Tobias Kowatsch

Objective: This study aimed to investigate the impact of the ongoing war in Ukraine on the mental health of Ukrainians, focusing on war-induced trauma, disturbances in self-organization, post-traumatic stress disorder, complex post-traumatic stress disorder, anxiety, stress, and depression. Method: Data was collected from 703 participants six months after the full-scale invasion using a structured questionnaire that included sections on socio-demographic information, trauma-related issues, and mental health. Results: The study found that levels of depression and anxiety were relatively low, while stress and resilience were relatively high among Ukrainians affected by the war. However, those who were directly exposed to military actions, physical violence, or severe human suffering had higher levels of anxiety, depression, stress, and trauma-related symptoms. The war experience varied by gender, age, and living conditions. Participants who stayed in Ukraine had significantly lower anxiety, depression, stress, and trauma-related symptoms compared to those who moved abroad. Anxiety, depression, stress, low resilience, and subjective satisfaction with living conditions were predictors of trauma-related symptoms, including PTSD and CPTSD. Conclusions: These findings suggest that the mental health of Ukrainians affected by the war was impacted differently depending on their level of exposure to violence and their living conditions. Additionally, the study identified several predictors of trauma-related symptoms, including PTSD and CPTSD, such as anxiety, depression, stress, low resilience, and subjective satisfaction with living conditions. Future research should further explore the relationships between trauma type, sociodemographic factors, resilience, stress, anxiety, depression, and PTSD and CPTSD to better understand the mediation mechanisms underlying these relationships and to develop effective interventions to support the well-being of Ukrainians during this difficult time.

Objective This study examines the prevalence and predictors of mental health issues, specifically anxiety, depression, and stress, among Ukrainians during the military conflict with Russia. Method A cross-sectional correlational study was conducted six months after the beginning of the conflict. Sociodemographic factors, traumatic experiences, anxiety, depression, and stress were assessed. The study included 706 participants, both men and women, from different age groups and living in various regions of Ukraine. The data were collected from August till October 2022. Results The study found that a large portion of the Ukrainian population shows increased levels of anxiety, depression, and stress due to the war. Women were found to be more vulnerable to mental health issues than men, and younger people were found to be more resilient. Worsened financial and employment statuses predicted increased anxiety. Ukrainians who fled the conflict to other countries exhibited higher levels of anxiety, depression, and stress. Direct exposure to trauma predicted increased anxiety and depression, while war-related exposure to “other stressful events” predicted increased acute stress levels. Conclusion The findings of this study highlight the importance of addressing the mental health needs of Ukrainians affected by the ongoing conflict. Interventions and support should be tailored to address the specific needs of different groups, particularly women, younger individuals, and those with worsened financial and employment statuses.

Background Depression remains a global health problem, with its prevalence rising worldwide. Digital biomarkers are increasingly investigated to initiate and tailor scalable interventions targeting depression. Due to the steady influx of new cases, focusing on treatment alone will not suffice; academics and practitioners need to focus on the prevention of depression (i.e., addressing subclinical depression). Aim With our study, we aim to (i) develop digital biomarkers for subclinical symptoms of depression, (ii) develop digital biomarkers for severity of subclinical depression, and (iii) investigate the efficacy of a digital intervention in reducing symptoms and severity of subclinical depression. Method Participants will interact with the digital intervention BEDDA consisting of a scripted conversational agent, the slow-paced breathing training Breeze, and actionable advice for different symptoms. The intervention comprises 30 daily interactions to be completed in less than 45 days. We will collect self-reports regarding mood, agitation, anhedonia (proximal outcomes; first objective), self-reports regarding depression severity (primary distal outcome; second and third objective), anxiety severity (secondary distal outcome; second and third objective), stress (secondary distal outcome; second and third objective), voice, and breathing. A subsample of 25% of the participants will use smartwatches to record physiological data (e.g., heart-rate, heart-rate variability), which will be used in the analyses for all three objectives. Discussion Digital voice- and breathing-based biomarkers may improve diagnosis, prevention, and care by enabling an unobtrusive and either complementary or alternative assessment to self-reports. Furthermore, our results may advance our understanding of underlying psychophysiological changes in subclinical depression. Our study also provides further evidence regarding the efficacy of standalone digital health interventions to prevent depression. Trial registration Ethics approval was provided by the Ethics Commission of ETH Zurich (EK-2022-N-31) and the study was registered in the ISRCTN registry (Reference number: ISRCTN38841716, Submission date: 20/08/2022).

Background Musculoskeletal conditions are the main drivers of global disease burden and cause significant direct and indirect health care costs. Digital health applications improve the availability of and access to adequate care. The German health care system established a pathway for the approval of “Digitale Gesundheitsanwendungen” (DiGAs; Digital Health Applications) as collectively funded medical services through the “Digitale-Versorgung-Gesetz” (Digital Health Care Act) in 2019. Objective This article presents real-world prescription data collected through the smartphone-based home exercise program “Vivira,” a fully approved DiGA, regarding its effect on self-reported pain intensity and physical inability in patients with unspecific and degenerative pain in the back, hip, and knee. Methods This study included 3629 patients (71.8% [2607/3629] female; mean age 47 years, SD 14.2 years). The primary outcome was the self-reported pain score, which was assessed with a verbal numerical rating scale. The secondary outcomes were self-reported function scores. To analyze the primary outcome, we used a 2-sided Skillings-Mack test. For function scores, a time analysis was not feasible; therefore, we calculated matched pairs using the Wilcoxon signed-rank test. Results Our results showed significant reductions in self-reported pain intensity after 2, 4, 8, and 12 weeks in the Skillings-Mack test (T3628=5308; P<.001). The changes were within the range of a clinically relevant improvement. Function scores showed a generally positive yet more variable response across the pain areas (back, hip, and knee). Conclusions This study presents postmarketing observational data from one of the first DiGAs for unspecific and degenerative musculoskeletal pain. We noted significant improvements in self-reported pain intensity throughout the observation period of 12 weeks, which reached clinical relevance. Additionally, we identified a complex response pattern of the function scores assessed. Lastly, we highlighted the challenges of relevant attrition at follow-up and the potential opportunities for evaluating digital health applications. Although our findings do not have confirmatory power, they illustrate the potential benefits of digital health applications to improve the availability of and access to medical care. Trial Registration German Clinical Trials Register DRKS00024051; https://drks.de/search/en/trial/DRKS00024051

Background Changing lifestyle patterns over the last decades have seen growing numbers of people in Asia affected by non-communicable diseases and common mental health disorders, including diabetes, cancer, and/or depression. Interventions targeting healthy lifestyle behaviours through mobile technologies, including new approaches such as chatbots, may be an effective, low-cost approach to prevent these conditions. To ensure uptake and engagement with mobile health interventions, however, it is essential to understand the end-users’ perspectives on using such interventions. The aim of this study was to explore perceptions, barriers, and facilitators to the use of mobile health interventions for lifestyle behaviour change in Singapore. Methods Six virtual focus group discussions were conducted with a total of 34 participants (mean ± SD; aged 45 ± 3.6 years; 64.7% females). Focus group recordings were transcribed verbatim and analysed using an inductive thematic analysis approach, followed by deductive mapping according to perceptions, barriers, facilitators, mixed factors, or strategies. Results Five themes were identified: (i) holistic wellbeing is central to healthy living (i.e., the importance of both physical and mental health); (ii) encouraging uptake of a mobile health intervention is influenced by factors such as incentives and government backing; (iii) trying out a mobile health intervention is one thing, sticking to it long term is another and there are key factors, such as personalisation and ease of use that influence sustained engagement with mobile health interventions; (iv) perceptions of chatbots as a tool to support healthy lifestyle behaviour are influenced by previous negative experiences with chatbots, which might hamper uptake; and (v) sharing health-related data is OK, but with conditions such as clarity on who will have access to the data, how it will be stored, and for what purpose it will be used. Conclusions Findings highlight several factors that are relevant for the development and implementation of mobile health interventions in Singapore and other Asian countries. Recommendations include: (i) targeting holistic wellbeing, (ii) tailoring content to address environment-specific barriers, (iii) partnering with government and/or local (non-profit) institutions in the development and/or promotion of mobile health interventions, (iv) managing expectations regarding the use of incentives, and (iv) identifying potential alternatives or complementary approaches to the use of chatbots, particularly for mental health.

Background: The current paper details findings from Elena+: Care for COVID-19, an app developed to tackle the collateral damage of lockdowns and social distancing, by offering pandemic lifestyle coaching across seven health areas: anxiety, loneliness, mental resources, sleep, diet and nutrition, physical activity, and COVID-19 information. Methods: The Elena+ app functions as a single-arm interventional study, with participants recruited predominantly via social media. We used paired samples T-tests and within subjects ANOVA to examine changes in health outcome assessments and user experience evaluations over time. To investigate the mediating role of behavioral activation (i.e., users setting behavioral intentions and reporting actual behaviors) we use mixed-effect regression models. Free-text entries were analyzed qualitatively. Results: Results show strong demand for publicly available lifestyle coaching during the pandemic, with total downloads (N = 7′135) and 55.8% of downloaders opening the app (n = 3,928) with 9.8% completing at least one subtopic (n = 698). Greatest areas of health vulnerability as assessed with screening measures were physical activity with 62% (n = 1,000) and anxiety with 46.5% (n = 760). The app was effective in the treatment of mental health; with a significant decrease in depression between first (14 days), second (28 days), and third (42 days) assessments: F2,38 = 7.01, p = 0.003, with a large effect size (η2G = 0.14), and anxiety between first and second assessments: t54 = 3.7, p = <0.001 with a medium effect size (Cohen d = 0.499). Those that followed the coaching program increased in net promoter score between the first and second assessment: t36 = 2.08, p = 0.045 with a small to medium effect size (Cohen d = 0.342). Mediation analyses showed that while increasing number of subtopics completed increased behavioral activation (i.e., match between behavioral intentions and self-reported actual behaviors), behavioral activation did not mediate the relationship to improvements in health outcome assessments. Conclusions: Findings show that: (i) there is public demand for chatbot led digital coaching, (ii) such tools can be effective in delivering treatment success, and (iii) they are highly valued by their long-term user base. As the current intervention was developed at rapid speed to meet the emergency pandemic context, the future looks bright for other public health focused chatbot-led digital health interventions.

Background Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, “LvL UP 1.0″, a smartphone-based lifestyle intervention aimed at preventing NCDs and CMDs. Materials and Methods A multidisciplinary team led the intervention design process of LvL UP 1.0, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding and prototype design, and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development. Results Preliminary research highlighted the importance of targeting holistic wellbeing (i.e., both physical and mental health). Accordingly, the first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily “Life Hacks” (healthy activity suggestions), breathing exercises, and journaling. In addition to the intervention components, formative research also stressed the need to introduce engagement-specific components to maximise uptake and long-term use. LvL UP includes a motivational interviewing and storytelling approach to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a mobile device. Conclusions The development process of LvL UP 1.0 led to an evidence-based and user-informed smartphone-based intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers.