The relationship between depression risk perception and self-help behaviours in high risk Canadians: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Self-help may reduce the risk of depression, and risk perception of depression may influence initiating self-help. It is unknown how risk perception is associated with self-help behaviours. The objectives of this study are to (1) describe the self-help strategies used by high-risk Canadians in relation to the accuracy of perceived depression risk, by sex, and (2) identify demographic and clinical factors associated with self-help behaviours. METHODS: Baseline data from a randomized controlled trial including 358 men and 356 women at high-risk of developing depression were used. Following methods used in cancer research, risk perception accuracy was determined by comparing the participant's self-perceived and objective risk of developing depression and classifying as accurate, over-estimation and under-estimation based on a ± 10% threshold. The participant's objective depression risk was assessed using sex-specific multivariable risk predictive algorithms. Frequency of using 14 self-help strategies was assessed. One-way ANOVA testing was used to detect if differences in risk perception accuracy groups existed, stratified by sex. Linear regression was used to investigate the clinical and demographic factors associated with self-help behaviours, also stratified. RESULTS: Compared to accurate-estimators, male over-estimators were less likely to "leave the house daily," and "participate in activities they enjoy." Male under-estimators were also less likely to "participate in activities they enjoy." Both male 'inaccurate' perception groups were more likely to 'create lists of strategies which have worked for feelings of depression in the past and use them'. There were no significant differences between self-help behaviours and risk perception accuracy in women. Regression modeling showed negative relationships between self-rated health and self-help scores, irrespective of sex. In women, self-help score was positively associated with age and educational attainment, and negatively associated with perceived risk. In men, a positive relationship with unemployment was also seen. CONCLUSIONS: Sex differences exist in the factors associated with self-help. Risk perception accuracy, work status, and self-rated health is associated with self-help behaviours in high-risk men. In women, factors related to self-help included age, education, self-rated health status, and perceived risk. More research is needed to replicate findings. TRIAL REGISTRATION: Prospectively registered at ClinicalTrials.gov (NCT02943876) as of 10/21/16.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".