Veteran Preferences and Willingness to Share Patient-Generated Health Data.

BACKGROUND: Technologies, including mobile health applications (apps) and wearables, offer new potential for gathering patient-generated health data (PGHD) from patients; however, little is known about patient preferences for and willingness to collect and share PGHD with their providers and healthcare systems. OBJECTIVE: Describe how patients use their PGHD and factors important to patients when deciding whether to share PGHD with a healthcare system. DESIGN: Cross-sectional mailed longitudinal survey supplemented with administrative data within the Veterans Health Administration (VHA). SUBJECTS: National sample of Veterans who use VHA healthcare. MAIN MEASURES: Survey questions asked about demographics, willingness to use different devices to collect and share PGHD, what Veterans do with their PGHD, and factors important to Veterans when deciding whether to share PGHD with VHA. Administrative data provided information on Veteran health conditions. Multiple logistic regression models assessed factors associated with sharing PGHD with VHA. KEY RESULTS: Overall, 47% of our analytic cohort (n = 383/807) indicated that they share PGHD collected through apps or digital health devices with VHA. In adjusted logistic regression models, Veterans who believed the following factors were Very Important (versus Somewhat/Not At All Important) had higher odds of sharing PGHD with VHA: if their doctor (OR = 1.4; 95%CI, 1.0-2.0) or other healthcare team members (OR = 1.4; 95%CI, 1.0-1.9) recommended they do so; and knowing that their healthcare team would look at the data (OR = 1.4; 95%CI, 1.0-2.0) or use the information to inform their healthcare (OR = 1.5; 95%CI, 1.1-2.1). CONCLUSIONS: Our data suggest that healthcare team members can influence patient sharing of PGHD, as can a patient's knowledge that PGHD will be used in clinical practice. Efforts to increase the number of patients who share PGHD with a healthcare system may benefit from buy-in among healthcare team members, who appear to play an influential role in patient decisions to share data.

A Remotely Delivered, Personalized Music Therapy Pilot Intervention for Lonely Older Adults During the Covid-19 Pandemic.

Introduction: This study investigated a remotely delivered, therapist-facilitated, personalized music listening intervention for community-dwelling older adults experiencing loneliness during the Covid-19 pandemic. We assessed its feasibility and individuals' experiences of social connection and emotional well-being during the intervention. Methods: Ten cognitively unimpaired older adults who endorsed loneliness completed eight weekly sessions with a board-certified music therapist via Zoom. Participants were guided in developing two online personalized music playlists and were asked to listen to playlists for at least one hour daily. Feasibility metrics were attendance, accessibility, and compliance rates. Post-study interview responses were analyzed using a rapid qualitative methodology. Exploratory pre- and post-study measures of loneliness and other aspects of psychological well-being were obtained using validated questionnaires. Results: Ten participants (mean age 75.38 [65 to 85] years, 80% women) were enrolled from March to August 2021. Attendance and compliance rates were 100% and the accessibility rate was 90%. Most participants associated music with positive memories before the program and many reported that the intervention prompted them to reconnect with music or listen to music with greater intention. They cited increased connection from interacting with the music therapist and the music itself, as well as specific positive emotional impacts from integrating music into their daily lives. Median pre- to post-questionnaire measures of psychological function all changed in an improved direction. Discussion: Remotely delivered music therapy may be a promising intervention to promote regular music listening and socioemotional well-being in lonely older adults.

Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology.

BACKGROUND: Effective treatment of bipolar disorder (BD) requires prompt response to mood episodes. Preliminary studies suggest that predictions based on passive sensor data from personal digital devices can accurately detect mood episodes (e.g., between routine care appointments), but studies to date do not use methods designed for broad application. This study evaluated whether a novel, personalized machine learning approach, trained entirely on passive Fitbit data, with limited data filtering could accurately detect mood symptomatology in BD patients. METHODS: We analyzed data from 54 adults with BD, who wore Fitbits and completed bi-weekly self-report measures for 9 months. We applied machine learning (ML) models to Fitbit data aggregated over two-week observation windows to detect occurrences of depressive and (hypo)manic symptomatology, which were defined as two-week windows with scores above established clinical cutoffs for the Patient Health Questionnaire-8 (PHQ-8) and Altman Self-Rating Mania Scale (ASRM) respectively. RESULTS: As hypothesized, among several ML algorithms, Binary Mixed Model (BiMM) forest achieved the highest area under the receiver operating curve (ROC-AUC) in the validation process. In the testing set, the ROC-AUC was 86.0% for depression and 85.2% for (hypo)mania. Using optimized thresholds calculated with Youden's J statistic, predictive accuracy was 80.1% for depression (sensitivity of 71.2% and specificity of 85.6%) and 89.1% for (hypo)mania (sensitivity of 80.0% and specificity of 90.1%). CONCLUSION: We achieved sound performance in detecting mood symptomatology in BD patients using methods designed for broad application. Findings expand upon evidence that Fitbit data can produce accurate mood symptomatology predictions. Additionally, to the best of our knowledge, this represents the first application of BiMM forest for mood symptomatology prediction. Overall, results move the field a step toward personalized algorithms suitable for the full population of patients, rather than only those with high compliance, access to specialized devices, or willingness to share invasive data.

Evaluating Feasibility, Value and Characteristics of an Intergenerational Friendly Telephone Visit Program During the Covid-19 Pandemic.

OBJECTIVE: Volunteer organizations offer telephone outreach to older adults to relieve feelings of loneliness and to promote emotional well-being, though the feasibility, perceived value, and characteristics of the participant experience of these community interventions have not been well-studied. We examined these elements of an intergenerational college-based telephone call program during the Covid-19 pandemic. METHODS: Community-dwelling older adults and undergraduate volunteers engaged in eight, weekly, 30-minute, unscripted telephone conversations. Feasibility criteria included enrollment, retention, and attendance rates. A rapid qualitative analysis of program evaluation responses was used to extract themes related to participants' experiences of the intervention. RESULTS: Ten older adults (mean age [range] 74.53 [70-84] years, 88% women) and nine undergraduates were enrolled from February to August 2021, achieving recruitment targets and enrollment rates of 76.9% and 90%. Seven out of the 10 enrolled dyads completed the full series of eight telephone conversations and qualitative assessments over an average of 10.5 weeks. Most older adults who completed the call schedule valued the conversations as a source of social connection, noting the mutuality, respect, and broadened perspective that characterized their intergenerational relationships. Undergraduates described value in giving to others and in conversations that stimulated personal reflection and feelings of closeness. Undergraduates frequently described their experience as novel and broadening of their perspectives. CONCLUSION: Though study completion rate and participant experience varied across dyads, we found qualitative evidence of perceived value, active relationship-building and broadened perspectives among many older adults and undergraduates who completed an intergenerational telephone program.

Digital Mental Health Interventions for Depression: Scoping Review of User Engagement.

BACKGROUND: While many digital mental health interventions (DMHIs) have been found to be efficacious, patient engagement with DMHIs has increasingly emerged as a concern for implementation in real-world clinical settings. To address engagement, we must first understand what standard engagement levels are in the context of randomized controlled trials (RCTs) and how these compare with other treatments. OBJECTIVE: This scoping review aims to examine the state of reporting on intervention engagement in RCTs of mobile app-based interventions intended to treat symptoms of depression. We sought to identify what engagement metrics are and are not routinely reported as well as what the metrics that are reported reflect about standard engagement levels. METHODS: We conducted a systematic search of 7 databases to identify studies meeting our eligibility criteria, namely, RCTs that evaluated use of a mobile app-based intervention in adults, for which depressive symptoms were a primary outcome of interest. We then extracted 2 kinds of information from each article: intervention details and indices of DMHI engagement. A 5-element framework of minimum necessary DMHI engagement reporting was derived by our team and guided our data extraction. This framework included (1) recommended app use as communicated to participants at enrollment and, when reported, app adherence criteria; (2) rate of intervention uptake among those assigned to the intervention; (3) level of app use metrics reported, specifically number of uses and time spent using the app; (4) duration of app use metrics (ie, weekly use patterns); and (5) number of intervention completers. RESULTS: Database searching yielded 2083 unique records. Of these, 22 studies were eligible for inclusion. Only 64% (14/22) of studies included in this review specified rate of intervention uptake. Level of use metrics was only reported in 59% (13/22) of the studies reviewed. Approximately one-quarter of the studies (5/22, 23%) reported duration of use metrics. Only half (11/22, 50%) of the studies reported the number of participants who completed the app-based components of the intervention as intended or other metrics related to completion. Findings in those studies reporting metrics related to intervention completion indicated that between 14.4% and 93.0% of participants randomized to a DMHI condition completed the intervention as intended or according to a specified adherence criteria. CONCLUSIONS: Findings suggest that engagement was underreported and widely varied. It was not uncommon to see completion rates at or below 50% (11/22) of those participants randomized to a treatment condition or to simply see completion rates not reported at all. This variability in reporting suggests a failure to establish sufficient reporting standards and limits the conclusions that can be drawn about level of engagement with DMHIs. Based on these findings, the 5-element framework applied in this review may be useful as a minimum necessary standard for DMHI engagement reporting.

Conducting clinical studies targeting cognition in psychiatry: guiding principles and design.

Cognitive dysfunction is common in many psychiatric disorders. While it has long been described as a core feature in schizophrenia, more recent data suggest qualitatively similar impairments in patients with bipolar disorder and major depressive disorder. There is compelling evidence to suggest that cognitive impairment contributes directly to functional disability and reduced quality of like across these disorders. As current treatments focus heavily on "primary" symptoms of mood and psychosis, the standard of care typically leaves cognitive deficits unmanaged. With this in mind, the field has recently begun to consider intervening directly on this important symptom domain, with several ongoing trials in schizophrenia. Fewer studies have targeted cognition in bipolar disorder and still fewer in MDD. With progress toward considering this domain as a target for treatment comes the need for consensus guidelines and methodological recommendations on cognitive trial design. In this manuscript, we first summarize the work conducted to date in this area for schizophrenia and for bipolar disorder. We then begin to address these same issues in MDD and emphasize the need for additional work in this area.

Automated Text Messaging With Patients in Department of Veterans Affairs Specialty Clinics: Cluster Randomized Trial.

BACKGROUND: Acceptability of mobile phone text messaging as a means of asynchronous communication between health care systems and patients is growing. The US Department of Veterans Affairs (VA) has adopted an automated texting system (aTS) for national rollout. The aTS allows providers to develop clinical texting protocols to promote patient self-management and allows clinical teams to monitor patient progress between in-person visits. Texting-supported hepatitis C virus (HCV) treatment has not been previously tested. OBJECTIVE: Guided by the Practical, Robust Implementation and Sustainability Model (PRISM), we developed an aTS HCV protocol and conducted a mixed methods, hybrid type 2 effectiveness implementation study comparing two programs supporting implementation of the aTS HCV protocol for medication adherence in patients with HCV. METHODS: Seven VA HCV specialty clinics were randomized to usual aTS implementation versus an augmented implementation facilitation program. Implementation process measures included facilitation metrics, usability, and usefulness. Implementation outcomes included provider and patient use of the aTS HCV protocol, and effectiveness outcomes included medication adherence, health perceptions and behaviors, and sustained virologic response (SVR). RESULTS: Across the seven randomized clinics, there were 293 facilitation events using a core set of nine implementation strategies (157 events in augmented implementation facilitation, 136 events in usual implementation). Providers found the aTS appropriate with high potential for scale-up but not without difficulties in startup, patient selection and recruitment, and clinic workflow integration. Patients largely found the aTS easy to use and helpful; however, low perceived need for self-management support contributed to high declination. Reach and use was modest with 197 patients approached, 71 (36%) enrolled, 50 (25%) authenticated, and 32 (16%) using the aTS. In augmented implementation facilitation clinics, more patients actively used the aTS HCV protocol compared with usual clinic patients (20% vs 12%). Patients who texted reported lower distress about failing HCV treatment (13/15, 87%, vs 8/15, 53%; P=.05) and better adherence to HCV medication (11/15, 73%, reporting excellent adherence vs 6/15, 40%; P=.06), although SVR did not differ by group. CONCLUSIONS: The aTS is a promising intervention for improving patient self-management; however, augmented approaches to implementation may be needed to support clinician buy-in and patient engagement. Considering the behavioral, social, organizational, and technical scale-up challenges that we documented, successful and sustained implementation of the aTS may require implementation strategies that operate at the clinic, provider, and patient levels. TRIAL REGISTRATION: Retrospectively registered at ClinicalTrials.gov NCT03898349; https://clinicaltrials.gov/ct2/show/NCT03898349.

How Do Patients with Mental Health Diagnoses Use Online Patient Portals? An Observational Analysis from the Veterans Health Administration.

Online patient portals may be effective for engaging patients with mental health conditions in their own health care. This retrospective database analysis reports patient portal use among Veterans with mental health diagnoses. Unadjusted and adjusted odds of portal feature use was calculated using logistic regressions. Having experienced military sexual trauma or having an anxiety disorder, post-traumatic stress disorder, or depression were associated with increased odds of portal use; bipolar, substance use, psychotic and adjustment disorders were associated with decreased odds. Future research should examine factors that influence portal use to understand diagnosis-level differences and improve engagement with such tools.

Practical application of opt-out recruitment methods in two health services research studies.

BACKGROUND: Participant recruitment is an ongoing challenge in health research. Recruitment may be especially difficult for studies of access to health care because, even among those who are in care, people using services least often also may be hardest to contact and recruit. Opt-out recruitment methods (in which potential participants are given the opportunity to decline further contact about the study (opt out) following an initial mailing, and are then contacted directly if they have not opted out within a specified period) can be used for such studies. However, there is a dearth of literature on the effort needed for effective opt-out recruitment. METHODS: In this paper we describe opt-out recruitment procedures for two studies on access to health care within the U.S. Department of Veterans Affairs. We report resource requirements for recruitment efforts (number of opt-out packets mailed and number of phone calls made). We also compare the characteristics of study participants to potential participants via t-tests, Fisher's exact tests, and chi-squared tests. RESULTS: Recruitment rates for our two studies were 12 and 21%, respectively. Across multiple study sites, we had to send between 4.3 and 9.2 opt-out packets to recruit one participant. The number of phone calls required to arrive at a final status for each potentially eligible Veteran (i.e. study participation or the termination of recruitment efforts) were 2.9 and 6.1 in the two studies, respectively. Study participants differed as expected from the population of potentially eligible Veterans based on planned oversampling of certain subpopulations. The final samples of participants did not differ statistically from those who were mailed opt-out packets, with one exception: in one of our two studies, participants had higher rates of mental health service use in the past year than did those mailed opt-out packets (64 vs. 47%). CONCLUSIONS: Our results emphasize the practicality of using opt-out methods for studies of access to health care. Despite the benefits of these methods, opt-out alone may be insufficient to eliminate non-response bias on key variables. Researchers will need to balance considerations of sample representativeness and feasibility when designing studies investigating access to care.

Understanding collaborative care implementation in the Department of Veterans Affairs: core functions and implementation challenges.

BACKGROUND: The collaborative care model is an evidence-based practice for treatment of depression in which designated care managers provide clinical services, often by telephone. However, the collaborative care model is infrequently adopted in the Department of Veterans Affairs (VA). Almost all VA medical centers have adopted a co-located or embedded approach to integrating mental health care for primary care patients. Some VA medical centers have also adopted a telephone-based collaborative care model where depression care managers support patient education, patient activation, and monitoring of adherence and progress over time. This study evaluated two research questions: (1) What does a dedicated care manager offer in addition to an embedded-only model? (2) What are the barriers to implementing a dedicated depression care manager? METHODS: This study involved 15 qualitative, multi-disciplinary, key informant interviews at two VA medical centers where reimbursement options were the same- both with embedded mental health staff, but one with a depression care manager. Participant interviews were recorded and transcribed. Thematic analysis was used to identify descriptive and analytical themes. RESULTS: Findings suggested that some of the core functions of depression care management are provided as part of embedded-only mental health care. However, formal structural attention to care management may improve the reliability of care management functions, in particular monitoring of progress over time. Barriers to optimal implementation were identified at both sites. Themes from the care management site included finding assertive care managers to hire, cross-discipline integration and collaboration, and primary care provider burden. Themes from interviews at the embedded site included difficulty getting care management on leaders' agendas amidst competing priorities and logistics (staffing and space). CONCLUSIONS: Providers and administrators see depression care management as a valuable healthcare service that improves patient care. Barriers to implementation may be addressed by team-building interventions to improve cross-discipline integration and communication. Findings from this study are limited in scope to the VA healthcare system. Future investigation of whether alternative barriers exist in implementation of depression care management programs in non-VA hospital systems, where reimbursement rates may be a more prominent concern, would be valuable.

Fat Reduction Efforts: A 24-Month Longitudinal Comparison of a Large Sample of Maintainers, Relapsers, and Non-Changers.

This research examined dynamic transtheoretical model (TTM) constructs for dietary fat reduction. This secondary data analysis pooled three large population-based TTM-tailored school, worksite, medical, and home-based intervention studies and examined use of constructs across three groups organized by longitudinal progress (dynatypes): Maintainers, Relapsers, and Stable Non-Changers. The criteria for successful change, at the time, were that less than 30% of calories came from fat. A total of 2,718 adults met criteria for an unhealthy diet at baseline. The majority of participants were female, White, married, and middle-aged. Demographics, Stage of Change, Processes of Change, Decisional Balance, and Temptations were measured. Dynatype groups were assessed with reliable and valid scales assessing constructs at baseline and 6, 12, and 24 months. Analyses included a multivariate analysis of variance followed by a series of analyses of variance, with Tukey follow-up tests assessing differences in use of TTM constructs across the three groups at each time point. Relapsers and Maintainers were similar in their use of all TTM Processes of Change at baseline, with the exception of Self-Liberation (η(2) = 0.15, p < .001) and Reinforcement Management (η(2) = 0.01, p < .001). Although Relapsers reverted to an unhealthy diet, their overall greater use of Processes of Change suggests that their behaviors and strategy use remain better than that of the Stable Non-Changer group. Results suggest that specific cognitive and behavioral constructs may contribute differentially to intervention outcomes.

Transtheoretical Principles and Processes for Adopting Physical Activity: A Longitudinal 24-Month Comparison of Maintainers, Relapsers, and Nonchangers.

This study examined longitudinal differences in use of transtheoretical model (TTM) behavior change constructs in maintainers (who reached and maintained exercise guidelines), relapsers (who reached guidelines, then regressed), and nonchangers (who did not reach guidelines). Data from two population-based TTM-tailored randomized trial intervention groups targeting exercise behavior (N = 1050) were pooled, and analyses assessed differences in TTM constructs between the three groups at baseline, 12 months, and 24 months. Findings indicated that relapsers tended to use TTM variables similarly to maintainers with the exception of self-efficacy, consciousness raising, and most behavioral processes of change, at 24 months. Nonchangers, however, used all TTM variables less than maintainers at nearly every time point. Findings suggest that relapsers remain more active than nonchangers in terms of use of change processes. Poor response to interventions (nonchangers) may be predicted by low baseline engagement in change processes. Although relapsers reverted to physical inactivity, their overall greater use of TTM constructs suggests that their efforts to change remain better than those of the stable nonchanger group. Future research can focus on treatment engagement strategies to help the stable nonchangers initiate change and to help relapsers to maintain treatment gains.

Perceived loneliness and social support in bipolar disorder: relation to suicidal ideation and attempts.

BACKGROUND: The suicide rate in bipolar disorder (BD) is among the highest across all psychiatric disorders. Identifying modifiable variables that relate to suicidal thoughts and behaviors (STBs) in BD may inform prevention strategies. Social connectedness is a modifiable variable found to relate to STBs in the general population, but differences exist across subgroups of the general population and findings specifically in BD have been equivocal. We aimed to clarify how perceived social connectedness relates to STBs in BD. METHOD: 146 adults (86 BD, 60 healthy controls) completed clinical interviews (Hamilton Depression Rating Scale; Structured Clinical Interview for DSM-5) and self-report measures of loneliness (UCLA Loneliness Scale) and social support (Interpersonal Support Evaluation List). Analyses explored differences in indicators of social connectedness (loneliness and social support) between BD participants and healthy controls, and explored relationships between STBs (lifetime suicide attempts and current suicidal ideation) and indicators of social connectedness in BD participants. RESULTS: BD participants reported significantly higher loneliness and lower social support than healthy controls. In BD participants, perceived social support was significantly related to both ever having attempted suicide and number of lifetime attempts. Interestingly, perceived loneliness, but not social support, was significantly associated with current suicidal ideation. CONCLUSIONS: Findings expand the evidence base supporting a relationship between perceived social connectedness and STBs in BD. They suggest that this modifiable variable could be a fruitful treatment target for preventing STBs in BD.

Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research.

Background: Mental illness remains a major global health challenge largely due to the absence of definitive biomarkers applicable to diagnostics and care processes. Although remote sensing technologies, embedded in devices such as smartphones and wearables, offer a promising avenue for improved mental health assessments, their clinical integration has been slow. Objective: This scoping review, following preferred reporting items for systematic reviews and meta-analyses guidelines, explores validation studies of remote sensing in clinical mental health populations, aiming to identify critical factors for clinical translation. Methods: Comprehensive searches were conducted in six databases. The analysis, using narrative synthesis, examined clinical and socio-demographic characteristics of the populations studied, sensing purposes, temporal considerations and reference mental health assessments used for validation. Results: The narrative synthesis of 50 included studies indicates that ten different sensor types have been studied for tracking and diagnosing mental illnesses, primarily focusing on physical activity and sleep patterns. There were many variations in the sensor methodologies used that may affect data quality and participant burden. Observation durations, and thus data resolution, varied by patient diagnosis. Currently, reference assessments predominantly rely on deficit focussed self-reports, and socio-demographic information is underreported, therefore representativeness of the general population is uncertain. Conclusion: To fully harness the potential of remote sensing in mental health, issues such as reliance on self-reported assessments, and lack of socio-demographic context pertaining to generalizability need to be addressed. Striking a balance between resolution, data quality, and participant burden whilst clearly reporting limitations, will ensure effective technology use. The scant reporting on participants' socio-demographic data suggests a knowledge gap in understanding the effectiveness of passive sensing techniques in disadvantaged populations.

Mental health provider perspectives on a mobile health application to support remote measurement-based care: Challenges and impacts.

Measurement-based care (MBC) comprises collecting patient-reported outcomes data using validated assessments and using that information to support treatment. The Veterans Health Administration (VHA) has developed technology platforms to support MBC, including the Mental Health Checkup (MHC) mobile health application (app). Our objective was to examine VHA mental health provider perspectives on the MHC app. We completed a mixed-methods, sequential explanatory evaluation of MHC. We surveyed 284 VHA mental health providers who used MHC, then conducted semistructured telephone interviews with a purposefully selected subset of survey respondents (n = 20). Approximately half of survey respondents agreed that MHC allowed them to collect assessment data from veterans more frequently than before (51%) and that they more frequently discussed assessment results with veterans because of MHC (50%) and used those results to inform goal-setting discussions (50%) and treatment decision making (51%). Bivariate analyses indicated a positive relationship between frequency of MHC use and the aforementioned impacts on care. Interview data conveyed both advantages (e.g., increased treatment efficiency, improved treatment decision making) and challenges (e.g., limited assessment availability, difficulties engaging veterans in completing assessments through the app) to using MHC. This evaluation demonstrated how MHC supported providers working to implement MBC. The app enhanced their ability to reach and engage veterans and incorporate assessment data into clinical encounters. Still, many did not perceive that MHC was impactful on mental health care delivery; given that providers who used MHC more frequently reported more positive impressions of MHC, this may be related to how frequently they used the app. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward.

Purpose of the review: Digital mental health interventions (DMHIs) are an effective and accessible means of addressing the unprecedented levels of mental illness worldwide. Currently, however, patient engagement with DMHIs in real-world settings is often insufficient to see clinical benefit. In order to realize the potential of DMHIs, there is a need to better understand what drives patient engagement. Recent findings: We discuss takeaways from the existing literature related to patient engagement with DMHIs and highlight gaps to be addressed through further research. Findings suggest that engagement is influenced by patient-, intervention- and systems-level factors. At the patient-level, variables such as sex, education, personality traits, race, ethnicity, age and symptom severity appear to be associated with engagement. At the intervention-level, integrating human support, gamification, financial incentives and persuasive technology features may improve engagement. Finally, although systems-level factors have not been widely explored, the existing evidence suggests that achieving engagement will require addressing organizational and social barriers and drawing on the field of implementation science. Summary: Future research clarifying the patient-, intervention- and systems-level factors that drive engagement will be essential. Additionally, to facilitate improved understanding of DMHI engagement, we propose the following: (a) widespread adoption of a minimum necessary 5-element engagement reporting framework; (b) broader application of alternative clinical trial designs; and (c) directed efforts to build upon an initial parsimonious conceptual model of DMHI engagement.

Modafinil's effects on cognition and sleep quality in affectively-stable patients with bipolar disorder: a pilot study.

Introduction: Despite advances in the treatment of bipolar disorder (BD), most patients do not achieve complete inter-episode recovery and functional disability is common. During periods of relative remission, many patients continue to experience neurocognitive dysfunction, reduced daytime activity levels, and sleep disturbances. This 8-week, randomized, placebo-controlled pilot study evaluated the feasibility, safety and preliminary efficacy of the wake-promoting drug, modafinil (Provigil®), on neurocognitive functioning, daytime sleepiness, and sleep quality in affectively-stable BD patients. Methods: Twelve individuals with affectively-stable BD were recruited and randomized to a flexible dose of modafinil (100 to 200 mg/day) or placebo, adjunctive to a therapeutic dose of a mood stabilizer. Weekly in-person visits tracked sleep quality and daytime sleepiness as well as side effects and mood symptoms. Neurocognitive functioning was assessed at baseline, week 4, and week 8. Results: No serious adverse events were reported. Newly emergent side effects in the modafinil group included heart palpitations, itching, fatigue, and decreased energy. Two patients discontinued modafinil owing to side effects and one of these patients withdrew from the study. One patient discontinued placebo and was withdrawn from the study. Preliminary evaluations of clinical efficacy showed a marginally significant interaction between treatment group and time in two cognitive domains (speed of processing and verbal learning), indicating greater improvement in the modafinil group versus placebo. Additionally, there was a marginally significant effect of treatment group on daytime sleepiness, suggesting lower daytime sleepiness in the modafinil group versus placebo. Counterintuitively, we found a significant treatment group by time interaction effect on sleep quality, suggesting greater improvement in sleep quality in the placebo group versus the modafinil group. Discussion: Results suggest that modafinil is a relatively safe medication for affectively-stable BD patients when given with adjunctive mood stabilizers. Results are suggestive of cognitive benefit and improved daytime sleepiness, but worse sleep quality in those patients prescribed modafinil. A fully powered clinical trial is warranted with specific attention to the characteristics of patients who are most likely to benefit from treatment with modafinil and other methodological lessons learned from this pilot. Clinical trial registration: ClinicalTrials.gov, identifier NCT01965925.

Innovative Technologies in CNS Trials: Promises and Pitfalls for Recruitment, Retention, and Representativeness.

Objective: Recruitment of a sufficiently large and representative patient sample and its retention during central nervous system (CNS) trials presents major challenges for study sponsors. Technological advances are reshaping clinical trial operations to meet these challenges, and the COVID-19 pandemic further accelerated this development. Method of Research: The International Society for CNS Clinical Trials and Methodology (ISCTM; www.isctm.org) Innovative Technologies for CNS Trials Working Group surveyed the state of technological innovations for improved recruitment and retention and assessed their promises and pitfalls. Results: Online advertisement and electronic patient registries can enhance recruitment, but challenges with sample representativeness, conversion rates from eligible prescreening to enrolled patients, data privacy and security, and patient identification remain hurdles for optimal use of these technologies. Electronic medical records (EMR) mining with artificial intelligence (AI)/machine learning (ML) methods is promising but awaits translation into trials. During the study treatment phase, technological innovations increasingly support participant retention, including adherence with the investigational treatment. Digital tools for adherence and retention support take many forms, including patient-centric communication channels between researchers and participants, real-time study reminders, and digital behavioral interventions to increase study compliance. However, such tools add technical complexities to trials, and their impact on the generalizability of results are largely unknown. Conclusion: Overall, the group found a scarcity of systematic data directly assessing the impact of technological innovations on study recruitment and retention in CNS trials, even for strategies with already high adoption, such as online recruitment. Given the added complexity and costs associated with most technological innovations, such data is needed to fully harness technologies for CNS trials and drive further adoption.

Treated individuals who progress to action or maintenance for one behavior are more likely to make similar progress on another behavior: coaction results of a pooled data analysis of three trials.

OBJECTIVE: This study compared, in treatment and control groups, the phenomena of coaction, which is the probability that taking effective action on one behavior is related to taking effective action on a second behavior. METHODS: Pooled data from three randomized trials of Transtheoretical Model (TTM) tailored interventions (n=9461), completed in the U.S. in 1999, were analyzed to assess coaction in three behavior pairs (diet and sun protection, diet and smoking, and sun protection and smoking). Odds ratios (ORs) compared the likelihood of taking action on a second behavior compared to taking action on only one behavior. RESULTS: Across behavior pairs, at 12 and 24 months, the ORs for the treatment group were greater on an absolute basis than for the control group, with two being significant. The combined ORs at 12 and 24 months, respectively, were 1.63 and 1.85 for treatment and 1.20 and 1.10 for control. CONCLUSIONS: The results of this study with addictive, energy balance and appearance-related behaviors were consistent with results found in three studies applying TTM tailoring to energy balance behaviors. Across studies, there was more coaction within the treatment group. Future research should identify predictors of coaction in more multiple behavior change interventions.

Provider perspectives on telemental health implementation: Lessons learned during the COVID-19 pandemic and paths forward.

After years of slow and fragmented implementation of telemental health (TMH), the coronavirus disease (COVID-19) pandemic necessitated widespread adoption. With the initial state of public health emergency behind us, we are at a decision point on whether to continue with TMH or return to a largely in-person care model. In this qualitative study, we investigated clinicians' perspectives on advantages and disadvantages of TMH in outpatient mental healthcare as well as considerations for future implementation. We conducted 29 semistructured interviews with outpatient mental health providers. Data were analyzed using rapid qualitative analysis methodology. Advantages included increased utilization of services, improved therapeutic processes, and improved provider wellbeing. Providers, however, also noted that TMH has some disadvantages in terms of therapeutic processes and provider wellbeing, and they reported technology issues as an additional disadvantage. Overall providers reported they can provide high quality care via TMH, but indicated some patient populations and appointment types are a better fit for in-person services. Most providers preferred a hybrid model of care moving forward with reimbursement discrepancies and out-of-state licensure restrictions as barriers. They indicated that, as TMH becomes a mainstay in psychiatric care, training and professional guidelines will be important. Continued implementation of TMH alongside in-person care is likely to offer improved access and enhanced service quality when applied to the right patient populations and appointment types. Effective implementation may require policy and systems level support on equitable reimbursement rates, out-of-state licensure restrictions and professional guidelines for delivering TMH. (PsycInfo Database Record (c) 2022 APA, all rights reserved).