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Factor structure and proposed scoring revision of the Three-Dimensional Psychological Pain Scale

2021· article· en· W3174292352 on OpenAlexaff
Ronald R. Holden, Rui C. Campos, Christine Lambert, Ana Correia Simões, Sara Costa, Ana Sofia Pio, Joana Spínola, Diandra Marques

Bibliographic record

VenuePsicologia · 2021
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisClinical psychologyStructural equation modelingReliability (semiconductor)CognitionInternal consistencyExploratory factor analysisScale (ratio)Psychological painPsychometricsPsychiatry

Abstract

fetched live from OpenAlex

The development of psychometrically sound measures to assess mental pain are important because research has consistently demonstrated a robust relationship to suicide risk. The current research evaluated the Three-Dimensional Psychological Pain Scale (TDPPS) structure, a suicide-relevant measure intended to articulate pain into affective, cognitive, and behavioral facets. As the first Western study to evaluate the TDPPS structure with non-Chinese respondents, six samples comprising 1,627 adults participated. Neither confirmatory factor analyses nor exploratory structural equation modeling supported the hypothesized three-dimensional structure of the TDPPS but, instead, identified two dimensions: pain escape and pain emotions. Scales based on these two dimensions demonstrated replicability in cross-validation and score internal consistency reliability. Furthermore, validity for scores on these two scales was confirmed through moderate associations with another pain measure and scales of suicidal behavior and depression. Findings extend knowledge of TDPPS’s structure of psychological pain and suggest a scale scoring revision.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.999

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)0.0020.000

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 head0.044
GPT teacher head0.321
Teacher spread0.276 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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