Personal Devices to Monitor Physical Activity and Nutritional Intake After Colorectal Cancer Surgery: Feasibility Study
Bibliographic record
Abstract
BACKGROUND: The use of self-monitoring devices is promising for improving perioperative physical activity and nutritional intake. OBJECTIVE: This study aimed to assess the feasibility, usability, and acceptability of a physical activity tracker and digital food record in persons scheduled for colorectal cancer (CRC) surgery. METHODS: This observational cohort study was conducted at a large training hospital between November 2019 and November 2020. The study population consisted of persons with CRC between 18- and 75 years of age who were able to use a smartphone or tablet and scheduled for elective surgery with curative intent. Excluded were persons not proficient in Dutch or following a protein-restricted diet. Participants used an activity tracker (Fitbit Charge 3) from 4 weeks before until 6 weeks after surgery. In the week before surgery (preoperative) and the fifth week after surgery (postoperative), participants also used a food record for 1 week. They shared their experience regarding usability (system usability scale, range 0-100) and acceptability (net promoter score, range -100 to +100). RESULTS: In total, 28 persons were included (n=16, 57% male, mean age 61, SD 8 years), and 27 shared their experiences. Scores regarding the activity tracker were as follows: preoperative median system usability score, 85 (IQR 73-90); net promoter score, +65; postoperative median system usability score, 78 (IQR 68-85); net promotor score, +67. The net promoter scores regarding the food record were +37 (preoperative) and-7 (postoperative). CONCLUSIONS: The perioperative use of a physical activity tracker is considered feasible, usable, and acceptable by persons with CRC in this study. Preoperatively, the use of a digital food record was acceptable, and postoperatively, the acceptability decreased.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".