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Record W4361015755 · doi:10.2196/42114

Adaptation of a Mobile Interactive Obesity Treatment Approach for Early Severe Mental Illness: Protocol for a Mixed Methods Implementation and Pilot Randomized Controlled Trial

2023· article· en· W4361015755 on OpenAlexvenueno aff
Ginger E. Nicol, Madeline O. Jansen, Amanda Ricchio, Julia Schweiger, Katie Keenoy, J. Philip Miller, Elaine H. Morrato, Zhaohua Guo, Bradley Evanoff, Joseph Parks, John W. Newcomer

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Center for Advancing Translational SciencesNational Institute of Mental HealthNational Institutes of HealthInstitute of Clinical and Translational Sciences
KeywordsIntervention (counseling)Mental healthMedicinePopulationPsychological interventionMental illnessRandomized controlled trialUsabilityAdaptation (eye)StakeholderClinical trialPsychologyNursingPsychiatryComputer scienceEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity is common in individuals with severe mental illness (SMI), contributing to a significantly shortened lifespan when compared to the general population. Available weight loss treatments have attenuated efficacy in this population, underscoring the importance of prevention and early intervention. OBJECTIVE: Here, we describe a type 1 hybrid study design for adapting and pilot-testing an existing mobile health intervention for obesity prevention in individuals with early SMI and Class I or early-stage obesity, defined as a BMI of 30-35. METHODS: An existing, evidence-based interactive obesity treatment approach using low-cost, semiautomated SMS text messaging was selected for adaptation. Community mental health clinics and Clubhouse settings in Eastern Missouri and South Florida were identified to participate. This study has the following 3 aims. First, using the Enhanced Framework for Reporting Adaptations and Modifications to Evidence-based interventions, contextual aspects of the clinical and digital treatment environments are identified for adaptation, considering 5 main stakeholder groups (clinical administrators, prescribing clinicians, case managers, nurses, and patients). Following a 2-week trial of unadapted SMS text messaging, Innovation Corps methods are used to discover needed intervention adaptations by stakeholder group and clinical setting. Second, adaptations to digital functionality and intervention content will be made based on themes identified in aim 1, followed by rapid usability testing with key stakeholders. A process for iterative treatment adaptation will be developed for making unplanned modifications during the aim 3 implementation pilot study. Individuals working in partner community mental health clinics and Clubhouse settings will be trained in intervention delivery. Third, in a randomized pilot and feasibility trial, adults with 5 years or less of treatment for an SMI diagnosis will be randomized 2:1 to 6 months of an adapted interactive obesity treatment approach or to an attentional control condition, followed by a 3-month extension phase of SMS text messages only. Changes in weight, BMI, and behavioral outcomes, as well as implementation challenges, will be evaluated at 6 and 9 months. RESULTS: Institutional review board approval for aims 1 and 2 was granted on August 12, 2018, with 72 focus group participants enrolled; institutional review board approval for aim 3 was granted on May 6, 2020. To date, 52 participants have been enrolled in the study protocol. CONCLUSIONS: In this type 1 hybrid study design, we apply an evidence-based treatment adaptation framework to plan, adapt, and feasibility test a mobile health intervention in real-world treatment settings. Resting at the intersection of community mental health treatment and physical health promotion, this study aims to advance the use of simple technology for obesity prevention in individuals with early-stage mental illness. TRIAL REGISTRATION: ClinicalTrials.gov NCT03980743; https://clinicaltrials.gov/ct2/show/NCT03980743. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42114.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.051
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.078
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.040
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0090.006
Bibliometrics0.0030.004
Science and technology studies0.0050.004
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0780.013

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.335
GPT teacher head0.660
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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