Reduction of Financial Health Incentives and Changes in Physical Activity
Bibliographic record
Abstract
Importance: Governments and others continue to use financial incentives to influence citizen health behaviors like physical activity. However, when delivered on a population scale they can be prohibitively costly, suggesting more sustainable models are needed. Objectives: To evaluate the association of incomplete financial incentive withdrawal ("schedule thinning") with physical activity after more than a year of incentive intervention and to explore whether participant characteristics (eg, app engagement and physical activity) are associated with withdrawal outcomes. Design, Setting, and Participants: This case-control study with a pre-post quasi-experimental design included users of a government-funded health app focused on financial incentives. Eligible participants were residents in 3 Canadian provinces over 25 weeks in 2018 and 2019. Data were analyzed from July 2021 to December 2022. Exposure: Due to fiscal constraints, financial incentives for daily physical activity goals were withdrawn in Ontario in December 2018 (case)-representing a 90% reduction in incentive earnings-but not in British Columbia or Newfoundland and Labrador (controls). Main Outcome and Measures: The primary outcome was objectively assessed weekly mean daily step count. Linear regression models were used to compare pre-post changes in daily step counts between provinces (a difference-in-differences approach). Separate models were developed to examine factors associated with changes in daily step count (eg, app engagement and physical activity). Clinically meaningful initial effect sizes were previously reported (approximately 900 steps/d overall and 1800 steps/d among the physically inactive). Results: In total there were 584 760 study participants (mean [SD] age, 34.3 [15.5] years; 220 388 women [63.5%]), including 438 731 from Ontario, 124 101 from British Columbia, and 21 928 from Newfoundland and Labrador. Significant physical activity declines were observed when comparing pre-post changes in Ontario to British Columbia (-198 steps/d; 95% CI, -224 to -172 steps/d) and Newfoundland and Labrador (-274 steps/d; 95% CI, -323 to -225 steps/d). The decrease was most pronounced for highly engaged Ontario users (-328 steps/d; 95% CI, -343 to -313 steps/d). Among physically inactive Ontario users, physical activity did not decline following withdrawal (107 steps/d; 95% CI, 90 to 124 steps/d). Conclusions and Relevance: In this case-control study of incomplete financial incentive withdrawal, statistically significant daily step count reductions were observed in Ontario; however, these declines were modest and not clinically meaningful. Amidst substantial program savings, the physical activity reductions observed here may be acceptable to decision-makers working within finite budgets.
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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 | 0.012 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".