RPD112 - Predictive correlates of Spiritual Distress: Advancing Whole-Person Palliative Care Through Risk Screening

Key Message : Interprofessional (IP) research is warranted to comprehensively address early and accurate identification of spiritual distress (SD) through SD risk screening. Analysis of hospice and palliative care datasets has generated an item pool for an SD risk screening instrument and positions the IP research team for subsequent phases of instrument development.

Abstract: Timely, whole-person care is achieved through swift interprofessional (IP) collaboration.1–3 In addressing spiritual distress (SD), this collaboration is paramount. However, early and accurate identification of SD remains inconsistent, even within hospice and palliative care (PC). Variability arises from limited recognition of SD risk factors, ineffective screening, and delayed or absent coordination among IP team members.4–7 Therefore, IP collaborative research is warranted to address these limitations through SD risk screening, which has significant implications for comprehensive, IP care during serious or terminal illness. As part of developing and validating a SD screening instrument for adult hospice and PC patients, this research aimed to identify variables with the strongest predictive relationships to SD and generate items for instrument construction and validation. The Hospice Admission Dataset (HAD) and PC dataset are secondary datasets of adult patients (≥18 years) admitted to home hospice (n = 3,484) or palliative care services (n = 4,887). Variables available in the HAD included age, gender, marital status, race/ethnicity, religion or spiritual practice, diagnosis, location of services, time from admission to comprehensive spiritual assessment, and pain level.4 The PC dataset included ESAS-FS symptom and SD data, age, gender identity, sexual orientation, race, ethnicity, Healthy Places Index (HPI) score, diagnosis, code status, marital status, and religion. Descriptive and relational analyses were conducted using Intellectus Statistics (α = 0.05). Significant correlates of SD (p ≤ .05) in these datasets included age (younger), marital status (single, divorced, separated), gender identity (non-binary), religion and/or spiritual practice, diagnosis (cancer, heart disease, pulmonary disease), code status (full code), location of hospice services (skilled nursing/long term care facility or inpatient hospital/hospice facility), pain level (moderate to severe), all ESAS-FS symptoms, and HPI scores. Findings expand the SD item pool and position the IP research team for subsequent phases of instrument development.

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