The cost of lower self-esteem: Testing a self- and social-bonds model of health.
Bibliographic record
Abstract
The authors draw upon social, personality, and health psychology to propose and test a self-and-social-bonds model of health. The model contends that lower self-esteem predicts health problems and that poor-quality social bonds explain this association. In Study 1, lower self-esteem prospectively predicted reports of health problems 2 months later, and this association was explained by subjective reports of poor social bonds. Study 2 replicated the results of Study 1 but used a longitudinal design with 6 waves of data collection, assessed self-reports of concrete health-related behaviors (i.e., number of visits to the doctor and classes missed due to illness), and measured both subjective and objective indicators of quality of social bonds (i.e., interpersonal stress and number of friends). In addition, Study 2 showed that poor-quality social bonds predicted acute drops in self-esteem over time, which in turn predicted acute decreases in quality of social bonds and, consequently, acute increases in health problems. In both studies, alternative explanations to the model were tested.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".