Evaluating the Effectiveness of a Mobile App for Breast Cancer Self-Management on Self-Efficacy: Nonrandomized Intervention Trial
Bibliographic record
Abstract
BACKGROUND: Numerous mobile apps have been developed for patients with cancer. However, there is still no comprehensive app for patients with breast cancer that integrates evidence-based medical information, psychological support, and schedule management through a multidisciplinary medical approach. OBJECTIVE: We aimed to investigate whether a mobile app designed to assist in the self-management of patients with breast cancer is feasible and positively affects their self-efficacy and other psychological aspects. METHODS: The Cancer Manager (CAMA) app was developed to assist in the self-management of patients with breast cancer and survivors of cancer according to cancer trajectory. Its functionalities include providing evidence-based digitalized information created by experts, managing patients' medication and medical appointment schedules, and providing a delayed question and answer system for patients to query health care professionals. In this nonrandomized intervention trial, we analyzed data from 66 patients with breast cancer, divided into experimental (CAMA: n=34, 52%) and control (treatment as usual: n=32, 48%) groups. Group allocation was determined based on the patient's willingness to use the app and access to compatible smartphones. Outcome measures included the Korean version of the Cancer Survivor Self-Efficacy Scale, the Korean version of the Mini-Mental Adjustment to Cancer (K-Mini-MAC) Scale, the World Health Organization Quality of Life Brief Version, Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Menopause Emotional Symptoms Questionnaire (MESQ). A user satisfaction survey was also conducted. RESULTS: =4.30; P=.04). Changes in the anxious preoccupation subscale of the K-Mini-MAC Scale scores were positively correlated with changes in the PHQ-9 (r=0.46; P=.007) and GAD-7 (r=0.41; P=.02) scores and negatively correlated with changes in the positive attitude subscale of the K-Mini-MAC Scale scores (r=-0.36; P=.04). Changes in the PHQ-9 scores were positively correlated with changes in the GAD-7 (r=0.66; P<.001) and MESQ (r=0.35; P=.04) scores. The user satisfaction survey offered insights into the CAMA app's positive impact; trust-building outcomes; and opportunities for enhancement, such as the inclusion of communication tools and continued content enrichment. CONCLUSIONS: The mobile app for breast cancer self-management, CAMA, was deemed feasible and showed promise in improving the patients' self-efficacy regarding seeking help and support, positive attitude toward cancer, and psychological well-being. In addition, its use might help reduce anxious preoccupation with cancer, depressive mood, anxiety, and menopausal emotional symptoms. TRIAL REGISTRATION: Clinical Research Information Service KCT0007917; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=23348.
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".