Improvement in Quality of Life After Early Interactive Human Coaching via a Mobile App in Postgastrectomy Patients With Gastric Cancer: Prospective Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Patients undergoing gastrectomy usually experience postgastrectomy syndrome and face difficulties adapting to a regular diet. Human health coaching via a mobile app has recently been applied to patients with chronic metabolic diseases, with significant improvements being observed in clinical outcomes. OBJECTIVE: This study aimed to compare the quality of life and nutritional outcomes of human health coaching via a mobile app with those of conventional face-to-face counseling in postgastrectomy patients with gastric cancer. METHODS: This was a prospective randomized controlled trial, and patients were enrolled between May 2020 and August 2022. The mobile coaching group received health coaching that provides personalized advice based on self-recorded health data via a mobile app from assigned coaches for 3 months after discharge, and the conventional counseling group underwent dietary consultations with a clinical dietitian 1 and 3 months postoperatively. The primary end point for sample size calculation was the eating restriction score on the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire gastric cancer module 1 month postoperatively. Secondary end points included changes in other subscales of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and gastric cancer module, as well as nutritional outcomes assessed preoperatively and 1, 3, 6, and 12 months postoperatively. RESULTS: Data from 88.9% (160/180) of enrolled patients were analyzed after excluding dropouts. In the mobile coaching group (n=76), 66% (n=50) of patients who used the mobile app for ≥8 weeks were classified as active users. No significant difference in eating restriction 1 month postoperatively was found between the mobile coaching and conventional counseling groups. However, the mobile coaching group reported less dyspnea during the entire period (P=.01), less eating restriction at 6 months (P=.045), and less negative body image 3 months postoperatively (P=.04) than the conventional counseling group (n=84). Exploratory subgroup analyses based on age, sex, and operation type indicated that younger patients (<60 years), female patients, and those who underwent distal gastrectomy had better quality of life from mobile coaching. In the mobile coaching group, exploratory subgroup analyses based on mobile activity showed that active users had a better global health status than inactive users (P=.005). However, no significant differences in body composition or nutritional parameters were observed between the mobile coaching and conventional counseling groups or between active and inactive users in the mobile coaching group. CONCLUSIONS: Although this trial did not show a significant difference in eating restriction 1 month postoperatively, human coaching via a mobile app was associated with fewer symptoms in some scales compared to conventional counseling in postgastrectomy patients with gastric cancer. The intervention might help patients manage their symptoms and adapt to their diet. TRIAL REGISTRATION: ClinicalTrials.gov NCT04394585; https://clinicaltrials.gov/study/NCT04394585.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".