A Tailored Text Messaging Intervention (Text4HF) to Improve Self-Care in Patients with Heart Failure: Protocol for a Pilot Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
Background: Heart failure (HF) is a major public health problem associated with frequent hospitalizations, high mortality, and substantial health care costs. Self-care is fundamental to improving health outcomes; yet, self-care is commonly poor among patients with HF. SMS text messaging interventions may provide a simple, scalable, and accessible strategy to support HF self-care, particularly among older adults who may face barriers to using more complex digital health technologies. However, the efficacy of text messaging as a standalone intervention for patients with HF remains underexplored. Objective: This protocol paper describes the rationale and design of a pilot randomized controlled trial examining the feasibility, acceptability, and preliminary efficacy of an individually Tailored Text Messaging Intervention to Improve Self-Care in Adults with HF (Text4HF). Methods: This study is a single-site, stage I, parallel-group randomized controlled trial. Participants (n=30) are community-dwelling adults aged 50 years or older with stage C HF and suboptimal self-care, defined as a score of 3 or less on at least 2 items of the Self-Care of Heart Failure Index (SCHFI v7.2). Participants are randomized (1:1) to either a 12-week tailored text messaging intervention (Text4HF) plus usual care or usual care alone. Text messages are triggered based on patient responses to validated instruments assessing evidence-based, modifiable behavioral factors of HF self-care. Feasibility (recruitment and retention) and acceptability of the intervention are assessed as key process outcomes. The main exploratory patient-reported outcome is HF self-care (SCHFI v7.2). Other patient-reported outcomes include medication adherence, adherence to a heart-healthy diet, HF knowledge, health-related quality of life, self-efficacy, and health beliefs. Results: This study was funded in June 2022, and participant recruitment began in September 2024. A total of 26 participants have been enrolled and randomized to the intervention (n=13) and control (n=13) groups. Participants have a mean age of 60 (SD 6.6) years, 46% (12/26) are female, and 73% (19/26) identify as non-Hispanic Black. Half of the participants are individuals with reduced ejection fraction. Study completion is anticipated in June 2026. Conclusions: This protocol describes an important step toward evaluating a scalable, low-cost text messaging intervention designed to improve self-care in patients with HF. Study findings will provide critical data on feasibility and acceptability to guide a future fully powered efficacy trial of Text4HF.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.114 | 0.013 |
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.
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".