Ludwig Boltzmann Institute for Health Technology Assessment

Telehealth systems have shown to facilitate lifestyle changes like an increase in physical activity. Therefore, an easily quantifiable measure of physical activity levels for both assessing a patient's status quo and tracking physical activity development is needed. The aim of this work was to map semi-structured activities reported as type-intensity-duration triplets in the DiabMemory telehealth system to Metabolic Equivalents of Task (METs). The activity data of 947 telehealth patients were analyzed to create a mapping table between type-intensity pairs and MET values from a preexisting compendium. Additionally, the distribution of activity types and resulting MET scores was evaluated. Combining the MET scores with the duration resulted in the quantified activity measure (MET-minutes). A significant difference in the MET-minutes per activity type (p < 0.0001) was identified. In the future, our method of mapping semi-structured data to METs will serve as a support the evaluation of the effectiveness of DiabMemory.

Regular physical activity constitutes a crucial secondary prevention behaviour for people who have had an acute cardiac event. Nonetheless, sustained physical activity levels of the cardiac population are in need of improvement. Applying the Intervention Mapping approach, we describe a generic logic model for developing behavioural interventions to increase and maintain physical activity among those who have had an acute cardiac event. The development of the logic model was both data- and theory-driven, which enhances the effectiveness of the behavioural interventions developed using the logic model. The logic model may additionally be used to indicate research gaps, to solidify the underpinnings of already established behavioural interventions, and as a reflection tool for healthcare providers and individuals' behaviour. A generic logic model like the one presented here can be developed for key behavioural outcomes related to preventing other highly relevant health problems. We further recommend that future empirical research focuses on determinants of social support provision for cardiac patients' physical activity.

This work explores the interaction design around the approach of making use of otherwise idle waiting times to perform short bouts of exercise. We provide insights on (1) how digital tools can support the utilisation of waiting times for physical activity, and (2) how an application that makes exercises suggestions in a manner designed to be frictionless is experienced by users. We developed the Active Waiting (AW) app, a prototype for addressing physical activity barriers such as time and effort, as well as an additional barrier related to the social awkwardness linked to performing exercises in public. AW was iteratively evaluated through guerrilla testing and a field study. Study participants appreciated the application for making waiting times more interesting, offering viable exercise suggestions, encouraging the taking of additional (active) breaks, and most of all the possibility to select unobtrusive exercises. The study indicates that unobtrusive and easily accessible exercises integrated into waiting times can effectively reduce barriers to physical activity. While the app was well-received for enabling meaningful use of waiting time, future work could explore more proactive approaches to encourage consistent usage in diverse daily contexts.

This paper explores the viable design of collaborative game elements to promote physical activity in the context of digital health interventions. We investigate the role of social relatedness in motivating users to engage in achieving step-count goals. The study utilised a minimalistic multiplayer step counter game called Shared Achievements, implementing group-based "collaborative effort" mechanics. Participants used the application with acquainted team members for two weeks. Outcomes highlight the importance of communication and shared goals in fostering motivation and adherence. While group dynamics and social support enhanced engagement, challenges such as unequal contributions and competitive pressures were identified. The study underscores the need for careful design considerations to balance competition and collaboration, suggesting digital health tools can benefit from social achievement mechanics and incorporating motivational strategies tailored to different user preferences.

BackgroundThere has been a surge in the development of apps that aim to improve health, physical activity (PA), and well-being through behavior change. These apps often focus on creating a long-term and sustainable impact on the user. Just-in-time adaptive interventions (JITAIs) that are based on passive sensing of the user’s current context (eg, via smartphones and wearables) have been devised to enhance the effectiveness of these apps and foster PA. JITAIs aim to provide personalized support and interventions such as encouraging messages in a context-aware manner. However, the limited range of passive sensing capabilities often make it challenging to determine the timing and context for delivering well-accepted and effective interventions. Ecological momentary assessment (EMA) can provide personal context by directly capturing user assessments (eg, moods and emotions). Thus, EMA might be a useful complement to passive sensing in determining when JITAIs are triggered. However, extensive EMA schedules need to be scrutinized, as they can increase user burden.ObjectiveThe aim of the study was to use machine learning to balance the feature set size of EMA questions with the prediction accuracy regarding of enacting PA.MethodsA total of 43 healthy participants (aged 19‐67 years) completed 4 EMA surveys daily over 3 weeks. These surveys prospectively assessed various states, including both motivational and volitional variables related to PA preparation (eg, intrinsic motivation, self-efficacy, and perceived barriers) alongside stress and mood or emotions. PA enactment was assessed retrospectively via EMA and served as the outcome variable.ResultsThe best-performing machine learning models predicted PA engagement with a mean area under the curve score of 0.87 (SD 0.02) in 5-fold cross-validation and 0.87 on the test set. Particularly strong predictors included self-efficacy, stress, planning, and perceived barriers, indicating that a small set of EMA predictors can yield accurate PA prediction for these participants.ConclusionsA small set of EMA-based features like self-efficacy, stress, planning, and perceived barriers can be enough to predict PA reasonably well and can thus be used to meaningfully tailor JITAIs such as sending well-timed and context-aware support messages.

Becoming a parent, while often perceived as a joyous event, can also be a vulnerable life transition, with approximately one in five mothers experiencing perinatal mental illness. Peer support is recommended for its preventive and therapeutic benefits. However, relevant program components of perinatal mental health peer support remain to be identified. This review aims to (1) identify peer support programs in perinatal mental health through existing reviews and to (2) synthesize the components of these programs. A systematic literature review guided by PRISMA was conducted searching four databases, supplemented by hand searches. The Template for Intervention Description and Replication (TIDieR) checklist facilitated the systematic extraction and synthesis of program components. Eleven peer support programs were identified from three reviews, largely conducted in English-speaking countries. The identified reviews highlight the benefits of peer support in perinatal mental health. Key components of individual programs were contextual background, materials, provider training and support, delivery modes and locations, and evaluation. Sharing lived experience and providing flexible support were central to all programs. Aspects of flexibility, authenticity and the challenges of program evaluation in peer support must be considered. Findings can now inform future planning and implementation efforts of peer support programs in periantal mental health.

BackgroundSmartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments.ObjectiveWe examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts.MethodsFollowing the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges.ResultsWe retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition.ConclusionsOur findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.

BackgroundTranexamic acid is an antifibrinolytic drug that is commonly administered for obstetric haemorrhage. Conventional viscoelastic tests are not sensitive to tranexamic acid, but the novel ClotPro® TPA-test can measure tranexamic acid-induced inhibition of fibrinolysis. We aimed to evaluate the TPA-test in pregnant and non-pregnant women. MethodsWe performed an in vitro study of whole blood samples spiked with tranexamic acid from pregnant women in the first, second, and third trimester (n=20 per group) and from non-pregnant women (n=20). We performed ClotPro TPA-tests of whole blood sample and ClotPro EX-tests, FIB-tests, and TPA-tests. ResultsClot lysis was inhibited in a concentration-dependent manner up to a tranexamic acid concentration of 6.25 mg L−1. At tranexamic acid concentrations of 12.5 mg L−1 and above, clot lysis was completely inhibited. The concentration–effect relationship of tranexamic acid did not differ in a clinically important manner in blood from pregnant women across all three trimesters or from non-pregnant controls. A median maximum lysis cut-off value of at9 least 16% (25–75th percentiles 15–18), a median clot lysis time of 3600 s (25–75th percentiles 3600–3600), or both was associated with a tranexamic acid concentration of least 12.5 mg L−1. ConclusionsThe ClotPro® TPA-test is sensitive in detecting inhibition of fibrinolysis by tranexamic acid in whole blood samples of pregnant and non-pregnant women. The concentration–effect relationship of tranexamic acid to inhibit fibrinolysis in whole blood did not differ for women in the first, second, and third trimester or for non-pregnant women.

Hintergrund Etwa 20% der Frauen und 10% der Männer sind von psychischen Problemen während der Schwangerschaft und im ersten Lebensjahr des Kindes betroffen. Aufgrund der potentiell schwerwiegenden Auswirkungen auf Eltern und Kind besteht ein dringender Bedarf an einer raschen, wirksamen Versorgung. In Österreich ist bisher weder ein routinemäßiges Screening implementiert noch sind entsprechende Versorgungsstrukturen flächendeckend verfügbar. Ziel eines Scoping Reviews war die Identifizierung und Analyse internationaler Modelle und Leitlinien zur Prävention und Versorgung peripartaler psychischer Erkrankungen.