Characterization of functioning in breast cancer survivors: an interpretive descriptive analysis study based on the international classification of functioning, disability, and health (ICF) and the Item-Perspective Classification Framework
Bibliographic record
Abstract
Abstract Purpose Breast cancer survivors experience a range of disabilities compromise their independent function. This study aimed to examine their perspectives and experts on their functioning and interpret concepts with the international classification of functioning, disability, and health (ICF) and the Item-Perspective Classification Framework (IPF). Methods Interpretive descriptive methods were used with in-depth interviewing with 16 breast cancer survivors and 22 experts using a semi-structured interview guide. The interviews were recorded, transcribed, and qualitatively analyzed using thematic analysis. The extracted data were linked to the ICF Core Set for Breast cancer and were interpreted by the IPF. Results Four main themes emerged to define the functioning of BC survivors: body functioning, physical functioning, social functioning, and mental functioning. Three other factors were also categorized as modifiers of functioning personal, emotional, and environmental. The 592 extracted meaningful concepts were linked to 38 (47%) categories from the ICF: 16 Body Functions, 14 Activities and Participation, and 8 Environmental Factors. The IPF classified all the extracted concepts, and most rational appraisals fell in the biological (B) domain. The concepts that required emotional appraisal were classified in Psychology (P). Conclusion Psychological and emotional factors were pivotal in defining functioning in patients with BC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".