Optimism, pessimism, and physical health among youth: a scoping review
Bibliographic record
Abstract
OBJECTIVE: High levels of optimism (and low levels of pessimism) are associated with improved physical health in adults. However, relatively less is known about these relations in youth. The present study aimed to review the literature investigating optimism, pessimism, and physical health in children and adolescents from populations with and without health conditions. METHODS: We conducted a scoping review up until February 2024. Studies were included if they sampled youth (average age ≤18 years) and treated optimism or pessimism as predictors of health behaviors or outcomes. Data on study and sample characteristics, health outcome, optimism construct, and findings were extracted from eligible papers and results were synthesized. RESULTS: Sixty studies were retained. Most studies were conducted in North America, with adolescents, and used cross-sectional designs and self-reported measures of health. Measures of optimism and pessimism differed across studies. Roughly one-third of studies sampled medical populations. Health categories included substance use, diet and physical activity, sexual health practices, medical adherence, other health behaviors, cardiometabolic health, subjective health/health-related quality of life, pain, sleep, and oral health. Generally, we observed adaptive associations between optimism and health. Higher optimism and lower pessimism were most consistently associated with lower rates of substance use and lower cardiometabolic risk. CONCLUSIONS: The presence of optimism or the absence of pessimism appears to be associated with various adaptive health outcomes among youth with and without health conditions. Developmental, methodological, and clinical considerations for future research are discussed, such as conducting longitudinal studies with objective measures of health and psychometrically validated instruments.
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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".