ArticleJMIR research protocols2025
Feasibility of Digitally Identifying and Minimizing Stressors in Palliative Care Workplaces by Measuring Stress Continuously for Nurses Through Wearable Sensors (DiPa): Protocol for a Prospective Cross-Sectional Study.
Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundNursing in palliative medicine combines primary patient care with the special challenges of this medical field (eg, handling the processes of dying, grief, and death). These cause high stress levels and burden on the nursing staff, resulting in an early exit from working life because of physical or psychological disorders like burnout.
objectiveDiPa (digitally identifying and minimizing stressors in palliative care) is a prospective study investigating the feasibility of measuring burden and its causes in palliative care using methods of subjective and objective stress detection. Based on these results, stress-reducing interventions are to be deduced and evaluated. In this paper, we present our study protocol.
methodsThe nursing staff of an inpatient university palliative hospital ward gathered data over 6 weeks. Each was equipped with a smart wristband and a smartphone that continuously measure physiological and ambient parameters throughout their working day. These objective data were enriched by subjective measurements: a questionnaire at the beginning of the study that assessed multiple potential stressful situations and constellations in the private and working environment as well as ecological momentary assessments (EMAs) during the workday. The EMAs were prompted by scanning near-field communication (NFC) tags placed at different locations on the ward. The ongoing data analyses will be processed using computer algorithms partly programmed specifically for this study and partly drawn from existing libraries, such as toolboxes for neurophysiological signal processing for Python. Comparisons between subjective and objective measures and group comparisons between variables of interest will be made using inferential statistics, including regression analyses and analyses of variance. Data analysis using machine learning algorithms will be implemented once sufficient data are gathered.
resultsThe study was funded in October 2019. As of July 2025, 12 of 18 nurses in the palliative care unit consented to participate in our study. We expect to start detailed data analysis in in the third quarter of 2025 and to finish and publish our results in 2026.
conclusionsThe DiPa study aims at testing the feasibility of measuring and merging subjective and objective stress parameters for palliative care nurses.
trial registrationGerman Register for Clinical Studies DRKS00024425; https://drks.de/search/en/trial/DRKS00024425/details. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63549.
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