S2-1 Keynote lecture: developing educational and clinical models in interprofessional spiritual care: an essential component of palliative care
Bibliographic record
Abstract
<h3></h3> This session will describe pivotal efforts that have led to models and national and global guidelines for interprofessional spiritual care led by the George Washington University’s Institute for Spirituality and Health (GWish). The first is developing innovative curricula in spirituality and health for medical schools in the United States, resulting in National Consensus-based competencies for spirituality and health curricula to better prepare them to provide spiritual care. From this work, an innovative professional development educational program called GWish Reflection Rounds (GRR), was developed as part of professional development of medical students to help them reflect on their relationships with patients and how that impacts their awareness of their own call to serve others who suffer. The second major efforts have been in developing global consensus-based models and guidelines for interprofessional spiritual care. These consensus conferences defined spirituality broadly as a search for meaning, purpose and transcendence, and a connection to the significant or sacred, and provided recommendations for the field of palliative care. These guidelines are based on a generalist-specialist model of care where all clinicians who care for patients with serious and chronic illness are the generalists and the spiritual care professionals are the experts. These guidelines in part contributed to the spiritual domain of the WHA resolution on palliative care and served as the basis of a new initiative called ISPEC—Interprofessional Spiritual Care Education Curriculum, a national and international project to provide spiritual care education to clinicians in partnership with spiritual care professionals. Finally, this session will review current global efforts in collaboration with chaplaincy organizations and health systems to prioritize spiritual care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".