Acceptability and feasibility of survivorship care plans and an accompanying mobile health intervention for adolescent and young adult survivors of childhood cancer
Bibliographic record
Abstract
BACKGROUND: Self-management interventions for adolescent and young adult (AYA) survivors of childhood cancer are needed. The present study reports on the acceptability and feasibility of delivering survivorship care plans (SCPs) and an accompanying app to AYA. PROCEDURE: AYA (n = 224) ages 15-29 who completed treatment for cancer were randomized and received a digital SCP only or an SCP plus a mobile app intended to enhance self-management. For 16 weeks, the app delivered one to two daily messages complementing information in their SCP and tailored based on age, treatment, and health goal. Data are presented on feasibility, self-reported acceptability (including satisfaction and perceived benefits) and its relationship to app engagement (for those in app group), and feedback from qualitative interviews conducted with 10 AYA. RESULTS: The SCP and app proved feasible as evidenced by high recruitment and retention, access to technology, time analysis, moderate app engagement, and minimal technical issues. However, 12% reported never reading the SCP and 8% never used the app. The app and SCP were acceptable to AYA, and SCP acceptability ratings did not differ between groups. For those with the app, acceptability was positively related to message engagement. AYA recommended enhanced individualization and design features of the SCP and app. CONCLUSIONS: Results support the use of tailored SCPs and mobile health interventions for most AYA, as well as the need for further refinement and research. Delivery of SCPs and digital interventions are acceptable and feasible to AYA survivors, and may help promote health-related knowledge and survivorship self-management.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".