Description of a training protocol to improve research reproducibility for dignity therapy: an interview-based intervention
Bibliographic record
Abstract
BACKGROUND: Dignity Therapy (DT) has been implemented over the past 20 years, but a detailed training protocol is not available to facilitate consistency of its implementation. Consistent training positively impacts intervention reproducibility. OBJECTIVE: The objective of this article is to describe a detailed method for DT therapist training. METHOD: Chochinov's DT training seminars included preparatory reading of the DT textbook, in-person training, and practice interview sessions. Building on this training plan, we added feedback on practice and actual interview sessions, a tracking form to guide the process, a written training manual with an annotated model DT transcript, and quarterly support sessions. Using this training method, 18 DT therapists were trained across 6 sites. RESULTS: The DT experts' verbal and written feedback on the practice and actual sessions encouraged the trainees to provide additional attention to eight components: (1) initial framing (i.e., clarifying and organizing of the patient's own goals for creating the legacy document), (2) verifying the patient's understanding of DT, (3) gathering the patient's biographical information, (4) using probing questions, (5) exploring the patient's story thread, (6) refocusing toward the legacy document creation, (7) inviting the patient's expression of meaningful messages, and (8) general DT processes. Evident from the ongoing individual trainee mentoring was achievement and maintenance of adherence to the DT protocol. DISCUSSION: The DT training protocol is a process to enable consistency in the training process, across waves of trainees, toward the goal of maintaining DT implementation consistency. This training protocol will enable future DT researchers and clinicians to consistently train therapists across various disciplines and locales. Furthermore, we anticipate that this training protocol could be generalizable as a roadmap for implementers of other life review and palliative care interview-based interventions.
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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 | 0.101 | 0.106 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.031 | 0.016 |
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".