Assessing the psychological predictors of benefit finding in patients with head and neck cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Some individuals are able to gain psychological benefits from illness and adversity, such as a greater sense of purpose and closer relationships, termed 'benefit finding' (BF). The main aim of this study was to explore the extent to which BF is reported in patients with head and neck cancer (HNC). Secondary aims were to establish the relationships between BF, other patient-reported outcomes and predictive factors such as coping strategy and level of optimism. METHODS: This repeat measures study was conducted with 103 newly diagnosed patients with HNC. Self-completion questionnaires were used to assess BF pre-treatment and 6 months after treatment and pre-treatment coping, optimism, quality of life, anxiety and depression. Sixty-eight patients (66%) completed follow-ups. RESULTS: Moderate to high levels of BF were reported. Anxiety, depression and quality of life were not related to BF. Regression models of BF total score and three new factor analysed BF scales indicated that use of emotional support and active coping strategies were predictive of finding more positive consequences. Optimism, living with a partner and higher educational attainment were also found to have a protective effect. The amount of variance in BF explained by these five pre-treatment factors ranged from 32 to 46%. CONCLUSIONS: These findings demonstrate that both dispositional and potentially modifiable factors, in particular optimism and coping strategies, were associated with patients identifying positive consequences of a diagnosis of HNC. To maximise patient's longer-term resilience and adaptation, components of BF, either directly or via coping strategies, could be targeted for intervention.
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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 | 0.000 |
| 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 it