders (48/101, 47.5%) had the longest waiting times, with almost half (103/209, 49.3%) of these diagnoses taking >6 months. Participants stated that waiting times resulted in symptoms worsening (262/353, 74.2%), lower quality of life (166/353, 47%), and the necessity to seek emergency care (109/353, 30.9%). Of the 618 participants, 386 (62.5%) stated that they felt that their mental health symptoms were not always taken seriously by their health care provider and 297 (48.1%) were not given any psychoeducational information. The majority of the respondents (416/595, 77.5%) did not have the chance to discuss mental health support and treatment options. Critically, 16.1% (96/595) did not find any treatment or support provided at all helpful, with 63% (48/76) having discontinued treatment with no effective alternatives. Furthermore, 88.3% (545/617) of the respondents) had sought help on the web regarding mental health symptoms, and 44.4% (272/612) had used a web application or smartphone app for their mental health. Psychoeducation (364/596, 61.1%), referral to a health care professional (332/596, 55.7%), and symptom monitoring (314/596, 52.7%) were the most desired app features. Only 6.8% (40/590) of the participants said that they would not be interested in using a mental health assessment app. Respondents were the most interested to receive an overall severity score of their mental health symptoms (441/546, 80.8%) and an indication of whether they should seek mental health support (454/546, 83.2%).

CONCLUSIONS

Key gaps in current UK mental health care provision are highlighted. Assessment and treatment waiting times together with a lack of information regarding symptoms and treatment options translated into poor care experiences. The participants' responses provide proof-of-concept support for the development of a digital mental health assessment app and valuable recommendations regarding desirable app features.

The Polarization of Clinician and Service Staff Perspectives After the Use of Health Information Technology in Youth Mental Health Services: Implementation and Evaluation Study

BACKGROUND

Highly personalized care is substantially improved by technology platforms that assess and track patient outcomes. However, evidence regarding how to successfully implement technology in real-world mental health settings is limited.

OBJECTIVE

This study aimed to naturalistically monitor how a health information technology (HIT) platform was used within 2 real-world mental health service settings to gain practical insights into how HIT can be implemented and sustained to improve mental health service delivery.

METHODS

An HIT (The Innowell Platform) was naturally implemented in 2 youth mental health services in Sydney, Australia. Web-based surveys (n=19) and implementation logs were used to investigate staff attitudes toward technology before and after implementation. Descriptive statistics were used to track staff attitudes over time, whereas qualitative thematic analysis was used to explore implementation log data to gain practical insights into useful implementation strategies in real-world settings.

RESULTS

After the implementation, the staff were nearly 3 times more likely to agree that the HIT would improve care for their clients (3/12, 25% agreed before the implementation compared with 7/10, 70% after the implementation). Despite this, there was also an increase in the number of staff who disagreed that the HIT would improve care (from 1/12, 8% to 2/10, 20%). There was also decreased uncertainty (from 6/12, 50% to 3/10, 30%) about the willingness of the service to implement the technology for its intended purpose, with similar increases in the number of staff who agreed and disagreed with this statement. Staff were more likely to be uncertain about whether colleagues in my service are receptive to changes in clinical processes (not sure rose from 5/12, 42% to 7/10, 70%). They were also more likely to report that their service already provides the best mental health care (agreement rose from 7/12, 58% to 8/10, 80%). After the implementation, a greater proportion of participants reported that the HIT enabled shared or collaborative decision-making with young people (2/10, 20%, compared with 1/12, 8%), enabled clients to proactively work on their mental health care through digital technologies (3/10, 30%, compared with 2/12, 16%), and improved their response to suicidal risk (4/10, 40% compared with 3/12, 25%).

CONCLUSIONS

This study raises important questions about why clinicians, who have the same training and support in using technology, develop more polarized opinions on its usefulness after implementation. It seems that the uptake of HIT is heavily influenced by a clinician's underlying beliefs and attitudes toward clinical practice in general as well as the role of technology, rather than their knowledge or the ease of use of the HIT in question.

Factors affecting the acceptance of tele-psychiatry: a scoping study

BACKGROUND

In today's digital world, providing services through telemedicine has become an essential issue in health systems, and the Covid-19 pandemic has made this necessity even more apparent. On the other hand, mental health services are needed more than ever, and their nature makes their delivery via telemedicine more feasible than other specialized services. This study aimed to determine the factors affecting the acceptance of telemedicine among users of this technology in the field of mental health.

METHODS

This article is a scoping review based on the PRISMA guidelines and without any time limit until June 20, 2022. The search was performed in PubMed, Scopus, Web of Science, and PsycINFO databases using keywords related to the three fields of telemedicine, acceptance, and mental disorders. Two authors independently selected the studies based on inclusion and exclusion criteria. Then the data were collected using a data extraction form, and finally, the results were determined using the content analysis method.

RESULTS

Five main factors affect the acceptance of telemedicine among users of this technology in the field of mental health: perceived effectiveness, users' understanding of the effects of telemedicine on the quality and outcomes of care delivery, technological aspects, organizational change capacity, the nature of the disease and psychological and psychosocial factors. These main factors are associated with 21 related sub-factors.

CONCLUSIONS

Revealing the factors affecting the acceptance of telemedicine among recipients and providers of services, as key actors in health systems, can help managers and policymakers to successfully implement telemedicine in the less-regarded field of mental health, especially in the early stages.

Factors Affecting Digital Tool Use in Client Interaction According to Mental Health Professionals: Interview Study

BACKGROUND

Digital tools and interventions are being increasingly developed in response to the growing mental health crisis, and mental health professionals (MHPs) considerably influence their adoption in client practice. However, how MHPs use digital tools in client interaction is yet to be sufficiently understood, which poses challenges to their design, development, and implementation.

OBJECTIVE

This study aimed to create a contextual understanding of how MHPs use different digital tools in clinical client practice and what characterizes the use across tools.

METHODS

A total of 19 Finnish MHPs participated in semistructured interviews, and the data were transcribed, coded, and inductively analyzed.

RESULTS

We found that MHP digital tool use was characterized by 3 distinct functions: communication, diagnosis and evaluation, and facilitating therapeutic change. The functions were addressed using analog tools, digitized tools that mimic their analog counterparts, and digital tools that use the possibilities native to digital. The MHP-client communication included various media alongside face-to-face meetings, the MHPs increasingly used digitized tools in client evaluation, and the MHPs actively used digitized materials to facilitate therapeutic change. MHP tool use was generally characterized by adaptability-it was negotiated in client interactions. However, there was considerable variance in the breadth of MHPs' digital toolbox. The existing clinical practices emphasized MHP-client interaction and invited incremental rather than radical developments, which challenged the achievement of the scalability benefits expected from digital tools.

CONCLUSIONS

MHPs use digitized and digital tools in client practice. Our results contribute to the user-centered research, development, and implementation of new digital solutions in mental health care by classifying them according to their function and medium and describing how MHPs use and do not use them.

A machine learning approach to determine resilience utilizing wearable device data: analysis of an observational cohort

Objective

To assess whether an individual's degree of psychological resilience can be determined from physiological metrics passively collected from a wearable device.

Materials and Methods

Data were analyzed in this secondary analysis of the Warrior Watch Study dataset, a prospective cohort of healthcare workers enrolled across 7 hospitals in New York City. Subjects wore an Apple Watch for the duration of their participation. Surveys were collected measuring resilience, optimism, and emotional support at baseline.

Results

We evaluated data from 329 subjects (mean age 37.4 years, 37.1% male). Across all testing sets, gradient-boosting machines (GBM) and extreme gradient-boosting models performed best for high- versus low-resilience prediction, stratified on a median Connor-Davidson Resilience Scale-2 score of 6 (interquartile range = 5-7), with an AUC of 0.60. When predicting resilience as a continuous variable, multivariate linear models had a correlation of 0.24 (P = .029) and RMSE of 1.37 in the testing data. A positive psychological construct, comprised of resilience, optimism, and emotional support was also evaluated. The oblique random forest method performed best in estimating high- versus low-composite scores stratified on a median of 32.5, with an AUC of 0.65, a sensitivity of 0.60, and a specificity of 0.70.

Discussion

In a post hoc analysis, machine learning models applied to physiological metrics collected from wearable devices had some predictive ability in identifying resilience states and a positive psychological construct.

Conclusions

These findings support the further assessment of psychological characteristics from passively collected wearable data in dedicated studies.

Trauma-Informed Care in Digital Health Technologies: Protocol for a Scoping Review

BACKGROUND

The use of digital health technologies is becoming increasingly common across the globe as they offer immense potential to enhance health care delivery by promoting accessibility, flexibility, and personalized care, connecting patients to health care professionals, and offering more efficient services and treatments to remote residents. At the same time, there is an increasing recognition of how digital health can inadvertently foment psychological trauma. This phenomenon has led to the adoption of trauma-informed care in designing and deploying digital health technologies. However, how trauma-informed care is defined and characterized, and the various trauma-informed care strategies used in designing and deploying digital health technologies remain unexplored.

OBJECTIVE

This scoping review aims to explore and synthesize the literature on how trauma-informed care is defined and characterized in digital health and the various trauma-informed care principles, strategies, or recommendations used in designing and deploying digital health.

METHODS

This review will draw on the Joanna Briggs Institute's updated methodological guidance for scoping reviews. A search will be conducted on CINAHL, PubMed, Embase, Compendex Engineering Village, Web of Science, Scopus, and PsycINFO. This review will consider published research studies and unpublished work (gray literature). Studies will be included if they applied trauma-informed care in designing or deploying digital health for patients across all geographical locations or provide trauma-informed recommendations on how web developers should develop digital health. Studies will be limited to publications within the past 10 years and studies in all languages will be considered. Two independent reviewers will screen the titles and abstracts, and then perform a full-text review. Data will be extracted into a data extraction tool developed for this study.

RESULTS

The scoping review was undergoing a full search as of April 2023. The main results will synthesize the peer-reviewed and gray literature on adopting trauma-informed care practices in digital health research and development. The study is expected to be completed by December 2023 and the results are expected to be published in a peer-reviewed journal.

CONCLUSIONS

This review is expected to provide the knowledge base on the adoption of trauma-informed care in designing and deploying digital health. This knowledge can lead to more engaging, and likely, more effective digital health interventions that have less potential for harm. A synthesis of the various trauma-informed care strategies in digital health will also provide a trauma-informed language by enabling researchers and digital health developers to consider trauma as a critical factor in each stage of the design process.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46842.

Trends in Health Communication: Social Media Needs and Quality of Life among Older Adults in Malaysia

BACKGROUND

While social media continues to dominate, social media platforms have become powerful health communication tools for older users. However, fulfilling their social media needs can be both detrimental and beneficial to their quality of life (QoL). This study assessed social media needs as they relate to QoL among older adults in Malaysia.

METHODS

We conducted a cross-sectional study and adopted convenience sampling to recruit participants. The participants were required to self-report their sociodemographic profile, social media use and needs, and QoL. Social media use and needs were assessed using the Social Networking Sites Uses and Needs (SNSUN) scale, and QoL was assessed using the WHOQOL-BREF questionnaire. Multiple linear regression was performed to identify the predictors of QoL.

RESULTS

The findings revealed that the fulfilment of social integrative needs was the strongest predictor of higher QoL in all domains. However, those using social media for their affective needs demonstrated lower psychological health quality.

CONCLUSIONS

Fulfilling social integrative needs is the key to improving the QoL among older adults. The continuous development of age-friendly applications is essential to keep up with constantly changing social media trends and bridge the gap of social media inequalities. More importantly, it would enable older adults to utilize social media to its fullest potential and enjoy a higher QoL through accessible health communication tools.

A Novel Screening, Brief Intervention, and Referral to Treatment (SBIRT) Based Model for Mental Health in Occupational Health Implemented on Smartphone and Web-Based Platforms: Development Study With Results From an Epidemiologic Survey

BACKGROUND

While the importance of mental health is well-recognized in the field of occupational health, implementation of effective strategies in the workplace has been limited by gaps in infrastructure, program comprehensiveness, coverage, and adherence. The authors developed a Screening, Brief Intervention, and Referral to Treatment (SBIRT) model based occupational mental health intervention, and implemented in a web-based format with a smartphone application.

METHODS

The SBIRT-based intervention was developed by a multidisciplinary team, including occupational health physicians, nurses, psychiatrists, and software developers. The following mental health areas were included, based on outcomes of an epidemiological survey conducted: insomnia, depression, anxiety, problematic alcohol use, and suicidal risk. The viability of the two-step evaluation process utilizing a combination of the brief version and the full-length version of the questionnaire was examined using responses from the survey. The intervention was adjusted according to the survey results and expert opinions.

RESULTS

The epidemiological survey included 346 employees who completed the long-form version of mental health scales. These data were the used to confirm the diagnostic value of using a combination of short-form and long-form version of the scales for screening in the SBIRT model. The model uses a smartphone application for screening, provision of psychoeducation, and for surveillance. The universal methods of the model ensure it can be implemented by all occupational managers, regardless of their specialization in mental health. In addition to the two-step screening procedure to identify employees at-risk for mental health problems, the model includes a stepped care approach, based on risk stratification, to promote mental health education, management, and follow-up for continuous care.

CONCLUSION

The SBIRT model-based intervention provides an easy-to-implement approach for the management of mental health in the workplace. Further studies are required to examine the effectiveness and feasibility of the model.

A qualitative exploration of college students' experiences using mobile apps to improve self-care during the COVID-19 pandemic

Objective: This project examines students' experiences using a mental health mobile application (app) as part of a class assignment developed to support student well-being. Participants: Data was collected from 265 undergraduate students enrolled in a psychology course during the COVID-19 pandemic. Methods: Students developed a self-care goal and used an app to support progress toward it. Thematic analysis was applied to students' written reflections about their experiences using the app and practicing self-care. Results: Students reported using an app for self-care was 1) more helpful than expected for improving focus, productivity, motivation, sleep, and mental health symptoms; 2) challenging due to loss of interest, slow improvement, difficulty integrating into routine, or negative feelings triggered; and 3) influenced by the pandemic and transition to remote learning. Conclusions: A classroom assignment designed to promote self-care using a mental health app shows promise. Future research is needed to better understand engagement and impact.

A Pilot Study of the Effects of Individualized Home Dual Task Training by Mobile Health Technology in People with Dementia

The objective of this pilot study was to evaluate the effects of dual-task training implemented by mobile health technology on performance on motor and dual-task tests in subjects with dementia. Nineteen subjects with a medical diagnosis of dementia were assigned to an experimental group (EG, n = 12) or control group (CG, n = 7). The EG participated in 24 sessions (3/week) of a homebase dual-task exercises program, in addition to their ongoing cognitive and physiotherapy treatment. The training program was implemented individually in the patient's home by caregivers or relatives through electronic devices controlled by a mobile application. Before (Pre) and after (Post) the program, performance on motor and motor/cognitive (dual-task) tests were evaluated. Motor evaluation included gait at preferred and maximal speed, the Up and Go, and the Handgrip Strength test. Dual-task tests included gait with subtraction 3 s from 100 and naming animals (verbal fluency). The CG only performed the evaluations in addition to their cognitive and physiotherapy treatment. The statistical analysis (ANOVA Group*Test) showed a statically significant improvement for both dual-task tests in the EG after the training program, while the CG showed an impairment in the verbal fluency test. Conclusion: the implementation of a home exercise program carried out with mobile technology in people with dementia is feasible and positively affects their performance on dual tasks.

Empirical study of factors that influence the perceived usefulness of online mental health community members

Online mental health communities have become a major platform where individuals can talk about their mental health problems and obtain social support. This study aims to understand the antecedents of perceived usefulness among members in an online mental health community, while providing reference for the managers and users of online mental health communities. We obtained a total of 143,190 posts from ReachOut.com released by the CLPsych2017 shared task. Then, we used text mining to derive the independent and dependent variables. Next, a structural equation model observing the perceived usefulness of online mental health community members was constructed from the perspective of an information adoption model. The informativeness of help-seeking posts had a significant positive relationship with the information quality of reply posts; the information quality of reply posts was a significant positive predictor of perceived usefulness, with the information quality of reply posts partially mediating the relationship between the informativeness of help-seeking posts and perceived usefulness. The information provided by online mental health community members' help-seeking posts and the quality of replies were found to be the factors that influenced perceived usefulness. This study highlights the importance of the information quality of reply posts and provides useful insights for administrators who can help users to improve their response quality and obtain the support they need.

Prescribing Trends in Psychotropic Medications Among Outpatients of a Latin American Healthcare Setting: A Five-Year Retrospective Study

Introduction Mental health problems affect millions worldwide, and the prescription of psychotropic drugs is increasing globally. The World Health Organization (WHO) has emphasized the need for proper monitoring of psychotropic drug prescriptions. This study aims to characterize and find trends in the prescription of psychotropics in a Latin American General Hospital. Methods The study analyzed the dispensation of psychotropic prescriptions to outpatients at three pharmacies in the central headquarters of Hospital Clínica Bíblica in San José, Costa Rica, from 2017 to 2021. Psychotropic drugs were classified by the Anatomical Therapeutic Chemical (ATC) code, and the amount of each medication dispensed was standardized using the defined daily dose per 10,000 population per day metric. Patients' ages were categorized into four groups: under 18 years, 18 to 39 years, 40 to 64 years, and 65 years and above. The prescriptions were categorized according to medical specialty. Regression analyses were performed to determine the significance of trends observed in the data Results A total of 5793 psychotropic prescriptions were recorded. The average age of the patients was 58 years. The total consumption of psychotropics decreased by 33.94% from 2017 to 2021, with the most significant decline until 2020. However, there was an increase in consumption in 2021. Clonazepam was the most consumed medication, followed by bromazepam and alprazolam, which was the sole drug to exhibit an escalation in usage between 2017 and 2021. Regression analysis showed that only alprazolam and zopiclone had statistically significant trends. The highest number of prescriptions was dispensed to patients aged between 40 and 64 years, followed by those aged over 65 years. Anxiolytics were also the most commonly prescribed group of drugs. General medicine (20.22%), psychiatry (19.95%), and internal medicine (12.73%) were the primary specialties that prescribed psychotropic; 38.6% of prescriptions were associated with the 10th decile of patients, and 44.9% of prescriptions were issued by the 10th decile of physicians.  Conclusion The consumption of psychotropic drugs decreased from 2017 to 2020 but increased in 2021, with alprazolam being the only drug that showed an increase in consumption throughout the entire period. General practitioners and psychiatrists were found to be the specialties that most commonly prescribe these medications. The study found significant trends only for the consumption of alprazolam and zopiclone and for prescription patterns among psychiatrists and internal medicine physicians.

Mental health awareness of secondary schools students: Mediating roles of knowledge on mental health, knowledge on professional help, and attitude towards mental health

Purpose

The mental health situation among adolescents in Malaysia has reached a worrying state with the rising number of cases. Despite a significant increase in the literature on mental health, there is a lack of studies that focused on mental health awareness. Therefore, this study aimed to investigate the factors affecting Malaysian youth's mental health awareness as well as the mediating roles of knowledge on mental health, knowledge on professional help, and attitude towards mental health.

Methods

Self-administered questionnaires were distributed to 450 secondary school students aged 15-19 years old in Kuala Lumpur and Melaka who were recruited via purposive sampling. Data analysis was performed using SPSS and SmartPLS to obtain the descriptive analysis, measurement model, and structural model.

Results

The results indicated that mental health awareness was influenced by knowledge on mental health and attitude towards mental health. The findings also revealed that familiarity and media exposure were important determinants of knowledge on mental health, knowledge on professional help, and attitude towards mental health. Moreover, the results indicated that knowledge on mental health positively mediated the relationship between media exposure and mental health awareness. Besides, attitude towards mental health also found to play mediating roles between familiarity and mental health awareness, as well as between media exposure and mental health awareness.

Conclusion

This study contributed important knowledge to the limited literature in this contemporary domain. An effective public mental health campaign is needed to reduce the burden of disease and the cost of mental illness.

The Electronic Mental Wellness Tool as a Self-Administered Brief Screening Instrument for Mental Disorders in the General Spanish Population during the Post-COVID-19 Era

(1) Background: In the "post-COVID-19 era", there is a need to focus on properly assessing and addressing the extent of its well-established mental health collateral damage. The "Electronic Mental Wellness Tool" (E-mwTool) is a 13-item validated stepped-care or stratified management instrument that aims at the high-sensitivity captures of individuals with mental health disorders to determine the need for mental health care. This study validated the E-mwTool in a Spanish-speaking population. (2) Methods: It is a cross-sectional validation study using the Mini International Neuropsychiatric Interview as a criterion standard in a sample of 433 participants. (3) Results: About 72% of the sample had a psychiatric disorder, and 67% had a common mental disorder. Severe mental disorders, alcohol use disorders, substance use disorders, and suicide risk had a much lower prevalence rate (6.7%, 6.2%, 3.2%, and 6.2%, respectively). The first three items performed excellently in identifying any mental health disorder with 0.97 sensitivity. Ten additional items classified participants with common mental disorders, severe mental disorders, substance use disorders, and suicide risk. (4) Conclusions: The E-mwTool had high sensitivity in identifying common mental disorders, alcohol and substance use disorders, and suicidal risk. However, the tool's sensitivity in detecting low-prevalence disorders in the sample was low. This Spanish version may be useful to detect patients at risk of mental health burden at the front line of primary and secondary care in facilitating help-seeking and referral by their physicians.

Effectiveness of Digital Guided Self-help Mindfulness Training During Pregnancy on Maternal Psychological Distress and Infant Neuropsychological Development: Randomized Controlled Trial

BACKGROUND

Maternal psychological distress during pregnancy is associated with unfavorable outcomes in infants. Mindfulness-based interventions (MBIs) can effectively alleviate psychological distress, but there are often barriers to the access of face-to-face interventions.

OBJECTIVE

This study aimed to investigate the effectiveness of a digital guided self-help (GSH) MBI (GSH-MBI) in reducing maternal psychological distress and improving infant neuropsychological performance.

METHODS

This was a randomized controlled trial. We recruited 160 women who were 12 to 20 weeks pregnant and exhibited psychological distress. We randomized them into a digital GSH-MBI group and a control group (usual perinatal care). The digital GSH-MBI consisted of a 6-week intervention through a WeChat mini program, with a daily reminder sent to the participants by a research assistant via WeChat. The primary outcomes consisted of maternal psychological distress, including depression, anxiety, and pregnancy-related anxiety symptoms, which were assessed at 6 time points from baseline to 6 months post partum (only pregnancy-related anxiety symptoms were assessed 3 times during pregnancy). The secondary outcomes were infant neuropsychological outcomes, including temperament and developmental behaviors, which were assessed at 6 weeks and 6 months post partum.

RESULTS

Compared with the control group, the digital GSH-MBI group showed a significant reduction in depression, anxiety, and pregnancy-related anxiety symptoms. In addition, the scores of the digital GSH-MBI group were lower than those of the control group for the 3 types of infant temperament at 6 weeks post partum, including quality of mood, distractibility, and adaptability.

CONCLUSIONS

Digital GSH-MBIs are effective in alleviating psychological distress among pregnant women and protecting infant outcomes.

TRIAL REGISTRATION

Chinese Clinical Trial Register ChiCTR2000040717; https://www.chictr.org.cn/showproj.aspx?proj=65376.

Impact of Coding Educational Programs (CEP) on Digital Media Problematic Use (DMPU) and on Its Relationship with Psychological Dependence and Emotional Dysregulation

Alongside the positive effects linked to the introduction of digital technologies into our lives, particular dysfunctional behaviors in the use of digital tools have appeared, through which the expression of conditions such as addiction, difficulties in affective and behavioral self-regulation and mental health problems have been channeled. The present study aims to investigate, in a sample of young students aged m = 12.91 (ds = 0.56) years, whether Coding Educational Programs (CEP), deployed to 44.9% of the sample, is effective in psychological dependence, emotional self-regulation and Digital Media Problematic Use (DMPU), as self-assessed through questionnaires (DERS, DSRS, IAT, MPIQ and MPPUS). CEP had no effect on emotional dysregulation or on DMPU. They were effective in the time management of mobile phone use, with students rescheduling from daytime use on working days to daytime use on the weekend. Moreover, people who attended CEP more frequently used smartphones for orienting themselves and for obtaining information. In conclusion, CEP are effective in achieving a more functional and important use of smartphones and better time management. It is possible that CEP effect on metacognition could reduce DMPU if alternative ways to regulate emotions are available.

A comprehensive review on emerging trends in the dynamic evolution of digital addiction and depression

Introduction

Using digital addiction as an umbrella term to cover any type of addictions to digital technologies such as the internet, smartphones, social media, or video games, the current study aimed to reveal the intellectual structure and evolution of research addressing digital addiction-depression relationship.

Methods

The study combined bibliometric and science mapping analysis methods for this purpose. Data for the study was gathered from Web of Science Core Collection after a comprehensive process of data search/extraction, and 241 articles were included in the final data set. A period-based, comparative science mapping analysis was performed using the SciMAT software.

Results

The analysis of data over three periods, Period 1 (1983-2016), Period 2 (2017-2019), and Period 3 (2020-2022) showed that internet addiction was the most significant theme across all three periods, which was followed by social media addiction. Depression, which emerged as a significant theme during Period 1, was later covered under anxiety disorder theme. Research interest was mostly on factors related to both addiction and depression such as cognitive distortion, insomnia, loneliness, self-esteem, social support, alexithymia, as well as cybervictimization or academic performance.

Discussion

The results suggested that much research is warranted on the digital addiction-depression relationship in different age cohorts, especially children and elderly. Similarly, the current analysis showed that this line of research particularly focused on internet, gaming and social media addiction, and evidence with regard to other types of digital addiction or related compulsive behaviors was almost absent. In addition, research was mostly inclined to understanding cause-effect relationships, which is significant, but preventive strategies seemed to be barely addressed. Likewise, the smartphone addiction-depression relationship arguably garnered less research interest, so future research would contribute to the field in this respect.

Digital Intervention For The Management Of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive, multifactorial, chronic, neurodegenerative disease with high prevalence and limited therapeutic options, making it a global health crisis. Being the most common cause of dementia, AD erodes the cognitive, functional, and social abilities of the individual and causes escalating medical and psychosocial needs. As yet, this disorder has no cure and current treatment options are palliative in nature. There is an urgent need for novel therapy to address this pressing challenge. Digital therapeutics (Dtx) is one such novel therapy that is gaining popularity globally. Dtx provides evidence based therapeutic interventions driven by internet and software, employing tools such as mobile devices, computers, videogames, apps, sensors, virtual reality aiding in the prevention, management, and treatment of ailments like neurological abnormalities and chronic diseases. Dtx acts as a supportive tool for the optimization of patient care, individualized treatment and improved health outcomes. Dtx uses visual, sound and other non-invasive approaches for instance-consistent therapy, reminiscence therapy, computerised cognitive training, semantic and phonological assistance devices, wearables and computer-assisted rehabilitation environment to find applications in Alzheimer's disease for improving memory, cognition, functional abilities and managing motor symptom. A few of the Dtx-based tools employed in AD include "Memory Matters", "AlzSense", "Alzheimer Assistant", "smart robotic dog", "Immersive virtual reality (iVR)" and the most current gamma stimulation. The purpose of this review is to summarize the current trends in digital health in AD and explore the benefits, challenges, and impediments of using Dtx as an adjunctive therapy for the management of AD.

AI-based chatbot micro-intervention for parents: Meaningful engagement, learning, and efficacy

Introduction

Mental health issues have been on the rise among children and adolescents, and digital parenting programs have shown promising outcomes. However, there is limited research on the potential efficacy of utilizing chatbots to promote parental skills. This study aimed to understand whether parents learn from a parenting chatbot micro intervention, to assess the overall efficacy of the intervention, and to explore the user characteristics of the participants, including parental busyness, assumptions about parenting, and qualitative engagement with the chatbot.

Methods

A sample of 170 parents with at least one child between 2-11 years old were recruited. A randomized control trial was conducted. Participants in the experimental group accessed a 15-min intervention that taught how to utilize positive attention and praise to promote positive behaviors in their children, while the control group remained on a waiting list.

Results

Results showed that participants engaged with a brief AI-based chatbot intervention and were able to learn effective praising skills. Although scores moved in the expected direction, there were no significant differences by condition in the praising knowledge reported by parents, perceived changes in disruptive behaviors, or parenting self-efficacy, from pre-intervention to 24-hour follow-up.

Discussion

The results provided insight to understand how parents engaged with the chatbot and suggests that, in general, brief, self-guided, digital interventions can promote learning in parents. It is possible that a higher dose of intervention may be needed to obtain a therapeutic change in parents. Further research implications on chatbots for parenting skills are discussed.

The gold-standard treatment for social anxiety disorder: A roadmap for the future

Exposure therapy (ET), which follows the Pavlovian extinction model, is regarded as the gold-standard treatment for social anxiety disorder (SAD). The prospect of virtual reality in lieu of a traditional laboratory setting for the treatment of SAD has not been rigorously explored. The aim of the review was to summarize, find gaps in the current literature, and formulate future research direction by identifying two broad research questions: the comparative efficacy between in vivo ET and virtual reality exposure therapy (VRET) and the effectiveness of the Pavlovian extinction model in treating SAD. The criteria for effectiveness were effect size, relapse prevention, attrition rate and ecological validity. A literature search on recent randomized controlled trials yielded a total of 6 original studies (N=358), excluding duplication and overlapping participants. All studies supported that VRET was as effective as in vivo ET. Behavioral therapy that follows classical conditioning principles has a high attrition and relapse rate. Comparisons were drawn between the efficacy of the Pavlovian extinction model and other existing models, including third-wave approaches. The neural markers are suggested to be included as efficacy measures in treating SAD. The gold-standard treatment for SAD requires a paradigm shift through rigorous longitudinal comparative studies.