Examining Mental Workload Relating to Digital Health Technologies in Health Care: A Systematic Review focusing on Assessment Methods (Preprint)

BACKGROUND The workload in healthcare is steadily increasing – healthcare professionals (HCP) report stress and a very demanding environment. As a result, mental health issues are on the rise among HCP, the proneness to errors in tasks could increase. The digitization of patient care is intended to counteract processes of demographic change, that could be in relation to high stress levels. It remains unclear whether the Health Information System(s) (HIS) and digital health technologies (DHT) used, relieve the professionals or even represent a further burden. The mental construct that describes this burden of technologies is Mental Workload (MWL). Work in the clinic can be viewed as working in safety-critical environments: Particularly in this sensitive setting, the measurement methods of MWL are relevant - mainly due to their strongly differing intrusiveness and sensitivity. The method of eye tracking could provide a useful way to measure MWL directly in the field. OBJECTIVE The systematic review addresses two different, but related objectives. 1. In which manner do DHT contribute to the overall MWL of health care workers: which aspects or factors of DHT contribute to an increase of MWL? 2. Which methods/ assessments are applied to measure MWL related to HIS/ Digital Technologies? 2.1. Which role does Eye tracking/ Pupillometry play in context of measure? 2.2. Which outcomes are being assessed via eye tracking? METHODS Following the PRISMA statement, we conducted a systematic review. Based on the research questions, we defined keywords that were combined to search terms. The review followed the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis and data synthesis. RESULTS The literature search process resulted in 25 included studies that have studied the resulting MWL of healthcare workers from using DHT in health care settings. The main results can be grouped by two categories: assessment methods and factors of DHT contributing to MWL. A major part of the studies applied subjective methods for the assessment of MWL (Most applied method: NASA TLX). Eye tracking didn’t play a relevant role. The factors contributing to a higher MWL were clustered by organizational and system factors. CONCLUSIONS Our review of 25 papers shows a diverse assessment approach of MWL related to DHT of HCPs as well as two groups of relevant contributing factors to MWL Although methodological biases were identified, we promote further research concentrating on adequate assessments for relevant settings. We also like to promote the evaluation of quality criteria. CLINICALTRIAL PROSPERO registration: CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271&ID=CRD42021233271 Protocol: JMIR Res Protoc 2021;10(8): e29126; https://doi.org/10.2196/29126