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BACKGROUND: Digital Mental Health (DMH) tools are an effective, readily accessible, and affordable form of mental health support. However, sustained engagement with DMH is suboptimal, with limited research on DMH engagement. The Health Action Process Approach (HAPA) is an empirically supported theory of health behavior adoption and maintenance. Whether this model also explains DMH tool engagement remains unknown. OBJECTIVE: This study examined whether an adapted HAPA model predicted engagement with DMH via a self-guided website. METHODS: Visitors to the Mental Health America (MHA) website were invited to complete a brief survey measuring HAPA constructs. This cross-sectional study tested the adapted HAPA model with data collected using voluntary response sampling from 16,078 sessions (15,619 unique IP addresses from United States residents) on the MHA website from October 2021 through February 2022. Model fit was examined via structural equation modeling in predicting two engagement outcomes: (1) choice to engage with DMH (ie, spending 3 or more seconds on an MHA page, excluding screening pages) and (2) level of engagement (ie, time spent on MHA pages and number of pages visited, both excluding screening pages). RESULTS: Participants chose to engage with the MHA website in 94.3% (15,161/16,078) of the sessions. Perceived need (ß=.66; P<.001), outcome expectancies (ß=.49; P<.001), self-efficacy (ß=.44; P<.001), and perceived risk (ß=.17-.18; P<.001) significantly predicted intention, and intention (ß=.77; P<.001) significantly predicted planning. Planning was not significantly associated with choice to engage (ß=.03; P=.18). Within participants who chose to engage, the association between planning with level of engagement was statistically significant (ß=.12; P<.001). Model fit indices for both engagement outcomes were poor, with the adapted HAPA model accounting for only 0.1% and 1.4% of the variance in choice to engage and level of engagement, respectively. CONCLUSIONS: Our data suggest that the HAPA model did not predict engagement with DMH via a self-guided website. More research is needed to identify appropriate theoretical frameworks and practical strategies (eg, digital design) to optimize DMH tool engagement.
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Internet , Humanos , Estudios Transversales , Masculino , Femenino , Adulto , Persona de Mediana Edad , Estados Unidos , Encuestas y Cuestionarios , Salud Mental , Conductas Relacionadas con la SaludRESUMEN
OBJECTIVE: The authors compared the engagement, clinical outcomes, and adverse events of text or voice message-based psychotherapy (MBP) versus videoconferencing-based psychotherapy (VCP) among adults with depression. METHODS: The study used a sequential multiple-assignment randomized trial design with data drawn from phase 1 of a two-phase small business innovation research study. In total, 215 adults (ages ≥18 years) with depression received care from Talkspace, a digital mental health care company. Participants were initially randomly assigned to receive either asynchronous MBP or weekly VCP. All therapists provided evidence-based treatments such as cognitive-behavioral therapy. After 6 weeks of treatment, participants whose condition did not show a response on the Patient Health Questionnaire-9 or was rated as having not improved on the Clinical Global Impressions scale were randomly reassigned to receive either weekly VCP plus MBP or monthly VCP plus MBP. Longitudinal mixed-effects models with piecewise linear time trends applied to multiple imputed data sets were used to address missingness of data. RESULTS: Participants who were initially assigned to the MBP condition engaged with their therapists over more weeks than did participants in the VCP condition (7.8 weeks for MBP vs. 4.9 weeks for VCP; p<0.001). No meaningful differences were observed between the two groups in rates of change by 6 or 12 weeks for depression, anxiety, disability, or global ratings of improvement. Neither treatment resulted in any adverse events. CONCLUSIONS: MBP appears to be a viable alternative to VCP for treating adults with depression.
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BACKGROUND: Intervention adaptation is often necessary to improve the fit between evidence-based practices/programs and implementation contexts. Existing frameworks describe intervention adaptation processes but do not provide detailed steps for prospectively designing adaptations, are designed for researchers, and require substantial time and resources to complete. A pragmatic approach to guide implementers through developing and assessing adaptations in local contexts is needed. The goal of this project was to develop Making Optimal Decisions for Intervention Flexibility during Implementation (MODIFI), a method for intervention adaptation that leverages human centered design methods and is tailored to the needs of intervention implementers working in applied settings with limited time and resources. METHOD: MODIFI was iteratively developed via a mixed-methods modified Delphi process. Feedback was collected from 43 implementation research and practice experts. Two rounds of data collection gathered quantitative ratings of acceptability and inclusion (Round 1) and feasibility (Round 2), as well as qualitative feedback regarding MODIFI revisions analyzed using conventional content analysis. RESULTS: In Round 1, most participants rated all proposed components as essential but identified important avenues for revision which were incorporated into MODIFI prior to Round 2. Round 2 emphasized feasibility, where ratings were generally high and fewer substantive revisions were recommended. Round 2 changes largely surrounded operationalization of terms/processes and sequencing of content. Results include a detailed presentation of the final version of the three-step MODIFI method (Step 1: Learn about the users, local context, and intervention; Step 2: Adapt the intervention; Step 3: Evaluate the adaptation) along with a case example of its application. DISCUSSION: MODIFI is a pragmatic method that was developed to extend the contributions of other research-based adaptation theories, models, and frameworks while integrating methods that are tailored to the needs of intervention implementers. Guiding teams to tailor evidence-based interventions to their local context may extend for whom, where, and under what conditions an intervention can be effective.
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Background: Implementation strategies are theorized to work well when carefully matched to implementation determinants and when factors-preconditions, moderators, etc.-that influence strategy effectiveness are prospectively identified and addressed. Existing methods for strategy selection are either imprecise or require significant technical expertise and resources, undermining their utility. This article outlines refinements to causal pathway diagrams (CPDs), a method for articulating the causal process through which implementation strategies work and offers illustrations of their use. Method: CPDs are a visualization tool to represent an implementation strategy, its mechanism(s) (i.e., the processes through which a strategy is thought to operate), determinants it is intended to address, factors that may impede or facilitate its effectiveness, and the series of outcomes that should be expected if the strategy is operating as intended. We offer principles for constructing CPDs and describe their key functions. Results: Applications of the CPD method by study teams from two National Institute of Health-funded Implementation Science Centers and a research grant are presented. These include the use of CPDs to (a) match implementation strategies to determinants, (b) understand the conditions under which an implementation strategy works, and (c) develop causal theories of implementation strategies. Conclusions: CPDs offer a novel method for implementers to select, understand, and improve the effectiveness of implementation strategies. They make explicit theoretical assumptions about strategy operation while supporting practical planning. Early applications have led to method refinements and guidance for the field.
Advances to the Causal Pathway Diagramming Method to Enhance Implementation Precision Plain Language Summary Implementation strategies often fail to produce meaningful improvements in the outcomes we hope to impact. Better tools for choosing, designing, and evaluating implementation strategies may improve their performance. We developed a tool, causal pathway diagrams (CPD), to visualize and describe how implementation strategies are expected to work. In this article, we describe refinements to the CPD tool and accompanying approach. We use real illustrations to show how CPDs can be used to improve how to match strategies to barriers, understand the conditions in which those strategies work best, and develop generalizable theories describing how implementation strategies work. CPDs can serve as both a practical and scientific tool to improve the planning, deployment, and evaluation of implementation strategies. We demonstrate the range of ways that CPDs are being used, from a highly practical tool to improve implementation practice to a scientific approach to advance testing and theorizing about implementation strategies.
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BACKGROUND: For approximately one in five children who have social, emotional, and behavioral (SEB) challenges, accessible evidence-based prevention practices (EBPPs) are critical. In the USA, schools are the primary setting for children's SEB service delivery. Still, EBPPs are rarely adopted and implemented by front-line educators (e.g., teachers) with sufficient fidelity to see effects. Given that individual behavior change is ultimately required for successful implementation, focusing on individual-level processes holds promise as a parsimonious approach to enhance impact. Beliefs and Attitudes for Successful Implementation in Schools for Teachers (BASIS-T) is a pragmatic, multifaceted pre-implementation strategy targeting volitional and motivational mechanisms of educators' behavior change to enhance implementation and student SEB outcomes. This study protocol describes a hybrid type 3 effectiveness-implementation trial designed to evaluate the main effects, mediators, and moderators of the BASIS-T implementation strategy as applied to Positive Greetings at the Door, a universal school-based EBPP previously demonstrated to reduce student disruptive behavior and increase academic engagement. METHODS: This project uses a blocked randomized cohort design with an active comparison control (ACC) condition. We will recruit and include approximately 276 teachers from 46 schools randomly assigned to BASIS-T or ACC conditions. Aim 1 will evaluate the main effects of BASIS-T on proximal implementation mechanisms (attitudes, subjective norms, self-efficacy, intentions to implement, and maintenance self-efficacy), implementation outcomes (adoption, reach, fidelity, and sustainment), and child outcomes (SEB, attendance, discipline, achievement). Aim 2 will examine how, for whom, under what conditions, and how efficiently BASIS-T works, specifically by testing whether the effects of BASIS-T on child outcomes are (a) mediated via its putative mechanisms of behavior change, (b) moderated by teacher factors or school contextual factors, and (c) cost-effective. DISCUSSION: This study will provide a rigorous test of BASIS-T-a pragmatic, theory-driven, and generalizable implementation strategy designed to target theoretically-derived motivational mechanisms-to increase the yield of standard EBPP training and support strategies. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT05989568. Registered on May 30, 2023.
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Motivación , Autoeficacia , Niño , Humanos , Emociones , Estudiantes , Instituciones Académicas , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
Exposure is an important element of treatment for many evidence-based treatments but can be challenging to implement. Supervision strategies to support exposure delivery may be an important tool to facilitate the use of exposure techniques; however, they must be considered and used in the context of the supervisory alliance. The present study examined relations between supervisory alliance and fidelity to the trauma narrative (TN; i.e., imaginal exposure) component of Trauma-Focused Cognitive Behavioral Therapy. We also examined how supervisory alliance moderated the effect of behavioral rehearsal use in supervision on TN fidelity. We analyzed data from a randomized controlled trial, in which forty-two supervisors and their clinicians (N = 124) from 28 Washington State community-based mental health offices participated. Clinicians were randomized to receive one of two supervision conditions-symptom and fidelity monitoring (SFM) or SFM with behavioral rehearsal (SFM + BR). Supervisory alliance alone did not predict delivery (i.e., occurrence) or extensiveness of delivery of the trauma narrative. Client-focused supervisory alliance moderated the effectiveness of behavioral rehearsal-as client-focused alliance increased, the odds of delivering the TN also increased significantly. Future research should further investigate how to appropriately match supervision techniques with supervisory dyads and explore the interplay of alliance with supervision techniques a supervisor might employ.
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Terapia Cognitivo-Conductual , Humanos , Terapia Cognitivo-Conductual/métodos , Aprendizaje , WashingtónRESUMEN
Background: Intervention adaptation is often necessary to improve the fit between evidence-based practices/programs and implementation contexts. Existing frameworks describe intervention adaptation processes but do not provide detailed steps for prospectively designing adaptations, are designed for researchers, and require substantial time and resources to complete. A pragmatic approach to guide implementers through developing and assessing adaptations in local contexts is needed. The goal of this project was to develop Making Optimal Decisions for Intervention Flexibility during Implementation (MODIFI), a method for intervention adaptation that leverages human centered design methods and is tailored to the needs of intervention implementers working in applied settings with limited time and resources. Method: MODIFI was iteratively developed via a mixed-methods modified Delphi process. Feedback was collected from 43 implementation research and practice experts. Two rounds of data collection gathered quantitative ratings of acceptability (Round 1) and feasibility (Round 2), as well as qualitative feedback regarding MODIFI revisions analyzed using conventional content analysis. Results: In Round 1, most participants rated all proposed components as essential but identified important avenues for revision which were incorporated into MODIFI prior to Round 2. Round 2 emphasized feasibility, where ratings were generally high and fewer substantive revisions were recommended. Round 2 changes largely surrounded operationalization of terms/processes and sequencing of content. Results include a detailed presentation of the final version of the three-step MODIFI method (Step 1: Learn about the users, local context, and intervention; Step 2: Adapt the intervention; Step 3: Evaluate the adaptation) along with a case example of its application. Discussion: MODIFI is a pragmatic method that was developed to extend the contributions of other research-based adaptation theories, models, and frameworks while integrating methods that are tailored to the needs of intervention implementers. Guiding teams to tailor evidence-based interventions to their local context may extend for whom, where, and under what conditions an intervention can be effective.
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BACKGROUND: For youth receiving care in community mental health centers, comorbidities are the rule rather than the exception. Using measurement-based care (MBC), or the routine evaluation of symptoms to inform care decisions, as the foundation of treatment for youth with comorbid problems significantly improves the impact of psychotherapy by focusing care and building engagement and alliance. MBC increases the rate of symptom improvement, detects clients who would otherwise deteriorate, and alerts clinicians to non-responders. Despite its demonstrated utility, MBC is rarely implemented with fidelity; less than 15% of providers report using MBC per recommendations. Previous efforts to support MBC implementation have yielded suboptimal outcomes, in part, due to organizations' challenges with identifying and prioritizing barriers and selecting and developing strategies to overcome them. New methods are needed for identifying and prioritizing barriers, and matching strategies to barriers to optimize MBC implementation and treatment quality to improve youth mental health outcomes in community settings. METHODS: Pragmatic implementation methods will be piloted in four diverse community mental health centers. Methods include (a) rapid evidence synthesis; (b) rapid ethnography; (c) design kits (e.g., kits with disposable cameras, journals, maps); (d) barrier prioritization, and (e) causal pathway diagramming. These activities will generate actionable barriers; subsequently, we will use facilitated group processes to prioritize barriers and develop causal pathway diagrams to match strategies to barriers to create implementation plans that optimize MBC fidelity (Aim 1). We will track strategy deployment for 6 months, then compare MBC fidelity for another 6 months post-implementation with data from 2 years of historical controls (Aim 2). Finally, we will co-design a toolkit for design kit methods with youth and the practice and scientific communities (Aim 3). DISCUSSION: Optimizing MBC implementation in community mental health centers could transform youth mental health care by ensuring the most pressing symptoms are targeted early in treatment. The discussion section highlights expected challenges and limits to using the five methods, including recruitment and engagement given the high pressure on community mental health settings. TRIAL REGISTRATION: Clinicaltrials.gov. NCT05644756 . Registered on 18 November 2022. This trial was retrospectively registered.
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BACKGROUND: Digital mental health interventions, such as 2-way and asynchronous messaging therapy, are a growing part of the mental health care treatment ecosystem, yet little is known about how users engage with these interventions over the course of their treatment journeys. User engagement, or client behaviors and therapeutic relationships that facilitate positive treatment outcomes, is a necessary condition for the effectiveness of any digital treatment. Developing a better understanding of the factors that impact user engagement can impact the overall effectiveness of digital psychotherapy. Mapping the user experience in digital therapy may be facilitated by integrating theories from several fields. Specifically, health science's Health Action Process Approach and human-computer interaction's Lived Informatics Model may be usefully synthesized with relational constructs from psychotherapy process-outcome research to identify the determinants of engagement in digital messaging therapy. OBJECTIVE: This study aims to capture insights into digital therapy users' engagement patterns through a qualitative analysis of focus group sessions. We aimed to synthesize emergent intrapersonal and relational determinants of engagement into an integrative framework of engagement in digital therapy. METHODS: A total of 24 focus group participants were recruited to participate in 1 of 5 synchronous focus group sessions held between October and November 2021. Participant responses were coded by 2 researchers using thematic analysis. RESULTS: Coders identified 10 relevant constructs and 24 subconstructs that can collectively account for users' engagement and experience trajectories in the context of digital therapy. Although users' engagement trajectories in digital therapy varied widely, they were principally informed by intrapsychic factors (eg, self-efficacy and outcome expectancy), interpersonal factors (eg, the therapeutic alliance and its rupture), and external factors (eg, treatment costs and social support). These constructs were organized into a proposed Integrative Engagement Model of Digital Psychotherapy. Notably, every participant in the focus groups indicated that their ability to connect with their therapist was among the most important factors that were considered in continuing or terminating treatment. CONCLUSIONS: Engagement in messaging therapy may be usefully approached through an interdisciplinary lens, linking constructs from health science, human-computer interaction studies, and clinical science in an integrative engagement framework. Taken together, our results suggest that users may not view the digital psychotherapy platform itself as a treatment so much as a means of gaining access to a helping provider, that is, users did not see themselves as engaging with a platform but instead viewed their experience as a healing relationship. The findings of this study suggest that a better understanding of user engagement is crucial for enhancing the effectiveness of digital mental health interventions, and future research should continue to explore the underlying factors that contribute to engagement in digital mental health interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04507360; https://clinicaltrials.gov/ct2/show/NCT04507360.
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Schools offer an advantageous setting for the prevention, early identification, and treatment of mental health problems for youth. However, school mental health (SMH) services are typically not based on evidence for effectiveness, nor are they efficiently delivered, with SMH practitioners (SMHPs) able to only treat a small number of students in need. The current study evaluated the feasibility, acceptability, efficiency, and outcomes of a four-session assessment, engagement, problem-solving, and triage strategy for SMHPs that aimed to improve efficiency while being based on elements of evidence-based care. The study, conducted in 15 US school districts in three states, used stratified random assignment to assign 49 high schools and their participating SMHP(s) to either the Brief Intervention for School Clinicians (BRISC; N = 259 students) or services as usual (SAU; N = 198 students). SMHPs implemented BRISC elements with adequate to excellent fidelity and reported the strategy was feasible and well-aligned with presenting problems. Students assigned to BRISC reported significantly greater engagement in SMH at 2 months and completion of SMH treatment by 6 months. BRISC-assigned SMHPs reported significantly greater treatment completion after four sessions (53.4%) compared to SAU (15.4%). Students in the BRISC condition also reported significantly greater reduction in problem severity as evaluated by the Youth Top Problems Assessment. No differences were found for anxiety or depression symptoms or overall functioning. Results indicate that BRISC is a feasible early intervention and triage strategy that may aid in more efficient provision of SMH services with no compromise to SMH effectiveness.
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Ansiedad , Triaje , Adolescente , Humanos , Solución de Problemas , Medición de Riesgo , EstudiantesRESUMEN
There has been a call to shift from treating theories as static products to engaging in a process of theorizing that develops, modifies, and advances implementation theory through the accumulation of knowledge. Stimulating theoretical advances is necessary to improve our understanding of the causal processes that influence implementation and to enhance the value of existing theory. We argue that a primary reason that existing theory has lacked iteration and evolution is that the process for theorizing is obscure and daunting. We present recommendations for advancing the process of theorizing in implementation science to draw more people in the process of developing and advancing theory.
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Group-based didactic training is a cornerstone implementation strategy used to support the adoption and delivery of evidence-based prevention programs (EBPP) by teachers in schools, but it is often insufficient to drive successful implementation. Beliefs and Attitudes for Successful Implementation in Schools for Teachers (BASIS-T) is a theory-based, motivational implementation strategy designed to increase the yield of EBPP training and consultation. The purpose of this study was to examine the longitudinal effects of BASIS-T on hypothesized mechanisms of behavior change (e.g., attitudes toward EBPP, self-efficacy, intentions to implement) and implementation and student outcomes associated with a well-established universal prevention program-the good behavior game (GBG). This pilot trial included 82 elementary school teachers from nine public elementary schools who were randomly assigned at the school-level to the BASIS-T (n = 43) or active comparison (n = 39) condition, with both conditions receiving training and consultation of the good behavior game by a third-party purveyor. Analyses included mixed-effects and multilevel growth modeling of adoption, mechanisms of behavior change, and student behavior outcomes. Meaningful effects were found favoring BASIS-T on immediate adoption of the GBG within the first month of school (74% vs. 40%) and self-efficacy (p < 0.05). These findings advance our understanding of the type of implementation strategies that complement pre-implementation training and post-training consultation in schools by identifying the importance of task self-efficacy as a mechanism of behavior change related to adoption for prevention programming. Supplementary Information: The online version contains supplementary material available at 10.1007/s12310-022-09536-z.
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Background: Strategies to implement evidence-based interventions (EBIs) in children's mental health services have complex direct and indirect causal impacts on multiple outcomes. Ripple effects are outcomes caused by EBI implementation efforts that are unplanned, unanticipated, and/or more salient to stakeholders other than researchers and implementers. The purpose of the current paper is to provide a compilation of possible ripple effects associated with EBI implementation strategies in children's mental health services, to be used for implementation planning, research, and quality improvement. Methods: Participants were identified via expert nomination and snowball sampling. Online surveys were completed by 81 participants, each representing one of five roles: providers of mental health services to children or youth, researchers, policy makers, caregivers, and youth. A partially directed conventional content analysis with consensus decision making was used to code ripple effects. Results: Four hundred and four unique responses were coded into 66 ripple effects and 14 categories. Categories include general knowledge, skills, attitudes, and confidence about using EBIs; general job-related ripple effects; EBI treatment adherence, fidelity, and alignment; gaming the system; equity and stigma; shifting roles, role clarity, and task shifting; economic costs and benefits; EBI treatment availability, access, participation, attendance, barriers, and facilitators; clinical process and treatment quality; client engagement, therapeutic alliance, and client satisfaction; clinical organization structure, relationships in the organization, process, and functioning; youth client and caregiver outcomes; and use of EBI strategies and insights in one's own life. Conclusions: This research advances the field by providing children's mental health implementers, researchers, funders, policy makers, and consumers with a menu of potential ripple effects. It can be a practical tool to ensure compliance with guidance from Quality Improvement/Quality Assurance, Complexity Science, and Diffusion of Innovation Theory. Future phases will match potential ripple effects with salient children's mental health implementation strategies for each participant role.
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BACKGROUND: During the COVID-19 pandemic, the general public was concerned about the mental health impacts of unemployment due to COVID-19 and the stress essential workers experienced during this time. Several reports indicated that people in distress were turning to digital technology, but there was little evidence about the impact of these tools on mitigating distress. OBJECTIVE: This study seeks to determine the acceptability, feasibility, usability, and effectiveness of mobile mental health apps for decreasing mental health symptoms in essential workers and unemployed individuals with suicide risk. METHODS: We recruited participants who indicated that they were unemployed because of COVID-19 or were COVID-19-designated essential workers. Participants were randomized to 1 of 4 free commercial mobile apps for managing distress that were (1) highly rated by PsyberGuide and (2) met the criteria for intervention features these participants indicated were desirable in a previous survey. Participants used the apps for 4 weeks and completed baseline and 4-week self-assessments of depression, anxiety emotional regulation, and suicide risk. RESULTS: We found no differences between the apps in any outcome but did find significant changes in depression and anxiety over time (Patient Health Questionnaire [PHQ]-9: estimate=-1.5, SE 0.2, 95% CI -1.1 to -1.8, P<.001; Generalized Anxiety Disorder Scale [GAD]-7: estimate=-1.3, SE 0.2, 95% CI -1.0 to -1.6, P<.001). We found no significant changes in suicidal behavior (Suicide Behaviors Questionnaire-Revised [SBQ-R]) or emotional regulation (Difficulties in Emotion Regulation Scale - Short Form [DERS-SF]) for the 4 weeks. We did find a significant dose-response pattern for changes in depression and anxiety. Using the app at least once a week resulted in greater improvements in treatment conditions over time on depression (estimate=-0.6, SE 0.2, 95% CI 1.0-0.2, P=.003) and anxiety (estimate=0.1, SE 0.2, 95% CI 0.4-0.6, P=.78). There was no association between app frequency and changes in suicidal behavior (SBQ-R) or emotional regulation (DERS-SF). We further found a significant difference between the conditions with regard to app usability, with the control app being the most usable (meanBeautiful Mood 72.9, SD 16.7; meanCOVID Coach 71.2, SD 15.4; meanCalm 66.8, SD 17.3; mean7 Cups 65.2, SD 17.7). We found no significant differences for app acceptability or appropriateness. CONCLUSIONS: Few studies have evaluated prospectively the utility and usability of commercial apps for mood. This study found that free, self-guided commercial mobile mental health apps are seen as usable, but no one app is superior to the other. Although we found that regular use is indicated for effects on depression and anxiety to occur in those who are more symptomatic, regression to the mean cannot be ruled out. TRIAL REGISTRATION: ClinicalTrials.gov NCT04536935; https://tinyurl.com/mr36zx3s.
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COVID-19 , Aplicaciones Móviles , Humanos , Salud Mental , Desempleo , PandemiasRESUMEN
Numerous studies have found that long term retention is very low in remote clinical studies (>4 weeks) and to date there is limited information on the best methods to ensure retention. The ability to retain participants in the completion of key assessments periods is critical to all clinical research, and to date little is known as to what methods are best to encourage participant retention. To study incentive-based retention methods we randomized 215 US adults (18+ years) who agreed to participate in a sequential, multiple assignment randomized trial to either high monetary incentive (HMI, $125 USD) and combined low monetary incentive ($75 USD) plus alternative incentive (LMAI). Participants were asked to complete daily and weekly surveys for a total of 12 weeks, which included a tailoring assessment around week 5 to determine who should be stepped up and rerandomized to one of two augmentation conditions. Key assessment points were weeks 5 and 12. There was no difference in participant retention at week 5 (tailoring event), with approximately 75% of the sample completing the week-5 survey. By week 10, the HMI condition retained approximately 70% of the sample, compared to 60% of the LMAI group. By week 12, all differences were attenuated. Differences in completed measures were not significant between groups. At the end of the study, participants were asked the impressions of the incentive condition they were assigned and asked for suggestions for improving engagement. There were no significant differences between conditions on ratings of the fairness of compensation, study satisfaction, or study burden, but study burden, intrinsic motivation and incentive fairness did influence participation. Men were also more likely to drop out of the study than women. Qualitative analysis from both groups found the following engagement suggestions: desire for feedback on survey responses and an interest in automated sharing of individual survey responses with study therapists to assist in treatment. Participants in the LMAI arm indicated that the alternative incentives were engaging and motivating. In sum, while we were able to increase engagement above what is typical for such study, more research is needed to truly improve long term retention in remote trials.
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BACKGROUND: People often prefer evidence-based psychosocial interventions (EBPIs) for mental health care; however, these interventions frequently remain unavailable to people in nonspecialty or integrated settings, such as primary care and schools. Previous research has suggested that usability, a concept from human-centered design, could support an understanding of the barriers to and facilitators of the successful adoption of EBPIs and support the redesign of EBPIs and implementation strategies. OBJECTIVE: This study aimed to identify and categorize usability issues in EBPIs and their implementation strategies. METHODS: We adapted a usability issue analysis and reporting format from a human-centered design. A total of 13 projects supported by the National Institute of Mental Health-funded Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center at the University of Washington used this format to describe usability issues for EBPIs and implementation strategies with which they were working. Center researchers used iterative affinity diagramming and coding processes to identify usability issue categories. On the basis of these categories and the underlying issues, we propose heuristics for the design or redesign of EBPIs and implementation strategies. RESULTS: The 13 projects reported a total of 90 usability issues, which we categorized into 12 categories, including complex and/or cognitively overwhelming, required time exceeding available time, incompatibility with interventionist preference or practice, incompatibility with existing workflow, insufficient customization to clients/recipients, intervention buy-in (value), interventionist buy-in (trust), overreliance on technology, requires unavailable infrastructure, inadequate scaffolding for client/recipient, inadequate training and scaffolding for interventionists, and lack of support for necessary communication. These issues range from minor inconveniences that affect a few interventionists or recipients to severe issues that prevent all interventionists or recipients in a setting from completing part or all of the intervention. We propose 12 corresponding heuristics to guide EBPIs and implementation strategy designers in preventing and addressing these usability issues. CONCLUSIONS: Usability issues were prevalent in the studied EBPIs and implementation strategies. We recommend using the lens of usability evaluation to understand and address barriers to the effective use and reach of EBPIs and implementation strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14990.
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Trastornos Mentales , Intervención Psicosocial , Adolescente , Adulto , Humanos , Estados UnidosRESUMEN
BACKGROUND: Depression is a common psychiatric condition with an estimated lifetime prevalence for major depression of 16.6% in the US adult population and is effectively treated through psychotherapy. The widespread availability of the internet and personal devices such as smartphones are changing the landscape of delivery of psychotherapy; however, little is known about whether and for whom this type of therapy is beneficial, and whether having synchronous video-based sessions provides additional benefits to clients above and beyond messaging-based therapy. OBJECTIVE: This study examined the outcomes associated with the use of a digital platform (Talkspace) for technology-mediated psychotherapy. We examined the duration of client engagement in therapy and client depression score trajectories over 16 weeks. We explored the association of client characteristics, therapist characteristics, and service plan type with time-to-disengagement and trajectories of change in depression scores. METHODS: This naturalistic observational study assessed data collected routinely by the platform between January 2016 and January 2018 and examined psychotherapy outcomes among a large representative sample of adult clients with clinically significant depression. Treatment disengagement was defined as a lack of client-initiated communication for more than 4 weeks. Clients completed the Patient Health Questionnaire-8 item (PHQ-8) at intake and every 3 weeks via an in-app survey. Cox regression analysis was used to examine the time until and predictors of disengagement. Changes in depression scores and predictors of change over time were examined using mixed-effects regression. RESULTS: The study included 5890 clients and 1271 therapists. Client scores on the PHQ-8 declined over time, with the average client improving from a score of 15 to below the clinical cutoff of 10 by week 6. At the same time point, 37% of clients had disengaged from the therapy. When combined into a final Cox regression model, those who were more likely to disengage were clients aged 18 to 25 years versus those aged ≥50 years (odds ratio [OR] 0.82, 95% CI 0.74-0.9; P<.001), had higher education (OR 1.14, 95% CI 1.06-1.22; P<.001), had been in therapy before (OR 1.09, 95% CI 1.02-1.17; P=.01), and were living with a partner but unmarried versus single (OR 1.14, 95% CI 1.02-1.27; P=.02). Having a therapist with >10 years of experience was related to lower odds of disengagement (OR 0.87, 95% CI 0.8-0.94; P=.01). When combined into a final regression model predicting improvement in depression scores over time, clients showing more improvement were those with an associate's degree or higher (linear estimate=-0.07, P=.002) and higher intake PHQ-8 scores (estimate=3.73, P<.001). There were no differences based on the plan type. CONCLUSIONS: Our findings add to the growing literature showing the benefits of technology-mediated psychotherapy over a relatively brief period (16 weeks).
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Objective: Observational studies of practices used in clinical supervision-as-usual can be leveraged to advance the limited research on workplace-based supervision as an evidence-based treatment (EBT) implementation strategy. This exploratory observational study examined the presence of supervision approaches (comprised of supervision techniques) and whether these predicted clinicians' EBT technique delivery. Methods: Participants included 28 supervisors, 70 clinician supervisees, and 60 youth clients and guardians from 17 public mental health organizations. Data included audio recorded supervision-as-usual sessions over 1 year, audio recorded Trauma-focused Cognitive Behavioral Therapy (TF-CBT) treatment sessions with youth for 6 months, and youth-reported post-traumatic stress severity scores. Audio recordings of 438 supervision sessions were coded for session duration and the presence of 13 supervision techniques and intensity of their coverage. Audio recordings of 465 treatment sessions were coded for presence and intensity of coverage of TF-CBT practice elements. Agglomerative hierarchical cluster analysis examined the presence of clusters of supervision technique use, termed supervision approaches. Generalized estimating equations estimated the relation between supervision approaches and delivery of TF-CBT elements. Results: Two supervision approaches were identified- Supportive-Directive and Supportive- that discriminated between use of five supervision techniques. Clinicians who received a higher proportion of supportive-directive supervision sessions had greater odds of delivering the trauma narrative with a client. Conclusion: Findings suggest that patterns of supervision techniques can be identified and may shape EBT delivery. Supervision approaches show some evidence of being tailored to individual clinicians. Implications for the development of supervision implementation strategies and future directions are discussed.
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INTRODUCTION: Digital mental health tools have become popular alternatives to traditional psychotherapy. One emerging form of digital mental health is message-based care, the use of text messages or asynchronous voice or video messaging to provide psychotherapy. There has been no research into whether this is an effective method of psychotherapy as a stand-alone treatment or in combination with traditional psychotherapy. METHODS AND ANALYSIS: This is a sequential, multiple assignment randomised trial to compare message-based care, videoconference-psychotherapy and a combination of the two treatments in 1000 depressed adults. Participants will be recruited through Talkspace, a digital mental health company, and randomised to receive 6 weeks of either message-based care only or videoconference-psychotherapy only. At 6 weeks, participants will be evaluated for their response to treatment. Those with a 50% or more response to treatment will continue with their assigned condition. Those who do not respond will be randomised to either monthly videoconference-psychotherapy or weekly videoconference-psychotherapy plus message-based care. Primary outcomes will be depression and social functioning. We will also explore moderators of treatment outcome. ETHICS AND DISSEMINATION: The study received ethics approval from the University of Washington Institutional Review Board. Results of this study will be presented in peer-reviewed journals and at professional conferences. TRIAL REGISTRATION NUMBER: NCT04513080; Pre-results.
Asunto(s)
Telemedicina , Envío de Mensajes de Texto , Adulto , Depresión/terapia , Humanos , Salud Mental , Psicoterapia , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
BACKGROUND: Behavioral activation (BA) is rooted in the behavioral theory of depression, which states that increased exposure to meaningful, rewarding activities is a critical factor in the treatment of depression. Assessing constructs relevant to BA currently requires the administration of standardized instruments, such as the Behavioral Activation for Depression Scale (BADS), which places a burden on patients and providers, among other potential limitations. Previous work has shown that depressed and nondepressed individuals may use language differently and that automated tools can detect these differences. The increasing use of online, chat-based mental health counseling presents an unparalleled resource for automated longitudinal linguistic analysis of patients with depression, with the potential to illuminate the role of reward exposure in recovery. OBJECTIVE: This work investigated how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time. METHODS: Using distributional semantics methods applied to a large corpus of text-based online therapy sessions, we devised a set of novel BA-related categories for the Linguistic Inquiry and Word Count (LIWC) software package. We then analyzed the language used by 10,000 patients in online therapy chat logs for indicators of activation and other depression-related markers using LIWC. RESULTS: Despite their conceptual and operational differences, both previously established LIWC markers of depression and our novel linguistic indicators of activation were strongly associated with depression scores (Patient Health Questionnaire [PHQ]-9) and longitudinal patient trajectories. Emotional tone; pronoun rates; words related to sadness, health, and biology; and BA-related LIWC categories appear to be complementary, explaining more of the variance in the PHQ score together than they do independently. CONCLUSIONS: This study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support.