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Record W3014611419 · doi:10.1037/rep0000322

Factor structure and invariance of the pain catastrophizing scale in patients with chronic pain and their spouses.

2020· article· en· W3014611419 on OpenAlexaff
Fatemeh Akbari, Mohsen Dehghani, Somayyeh Mohammadi

Bibliographic record

VenueRehabilitation Psychology · 2020
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPain catastrophizingChronic painSpousePsycINFOClinical psychologyConfirmatory factor analysisPsychologyPhysical therapyMedicineStructural equation modelingMEDLINE

Abstract

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PURPOSE: This study was designed to investigate the equivalency and factor structure of the patients and significant others' version of pain catastrophizing scales in patients with chronic pain and their spouses who are not in pain. METHOD: Participants were 142 married couples in which 1 spouse reported chronic musculoskeletal pain. Confirmatory factor analyses were used to compare 4 models of pain catastrophizing, and to examine the invariance of the factor structure of the PCS-Patient version and the PCS-Significant other version in patients with chronic pain and their spouses. RESULTS: The results indicated that the 2-factor oblique model provided an adequate fit to the data of both patients with chronic pain and their spouses who are not in pain. Moreover, it was found that when gender was controlled, the hypothesized factor structures of the PCS-patient version and the PCS-Significant other version were invariant. Indeed, it was revealed that the PCS-Patient version and the PCS-Significant other version measure the same factors in couples in which 1 of them have a chronic pain condition. CONCLUSIONS: The findings of the current study showed that the 2-factor oblique model is the best fit in both samples (i.e., patients with chronic pain and their spouses). Therefore, it can be suggested that these versions can be used among patients and their spouses and the findings regarding them can be compared. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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)0.001
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 score0.029
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.242
Teacher spread0.236 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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