A test of integration of the activation hypothesis and the diathesis‐stress component of the hopelessness theory of depression
Bibliographic record
Abstract
OBJECTIVES: This prospective study tested the integration of the diathesis-stress component of the hopelessness theory of depression (Abramson, Metalsky, & Alloy, 1989) and Persons and Miranda's (1992) activation hypothesis (i.e. depressogenic inferential styles are typically latent cognitive processes that must be primed in order to be accurately assessed). DESIGN: In order to test the diathesis-stress component of the hopelessness theory, we used a short-term longitudinal design. In order to test the activation hypothesis, inferential styles were assessed both before and after a negative cognitive priming questionnaire. METHODS: A group of 165 university students completed measures of inferential styles about the self, consequences, and causes before and after completing a negative cognitive priming questionnaire (Time 1). Participants also completed measures of depressive symptoms prior to completing the cognitive priming questionnaire and 5 weeks later (Time 2). Finally, negative events occurring between Time 1 and Time 2 were assessed. RESULTS: Contrary to the diathesis-stress component of the hopelessness theory, none of the unprimed inferential styles interacted with negative events to predict increases in depressive symptoms. In line with the integration of the hopelessness theory and the activation hypothesis, however, each of the primed inferential styles interacted with negative events to predict increases in depressive symptoms even after controlling for the proportion of variance in depressive symptoms accounted for by the unprimed inferential style stress interactions. CONCLUSION: Individuals with depressogenic inferential styles are likely to show increases in depressive symptoms following the occurrence of negative events. At the same time, these depressogenic inferential styles are typically latent cognitive processes that must be primed in order to be accurately assessed.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".