Digital Clinics and Mobile Technology Implementation for Mental Health Care

A non-randomized feasibility study of a voice assistant for parents to support their children's mental health

Background

Mental disorders affect one in seven Australian children and although effective, evidenced based treatments exist, there is a critical shortage of mental health clinicians which has created a "treatment gap." Artificial intelligence has the potential to address the high prevalence rates of mental disorders within overburdened mental health systems.

Methods

This was a non-randomized feasibility study to evaluate the novel application of voice technology to an evidence-based parenting intervention designed to support children's mental health. We deployed an Amazon Alexa app to parents recruited from the community (N = 55) and to parents with children receiving psychological treatment (N = 4). Parents from the community used the app independently whereas parents from the clinical group used the app in conjunction with attending a six-week parenting program. The primary outcome measure, feasibility was assessed in terms of acceptability, via recruitment and retention rates, quantitative surveys and qualitative interviews.

Results

In the community group, the recruitment rate was 23.8% and the retention rate 49.1%. In the clinical group, all 6 families approached for recruitment agreed to participate and 4 out of 6 completed the trial. Parents attending the parenting program spent on average, three times longer using the app than parents from the community. Overall, parents reported that the app contained easy-to-understand information on parenting, and that they could see the potential of voice technology to learn and practice parenting skills. Parents also faced several challenges, including difficulties with installation and interactions with the app and expressed privacy concerns related to voice technology. Further, parents reported that the voices used within the app sounded monotone and robotic.

Conclusion

We offer specific recommendations that could foster a better voice assistant user experience for parents to support their children's mental health. The app is highly scalable and has the potential to addresses many of the barriers faced by parents who attempt to access traditional parenting interventions.

Preliminary Investigation Into the Effectiveness of Group webSTAIR for Trauma-exposed Veterans in Primary Care

INTRODUCTION

A substantial number of trauma-exposed veterans seen in primary care report significant symptoms of PTSD and depression. While primary care mental health integration (PCMHI) providers have been successful in delivering brief mental health treatments in primary care, few studies have evaluated interventions that combine mobile health resources with PCMHI groups. This pilot study assessed the potential benefits of webSTAIR, a 10-module transdiagnostic treatment for trauma-exposed individuals, supported by 5 biweekly group sessions delivered via telehealth. The transdiagnostic and mobile health nature of the treatment, as well as the therapist and peer support provided through group sessions, may offer an innovative approach to increasing access to patient-centered and trauma-informed treatment in primary care settings.

MATERIALS AND METHODS

Thirty-nine male and female veterans with trauma-related symptoms (i.e., PTSD and/or depression) participated in group webSTAIR. Mixed effects analyses were conducted to assess changes in PTSD and depression at pre-, mid-, and post-treatment. Baseline symptom severity was assessed as a predictor of module completion and group attendance. The project was part of a VHA quality improvement project, and IRB approval was waived by the affiliated university.

RESULTS

Analyses revealed significant pre-to-post improvement in both PTSD and depression outcomes with a large effect size for PTSD (Hedges' gav = 0.88) and medium to large for depression (Hedges' gav = 0.73). Of participants who completed the baseline assessment, 90% began webSTAIR; of those, 71% completed the program. Baseline symptoms of PTSD and depression did not predict group attendance or module completion.

CONCLUSIONS

Good outcomes and a satisfactory retention rate suggest that group webSTAIR may provide easily accessible, high-quality, and effective treatment for patients presenting with trauma-related problems without increasing therapist or system burdens. The results suggest the value of conducting a randomized controlled trial to test the effectiveness of group webSTAIR relative to PCMHI usual care or other evidence-based, disorder-specific (e.g., PTSD) treatments for trauma-exposed individuals in PCMHI.

Perspectives on the Implementation of Mental Health Apps on Clinical Interventions in Mental Health

N/a.

Human technology intermediation to reduce cognitive load: understanding healthcare staff members' practices to facilitate telehealth access in a Federally Qualified Health Center patient population

OBJECTIVES

The aim of this study was to investigate how healthcare staff intermediaries support Federally Qualified Health Center (FQHC) patients' access to telehealth, how their approaches reflect cognitive load theory (CLT) and determine which approaches FQHC patients find helpful and whether their perceptions suggest cognitive load (CL) reduction.

MATERIALS AND METHODS

Semistructured interviews with staff (n = 9) and patients (n = 22) at an FQHC in a Midwestern state. First-cycle coding of interview transcripts was performed inductively to identify helping processes and participants' evaluations of them. Next, these inductive codes were mapped onto deductive codes from CLT.

RESULTS

Staff intermediaries used 4 approaches to support access to, and usage of, video visits and patient portals for FQHC patients: (1) shielding patients from cognitive overload; (2) drawing from long-term memory; (3) supporting the development of schemas; and (4) reducing the extraneous load of negative emotions. These approaches could contribute to CL reduction and each was viewed as helpful to at least some patients. For patients, there were beneficial impacts on learning, emotions, and perceptions about the self and technology. Intermediation also resulted in successful visits despite challenges.

DISCUSSION

Staff intermediaries made telehealth work for FQHC patients, and emotional support was crucial. Without prior training, staff discovered approaches that aligned with CLT and helped patients access technologies. Future healthcare intermediary interventions may benefit from the application of CLT in their design. Staff providing brief explanations about technical problems and solutions might help patients learn about technologies informally over time.

CONCLUSION

CLT can help with developing intermediary approaches for facilitating telehealth access.

Prevalence and determinants of postpartum depression among adolescent and adult mothers in Northwest Ethiopia

Postpartum depression (PPD) is a common mental health issue in resource-limited settings that negatively affects the well-being of mothers and children. However, PPD often remains untreated, leading to long-term consequences for families. Therefore, we examined the prevalence and determinants of PPD among adolescent and adult mothers in northwest Ethiopia. Data were collected from 374 adolescent (10-19 years) and 760 adult (20-34 years) mothers 6 weeks after childbirth. Data were analyzed using binary and multiple logistic regression. Adolescent mothers had a significantly higher proportion of PPD (37.4%) than adult mothers (20.1%) and were more likely to report low self-esteem (13.1% vs. 8.2%) and low social support (28.3% vs. 23.3%). Factors associated with PPD differed between adolescent and adult mothers. Adolescent mothers with PPD were more likely to report household food insecurity, low self-esteem, low knowledge of postpartum complications, and working in agriculture or professional/technical occupations. For adult mothers, factors associated with PPD included distance to the nearest health facility, medium social support, inadequate dietary diversity, and food insecurity. Results suggest that targeted interventions by age group are needed to reduce the burden of PPD in Ethiopia.

Protocol for a pilot study assessing a virtual mindfulness intervention for postpartum African American women

Elevated perinatal depressive symptoms are more common among disadvantaged African American women, and they are almost four times as likely to have postpartum posttraumatic stress compared to white women. For new mothers, depressive symptoms and posttraumatic stress can lead to negative parenting, poor mother-infant bonding, and delayed infant development. For African American women, a culturally adapted mindfulness-based intervention offers great potential as an acceptable approach to reduce psycho-behavioral symptoms and improve mother-infant interactions (i.e., bonding). Additionally, it is critical that mindfulness interventions consider time constraints of new mothers, provide accessible intervention delivery, address parenting, and consider the challenges of caring for an infant. Given these considerations, we describe a pilot research protocol in which we evaluate a culturally adapted mindfulness program: Mindfulness for African Americans Postpartum (MAAP). The intervention is based upon Kabat-Zinn's Mindfulness Based Stress Reduction program, but is adapted to include culturally relevant concepts of spirituality, inter-dependence, self-empowerment, and storytelling, which are salient to African American culture. To accommodate the needs of new mothers, a certified mindfulness interventionist delivers each session virtually using Zoom. The investigation uses a randomized controlled design in which African American women within 12 months of giving birth are randomized either to the MAAP intervention or to an Education Program. The primary aim is to determine the extent to which the MAAP intervention decreases maternal psycho-behavioral symptoms (perceived stress, depressive symptoms, anxiety, poor sleep, posttraumatic stress, and fatigue) and improves mother-infant bonding. A secondary aim is to explore the effects of MAAP on proinflammatory cytokines and oxytocin. Culturally adapted mindfulness interventions delivered virtually will make mindfulness more accessible and meaningful to populations, like African American new mothers, who are at higher risk for postpartum mood disorders and poor infant outcomes.

Engaging primary care clinicians in the selection of implementation strategies for toddler social-emotional health promotion in community health centers

BACKGROUND

Social-emotional risk for subsequent behavioral health problems can be identified at toddler age, a period where prevention has a heightened impact. This study aimed to meaningfully engage pediatric clinicians, given the emphasis on health promotion and broad reach of primary care, to prepare an Implementation Research Logic Model to guide the implementation of a screening and referral process for toddlers with elevated social-emotional risk.

METHOD

Using an adaptation of a previously published community partner engagement method, six pediatricians from community health centers (CHCs) comprised a Clinical Partner Work Group. The group was engaged in identifying determinants (barriers/facilitators), selecting and specifying strategies, strategy-determinant matching, a modified Delphi approach for strategy prioritization, and user-centered design methods. The data gathered from individual interviews, two group sessions, and a follow-up survey resulted in a completed Implementation Research Logic Model.

RESULTS

The Clinical Partner Work Group identified 16 determinants, including barriers (e.g., patient access to electronic devices) and facilitators (e.g., clinician buy-in). They then selected and specified 14 strategies, which were prioritized based on ratings of feasibility, effectiveness, and priority. The highest-rated strategies (e.g., integration of the screener into the electronic health record) provided coverage of all identified barriers and comprised the primary implementation strategy "package" to be used and tested.

CONCLUSIONS

Clinical partners provided important context and insights for implementation strategy selection and specification to support the implementation of social-emotional risk screening and referral in pediatric primary care. The methodology described herein can improve partner engagement in implementation efforts and increase the likelihood of success. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Ethical considerations for integrating multimodal computer perception and neurotechnology

Background

Artificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures.

Methods

We conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis.

Results

Stakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients' limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data.

Discussion

Our findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients' awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.

How effective are digital/e-health interventions for supporting prisoners with mental ill-health? An integrative review

PURPOSE

There has been a move towards the implementation of digital/e-health interventions for some time. Digital/e-health interventions have demonstrable efficacy in increasing individual empowerment, providing timely access to psychological interventions for those experiencing mental ill-health and improving outcomes for those using them. This study aims to determine the efficacy of digital/e-health interventions for individuals detained in prison who experience mental ill-health.

DESIGN/METHODOLOGY/APPROACH

A systematic search of five academic databases - CINAHL, ASSIA, PsycINFO, Embase and Medline - was completed in December 2020 and updated in February 2022. The review was guided by the Whittemore and Knafl (2005) framework for integrative reviews. A total of 6,255 studies were returned and screened by title and abstract. A full-text screening of nine (n = 9) studies was conducted.

FINDINGS

No study met the inclusion criteria for the clinical efficacy of digital/e-health interventions in a prison setting. Subsequently, a review of the literature that made it to the full-text review stage was conducted, and gaps in the literature were identified to inform policy, practice and future research.

ORIGINALITY/VALUE

To the best of the authors' knowledge, this is the first integrative review conducted on the efficacy of digital/e-health interventions for mental ill-health in prison settings.

Integrated Digital Mental Health Care: A Vision for Addressing Population Mental Health Needs

The unmet need for mental health care continues to rise across the world. This article synthesizes the evidence supporting the components of a hypothetical model of integrated digital mental health care to meet population-wide mental health needs. This proposed model integrates two approaches to broadening timely access to effective care: integrated, primary care-based mental health services and digital mental health tools. The model solves for several of the key challenges historically faced by digital health, through promoting digital literacy and access, the curation of evidence-based digital tools, integration into clinical practice, and electronic medical record integration. This model builds upon momentum toward the integration of mental health services within primary care and aligns with the principles of the Collaborative Care Model. Finally, the authors present the major next steps toward implementation of integrated digital mental health care at scale.

Greenway of Digital Health Technology During COVID-19 Crisis: Bibliometric Analysis, Challenges, and Future Perspective

Digital health has transformed the healthcare landscape by leveraging technology to improve patient outcomes and access to medical services. The COVID-19 pandemic has highlighted the urgent need for digital healthcare solutions that can mitigate the impact of the outbreak while ensuring patient safety. In this chapter, we delve into how digital health technologies such as telemedicine, mobile apps, and wearable devices can provide personalized care, reduce healthcare provider burden, and lower healthcare costs. We also explore the creation of a greenway of digital healthcare that safeguards patient confidentiality, enables efficient communication, and ensures cost-effective payment systems. This chapter showcases the potential of digital health to revolutionize healthcare delivery while ensuring patient well-being and medical staff satisfaction.

Standardising the role of a digital navigator in behavioural health: a systematic review

As the number and availability of digital mental health tools increases, patients and clinicians see benefit only when these tools are engaging and well integrated into care. Digital navigators-ie, members of health-care teams who are dedicated to supporting patient use of digital resources-offer one solution and continue to be piloted in behavioural health; however, little is known about the core features of this position. The aims of this systematic review were to assess how digital navigators are implemented in behavioural health, and to provide a standardised definition of this position. In January, 2023, we conducted a systematic literature search resulting in 48 articles included in this systematic review. Results showed high heterogeneity between four attributes of digital navigators: training specifications, educational background, frequency of communication, and method of communication with patients. Reported effect sizes for depression and anxiety were medium to large, but could not be synthesised due to study heterogeneity and small study sample size. This systematic review was registered with PROSPERO (CRD42023391696). Results suggest that digital navigator support can probably increase access to, engagement with, and clinical integration of digital health technology, with standards for training and defined responsibilities now emerging.

Testing a Digital Health App for Patients With Alcohol-Associated Liver Disease: Mixed Methods Usability Study

BACKGROUND

Alcohol-associated liver disease (ALD) is increasingly common and associated with serious and costly health consequences. Cessation of drinking can improve ALD morbidity and mortality; however, support for cessation is not routinely offered to those diagnosed with ALD, and continued drinking or resumption of drinking after diagnosis is common. Mobile health (mHealth) has the potential to offer convenient and scalable support for alcohol cessation to those diagnosed with ALD, but mHealth interventions for alcohol cessation have not been designed for or evaluated in a population with ALD.

OBJECTIVE

This study aims to understand how individuals with ALD would perceive and use an mHealth tool for alcohol cessation and to gather their perspectives on potential refinements to the tool that would allow it to better meet their needs.

METHODS

We interviewed 11 individuals who attended clinic visits related to their ALD to elicit their needs related to support for alcohol cessation and views on how mHealth could be applied. After completing initial interviews (pre), participants were provided with access to an mHealth app designed for alcohol cessation, which they used for 1 month. Afterward, they were interviewed again (post) to give feedback on their experiences, including aspects of the app that met their needs and potential refinements. We applied a mixed methods approach, including a qualitative analysis to identify major themes from the interview transcripts and descriptive analyses of use of the app over 1 month.

RESULTS

First, we found that a diagnosis of ALD is perceived as a motivator to quit drinking but that patients had difficulty processing the overwhelming amount of information about ALD they received and finding resources for cessation of alcohol use. Second, we found that the app was perceived as usable and useful for supporting drinking recovery, with patients responding favorably to the self-tracking and motivational components of the app. Finally, patients identified areas in which the app could be adapted to meet the needs of patients with ALD, such as providing information on the medical implications of an ALD diagnosis and how to care for their liver as well as connecting individuals with ALD to one another via a peer-to-peer support forum. Rates of app use were high and sustained across the entire study, with participants using the app a little more than half the days during the study on average and with 100% (11/11) of participants logging in each week.

CONCLUSIONS

Our results highlight the need for convenient access to resources for alcohol cessation after ALD diagnosis and support the potential of an mHealth approach to integrate recovery support into care for ALD. Our findings also highlight the ways the alcohol cessation app should be modified to address ALD-specific concerns.

Clinician and Patient Perspectives on the Use of Passive Mobile Monitoring and Self-Tracking for Patients With Serious Mental Illness: User-Centered Approach

BACKGROUND

Early intervention in mental health crises can prevent negative outcomes. A promising new direction is remote mental health monitoring using smartphone technology to passively collect data from individuals to rapidly detect the worsening of serious mental illness (SMI). This technology may benefit patients with SMI, but little is known about health IT acceptability among this population or their mental health clinicians.

OBJECTIVE

We used the Health Information Technology Acceptability Model to analyze the acceptability and usability of passive mobile monitoring and self-tracking among patients with serious mental illness and their mental health clinicians.

METHODS

Data collection took place between December 2020 and June 2021 in 1 Veterans Administration health care system. Interviews with mental health clinicians (n=16) assessed the acceptability of mobile sensing, its usefulness as a tool to improve clinical assessment and care, and recommendations for program refinements. Focus groups with patients with SMI (n=3 groups) and individual usability tests (n=8) elucidated patient attitudes about engaging in health IT and perceptions of its usefulness as a tool for self-tracking and improving mental health assessments.

RESULTS

Clinicians discussed the utility of web-based data dashboards to monitor patients with SMI health behaviors and receiving alerts about their worsening health. Potential benefits included improving clinical care, capturing behaviors patients do not self-report, watching trends, and receiving alerts. Clinicians' concerns included increased workloads tied to dashboard data review, lack of experience using health IT in clinical care, and how SMI patients' associated paranoia and financial instability would impact patient uptake. Despite concerns, all mental health clinicians stated that they would recommend it. Almost all patients with SMI were receptive to using smartphone dashboards for self-monitoring and having behavioral change alerts sent to their mental health clinicians. They found the mobile app easy to navigate and dashboards easy to find and understand. Patient concerns centered on privacy and "government tracking," and their phone's battery life and data plans. Despite concerns, most reported that they would use it.

CONCLUSIONS

Many people with SMI would like to have mobile informatics tools that can support their illness and recovery. Similar to other populations (eg, older adults, people experiencing homelessness) this population presents challenges to adoption and implementation. Health care organizations will need to provide resources to address these and support successful illness management. Clinicians are supportive of technological approaches, with adapting informatics data into their workflow as the primary challenge. Despite clear challenges, technological developments are increasingly designed to be acceptable to patients. The research development-clinical deployment gap must be addressed by health care systems, similar to computerized cognitive training. It will ensure clinicians operate at the top of their skill set and are not overwhelmed by administrative tasks, data summarization, or reviewing data that do not indicate a need for intervention.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/39010.

"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.

Understanding Mental Health Clinicians' Perceptions and Concerns Regarding Using Passive Patient-Generated Health Data for Clinical Decision-Making: Qualitative Semistructured Interview Study

BACKGROUND

Digital health-tracking tools are changing mental health care by giving patients the ability to collect passively measured patient-generated health data (PGHD; ie, data collected from connected devices with little to no patient effort). Although there are existing clinical guidelines for how mental health clinicians should use more traditional, active forms of PGHD for clinical decision-making, there is less clarity on how passive PGHD can be used.

OBJECTIVE

We conducted a qualitative study to understand mental health clinicians' perceptions and concerns regarding the use of technology-enabled, passively collected PGHD for clinical decision-making. Our interviews sought to understand participants' current experiences with and visions for using passive PGHD.

METHODS

Mental health clinicians providing outpatient services were recruited to participate in semistructured interviews. Interview recordings were deidentified, transcribed, and qualitatively coded to identify overarching themes.

RESULTS

Overall, 12 mental health clinicians (n=11, 92% psychiatrists and n=1, 8% clinical psychologist) were interviewed. We identified 4 overarching themes. First, passive PGHD are patient driven-we found that current passive PGHD use was patient driven, not clinician driven; participating clinicians only considered passive PGHD for clinical decision-making when patients brought passive data to clinical encounters. The second theme was active versus passive data as subjective versus objective data-participants viewed the contrast between active and passive PGHD as a contrast between interpretive data on patients' mental health and objective information on behavior. Participants believed that prioritizing passive over self-reported, active PGHD would reduce opportunities for patients to reflect upon their mental health, reducing treatment engagement and raising questions about how passive data can best complement active data for clinical decision-making. Third, passive PGHD must be delivered at appropriate times for action-participants were concerned with the real-time nature of passive PGHD; they believed that it would be infeasible to use passive PGHD for real-time patient monitoring outside clinical encounters and more feasible to use passive PGHD during clinical encounters when clinicians can make treatment decisions. The fourth theme was protecting patient privacy-participating clinicians wanted to protect patient privacy within passive PGHD-sharing programs and discussed opportunities to refine data sharing consent to improve transparency surrounding passive PGHD collection and use.

CONCLUSIONS

Although passive PGHD has the potential to enable more contextualized measurement, this study highlights the need for building and disseminating an evidence base describing how and when passive measures should be used for clinical decision-making. This evidence base should clarify how to use passive data alongside more traditional forms of active PGHD, when clinicians should view passive PGHD to make treatment decisions, and how to protect patient privacy within passive data-sharing programs. Clear evidence would more effectively support the uptake and effective use of these novel tools for both patients and their clinicians.

A framework for precision "dosing" of mental healthcare services: algorithm development and clinical pilot

BACKGROUND

One in five adults in the US experience mental illness and over half of these adults do not receive treatment. In addition to the access gap, few innovations have been reported for ensuring the right level of mental healthcare service is available at the right time for individual patients.

METHODS

Historical observational clinical data was leveraged from a virtual healthcare system. We conceptualize mental healthcare services themselves as therapeutic interventions and develop a prototype computational framework to estimate their potential longitudinal impacts on depressive symptom severity, which is then used to assess new treatment schedules and delivered to clinicians via a dashboard. We operationally define this process as "session dosing": 497 patients who started treatment with severe symptoms of depression between November 2020 and October 2021 were used for modeling. Subsequently, 22 mental health providers participated in a 5-week clinical quality improvement (QI) pilot, where they utilized the prototype dashboard in treatment planning with 126 patients.

RESULTS

The developed framework was able to resolve patient symptom fluctuations from their treatment schedules: 77% of the modeling dataset fit criteria for using the individual fits for subsequent clinical planning where five anecdotal profile types were identified that presented different clinical opportunities. Based on initial quality thresholds for model fits, 88% of those individuals were identified as adequate for session optimization planning using the developed dashboard, while 12% supported more thorough treatment planning (e.g. different treatment modalities). In the clinical pilot, 90% of clinicians reported using the dashboard a few times or more per member. Although most clinicians (67.5%) either rarely or never used the dashboard to change session types, numerous other discussions were enabled, and opportunities for automating session recommendations were identified.

CONCLUSIONS

It is possible to model and identify the extent to which mental healthcare services can resolve depressive symptom severity fluctuations. Implementation of one such prototype framework in a real-world clinic represents an advancement in mental healthcare treatment planning; however, investigations to assess which clinical endpoints are impacted by this technology, and the best way to incorporate such frameworks into clinical workflows, are needed and are actively being pursued.

Methods for Navigating the Mobile Mental Health App Landscape for Clinical Use

There are over 10,000 mental health and wellness apps on the market. Apps offer the opportunity to increase access to mental health care. However, with many apps to choose from and an app landscape that is largely unregulated, it can be difficult to incorporate this technology into clinical practice. The first step towards achieving this goal is to identify clinically relevant and appropriate apps. The purpose of this review is to discuss app evaluation, raise awareness of considerations involved in implementing mental health apps into clinical care, and provide an example of how apps can be used effectively in the clinical space. We discuss the current regulatory environment for health apps, how to evaluate apps, and implement them into clinical practice. We also showcase a digital clinic where apps are integrated into the clinical workflow and discuss barriers to app implementation. Mental health apps have the potential to increase access to care if they are clinically effective, easy to use, and protect patient privacy. Learning how to find, evaluate, and implement quality apps into practice is key in harnessing this technology for the benefit of patients.

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

The COVID-19 pandemic ravaged almost every walk of life but it triggered many challenges for the healthcare system, globally. Different cutting-edge technologies such as Internet of things (IoT), machine learning, Virtual Reality (VR), Big data, Blockchain etc. have been adopted to cope with this menace. In this regard, various surveys have been conducted to highlight the importance of these technologies. However, among these technologies, the role of mobile computing is of paramount importance which is not found in the existing literature. Hence, this survey in mainly targeted to highlight the significant role of mobile computing in alleviating the impacts of COVID-19 in healthcare sector. The major applications of mobile computing such as software-based solutions, hardware-based solutions and wireless communication-based support for diagnosis, prevention, self-symptom reporting, contact tracing, social distancing, telemedicine and treatment related to coronavirus are discussed in detailed and comprehensive fashion. A state-of-the-art work is presented to identify the challenges along with possible solutions in adoption of mobile computing with respect to COVID-19 pandemic. Hopefully, this research will help the researchers, policymakers and healthcare professionals to understand the current research gaps and future research directions in this domain. To the best level of our knowledge, this is the first survey of its type to address the COVID-19 pandemic by exploring the holistic contribution of mobile computing technologies in healthcare area.

eHealth Use on Acute Inpatient Mental Health Units: Implementation Processes, Common Practices, and Barriers to Use

Information technology to promote health (eHealth) is an important and growing area of mental healthcare, yet little is known about the use of patient-facing eHealth in psychiatric inpatient settings. This quality improvement project examined the current practices, barriers, implementation processes, and contextual factors affecting eHealth use across multiple Veteran Health Administration (VHA) acute mental health inpatient units. Staff from units serving both voluntary and involuntary patients (n = 49 from 37 unique sites) completed surveys regarding current, desired, and barriers to use of Veteran-facing eHealth technologies. Two subsets of respondents were then interviewed (high success sites in eHealth use, n = 6; low success sites, n = 4) to better understand the context of their eHealth use. Survey responses indicated that 20% or less of Veterans were using any type of eHealth technology while inpatient. Tablets and video chat were the most desired overall and most successfully used eHealth technologies. However, many sites noted difficulty implementing these technologies (e.g., limited Wi-Fi access). Qualitative analysis of interviews revealed differences in risk/benefit analysis and implementation support between high and low success eHealth sites. Despite desired use, patient-facing eHealth technology is not regularly implemented on inpatient units due to multiple barriers (e.g., limited staffing, infrastructure needs). Successful implementation of patient-facing eHealth may require an internal champion, guidance from external supports with experience in successful eHealth use, workload balance for staff, and an overall perspective shift in the benefits to eHealth technology versus the risks.

Weight Loss Expectations of Adults With Binge Eating: Cross-sectional Study With a Human-Centered Design Approach

BACKGROUND

People tend to overestimate their expectations for weight loss relative to what is achievable in a typical evidence-based behavioral weight management program, which can impact treatment satisfaction and outcomes. We are engaged in formative research to design a digital intervention that addresses binge eating and weight management; thus, understanding expectations among this group can inform more engaging intervention designs to produce a digital intervention that can achieve greater clinical success. Studies examining weight loss expectations have primarily focused on people who have overweight or obesity. Only one study has investigated weight loss expectations among people with binge eating disorder, a population that frequently experiences elevated weight and shape concerns and often presents to treatment with the goal of losing weight.

OBJECTIVE

The aim of the study is to investigate differences in weight loss expectations among people with varying levels of binge eating to inform the design of a digital intervention for binge eating and weight management. Such an evaluation may be crucial for people presenting for a digital intervention, given that engagement and dropout are notable problems for digital behavior change interventions. We tested the hypotheses that (1) people who endorsed some or recurrent binge eating would expect to lose more weight than those who did not endorse binge eating and (2) people who endorsed a more severe versus a low or moderate overvaluation of weight and shape would have higher weight loss expectations.

METHODS

A total of 760 adults (n=504, 66% female; n=441, 58% non-Hispanic White) completed a web-based screening questionnaire. One-way ANOVAs were conducted to explore weight loss expectations for binge eating status as well as overvaluation of shape and weight.

RESULTS

Weight loss expectations significantly differed by binge eating status. Those who endorsed some and recurrent binge eating expected to lose more weight than those who endorsed no binge eating. Participants with severe overvaluation of weight or shape expected to lose the most weight compared to those with low or moderate levels of overvaluation of weight and shape.

CONCLUSIONS

In the sample, people interested in a study to inform a digital intervention for binge eating and weight management overestimated their expectations for weight loss. Given that weight loss expectations can impact treatment completion and success, it may be important to assess and modify weight loss expectations among people with binge eating prior to enrolling in a digital intervention. Future work should design and test features that can modify these expectations relative to individuals' intended treatment goals to facilitate engagement and successful outcomes in a digital intervention.

Training Staff Across the Veterans Affairs Health Care System to Use Mobile Mental Health Apps: A National Quality Improvement Project

BACKGROUND

The National Center for PTSD, within the Department of Veterans Affairs (VA), has developed a suite of free, publicly available, evidence-informed apps that can reach an increasing number of veterans and bridge gaps in care by providing resources to those who are not engaged in mental health treatment. To expand the reach of these apps, staff across VA service lines learned about these apps, their features and limitations, and how to introduce them to veterans.

OBJECTIVE

This study aimed to develop, disseminate, and evaluate a training for multidisciplinary staff as part of a national quality improvement project to increase the reach of mobile mental health apps as a resource for veterans.

METHODS

Sites from all of VA's 18 geographic regions enrolled in this project. At each site, a minimum of 25 VA staff members who had direct contact with veterans, including staff from the mental health service line and all other service lines, were recruited to participate. Training included a 3-hour multidisciplinary core module, and a 1-hour clinical integration module designed specifically for mental health clinicians. Owing to the COVID-19 pandemic, the trainings were adapted to a live, web-based format. Pre- and posttraining surveys assessed program reach (ie, participants enrolled per site), satisfaction, and effectiveness of the training as measured by changes in knowledge, basic skills, and behavioral intentions to use apps with veterans.

RESULTS

A total of 1110 participants representing 34 disciplines at 19 VA sites completed the training. Overall, 67% (743/1109) of participants were mental health staff members. Sites averaged 58.4 participants (SD 36.49, median [IQR] 51). Most (961/1024, 93.85%) participants were satisfied with the training and reported that they (941/1018, 92.44%) would recommend it to others. App knowledge scores significantly increased from pretraining (mean 80.8% correct, SD 15.77%) to posttraining (mean 91.1% correct, SD 9.57%; P<.001). At posttraining, participants also reported greater confidence in their ability to show veterans how to download (z=-13.86; P<.001) and use VA mental health apps (z=-15.13; P<.001). There was near universal endorsement by staff for their intentions to recommend apps to veterans as well as their ability to think of at least one specific veteran to whom they could recommend an app. Staff also reported a strong motivation to encourage other VA staff to share apps with veterans.

CONCLUSIONS

The training far exceeded the initial goals for staff recruitment and training for all three metrics. Overall, 33% (366/1109) of participants came from service lines outside of mental health, indicating the feasibility of introducing these mental health resources during medical appointments and in other contexts.

A Framework for the Implementation of Digital Mental Health Interventions: The Importance of Feasibility and Acceptability Research

Digital mental health interventions (DMHIs) have the potential to serve a significantly wider portion of the population in need of mental health services. The coronavirus disease 2019 (COVID-19) pandemic has especially highlighted the exacerbation of mental health disparities among minoritized populations. Innovations and research on DMHIs continue to expand, reinforcing the need for a more systemic process of DMHI implementation. In practice, DMHI implementation often skips the fundamental steps of conducting acceptability and feasibility studies. We propose a DMHI implementation framework that identifies an acceptability and feasibility study as an essential first step, simultaneously centering equitable processes that address populations disproportionately affected by mental illness.

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

The recent advancement in mobile technologies has led to opening a new paradigm in the field of medical healthcare systems. The development of WBAN sensors, wearable devices, and 5G/6G wireless technology has made real-time monitoring and telecare of the patient feasible. The complex framework to secure sensitive data of the patient and healthcare professionals is critical. The fast computation of health data generated is crucial for disease prediction and trauma-related services; the security of data and financial transactions is also a major concern. Various models, algorithms, and frameworks have been developed to tame critical issues related to healthcare services. The efficiency of these frameworks and models depends on energy and time consumption. Thus, the review of recent emerging technologies in respect of energy and time consumption is required. This paper reviews the developments in recent mobile technologies, their application, and the comparative analysis of their performance parameters to explicitly understand the utility, capacity, and limitations. This will help to understand the shortcomings of the recent technologies for the development of better frameworks with higher performance capabilities as well as higher quality of services.

Why are Patient Portals Important in the Age of COVID-19? Reflecting on Patient and Team Experiences From a Toronto Hospital Network

The COVID-19 pandemic has changed how care is being delivered in Canada. With conventional in-person care being transitioned to virtual care, the approach that patients are able to engage and access their care has dramatically changed. At the University Health Network (UHN), which is Canada's largest academic and teaching hospital network, we expanded the myUHN Patient Portal in 2017 after its early adopter phase to enable patients and family members to view parts of their clinical notes and test results. As the pandemic progressed, we observed high adoption of myUHN to support virtual care and rapid delivery of COVID-19 test results in real time. In this article, we share and reflect on our experience of adapting myUHN to support the demands of the pandemic, including portal adoption outcomes across multiple waves of the pandemic, the impetus for increased patient experience staff dedicated for myUHN support, and patients’ perceptions of the value of the portal and virtual care. Based on these reflections, we outline our perspectives on the future role of patient portals to support patient care and experience in a post-pandemic environment.

The use of virtual complementary and integrative therapies by neurology outpatients: An exploratory analysis of two cross-sectional studies assessing the use of technology as treatment in an academic neurology department in New York City

Background

Prior to the COVID-19 pandemic, about half of patients from populations that sought care in neurology tried complementary and integrative therapies (CITs). With the increased utilization of telehealth services, we sought to determine whether patients also increased their use of virtual CITs.

Methods

We examined datasets from two separate cross-sectional surveys that included cohorts of patients with neurological disorders. One was a dataset from a study that examined patient and provider experiences with teleneurology visits; the other was a study that assessed patients with a history of COVID-19 infection who presented for neurologic evaluation. We assessed and reported the use of virtual (and non-virtual) CITs using descriptive statistics, and determined whether there were clinical characteristics that predicted the use of CITs using logistic regression analyses.

Findings

Patients who postponed medical treatment for non-COVID-19-related problems during the pandemic were more likely to seek CITs. Virtual exercise, virtual psychotherapy, and relaxation/meditation smartphone applications were the most frequent types of virtual CITs chosen by patients. In both studies, age was a key demographic factor associated with mobile/virtual CIT usage.

Interpretations

Our investigation demonstrates that virtual CIT-related technologies were utilized in the treatment of neurologic conditions during the pandemic, particularly by those patients who deferred non-COVID-related care.

Adapting and Implementing Apps for Mental Healthcare

PURPOSE OF REVIEW

To describe examples of adapting apps for use in mental healthcare and to formulate recommendations for successful adaptation in mental healthcare settings.

RECENT FINDINGS

International examples are given to explore implementation procedures to address this multitude of challenges. There are only few published examples of adapting apps for use in mental healthcare. From these examples and from results of studies in implementation science in general clinical settings, it can be concluded that the process of adapting apps for mental healthcare needs to address clinician training and information needs, user needs which include cultural adaptation and go beyond mere translation, and organizational needs for blending app use into everyday clinical mental healthcare workflows.

Evaluating a Low-Cost Technology to Enable People with Intellectual Disability or Psychiatric Disorders to Initiate and Perform Functional Daily Activities

People with intellectual disability or psychiatric disorders and cognitive dysfunctions may need assistive technology to maintain and improve their levels of functioning and independence. This study assessed a smartphone-based system to remind the user to initiate functional daily activities (e.g., setting a table for lunch) and perform them without the support of a caregiver. The system was evaluated through a non-concurrent multiple baseline design across two groups of participants. During the intervention sessions, the participants were provided with a system involving a Samsung Galaxy A3 smartphone fitted with the Easy Alarm YouTube application and audio files. The alarm served to remind the participant to carry out a planned activity. Following the reminder, the smartphone presented each of the step instructions preset for the activity. The data showed a statistically significant increase in the number of activities initiated independently from baseline to intervention for all participants. All participants also showed a significant increase in the number of activity steps correctly performed when supported by the smartphone. These results suggest that a low-cost system (i.e., smartphone) can be used to improve independence of people with intellectual disability or psychiatric disorders with cognitive dysfunctions.

Improving clinical decision-making in psychiatry: implementation of digital phenotyping could mitigate the influence of patient’s and practitioner’s individual cognitive biases

High stake clinical choices in psychiatry can be impacted by external irrelevant factors. A strong understanding of the cognitive and behavioural mechanisms involved in clinical reasoning and decision-making is fundamental in improving healthcare quality. Indeed, the decision in clinical practice can be influenced by errors or approximations which can affect the diagnosis and, by extension, the prognosis: human factors are responsible for a significant proportion of medical errors, often of cognitive origin. Both patient’s and clinician’s cognitive biases can affect decision-making procedures at different time points. From the patient’s point of view, the quality of explicit symptoms and data reported to the psychiatrist might be affected by cognitive biases affecting attention, perception or memory. From the clinician’s point of view, a variety of reasoning and decision-making pitfalls might affect the interpretation of information provided by the patient. As personal technology becomes increasingly embedded in human lives, a new concept called digital phenotyping is based on the idea of collecting real-time markers of human behaviour in order to determine the ‘digital signature of a pathology’. Indeed, this strategy relies on the assumption that behaviours are ‘quantifiable’ from data extracted and analysed through connected tools (smartphone, digital sensors and wearable devices) to deduce an ‘e-semiology’. In this article, we postulate that implementing digital phenotyping could improve clinical reasoning and decision-making outcomes by mitigating the influence of patient’s and practitioner’s individual cognitive biases.