An App-Based Just-in-Time Adaptive Self-management Intervention for Care Partners (CareQOL): Protocol for a Pilot Trial
Bibliographic record
Abstract
BACKGROUND: Care partners (ie, informal family caregivers) of individuals with health problems face considerable physical and emotional stress, often with a substantial negative impact on the health-related quality of life (HRQOL) of both care partners and care recipients. Given that these individuals are often overwhelmed by their caregiving responsibilities, low-burden self-management interventions are needed to support care partners to ensure better patient outcomes. OBJECTIVE: The primary objective of this study is to describe an intensive data collection protocol that involves the delivery of a personalized just-in-time adaptive intervention that incorporates passive mobile sensor data feedback (sleep and activity data from a Fitbit [Fitbit LLC]) and real time self-reporting of HRQOL via a study-specific app called CareQOL (University of Michigan) to provide personalized feedback via app alerts. METHODS: Participants from 3 diverse care partner groups will be enrolled (care partners of persons with spinal cord injury, care partners of persons with Huntington disease, and care partners of persons with hematopoietic cell transplantation). Participants will be randomized to either a control group, where they will wear the Fitbit and provide daily reports of HRQOL over a 3-month (ie, 90 days) period (without personalized feedback), or the just-in-time adaptive intervention group, where they will wear the Fitbit, provide daily reports of HRQOL, and receive personalized push notifications for 3 months. At the end of the study, participants will complete a feasibility and acceptability questionnaire, and metrics regarding adherence and attrition will be calculated. RESULTS: This trial opened for recruitment in November 2020. Data collection was completed in June 2021, and the primary results are expected to be published in 2022. CONCLUSIONS: This trial will determine the feasibility and acceptability of an intensive app-based intervention in 3 distinct care partner groups: care partners for persons with a chronic condition that was caused by a traumatic event (ie, spinal cord injury); care partners for persons with a progressive, fatal neurodegenerative disease (ie, Huntington disease); and care partners for persons with episodic cancer conditions that require intense, prolonged inpatient and outpatient treatment (persons with hematopoietic cell transplantation). TRIAL REGISTRATION: ClinicalTrials.gov NCT04556591; https://clinicaltrials.gov/ct2/show/NCT04556591. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32842.
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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 | 0.025 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.077 | 0.014 |
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".