My Zetterholm

Bio: My Zetterholm is an academic researcher from Linnaeus University. The author has contributed to research in topics: eHealth & Clinical decision support system. The author has an hindex of 1, co-authored 4 publications receiving 5 citations.

Digital Contact Tracing Applications during COVID-19: A Scoping Review about Public Acceptance

Abstract: Digital contact tracing applications (CTAs) have been one of the most widely discussed technical methods of controlling the COVID-19 outbreak. The effectiveness of this technology and its ethical justification depend highly on public acceptance and adoption. This study aims to describe the current knowledge about public acceptance of CTAs and identify individual perspectives, which are essential to consider concerning CTA acceptance and adoption. In this scoping review, 25 studies from four continents across the globe are compiled, and critical topics are identified and discussed. The results show that public acceptance varies across national cultures and sociodemographic strata. Lower acceptance among people who are mistrusting, socially disadvantaged, or those with low technical skills suggest a risk that CTAs may amplify existing inequities. Regarding determinants of acceptance, eight themes emerged, covering both attitudes and behavioral perspectives that can influence acceptance, including trust, privacy concerns, social responsibility, perceived health threat, experience of and access to technologies, performance expectancy and perceived benefits, and understanding. Furthermore, widespread misconceptions about the CTA function are a topic in need of immediate attention to ensure the safe use of CTAs. The intention-action gap is another topic in need of more research.

Current Knowledge about Providing Drug-Drug Interaction Services for Patients-A Scoping Review.

Abstract: Drug-drug interactions (DDIs) pose a major problem to patient safety. eHealth solutions have the potential to address this problem and generally improve medication management by providing digital services for health care professionals and patients. Clinical decision support systems (CDSS) to alert physicians or pharmacists about DDIs are common, and there is an extensive body of research about CDSS for professionals. Information about DDIs is commonly requested by patients, but little is known about providing similar support to patients. The aim of this scoping review was to explore and describe current knowledge about providing digital DDI services for patients. Using a broad search strategy and an established framework for scoping reviews, 19 papers were included. The results show that although some patients want to check for DDIs themselves, there are differences between patients, in terms of demands and ability. There are numerous DDI services available, but the existence of large variations regarding service quality implies potential safety issues. The review includes suggestions about design features but also indicates a substantial knowledge gap highlighting the need for further research about how to best design and provide digital DDI to patients without risking patient safety or having other unintended consequences.

Physio-digital Convergence : Aspects on Security

Abstract: The fast progressing development of mobile technologies and health applications has given rise to trends like health tracking and quantify self. This kind of mobile health applications can measure ...

Technology Mediated Nudging in a Mobile Health Context

Abstract: According to a vision for eHealth launched in 2016 by the Swedish Government, Sweden will be leading the way in using the potential of digitalization and eHealth to help people achieve a good and e ...

Patients’ view on information about medications: a pharmacy-based survey focusing on perceptions of pharmacists using a clinical decision support system

Abstract: The aim of this study was to describe patients’ view on information regarding their medication with focus on community pharmacists’ use of the clinical decision support system EES (electronic expert support system). This study was performed as a survey among patients who were collecting prescription medication at seven Swedish community pharmacies, with 281 respondents (response rate of 68%). Results show that patients receive information regarding their medication from many different sources with differences related to age, gender and native language. In general, most patients seemed satisfied with the information they had about their medicines, and with the information they got from pharmacists. Results show that awareness of how pharmacists work to improve medication safety, and knowledge about EES is low. However, results indicate that many patients have high trust in pharmacists, expect them to check for potential DRPs and are positive to pharmacists using EES more.

Health Belief Model

Abstract: This article presents an introduction to the Health Belief Model (HBM). The HBM states that the perception of a personal health behavior threat is influenced by at least three factors: general health values, interest and concern about health; specific beliefs about vulnerability to a particular health threat; and beliefs about the consequences of the health problem. Once an individual perceives a threat to his health and is simultaneously cued to action, if his perceived benefits outweighs his perceived costs, then the individual is most likely to undertake the recommended preventive health action. Key words: health promotion, health belief model, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, self-efficacy. Content available only in Romanian.

Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand

Abstract: With the constant mutation of COVID-19 variants, the need to reduce the spread should be explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread of the virus. This study aimed to explore factors affecting the actual use (AU) of the application through the use of machine learning algorithms (MLA) such as Random Forest Classifier (RFC) and Artificial Neural Network (ANN). An integrated Protection Motivation Theory (PMT) and the Unified Theory of Acceptance and Use of Technology (UTAUT) were considered. Using convenience sampling, a total of 907 valid responses from those who answered the online survey were voluntarily gathered. With 93.00% and 98.12% accuracy from RFC and ANN, it was seen that hedonic motivation and facilitating conditions were seen to be factors affecting very high AU; while habit and understanding led to high AU. It was seen that when people understand the impact and causes of the COVID-19 pandemic’s aftermath, its severity, and also see a way to reduce it, it would lead to the actual usage of a system. The findings of this study could be used by developers, the government, and stakeholders to capitalize on using the health-related applications with the intention of increasing actual usage. The framework and methodology used presented a way to evaluate health-related technologies. Moreover, the developing trends of using MLA for evaluating human behavior-related studies were further justified in this study. It is suggested that MLA could be utilized to assess factors affecting human behavior and technology used worldwide.

Understanding Digital Contact Tracing App Continuance: Insights from India

Abstract: Objectives Digital contact tracing (DCT) was touted as an effective alternative to lockdown and other restrictive measures in controlling the spread of the COVID-19 pandemic. Despite considerable investments in research and development, the usage of DCT apps was found to be phenomenally low across the world. In this context, the current study investigates the factors influencing citizens’ continuance intentions to use the DCT app. Methods A theoretical framework was developed by extending the Expectation-confirmation model (ECM) of Information system continuance with Technology trust theory and a contextual factor perceived security and privacy to predict citizens’ continuance intentions to use the DCT app. The model was empirically tested using data from a field survey of 206 actual users of a DCT app implemented in India. Results The findings reveal that user satisfaction, trust in government, and trust in technology are significant predictors of citizens’ continuance intention. The model demonstrates high explanatory power by explaining 57.8% of the variance of continuance intention. It also validates the role of perceived security and privacy and trust in technology in determining user satisfaction. Conclusion The study makes a theoretical contribution by extending the ECM framework to predict DCT app continuance behavior. The insights from the study could be helpful for developers and policymakers in crafting strategies to improve the usage of DCT apps during future disease outbreaks.

Using a Proximity-Detection Technology to Nudge for Physical Distancing in a Swedish Workplace During the COVID-19 Pandemic: Retrospective Case Study

Abstract: Background The recent COVID-19 pandemic has contributed to the emergence of several technologies for infectious disease management. Although much focus has been placed on contact-tracing apps, another promising new tactic is proximity tracing, which focuses on health-related behavior and can be used for primary prevention. Underpinned by theories on behavioral design, a proximity-detection system can be devised that provides a user with immediate nudges to maintain physical distance from others. However, the practical feasibility of proximity detection during an infectious disease outbreak has not been sufficiently investigated. Objective We aimed to evaluate the feasibility of using a wearable device to nudge for distance and to gather important insights about how functionality and interaction are experienced by users. The results of this study can guide future research and design efforts in this emerging technology. Methods In this retrospective case study, a wearable proximity-detection technology was used in a workplace for 6 weeks during the production of a music competition. The purpose of the technology was to nudge users to maintain their physical distance using auditory feedback. We used a mixed methods sequential approach, including interviews (n=8) and a survey (n=30), to compile the experiences of using wearable technology in a real-life setting. Results We generated themes from qualitative analysis based on data from interviews and open-text survey responses. The quantitative data were subsequently integrated into these themes: feasibility (implementation and acceptance—establishing a shared problem; distance tags in context—strategy, environment, and activities; understanding and learning; and accomplishing the purpose) and design aspects (a purposefully annoying device; timing, tone, and proximity; and additional functions). Conclusions This empirical study reports on the feasibility of using wearable technology based on proximity detection to nudge individuals to maintain physical distance in the workplace. The technology supports attention to distance, but the usability of this approach is dependent on the context and situation. In certain situations, the audio signal is frustrating, but most users agree that it needs to be annoying to ensure sufficient behavioral adaption. We proposed a dual nudge that involves vibration followed by sound. There are indications that the technology also facilitates learning how to maintain a greater distance from others, and that this behavior can persist beyond the context of technology use. This study demonstrates that the key value of this technology is that it places the user in control and enables immediate action when the distance to others is not maintained. This study provides insights into the emerging field of personal and wearable technologies used for primary prevention during infectious disease outbreaks. Future research is needed to evaluate the preventive effect on transmission and investigate behavioral changes in detail and in relation to different forms of feedback.