A mixed-methods pilot study of ‘LIFEView’ audiovisual technology: Virtual travel to support well-being and quality of life in palliative and end-of-life care patients
Bibliographic record
Abstract
Background:There is evidence that psychosocial and spiritual interventions of short duration, such as reminiscence therapy, provide positive impacts on quality of life and emotional and existential well-being in adults receiving palliative care.Aim:To determine (1) the feasibility of integrating ‘LIFEView’, a video-based software with >1600 videos of world destinations, in palliative care settings, and (2) positive, neutral or harmful effects of using ‘LIFEView’ videos.Design:A mixed-methods pre–post intervention pilot study was conducted to collect feasibility and preliminary data on physical and psychological symptoms, physiological indicators, spiritual well-being and aspects of quality of life.Setting/participants:Adult patients on an inpatient palliative care unit or receiving care from a community palliative care consultation team who were capable of providing consent and completing the outcome measures were eligible participants.Results:Overall, 27/41 (66%) participants took part in the study. Feasibility criteria, including participant acceptability, low participant burden, tool completion rate and retention rate, were fulfilled, though challenges were experienced with recruitment. Modest improvements, though non-significant, were shown on preliminary data collected on physical and psychological symptoms using the Edmonton Symptom Assessment System–revised, spiritual well-being assessed by the 12-item Functional Assessment of Chronic Illness Therapy – Spiritual Well-Being scale and physiological measurements. Qualitative analysis revealed five themes: motivations for using ‘LIFEView’, perceptions of the technology, reminiscence, ‘LIFEView’ as an adaptable technology and ongoing or future use.Conclusion:A future adequately powered study to investigate the impacts of ‘LIFEView’ on patient well-being and quality of life appears to be feasible.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".