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Record W4416595828 · doi:10.1177/10966218251399600

Mechanisms of Dignity Therapy: Positive Outcomes in Older Cancer Patients

2025· article· en· W4416595828 on OpenAlexaff
Susan Bluck, Mary Kate Koch, Yingwei Yao, Alyssa Crowe, Kiana Cogdill-Richardson, Harvey Max Chochinov, Diana J. Wilkie, Emily L. Mroz, Sheri Kittelson, Linda L. Emanuel, Carma L. Bylund

Bibliographic record

VenueJournal of Palliative Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsDignityEmpathyNarrativeIntervention (counseling)Narrative therapyExistentialismPalliative careQuality of life (healthcare)

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate two mechanisms, patient-level narrative richness and provider-patient empathy, of positive outcomes following Dignity Therapy, to focus provider training and intervention delivery. BACKGROUND: Dignity Therapy is a brief reminiscence-based psychotherapeutic intervention designed to help seriously ill patients preserve dignity, reduce distress, and improve quality of life. Identifying mechanisms through which the therapy works can improve training and delivery of this increasingly popular intervention. METHODS: = 7.45 years; 66% women) from palliative care programs across the United States completed Dignity Therapy with a trained provider. Transcripts of their interview sessions were examined using interactional analyses to determine provider-level empathic communication. Transcripts were also content-analyzed for patient-level narrative richness. Changes in dignity, peaceful awareness of prognosis, and completion of existential tasks from pre- to postintervention were assessed. RESULTS: = 0.009) even when accounting for patient demographics. Providers' level of empathic communication did not affect patient outcomes at traditional significance levels. Results were not moderated by patients' symptom severity. CONCLUSIONS: Dignity Therapy benefits patients most when they richly engage in the process, narrating their life story and describing their legacy with elements of communion, meaning, and purpose. Future research might aim to follow up on forms of empathy or other provider behavior that elicit rich narratives during therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.376
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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