Development of a Clinical Guide for Identifying Spiritual Distress in Family Members of Patients in the Intensive Care Unit
Bibliographic record
Abstract
Background: Spirituality is important for many family members of patients in the intensive care unit (ICU). Clinicians without training in spiritual care experience difficulty identifying when family members are experiencing distress of a spiritual nature. Objective: The purpose of this study was to develop a guide to help clinicians working in the ICU identify family members who may benefit from specialized spiritual support. Design: Cross-sectional study. Setting/Subjects: A national sample of spiritual health practitioners, family members, and ICU clinicians. Subjects: A panel of 21 spiritual health practitioners participated in a modified Delphi process to achieve consensus on items that suggest spiritual distress among family members of patients in the ICU through three rounds of remote review followed by an in-person conference and a final round of panelist feedback. Feedback on the final set of items was obtained from an end-user group of four family members and six ICU clinicians. Measurements: Quantitative data were summarized with descriptive statistics. Content analysis was used to analyze written comments. Results: A total of 220 items were iteratively reviewed and rated by panelists. Forty-six items were identified as essential for inclusion and developed into a clinical guide, including an introduction ( n = 1), definitions ( n = 2), risk factors ( n = 10), expressed concerns ( n = 12), emotions ( n = 7) and behaviors ( n = 7) that may suggest spiritual distress, questions to identify spiritual needs ( n = 6), and introducing spiritual support ( n = 1). Conclusions: We have developed an evidence-informed clinical guide that may help clinicians in the ICU identify family members experiencing spiritual distress.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".