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Record W3044841209 · doi:10.3389/fpsyg.2020.01642

Psychometric Testing of the Chinese Version of the Coping and Adaptation Processing Scale-Short Form in Adults With Chronic Illness

2020· article· en· W3044841209 on OpenAlexaff
Xiyi Wang, Leiwen Tang, Doris Howell, Jing Shao, Ruolin Qiu, Qi Zhang, Zhihong Ye

Bibliographic record

VenueFrontiers in Psychology · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Toronto
FundersDepartment of Health of Zhejiang ProvinceChina Scholarship Council
KeywordsPsychologyClinical psychologyAdaptation (eye)Coping (psychology)Scale (ratio)PsychometricsCognitive psychologyDevelopmental psychologyNeuroscience

Abstract

fetched live from OpenAlex

Background: Adaptive capacity may serve as an indicator of the individuals’ coping behaviors towards illness management and may contribute to day-to-day living with chronic illness and improved quality of life. Practical and well-constructed instruments for measuring adaptation have not been adequately explored. An English 15-item Coping and Adaptation Processing-Short Form (CAPS-SF) for assessing adaptation has been created and validated in line with the underlying tenets of Coping and Adaptation Processing theory, but there is no applicable Chinese version. Methods: The CAPS-SF was translated and culturally adapted into simplified Chinese. Among Chinese adults with chronic illness, eighty-one patients were selected for cultural adaptation and 288 patients were approached for psychometric testing. Content validity was evaluated by an expert panel. Construct validity was tested by confirmatory factor analysis. Concurrent validity and predictive validity were analyzed by Spearman correlation coefficient. Reliability was assessed by internal consistency and test-retest coefficients. Floor/ceiling effect was calculated. Results: Adequate content validity was ensured by the expert panel. A four-factor structure (resourceful and focused, self-initiated and knowing-based, physical and fixed, and positive and systematic) describing individuals’ coping strategies was identified and verified. Concurrent validity and predictive validity were demonstrated by strong correlations with the confrontation of coping mode (r= 0.46) and a quality of life measure (r= 0.58). The McDonald’s Omega coefficient of total scale was 0.82. Split-Half reliability and test-retest reliability were 0.87 and 0.87. No floor/ ceiling effect was present. Conclusions: The Chinese version CAPS-SF is a theoretically based and culturally acceptable instrument with sound psychometric properties. Further studies are advocated to refine its four-factor structure.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2020
Admission routes1
Has abstractyes

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