Do allogeneic bone marrow transplant candidates match coping to controllability of pre-treatment stressors?
Bibliographic record
Abstract
According to the Person x Situation theoretical framework, people adjust their coping to address the unique challenges of encountered stressors. Whether their strategies fit or appropriately address these stressor challenges influences adjustment. We examined the fit between pre-treatment stressors reported by hematological cancer patients awaiting allogeneic bone marrow transplantation (alloBMT) and their coping responses. Stressors were categorized as controllable versus uncontrollable; coping responses were categorized as problem- versus emotion-focused versus mixed (i.e., elements of both coping types). We hypothesized that patients would employ coping responses that fit the controllability of stressors (i.e., a match between stressor and coping response): problem-focused coping for controllable stressors and emotion-focused coping for uncontrollable stressors. In qualitative interviews, pre-BMT patients (10 men, 7 women) described encountered stressors and how they coped with them. Every reported stressor was linked with its associated coping response, resulting in a stressor-coping pair. We determined the proportion of total stressor-coping pairs in which the coping response matched the controllability of its linked stressor. Most stressor-coping pairs involving uncontrollable stressors showed the hypothesized match with emotion-focused or mixed coping. Contrary to hypotheses, fewer stressor-coping pairs that involved controllable stressors matched with problem-focused or mixed coping. Rather, these pairs were more likely to link controllable stressors with emotion-focused coping (i.e., mismatch between stressor controllability and type of coping). AlloBMT candidates may appraise the pre-treatment stage, globally, as permitting very little control. Coping efforts may consequently emphasize regulation of negative emotions (i.e., emotion-focused coping).
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".