Urban neighborhood environments and adult affective health outcomes in Canada
Bibliographic record
Abstract
Background: The lack of policy-ready research into the modifiable pathways linking neighborhoods to mental health outcomes—specifically the effects of neighborhood change on mental health—prompted the writing of this manuscript-based thesis. Objective: The first manuscript aims to elucidate the causal pathways and mechanisms through which neighborhoods affect depression outcomes in adult populations. The second manuscript seeks to summarize the observed relationships between neighborhood change and adult residents’ psychological well-being. The third manuscript tests the hypothesis that neighborhood change may be related to psychological outcomes in Canada. Methods: The two systematic reviews identified literature in scientific databases using reproducible selection criteria. The original research study examines 2745 urban, community-dwelling adult participants from Canada's National Population Health Survey (NPHS). Associations were analyzed using multivariate linear regressions, controlling for key demographic characteristics, and stratified by baseline deprivation exposure. Results: Neighborhood socioeconomic disadvantage, instability, disorder, and social capital are associated with depressive symptoms. The proposed modifiable pathways linking these neighborhood characteristics and depression include: 1) the level of neighborhood-based stress that is placed on individuals; 2) the formation and strength of protective and supportive social networks; 3) the level of resiliency to negative affectivity and stress; 4) the perceptions of the aesthetic and form of residential space; and 5) the sense of control and agency in place of residence. These pathways represent potential areas for future research and intervention. Additionally, neighborhood change was observed to have a significant effect on psychological well-being. This observation was validated in the Canadian context using NPHS data. We found that both an improvement of social settings and a worsening of material settings were associated with worsening distress scores at follow-up. Conclusions: Further research requires a more systematic use of longitudinal design and a diversity of physical and social environmental measures. Interventions aimed at improving affective resiliency need to be tested. Future research would benefit from continued investigation of neighborhood change, especially with regards to social and economic vulnerability.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".