Telehealth Behavioral Intervention for Chronic Disease Self-Management in Adults With Physical Disabilities (My Health, My Life, My Way): Protocol for Intervention Fidelity and Dashboard Design for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Individuals with physical disabilities experience higher rates of chronic health conditions than individuals without physical disabilities. Self-management programs that use health coaching are effective at eliciting health behavior change in health outcomes such as goal setting, adherence, and health care use. Additionally, web-based resources such as telehealth-based technologies, including SMSS text messaging, web-based applications, and educational multimedia content, can complement health coaching to improve health-related behaviors and the use of health services. The complexity of studies using these resources requires a fidelity protocol to ensure that health behavior studies are administered properly. OBJECTIVE: The My Health, My Life, My Way fidelity protocol provides methods, strategies, and procedures of a multifaceted telehealth program for individuals with permanent physical disabilities and chronic health conditions. This health behavior study is a randomized controlled trial with four study arms: (1) scheduled coaching calls with gamified rewards, (2) no scheduled coaching calls with gamified rewards, (3) scheduled coaching calls with fixed rewards, and (4) no scheduled coaching calls with fixed rewards. To guide the fidelity protocol developed, we used the National Institutes of Health Behavior Change Consortium framework (NIH BCC). METHODS: The fidelity intervention protocol was developed by using the 5 primary domains provided by the NIH BCC: study design, provider training, treatment delivery, treatment receipt, and enactment of treatment skills. Following the NIH BCC guidelines and implementing social cognitive theory, this study is designed to ensure that all study arms receive equal treatment across conditions and groups. Health coaches and providers will be trained to deliver consistent health coaching, and thus participants will receive appropriate attention. Educational content will be developed to account for health literacy and comprehension of the material. Multiple fidelity intervention steps such as coaching call logs, regular content review, and participant progress monitoring will translate to participants using the skills learned in their daily lives. Different monitoring steps will be implemented to minimize differences among the 4 treatment groups. RESULTS: My Health, My Life, My Way has been approved by the institutional review board and will begin enrollment in January 2024 and end in December 2024, with results reported in early 2025. CONCLUSIONS: Intervention fidelity protocols are necessary to ensure that health behavior change studies can be implemented in larger real-world settings. The My Health, My Life, My Way fidelity protocol has used the guidelines by the NIH BCC to administer a telehealth intervention combined with health coaching for individuals with physical disabilities and chronic health conditions. This fidelity protocol can be used as a complementary resource for other researchers who conduct similar research using telehealth technologies and health coaching in real-world settings. TRIAL REGISTRATION: ClinicalTrials NCT05481593; https://clinicaltrials.gov/study/NCT05481593. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53410.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.053 | 0.048 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.093 | 0.012 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".