The developmental course of loneliness in adolescence: Implications for mental health, educational attainment, and psychosocial functioning
Bibliographic record
Abstract
Abstract The present study examined patterns of stability and change in loneliness across adolescence. Data were drawn from the Environmental Risk (E-Risk) Longitudinal Twin Study, a UK population-representative cohort of 2,232 individuals born in 1994 and 1995. Loneliness was assessed when participants were aged 12 and 18. Loneliness showed modest stability across these ages ( r = .25). Behavioral genetic modeling indicated that stability in loneliness was explained largely by genetic influences (66%), while change was explained by nonshared environmental effects (58%). Individuals who reported loneliness at both ages were broadly similar to individuals who only reported it at age 18, with both groups at elevated risk of mental health problems, physical health risk behaviors, and education and employment difficulties. Individuals who were lonely only at age 12 generally fared better; however, they were still more likely to finish school with lower qualifications. Positive family influences in childhood predicted reduced risk of loneliness at age 12, while negative peer experiences increased the risk. Together, the findings show that while early adolescent loneliness does not appear to exert a cumulative burden when it persists, it is nonetheless a risk for a range of concomitant impairments, some of which can endure.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".