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Record W2005176540 · doi:10.1159/000288555

Validation of the Derogatis Stress Profile Using Laboratory and Real World Data

2010· article· en· W2005176540 on OpenAlexaff
Patricia L. Dobkin, Robert O. Pihl, Claude Breault

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsDouglas Mental Health University InstituteDouglas College
Fundersnot available
KeywordsPsychologyStressorAnxietyDigital signal processingPsychometricsClinical psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.337
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2010
Admission routes1
Has abstractyes

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