DIGNITY THERAPY FOR OLDER ADULTS WITH CANCER: COMMUNION FACILITATES DIGNITY
Bibliographic record
Abstract
Abstract Nearly 600,000 older Americans die a cancer-related death annually. Maintaining dignity is central to their quality of life. Dignity Therapy (DT; Chochinov, 2005) was designed to preserve dignity despite health declines. Patients report benefits of DT but mechanisms have not been empirically investigated. Grounded in gerontological life review research, DT involves therapists guiding patients to tell their unique life story and leave a legacy. This study investigates level of communion in the life story told in DT as a mechanism for DT efficacy. Communion reflects personal strivings for warm and close relationships (McAdams, 1986). Participants were 204 older cancer patients receiving outpatient palliative care (Mage= 66 years, SD = 7.43, 65% female) who participated in DT. Session narratives were audio-recorded and reliably (κ=.71–1) content-analyzed for communion themes (McAdams, 2001). Participants completed pre-post measures, including the Dignity Impact Scale. Mediation analyses showed significance for the direct effect of Dignity Impact from pre- to post-test, B = .50(.06), p < .001 as well as for paths from pre-test Dignity to Communion, B = .20(.08), p <.01 and from Communion to post-test Dignity, B = .20(.06), p = .001. Sobel test for the mediation effect of Communion between pre- to post-test Dignity was z = 2.06(.02), p = .039; point effect = .04. Participating in DT is shown to increase older cancer patients’ feelings of dignity. That is partially explained by the extent to which these older adults tell a life story rich in communion, reflecting on loving, caring relationships, during DT.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".