The experience of medical communication in adults with acute leukemia: Impact of age and attachment security
Bibliographic record
Abstract
BACKGROUND: Health care providers' (HCPs) communication with cancer patients provides both information and support. Younger patient age and greater difficulty accepting support (attachment security) have been linked to poorer communication experiences with HCPs. The present secondary data analysis examined the impact of age group and attachment security on perceived communication problems with HCPs in adults with acute leukemia (AL). METHODS: The sample included 95 younger (age < 40 years) and 225 older (age ≥ 40 years) patients with newly diagnosed or recently relapsed AL. We assessed avoidant and anxious attachment security (reluctance to accept support and fear of its unavailability, respectively) with the modified 16-item Experiences in Close Relationships Scale. The impact of age group and attachment security on perceived communication problems, measured with the Cancer Rehabilitation Evaluation System-Medical Interaction Subscale, was assessed based on the presence and extent of communication problems. RESULTS: Younger patients (OR = 1.79-1.82, P = .030) and those with greater avoidant (OR = 1.44, P = .001) or anxious attachment (OR = 1.38, P = .009) were more likely to report communication problems. A similar relationship was found between age (β's = -.17-.19, P = .015-.025), avoidant (β = .29, P = .013), or anxious attachment (β = .17, P = .031), and the extent of communication problems. A significant age-group × avoidant-attachment interaction (β = -.31, P = .008) suggested that more avoidant attachment was associated with more perceived communication problems in the younger but not in the older group. CONCLUSIONS: Younger patients with AL, especially those more reluctant to seek or accept support, perceive more communication problems with their HCPs than older patients. Greater attention by HCPs to their communication with younger patients is needed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".