Validation of the Derogatis Stress Profile Using Laboratory and Real World Data
Bibliographic record
Abstract
The Derogatis Stress Profile (DSP) is unique among the numerous measures of 'stress' in that it incorporates the interactional model of Lazarus and Folkman in a multidimensional structure. Derogatis has studied the psychometric properties of the DSP but its validity has not been demonstrated in the 'real world' nor has it been related to psychophysiological data. The present investigation was aimed at testing the validity of the DSP in these two areas. Forty-three men between the ages of 18 and 30 years completed the DSP, the Daily Hassles Scale (DHS), the Life Experiences Survey (LES), the Profile of Mood States (bipolar form), and the Jackson Personality Inventory (JPI). Participants were exposed to stressors in a laboratory setting as well as in the field while their heart rate was being monitored. Results supported the validity of the DSP, in part. The correlation between the DSP and JPI anxiety scores was significant as was the correlation between the DSP and the daily depression scores. The correlation between the Total Stress Score (TSS) of the DSP and DHS was significant as were the correlations between the TSS and LES scores. Moreover, the DSP scores were related to heart rate reactivity both in the laboratory and in the field.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".