Psychometric evaluation of Life Attitude Profile Scale-Revised in Patients with Cancer
Bibliographic record
Abstract
Abstract: Background and Aim Increasing life expectancy and improving the quality of life of patients with cancer is one of the health priorities. The attitude towards life is one of the most important effective factors. The objective of present study was psychometric evaluation of revised life attitude scale in cancer patients undergoing chemotherapy. Materials and Methods This was a methodological study. 138 patients with cancer patients undergoing chemotherapy have been selected by simple random sampling. First, the scale was translated to Persian. Internal consistency was estimated using Cronbach's coefficient alpha. The validity was determined by constructed validity using exploratory factor analysis exploratory, content validity (by calculating content validity index and content validity ratio) and also face validity. Results Results of factor analysis showed six essential factors as the basis of Persian life attitude profile-revised scale. The first factor (goals) explained the main portion of variance of scale’s questions. The index of Kaiser-Meyer-Olkin showed the adequacy of sample size. (0.601). Content validity index was 0.79-0.85. The content validity ratio for the above choices of scale was equal to +0.99 (p . - Reker G T and Peacock E J (1981) The Life Attitude Profile (LAP): A multidimensional instrument for assessing attitudes toward life. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement. 13 (3) 264. - Thompson P. The relationship of fatigue and meaning in life in breast cancer survivors. In: The relationship of fatigue and meaning in life in breast cancer survivors. Oncology nursing forum. Year P: 653-60. - Tomich P L and Helgeson V S (2002) Five years later: a cross]sectional comparison of breast cancer survivors with healthy women. Psycho]oncology. 11 (2) 154-69. - Yaghmaie F (2009) Content validity and its estimation. Journal of Medical Education. 3 (1) 25-7
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".