Dataset Information

Coach-Supported Versus Self-guided Digital Training Course for a Problem-solving Psychological Intervention for Nonspecialists: Protocol for a Pre-Post Nested Randomized Controlled Trial.

ABSTRACT:

Background

Psychosocial interventions delivered by nonspecialists can be effective at reducing common adolescent mental health problems in low-resource settings. However, there is a lack of evidence on resource-efficient methods for building capacity to deliver these interventions.

Objective

The objective of this study is to evaluate the effects of a digital training (DT) course, delivered in a self-guided format or with coaching, on nonspecialists' competency to deliver a problem-solving intervention intended for adolescents with common mental health problems in India.

Methods

We will conduct a pre-post study with a nested parallel, 2-arm, individually randomized controlled trial. The study aims to recruit 262 participants, randomized 1:1 to receive either a self-guided DT course or a DT course with weekly individualized coaching provided remotely by telephone. In both arms, the DT will be accessed over 4 to 6 weeks. Participants will be nonspecialists (ie, without prior practice-based training in psychological therapies) recruited from among university students and affiliates of nongovernmental organizations in Delhi and Mumbai, India.

Results

Outcomes will be assessed at baseline and 6 weeks post randomization using a knowledge-based competency measure that incorporates a multiple-choice quiz format. The primary hypothesis is that self-guided DT will lead to increased competency scores among novices with no prior experience of delivering psychotherapies. The secondary hypothesis is that digital training with coaching will have an incremental effect on competency scores compared with DT alone. The first participant was enrolled on April 4, 2022.

Conclusions

The study will address an evidence gap on the effectiveness of training methods for nonspecialist providers of adolescent mental health interventions in low-resource settings. The findings from this study will be used to support wider efforts to scale up evidence-based mental health interventions for young people.

Trial registration

ClinicalTrials.gov NCT05290142; https://clinicaltrials.gov/ct2/show/NCT05290142.

International registered report identifier (irrid)

DERR1-10.2196/41981.

SUBMITTER: Mathur S

PROVIDER: S-EPMC10337372 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Coach-Supported Versus Self-guided Digital Training Course for a Problem-solving Psychological Intervention for Nonspecialists: Protocol for a Pre-Post Nested Randomized Controlled Trial.

Mathur Sonal S Weiss Helen A HA Neuman Melissa M Field Andy P AP Leurent Baptiste B Shetty Tejaswi T J James E JE Nair Pooja P Mathews Rhea R Malik Kanika K Michelson Daniel D Patel Vikram V

JMIR research protocols 20230613

<h4>Background</h4>Psychosocial interventions delivered by nonspecialists can be effective at reducing common adolescent mental health problems in low-resource settings. However, there is a lack of evidence on resource-efficient methods for building capacity to deliver these interventions.<h4>Objective</h4>The objective of this study is to evaluate the effects of a digital training (DT) course, delivered in a self-guided format or with coaching, on nonspecialists' competency to deliver a problem ...[more]

PMID: 37310781

Similar Datasets

Project description:BackgroundArtificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care-related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated.ObjectiveThis study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety.MethodsA total of 26 participants completed 2 therapy sessions-an introductory (session 1) and a problem-solving (session 2)-with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants' perspectives regarding Lumen use.ResultsParticipants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen's on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions.ConclusionsOn the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services.

Project description:BackgroundResources are spent worldwide on the development of digital platforms and their user interfaces (UIs) for digital mental health services (DMHS). However, studies investigating the potential benefits of different UIs for DMHS are currently lacking. To fill this knowledge gap, the aim of this study was to investigate differences in treatment engagement between two different UIs for DMHS.MethodsA total of 397 participants from the Swedish general public were randomized (1:1) to use a self-guided digital problem-solving intervention during one week, either with an optimized UI (N = 198), based on user experience (UX) design principles and with automated features, or a basic UI (N = 199), analogous with a UI used in Swedish regular health care comprising elementary UI features and less automation. Primary outcome measures were self-rated usability, on the System Usability Scale, and treatment credibility, on the Credibility/Expectancy Questionnaire. Secondary outcome measures included behavioral engagement with the intervention.FindingsThere were no significant differences between the UIs in ratings of usability or treatment credibility. However, participants who used the optimized UI were significantly more engaged with the intervention as measured by usage of the intervention at least once (odds ratio 2.54, 95% CI [1.67, 3.85]), total number of generated solutions (mean difference 1.41, 95% CI [0.72, 2.11]), and mean number of generated solutions per initiated problem-solving attempt (mean difference 1.45, 95% CI [1.06, 1.85]). Other findings included participants using the optimized UI rating the intervention as easier to understand, while feeling more overwhelmed, than those using the basic UI.InterpretationOur findings indicate that an optimized UI based on UX design principles, in comparison to a basic UI comprising elementary UI features, do not affect overall self-rated usability or treatment credibility but increases some measures of behavioral engagement with a digital intervention.FundingFunded by the Government of Sweden, Ministry of Health and Social Affairs.

Project description:In this paper we argue that a synthesis of findings across the various sub-areas of research in complex problem solving and consequently progress in theory building is hampered by an insufficient differentiation of complexity and difficulty. In the proposed framework of person, task, and situation (PTS), complexity is conceptualized as a quality that is determined by the cognitive demands that the characteristics of the task and the situation impose. Difficulty represents the quantifiable level of a person's success in dealing with such demands. We use the well-documented "semantic effect" as an exemplar for testing some of the conceptual assumptions derived from the PTS framework. We demonstrate how a differentiation between complexity and difficulty can help take beyond a potentially too narrowly defined psychometric perspective and subsequently gain a better understanding of the cognitive mechanisms behind this effect. In an empirical study a total of 240 university students were randomly allocated to one of four conditions. The four conditions resulted from contrasting the semanticity level of the variable labels used in the CPS system (high vs. low) and two instruction conditions for how to explore the CPS system's causal structure (starting with the assumption that all relationships between variables existed vs. starting with the assumption that none of the relationships existed). The variation in the instruction aimed at inducing knowledge acquisition processes of either (1) systematic elimination of presumptions, or (2) systematic compilation of a mental representation of the causal structure underpinning the system. Results indicate that (a) it is more complex to adopt a "blank slate" perspective under high semanticity as it requires processes of inhibiting prior assumptions, and (b) it seems more difficult to employ a systematic heuristic when testing against presumptions. In combination, situational characteristics, such as the semanticity of variable labels, have the potential to trigger qualitatively different tasks. Failing to differentiate between 'task' and 'situation' as independent sources of complexity and treating complexity and difficulty synonymously threaten the validity of performance scores obtained in CPS research.

Dataset Information

Coach-Supported Versus Self-guided Digital Training Course for a Problem-solving Psychological Intervention for Nonspecialists: Protocol for a Pre-Post Nested Randomized Controlled Trial.

Background

Objective

Methods

Results

Conclusions

Trial registration

International registered report identifier (irrid)

Publications

Coach-Supported Versus Self-guided Digital Training Course for a Problem-solving Psychological Intervention for Nonspecialists: Protocol for a Pre-Post Nested Randomized Controlled Trial.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets