“Instead of Building More Buildings, They Should Plant More Trees”, a Photovoice Study of Determinants of Happiness and Sadness Among East London Adolescents
Bibliographic record
Abstract
Globally, mental health problems in adolescents, alongside associated morbidity and mortality, have never been higher. Local living, working and environmental conditions, socio-economics, and intra-individual and inter-individual processes impact mental health. The risk of developing mental health problems is higher in certain areas, including East London. However, limited research explores East London adolescents' experiences of mental health. An in-depth and locally situated understanding of determinants shaping East London adolescents' happiness and sadness is needed. This study used Photovoice, a qualitative method within a community-based participatory research methodology, to generate photographic and textual data, which was analyzed using reflexive thematic analysis. This method allows participants to be part of knowledge production and authors to present the data. Our findings underscore the bidirectional interplay between environmental factors and adolescents' happiness and sadness. Gratitude for nature was described as increasing happiness: adolescents connected to nature to memories, appreciation, and leisure opportunities. Adolescents were concerned about the fragility of nature in response to urban development. The urban environment was perceived as imposing, inspiring, and offering therapeutic benefits blighted by pollution. Beautiful areas were described as paradisical and lacking, revealing urban development and economic productivity disparities. Our research documents the voices of an under-researched group, revealing novel insights while empowering adolescents as co-producers of mental health research. This study indicates participatory research is valuable for granting adolescents autonomy and addressing misrepresentation. The findings implicate multiple stakeholders, including "Health in All Policies." By deepening our understanding of adolescent mental health in East London, our study can be leveraged to bolster the effectiveness and relevance of interventions for East London adolescents.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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 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".