Association between accessibility to key activities through multi-modal public transit network in the Montréal Metropolitan Region and subjective well-being
Bibliographic record
Abstract
Background: Access to physical locations and social networks determines how we create relationships with each other and how we can access material goods or intangible resources like knowledge and activities through which we can better our lives. Public transit may in that context influence individual subjective well-being through both the transit experience (during the trip) and as a mean of accessing key locations to meet our basic needs and promote personal development, increasing one’s satisfaction with their life.Goal: Using data from the 1st wave of Montréal participants from INTERACT, collected in 2018, this cross-sectional cohort design aims to determine if public transit accessibility is associated with increased subjective wellbeing scores at the individual level.Methods: 833 participants completed the VERITAS questionnaire (map-based survey) for the first cycle of the INTERACT study in 2018. The main exposure, the fit between transportation needs and public transit offer at the individual level (transit fit measure), was a new metric developed using open-access data from Google Maps. The outcome of interest, life satisfaction (a component of subjective well-being), was measured using the Personal Well-being Index 5th Edition (PWBI score). Multiple linear regressions were performed to characterize the association between the main exposure and subjective well-being, controlling for the frequency of public transit use and other covariates that could have an influence on public transit use and well-being (car ownership, age, gender, education level and physical health).Results: A multiple linear regression model adjusting for yearly transit use, car ownership, age, gender, education, and physical health showed an average increase of 0.99 points in the PWBI score per increment of 1 in the transit fit measure (β = 0.99 with 95% CI [-0.40, 2.38]), which was not statistically significant. Age (β = 0.15 with 95% CI [0.08, 0.22]), reported physical health (β = 0.50 with 95% CI [0.37, 0.63]) and education level points (β = 3.97 with 95% CI [1.37, 5.58]) were associated with life satisfaction. There is a strong signal that high public transit use ≥ 5 times/week) is negatively associated with life satisfaction (β = -3.46 with 95% CI [-7.19, 0.27]). The model using all covariates had an adjusted R2 of 0.1075, meaning that this model only explained 10.75% of the variance of the outcome variable.Conclusions: A novel public transit accessibility measurement methodology was developed based on fit between a user’s lifestyle choices (through daily-activities-related trips) and public transit offer, which will need further refinement. Further research should be done to enhance our understanding of the mechanisms underlying the complex relationship between access to public transport and subjective well-being. Public transit can have an impact on individuals’ subjective well-being through multiple pathways, which highlights the need for an integrated, intersectoral strategy to increase access
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".