Ignite Creation Date:
2025-12-25 @ 5:03 AM
Ignite Modification Date:
2025-12-26 @ 4:05 AM
Study NCT ID:
NCT07173218
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-09-15
First Post:
2025-09-08
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
ICU Nurses' Perspectives on a Nursing Workload Dashboard
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 60}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2025-10-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2026-02-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-08', 'studyFirstSubmitDate': '2025-09-08', 'studyFirstSubmitQcDate': '2025-09-08', 'lastUpdatePostDateStruct': {'date': '2025-09-15', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-09-15', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2026-01-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Implementation outcomes acceptance, adoptability, appropriateness and fidelity', 'timeFrame': '1 and 3 months after implementation', 'description': "The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the nurses' perspectives will be calculated."}]}, 'conditionsModule': {'keywords': ['Acceptance', 'Appropriateness', 'Feasibility', 'Nursing workload', 'Dashboard', 'Intensive Care Unit (ICU)'], 'conditions': ['Nursing Workload']}, 'descriptionModule': {'briefSummary': "Increasing patient complexity, staffing shortages, and administrative burdens have intensified nurses' workloads, contributing to burnout and reduced job satisfaction. These challenges were particularly evident in the intensive care units (ICU) during the COVID-19 outbreak. With the growing healthcare demand in front of us, it is essential to understand and manage perceived workload effectively to maintain high-quality care and promote staff well-being. A real-time overview of nursing workload may facilitate the identification of patients requiring additional support and enable more effective distribution of workload among nurses during shifts. A dashboard has therefore been developed for use in the ICU to provide an overview of the patients at the unit and their corresponding nursing workload. To assess whether this dashboard is fit for purpose, this study aims to evaluate nurses' perspectives on its implementation, focusing on acceptance, adoptability, appropriateness, and fidelity. Additionally, the model for the calculation of the nursing workload will be assessed in terms of its alignment with ICU nurses' perceived workload and its potential for automation with artificial intelligence (AI)."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'ICU nurses from Erasmus Medical Center', 'eligibilityCriteria': 'Inclusion Criteria:\n\n* An ICU nurse within the Erasmus Medical Center\n* Informed-consent is signed by the ICU nurse before the interview and survey'}, 'identificationModule': {'nctId': 'NCT07173218', 'briefTitle': "ICU Nurses' Perspectives on a Nursing Workload Dashboard", 'organization': {'class': 'OTHER', 'fullName': 'Erasmus Medical Center'}, 'officialTitle': "Nurses' Perspectives on the Implementation of a Nursing Workload Dashboard in the Intensive Care Unit", 'orgStudyIdInfo': {'id': '14382'}}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Willemijn Berkhout', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'MSc', 'investigatorFullName': 'Willemijn Berkhout', 'investigatorAffiliation': 'Erasmus Medical Center'}}}}