Cancer Exercise Mobile App: Reporting The First Analytics
Bibliographic record
Abstract
BACKGROUND: The Cancer Exercise mobile application (app) has been freely available to cancer survivors since 2020. The app was developed based on Social-Cognitive Theory incorporating several evidence-based behaviour change techniques and follows the American College of Sports Medicine Exercise Guidelines for cancer survivors. The Cancer Exercise app has not been assessed regarding performance and engagement. Here, we report some preliminary data on the usage and functionality of the app prior to testing its efficacy in a randomized control trial (RCT) in cancer survivors. PURPOSE: To report the Cancer Exercise mobile app iOS version user analytics since its launch and benchmark to other health and fitness apps. METHODS: Using data collected retrospectively from app inception (January 2020) to present (October 2023), we obtained the following app analytics for the iOS version of Cancer Exercise: total of downloads, conversion rate (people navigating in the app), location of users, and type of device. We also collected the total of downloads by source, usage (sessions per active device), and crashes. This data will be benchmarked with other health and fitness apps. RESULTS: The Cancer Exercise app had a total of 1700 downloads with 88% of those downloads to an iPhone. We note the conversion rate monthly average is 9% and it has been increasing in recent months (14.7%). Most users are in the United States (60%), United Kingdom (0.08%), or Canada (0.06%). A total of 1076 (63%) people searched the Cancer Exercise app on the App Store, 371 on a web referrer, and 123 on the app referrer. Among users who opt-in to share data about their health, the proportion of sessions per active device is 1.83% with an increase rate of 2.33%. The app had a total of 13 crashes (nearly 0%). When the performance is benchmarked to other health and fitness apps, the conversion rate is between the 50th and 75th percentile (14.7%) (and the crash rate is below the 25th percentile (~0.00%). CONCLUSION: The Cancer Exercise mobile app is highly functional. The total number of downloads and individuals searching for this digital tool shows that the Cancer Exercise app is worth testing in an RCT of cancer survivors.
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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 | 0.008 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.025 |
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".