Conscientiousness and Medication Adherence: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Approximately a quarter to a half of all people fail to take their medication regimen as prescribed (i.e. non-adherence). Conscientiousness, from the five-factor model of personality, has been positively linked to adherence to medications in several recent studies. PURPOSE: This study aimed to systematically estimate the strength and variability of this association across multiple published articles and to identify moderators of this relationship. METHOD: A literature search identified 16 studies (N = 3,476) that met the study eligibility criteria. Estimates of effect sizes (r) obtained in these studies were meta-analysed. RESULTS: Overall, a higher level of conscientiousness was associated with better medication adherence (r = 0.15; 95 % CI, 0.09, 0.21). Associations were significantly stronger in younger samples (r = 0.26, 95 % CI, 0.17, 0.34; k = 7). CONCLUSION: The small association between conscientiousness and medication adherence may have clinical significance in contexts where small differences in adherence result in clinically important effects.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.025 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".