Predictors of Pro-Environmental Behaviors in Adolescence: A Scoping Review
Bibliographic record
Abstract
Today’s adolescents will inevitably face the negative effects of climate change and will need to engage in pro-environmental behaviors (PEBs) as part of the solutions. The primary objective of this scoping review was to identify the individual, peer and family, and school and community predictors of PEB in adolescence. The secondary objectives were to highlight the main types of PEBs, the main conceptual frameworks examined in adolescence, and the main research gaps mentioned in prior studies. A bibliographic search on multiple databases was conducted. Among the 2578 records identified, 209 were retrieved and assessed for eligibility, and 62 met the inclusion criteria (i.e., peer-reviewed primary research articles published in English in the last ten years with adolescent data). Results reveal a heterogeneous set of correlates with an imbalance favoring individual correlates. The most frequent PEBs in the reviewed studies were linked to energy and water conservation. The most frequent theoretical frameworks were the Theory of Planned Behavior and the Value–Belief–Norm Theory, while the most frequently highlighted research gap was the use of cross-sectional designs. These results can inform the targets of interventions aimed at increasing PEBs, which are fundamental aspects of the psychology of sustainability and sustainable development.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".