Is dignity therapy feasible to enhance the end of life experience for people with motor neurone disease and their family carers?
Bibliographic record
Abstract
BACKGROUND: Development of interventions that address psychosocial and existential distress in people with motor neurone disease (MND) or that alleviate caregiver burden in MND family carers have often been suggested in the research literature. Dignity therapy, which was developed to reduce psychosocial and existential distress at the end of life, has been shown to benefit people dying of cancer and their families. These results may not be transferable to people with MND. The objectives of this study are to assess the feasibility, acceptability and potential effectiveness of dignity therapy to enhance the end of life experience for people with motor neurone disease and their family carers. METHODS/DESIGN: This is a cross-sectional study utilizing a single treatment group and a pre/post test design. The study population will comprise fifty people diagnosed with MND and their nominated family carers. Primarily quantitative outcomes will be gathered through measures assessed at baseline and at approximately one week after the intervention. Outcomes for participants include hopefulness, spirituality and dignity. Outcomes for family carers include perceived caregiver burden, hopefulness and anxiety/depression. Feedback and satisfaction with the intervention will be gathered through a questionnaire. DISCUSSION: This detailed research will explore if dignity therapy has the potential to enhance the end of life experience for people with MND and their family carers, and fill a gap for professionals who are called on to address the spiritual, existential and psychosocial needs of their MND patients and families. TRIAL REGISTRATION: ACTRN Trial Number: ACTRN12611000410954.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".