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Record W4412885690 · doi:10.1080/23311908.2025.2537520

Validation of the Greek version of the Family Problem Solving Communication Scale (FPSC) in breast cancer patients

2025· article· en· W4412885690 on OpenAlexfundno aff
Dimitrios Charos, M. Andriopoulou, Giannoula Kyrkou, Άννα Δελτσίδου, Nikolas Amplas, Maria Kolliopoulou, Grigorios Karampas, Victoria Vivilaki

Bibliographic record

VenueCogent Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
FundersUniversity of West AtticaMcMaster University
KeywordsPsychologyBreast cancerScale (ratio)Clinical psychologySocial psychologyCancerMedicineCartographyInternal medicine

Abstract

fetched live from OpenAlex

Family plays a vital role in supporting breast cancer patients. Recent studies have shown that increasing family resilience empowers family support for patients. The study aims to validate the Family Problem Solving Communication (FPSC) scale in breast cancer patients in the Greek population. A factor analysis was performed, and convergent validity and reliability were tested through Cronbach alpha, Split-Half reliability, Spearman-Brown Coefficient, and Guttman Split-Half Coefficient. According to the factor analysis, Bartlett’s Test of Sphericity coefficient (Chi-Square = 439.105, p = 0.000) showed that it has statistically significant correlations between items and the KMO index was 0. 860. The Cronbach α coefficient was 0.78, the Spearman-Brown coefficient was 0.603 and the Guttman Split-Half coefficient was 0.596. Finally, there was a correlation of the scale with FAD (r=0.328, F-COPES (r=0.290), and ECR-R (r=–0.424). The FPSC scale demonstrates satisfactory psychometric properties and is a suitable and useful psychometric instrument for investigating family resilience.

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)0.010
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.326
Teacher spread0.305 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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