The spiritual distress assessment tool: an instrument to assess spiritual distress in hospitalised elderly persons
Bibliographic record
Abstract
BACKGROUND: Although spirituality is usually considered a positive resource for coping with illness, spiritual distress may have a negative influence on health outcomes. Tools are needed to identify spiritual distress in clinical practice and subsequently address identified needs. This study describes the first steps in the development of a clinically acceptable instrument to assess spiritual distress in hospitalized elderly patients. METHODS: A three-step process was used to develop the Spiritual Distress Assessment Tool (SDAT): 1) Conceptualisation by a multidisciplinary group of a model (Spiritual Needs Model) to define the different dimensions characterizing a patient's spirituality and their corresponding needs; 2) Operationalisation of the Spiritual Needs Model within geriatric hospital care leading to a set of questions (SDAT) investigating needs related to each of the defined dimensions; 3) Qualitative assessment of the instrument's acceptability and face validity in hospital chaplains. RESULTS: Four dimensions of spirituality (Meaning, Transcendence, Values, and Psychosocial Identity) and their corresponding needs were defined. A formalised assessment procedure to both identify and subsequently score unmet spiritual needs and spiritual distress was developed. Face validity and acceptability in clinical practice were confirmed by chaplains involved in the focus groups. CONCLUSIONS: The SDAT appears to be a clinically acceptable instrument to assess spiritual distress in elderly hospitalised persons. Studies are ongoing to investigate the psychometric properties of the instrument and to assess its potential to serve as a basis for integrating the spiritual dimension in the patient's plan of care.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".