Examining Mental Workload Relating to Digital Health Technologies in Health Care: Systematic Review.

BACKGROUND: The workload in health care is increasing and hence, mental health issues are on the rise among health care professionals (HCPs). The digitization of patient care could be related to the increase in stress levels. It remains unclear whether the health information system or systems and digital health technologies (DHTs) being used in health care relieve the professionals or whether they represent a further burden. The mental construct that best describes this burden of technologies is mental workload (MWL). The measurement methods of MWL are particularly relevant in this sensitive setting. OBJECTIVE: This review aimed to address 2 different but related objectives: identifying the factors that contribute to the MWL of HCPs when using DHT and examining and exploring the applied assessments for the measurement of MWL with a special focus on eye tracking. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 statement, we conducted a systematic review and processed a literature search in the following databases: MEDLINE (PubMed), Web of Science, Academic Search Premier and CINAHL (EBSCO), and PsycINFO. Studies were eligible if they assessed the MWL of HCPs related to DHT. The review was conducted as per the following steps: literature search, article selection, data extraction, quality assessment (using the Standard Quality Assessment Criteria for Evaluation Primary Research Papers From a Variety of Fields [QualSyst]), data analysis, and data synthesis (narrative and tabular). The process was performed by 2 reviewers (in cases of disagreement, a third reviewer was involved). RESULTS: The literature search process resulted in 25 studies that fit the inclusion criteria and examined the MWL of health care workers resulting from the use of DHT in health care settings. Most studies had sample sizes of 10-50 participants, were conducted in the laboratory, and had quasi-experimental or cross-sectional designs. The main results can be grouped into two categories: assessment methods and factors related to DHT that contribute to MWL. Most studies applied subjective methods for the assessment of MWL. Eye tracking did not play a major role in the selected studies. The factors contributing to a higher MWL were clustered into organizational and systemic factors. CONCLUSIONS: Our review of 25 papers shows a diverse assessment approach toward the MWL of HCPs related to DHT as well as 2 groups of relevant contributing factors to MWL. Our results are limited in terms of interpretability and causality due to methodological weaknesses of the included studies and may be limited by some shortcomings in the search process. Future research should concentrate on adequate assessments of the MWL of HCPs dependent on the setting, the evaluation of quality criteria, and further assessment of the contributing factors to MWL. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271.

[Awareness and Use of Digital Health Services in Germany: A Cross-sectional Study Representative of the Population]. / Bekanntheit und Nutzung von digitalen Gesundheitsangeboten in Deutschland: eine bevölkerungsrepräsentative Querschnittsuntersuchung.

OBJECTIVES: In light of the current efforts of health policy to implement eHealth, the question arises which sections of the population already use online self-help in order to tailor them to users' needs. The present study aims to determine the differences in the use of health information and psychological online counseling based on socio-demographic variables, health status and previous illnesses. METHODS: The basis for the cross-sectional data analyses using logistic regression analysis was the innovation sample of the German socio-economic panel. Data were collected from September 2016 to February 2017, with 4802 participants aged between 17-95 years. RESULTS: Fifty-five percent of the sample searched for health information on the Internet, while 1.1% had experience with online counseling. Logistic regression analyses showed that online search for information was significantly determined by age (Odds Ratio (OR)=0.96; 95-%-CI=0.96-0.97), gender (OR=1.20; 95-%-CI=1.05-1.36), awareness of Internet therapy (OR=2.57; 95-%-CI=2.20-3.00), experience with psychotherapy (OR=1.40; 95-%-CI=1.16-1.69) and the diagnosis of asthma (OR=1.14; 95-%-CI=1.01-1.29) or stroke (OR=0.66; 95-%-CI=0.52-0.84). Regarding the use of online counseling, awareness of Internet therapy and experience with face-to-face psychotherapy proved to be significant determinants. CONCLUSION: For the first time, a reliable picture has become available of the determinants of the awareness of internet therapy and online self-help utilization among the German public that should enable target-group-specific strategies to improve the care situation.

How Does Mental Workload Influence the Adoption of Clinical Information Systems: An Exploratory Study.

Mental workload and technology acceptance are relevant factors that relate to use behavior and performance. Studies show a potential moderating effect of mental workload on predictors of technology acceptance. Aim of this study was the investigation of predictors of technology acceptance (UTAUT) related to clinical information systems and their relation to mental workload. This quasi-experimental study with 48 participants used the following measures: NASA TLX and UTAUT questionnaire. Participants had to perform three tasks on a clinical information system as well as four task-levels of the n-back task with increasing difficulty. Analyses show a high level of technology acceptance (M=3.82, SD=.76) and confirm performance expectancy as the most relevant predictor of behavioral intention (ß=.48, p<.001). A linear regression showed that a high level of mental workload has an influence on performance expectancy (F1,46=8.438, p<.05). The study shows an influence of mental workload on acceptance, the strength and role of which (e.g. moderation) needs to be further investigated, especially in the context of other determinants.

[Perception and mindfulness-based occupational therapy in people with mental disorders-A retrospective observational study on the SELWA-treatment]. / Wahrnehmungs- und achtsamkeitsbasierte Ergotherapie bei Menschen mit psychischen Störungen ­ Eine retrospektive Beobachtungsstudie zur Anwendung der SELWA-Behandlung.

During occupational therapeutic treatment of clients with mental disorders, perception and mindfulness-based techniques are used. However, little is known regarding relevant outcomes. Aim of the present study is to describe the results of a perception and mindfulness-based occupational therapeutic intervention (self-control techniques using perception-based methods (SELWA®) by S. Thielen) regarding the outcomes occupational performance and satisfaction in self-care, productivity and leisure, as well as concentration. The data of 28 clients (22 â™€, 6 â™‚; mean age = 42.8 (±SD 14.7) years) with mental disorders, that were collected before and after prescribed occupational therapeutic treatment, were analyzed. The outcomes were quantified using the Canadian Occupational Performance Measure (COPM) and the revision test, respectively. Significance of changes after the intervention was tested using the Wilcoxon-Signed Rank Test (p < 0.05). Effect sizes Cohen's dz and r were determined to evaluate the meaningfulness of changes. The occupational performance as well as the satisfaction in the COPM improved significantly after the therapeutic intervention (p < 0.001; dz = 2.37, r = 0.77 and dz = 2.24, r = 0.75). Moreover, the clients improved significantly in the revision test after the therapeutic intervention (p < 0.001; dz = 0.65, r = 0.31). Clients with mental disorders seem to benefit meaningfully from the SELWA®-treatment by S. Thielen regarding occupational performance and satisfaction in self-care, productivity and leisure. Furthermore, a moderate improvement of concentration seems to occur after the therapeutic intervention.

Examining the Mental Workload Associated With Digital Health Technologies in Health Care: Protocol for a Systematic Review Focusing on Assessment Methods.

BACKGROUND: The workload in health care is high; physicians and nurses report high stress levels due to a demanding environment where they often have to perform multiple tasks simultaneously. As a result, mental health issues among health care professionals (HCPs) are on the rise and the prevalence of errors in their daily tasks could increase. Processes of demographic change are partly responsible for even higher stress levels among HCPs. The digitization of patient care is intended to counteract these processes. However, it remains unclear whether these health information systems (HIS) and digital health technologies (DHT) support the HCPs and relieve stress, or if they 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 levels of intrusiveness and sensitivity. The method of eye tracking could be a useful way to measure MWL directly in the field. OBJECTIVE: The systematic review aims to address the following questions: (1) In which manner do DHT contribute to the overall MWL of HCPs? (2) Can we observe a direct or indirect effect of DHT on MWL? (3) Which aspects or factors of DHT contribute to an increase in MWL? (4) Which methods/assessments are applied to measure MWL related to HIS/DHT? (5) What role does eye tracking/pupillometry play in the context of measuring MWL? (6) Which outcomes are being assessed via eye tracking? METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement, we will conduct a systematic review. Based on the research questions, we define keywords that we then combine in search terms. The review follows the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis, and data synthesis. RESULTS: We expect results as well as a finalization of the review in the summer of 2021. CONCLUSIONS: This review will evaluate the impact of DHT on the MWL of HCPs. In addition, assessment methods of MWL in the context of digital technologies will be systematically analyzed. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29126.

Which Factors of Digitisation Bias the Work-Related Stress of Healthcare Employees? A Systematic Review.

BACKGROUND: Digitisation affects our working environment. It demands new cognitive and digital skills of healthcare employees. Technostress and burnout are more likely to occur due to the additional workload. AIM: Objective is the identification of determinants affecting work related technostress. METHODOLOGY: We carried out a systematic review according to the PRISMA statement. For the identification of the digital factors, we applied an inductive content analysis based on Mayring's theory. RESULTS: Included studies showed the following factors to be relevant for coping with technostress: autonomy, competence, understanding of roles, time pressure, attitude, security and ergonomics. The emerging factors serve the regulation of stress in the healthcare system and contribute to better healthcare and higher occupational safety.

Mental Workload Relating Health Information System - A Literature Review.

BACKGROUND: Assessing Mental Workload related to Health Information Systems can help to analyze weak points of the use of Health Information Systems and in health care work processes. Our objectives were to give an overview of current research and applied measurement methods as well as gaining insights into influencing factors of mental workload on the use of health information systems and vice versa. METHODS: We applied a structured literature research by searching for "mental workload" on PubMed. Studies were included into our review if they assessed related to Health Information Systems. RESULTS: The research in PubMed led to 124 articles, resulting in 17 papers taken into in-depth analyses. We identified three categories referring to different study design types. Additionally, articles showed that mental workload was influenced by using health information systems and vice versa. DISCUSSION: The review was limited to only one database but revealed that future research with sociotechnical focus including mental workload is necessary. CONCLUSION: In contrast to the high relevance only a few articles address mental workload in Health Information systems. The quality of the studies in terms of evidence and external validity appears to be largely in need of development and should be improved in ongoing research.

Relating Factors for Acceptance of Health Care Technology: Focus on Mental Workload.

Medical information systems and care robots are two typical examples of human computer interaction in health care. Although used in a stressful environment, effects on mental workload and acceptance are hardly evaluated. We conducted an experimental design including collaborative robotics and eye tracking in a nursing situation to test the practicability and plausibility of eye tracking as a measuring method for workload. Results showed that eye tracking is feasible if context factors are adjusted. Data reduction and classification of tasks are necessary.

Acceptance of mHealth Apps for Self-Management Among People with Hypertension.

BACKGROUND: Mobile health applications (mHealth apps) have the potential to help patients with chronic conditions such as hypertension by supporting self-management activities in daily life. However, the uptake of mHealth apps remains poor among patients. To improve the utilization of mHealth apps for hypertension, the analysis of the behavioral intention to use such applications must consider personality traits and illness-related perceptions. METHOD: Adults with hypertension in Germany and Austria filled out a self-administered questionnaire in a cross-sectional study based on the UTAUT-model in order to identify potential predictors for the behavioral intention to use mHealth applications as an indicator for their early acceptance. Beyond the four core determinants of acceptance of the UTAUT (performance expectancy, effort expectancy, social influence and facilitating conditions), self-efficacy, openness to experience and perceived health threat were analyzed as predictors. RESULTS: 145 participants (mean age 52.51 years, SD 14.33; 60% female) completed the survey. Acceptance was moderate on average (M = 3.26, SD = 1.07, min 1 to max 5). In a multiple hierarchical regression, performance expectancy and effort expectancy were confirmed as significant predictors of acceptance (step 1, R2 = .57, p < .001), while self-efficacy could not be confirmed (step 2, p = .87). In addition, perceived health threat (ß = .12, p < .05) and openness to experience (ß = .22, p < .001) had a significant influence on acceptance of mHealth apps for hypertension (step 3, overall model with R2 = .62). Age showed a negative association with the intention to use (ß = .22, p = .005) while no influence of gender could be found (p = .06). CONCLUSION: Above expectations regarding effectiveness and usability, openness to experience and perceived health threat make a significant contribution in predicting the acceptance of mHealth solutions in the field of chronic diseases.