A New Model for Ranking Schools of Public Health: The Public Health Academic Ranking.

Objectives: As there is no ranking designed for schools of Public Health, the aim of this project was to create one. Methods: To design the Public Health Academic Ranking (PHAR), we used the InCites Benchmarking and Analytics™ software and the Web Of Science™ Core Collection database. We collected bibliometric data on 26 schools of Public Health from each continent, between August and September 2022. We included 11 research indicators/scores, covering four criteria (productivity, quality, accessibility for readers, international collaboration), for the period 2017-2021. For the Swiss School of Public Health (SSPH+), a network gathering faculties across different universities, a specific methodology was used, with member-specific research queries. Results: The five top schools of the PHAR were: London School of Hygiene and Tropical Medicine, Public Health Foundation of India, Harvard T.H. Chan School of Public Health, SSPH+, Johns Hopkins Bloomberg School of Public Health. Conclusion: The PHAR allows worldwide bibliometric ordering of schools of Public Health. As this is a pilot project, the results must be taken with caution. This article aims to critically discuss its methodology and future improvements.

Efficacy of a digital lifestyle intervention on health-related QUAlity of life in non-small cell LUng CAncer survivors following inpatient rehabilitation: protocol of the QUALUCA Swiss multicentre randomised controlled trial.

INTRODUCTION: Non-small cell lung cancer (NSCLC) survivors suffer from impaired physical and psychological functioning and reduced health-related quality of life (HRQoL) that persist after active treatment ends. Sustaining rehabilitation benefits, promoting a healthy lifestyle and facilitating self-management at home require a multifaceted aftercare programme. We aim to investigate the effect of a 12-week digital lifestyle intervention on HRQoL and lifestyle-related outcomes in NSCLC survivors after completion of inpatient rehabilitation. METHODS AND ANALYSIS: QUAlity of life in LUng CAncer Survivors (QUALUCA) is a multicentre randomised controlled trial that follows a hybrid type 1 design. We randomly allocate participants in a 1:1 ratio to the intervention group (digital lifestyle intervention) or the control group (standard care) using block randomisation stratified by tumour stage and study site. Four accredited Swiss inpatient rehabilitation centres recruit participants. Key inclusion criteria are a diagnosis of NSCLC, an estimated life expectancy of ≥6 months and access to a smartphone or tablet. The 12-week intervention comprises physical activity, nutrition and breathing/relaxation, delivered through a mobile application (app). The primary outcome is the change in HRQoL from baseline (1 week after rehabilitation) to follow-up (3 months after baseline), assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30). Secondary outcomes include body mass index, self-reported physical activity, exercise capacity, risk of low protein intake, appetite, psychological distress, cancer-related fatigue, enablement and self-rated health. Explanatory outcomes in the intervention group include app usability, acceptability, appropriateness, and feasibility of the intervention, experiences and satisfaction with the intervention, and app usage data. We aim to enrol 88 participants. For the main statistical analysis, we will use analysis of covariance, adjusted for baseline measures, stratification variables, age and sex. ETHICS AND DISSEMINATION: The Ethics Committees of the Canton of Zurich (lead), the Canton of Bern and Northwest and Central Switzerland approved the study (2023-00245). We will disseminate study results to researchers, health professionals, study participants and relevant organisations, and through publications in international peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05819346.

A guide for a student-led doctoral-level qualitative methods short course in epidemiology: faculty and student perspectives.

Qualitative research and mixed methods are core competencies for epidemiologists. In response to the shortage of guidance on graduate course development, we wrote a course development guide aimed at faculty and students designing similar courses in epidemiology curricula. The guide combines established educational theory with faculty and student experiences from a recent introductory course for epidemiology and biostatistics doctoral students at the University of Zurich and Swiss Federal Institute of Technology, Zurich. We propose a student-centred course with inverse classroom teaching and practice exercises with faculty input. Integration of student input during the course development process helps align the course syllabus with student needs. The proposed course comprises six sessions that cover learning outcomes in comprehension, knowledge, application, analysis, synthesis and evaluation. Following an introductory session, the students engage in face-to-face interviews, focus group interviews, observational methods, analysis and how qualitative and quantitative methods are integrated in mixed methods. Furthermore, the course covers interviewer safety, research ethics, quality in qualitative research and a practice session focused on the use of interview hardware, including video and audio recorders. The student-led teaching characteristic of the course allows for an immersive and reflective teaching-learning environment. After implementation of the course and learning from faculty and student perspectives, we propose these additional foci: a student project to apply learned knowledge to a case study; integration in mixed-methods; and providing faculty a larger space to cover theory and field anecdotes.

Blending citizen science with natural language processing and machine learning: Understanding the experience of living with multiple sclerosis.

The emergence of new digital technologies has enabled a new way of doing research, including active collaboration with the public ('citizen science'). Innovation in machine learning (ML) and natural language processing (NLP) has made automatic analysis of large-scale text data accessible to study individual perspectives in a convenient and efficient fashion. Here we blend citizen science with innovation in NLP and ML to examine (1) which categories of life events persons with multiple sclerosis (MS) perceived as central for their MS; and (2) associated emotions. We subsequently relate our results to standardized individual-level measures. Participants (n = 1039) took part in the 'My Life with MS' study of the Swiss MS Registry which involved telling their story through self-selected life events using text descriptions and a semi-structured questionnaire. We performed topic modeling ('latent Dirichlet allocation') to identify high-level topics underlying the text descriptions. Using a pre-trained language model, we performed a fine-grained emotion analysis of the text descriptions. A topic modeling analysis of totally 4293 descriptions revealed eight underlying topics. Five topics are common in clinical research: 'diagnosis', 'medication/treatment', 'relapse/child', 'rehabilitation/wheelchair', and 'injection/symptoms'. However, three topics, 'work', 'birth/health', and 'partnership/MS' represent domains that are of great relevance for participants but are generally understudied in MS research. While emotions were predominantly negative (sadness, anxiety), emotions linked to the topics 'birth/health' and 'partnership/MS' was also positive (joy). Designed in close collaboration with persons with MS, the 'My Life with MS' project explores the experience of living with the chronic disease of MS using NLP and ML. Our study thus contributes to the body of research demonstrating the potential of integrating citizen science with ML-driven NLP methods to explore the experience of living with a chronic condition.

Longitudinal humoral and cell-mediated immune responses in a population-based cohort in Zurich, Switzerland between March and June 2022 - evidence for protection against Omicron SARS-CoV-2 infection by neutralizing antibodies and spike-specific T-cell responses.

OBJECTIVES: The correlate(s) of protection against SARS-CoV-2 remain incompletely defined. Additional information regarding the combinations of antibody and T cell-mediated immunity which can protect against (re)infection is needed. METHODS: We conducted a population-based, longitudinal cohort study including 1044 individuals of varying SARS-CoV-2 vaccination and infection statuses. We assessed spike (S)- and nucleocapsid (N)-immunoglobulin(Ig)G and wildtype, Delta, and Omicron-neutralizing antibody (N-Ab) activity. In a subset of 328 individuals, we evaluated S, membrane (M), and N-specific T cells. Three months later, we reassessed Ab (n = 964) and T cell (n = 141) responses and evaluated factors associated with protection from (re)infection. RESULTS: At the study start, >98% of participants were S-IgG seropositive. N-IgG and M/N-T-cell responses increased over time, indicating viral (re)exposure, despite existing S-IgG. Compared to N-IgG, M/N-T cells were a more sensitive measure of viral exposure. High N-IgG titers, Omicron-N-Ab activity, and S-specific-T-cell responses were all associated with a reduced likelihood of (re)infection over time. CONCLUSION: Population-level SARS-CoV-2 immunity is S-IgG-dominated, but heterogeneous. M/N-T-cell responses can distinguish previous infection from vaccination, and monitoring a combination of N-IgG, Omicron-N-Ab, and S-T-cell responses may help estimate protection against SARS-CoV-2 (re)infection.

Social media and internet search data to inform drug utilization: A systematic scoping review.

Introduction: Drug utilization is currently assessed through traditional data sources such as big electronic medical records (EMRs) databases, surveys, and medication sales. Social media and internet data have been reported to provide more accessible and more timely access to medications' utilization. Objective: This review aims at providing evidence comparing web data on drug utilization to other sources before the COVID-19 pandemic. Methods: We searched Medline, EMBASE, Web of Science, and Scopus until November 25th, 2019, using a predefined search strategy. Two independent reviewers conducted screening and data extraction. Results: Of 6,563 (64%) deduplicated publications retrieved, 14 (0.2%) were included. All studies showed positive associations between drug utilization information from web and comparison data using very different methods. A total of nine (64%) studies found positive linear correlations in drug utilization between web and comparison data. Five studies reported association using other methods: One study reported similar drug popularity rankings using both data sources. Two studies developed prediction models for future drug consumption, including both web and comparison data, and two studies conducted ecological analyses but did not quantitatively compare data sources. According to the STROBE, RECORD, and RECORD-PE checklists, overall reporting quality was mediocre. Many items were left blank as they were out of scope for the type of study investigated. Conclusion: Our results demonstrate the potential of web data for assessing drug utilization, although the field is still in a nascent period of investigation. Ultimately, social media and internet search data could be used to get a quick preliminary quantification of drug use in real time. Additional studies on the topic should use more standardized methodologies on different sets of drugs in order to confirm these findings. In addition, currently available checklists for study quality of reporting would need to be adapted to these new sources of scientific information.

Delivering Safe Surgical Care While Simultaneously Caring for Patients With COVID-19; Assessment of Patient Selection, Volume and Outcomes in a Tertiary Care Hospital.

Objectives: Compare patient selection and postoperative outcomes after surgical treatment for gastrointestinal disorders before and during the SARS-CoV-2 pandemic. Methods: We assessed gastrointestinal surgeries conducted at a tertiary center from 2017-2021 for differences in patient populations and procedures before (up to February 2020) and during the pandemic (March 2020 to December 2021). We analyzed mortality, Intensive Care Unit (ICU) length of stay, admission to ICU and postoperative complications for complex procedures using descriptive statistics and regression models. Results: 7309 procedures were analyzed, showing a caseload reduction in March and October 2020, but no statistical evidence for fewer overall procedures overall. Population characteristics differed with lower Body Mass Indices in 2020 and 2021, more patients smoking and with diabetes treated in 2020. There was no increased mortality, ICU length of stay and in 1,144 complex procedures assessed low overall morbidity at 90 days postoperative. Conclusion: Delivering surgical care while treating patients for COVID-19 in the same hospital was safe. Healthcare officials should consider continuing surgical care during future health crises as consequences of limiting surgical treatment for gastrointestinal disorders may be fatal for patients.

Trajectories of Seroprevalence and Neutralizing Activity of Antibodies against SARS-CoV-2 in Southern Switzerland between July 2020 and July 2021: An Ongoing, Prospective Population-Based Cohort Study.

OBJECTIVES: The COVID-19 pandemic continues, and evidence on infection- and vaccine-induced immunity is key. We assessed COVID-19 immunity and the neutralizing antibody response to virus variants across age groups in the Swiss population. STUDY DESIGN: We conducted a cohort study in representative community-dwelling residents aged five years or older in southern Switzerland (total population 353,343), and we collected blood samples in July 2020 (in adults only, N = 646), November-December 2020 (N = 1457), and June-July 2021 (N = 885). METHODS: We used a previously validated Luminex assay to measure antibodies targeting the spike (S) and the nucleocapsid (N) proteins of the virus and a high-throughput cell-free neutralization assay optimized for multiple spike protein variants. We calculated seroprevalence with a Bayesian logistic regression model accounting for the population's sociodemographic structure and the test performance, and we compared the neutralizing activity between vaccinated and convalescent participants across virus variants. RESULTS: The overall seroprevalence was 7.8% (95% CI: 5.4-10.4) by July 2020 and 20.2% (16.4-24.4) by December 2020. By July 2021, the overall seroprevalence increased substantially to 72.5% (69.1-76.4), with the highest estimates of 95.6% (92.8-97.8) among older adults, who developed up to 10.3 more antibodies via vaccination than after infection compared to 3.7 times more in adults. The neutralizing activity was significantly higher for vaccine-induced than infection-induced antibodies for all virus variants (all p values < 0.037). CONCLUSIONS: Vaccination chiefly contributed to the reduction in immunonaive individuals, particularly those in older age groups. Our findings on the greater neutralizing activity of vaccine-induced antibodies than infection-induced antibodies are greatly informative for future vaccination campaigns.

Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.

Machine learning has become a key driver of the digital health revolution. That comes with a fair share of high hopes and hype. We conducted a scoping review on machine learning in medical imaging, providing a comprehensive outlook of the field's potential, limitations, and future directions. Most reported strengths and promises included: improved (a) analytic power, (b) efficiency (c) decision making, and (d) equity. Most reported challenges included: (a) structural barriers and imaging heterogeneity, (b) scarcity of well-annotated, representative and interconnected imaging datasets (c) validity and performance limitations, including bias and equity issues, and (d) the still missing clinical integration. The boundaries between strengths and challenges, with cross-cutting ethical and regulatory implications, remain blurred. The literature emphasizes explainability and trustworthiness, with a largely missing discussion about the specific technical and regulatory challenges surrounding these concepts. Future trends are expected to shift towards multi-source models, combining imaging with an array of other data, in a more open access, and explainable manner.

Long COVID Through a Public Health Lens: An Umbrella Review.

Objectives: To synthesize existing evidence on prevalence as well as clinical and socio-economic aspects of Long COVID. Methods: An umbrella review of reviews and a targeted evidence synthesis of their primary studies, including searches in four electronic databases, reference lists of included reviews, as well as related article lists of relevant publications. Results: Synthesis included 23 reviews and 102 primary studies. Prevalence estimates ranged from 7.5% to 41% in non-hospitalized adults, 2.3%-53% in mixed adult samples, 37.6% in hospitalized adults, and 2%-3.5% in primarily non-hospitalized children. Preliminary evidence suggests that female sex, age, comorbidities, the severity of acute disease, and obesity are associated with Long COVID. Almost 50% of primary studies reported some degree of Long COVID-related social and family-life impairment, long absence periods off work, adjusted workloads, and loss of employment. Conclusion: Long COVID will likely have a substantial public health impact. Current evidence is still heterogeneous and incomplete. To fully understand Long COVID, well-designed prospective studies with representative samples will be essential.

Joys or Sorrows of Parenting During the COVID-19 Lockdown: A Scoping Review.

Objectives: The aim of this scoping review was to map out the existing evidence of the impact of the COVID-19 lockdown on parents of children and adolescents. We sought to: 1) identify parenting domains that were particularly affected by lockdown measures, 2) describe the challenges and opportunities of lockdown measures in these domains, and 3) define protective and exacerbating factors modulating the effect of lockdown measures on parents. Methods: We identified five main domains investigated in the context of parenting during the early COVID-19 lockdown derived from 84 studies: health and wellbeing, parental role, couple functioning, family and social relationships, and paid and unpaid work. For each domain, we listed challenges and opportunities, as well as discriminant factors. Results: The lockdown impacted all five different but interconnected domains, introduced new roles in parents' lives, and particularly affected women and vulnerable populations. Conclusion: This scoping review highlights the importance of approaching public health policymaking from a social justice perspective. Such an approach argues for social and public health policies to promote health accounting for its social, economic, political, and commercial determinants.

Individual participant data meta-analysis with mixed-effects transformation models.

One-stage meta-analysis of individual participant data (IPD) poses several statistical and computational challenges. For time-to-event outcomes, the approach requires the estimation of complicated nonlinear mixed-effects models that are flexible enough to realistically capture the most important characteristics of the IPD. We present a model class that incorporates general normally distributed random effects into linear transformation models. We discuss extensions to model between-study heterogeneity in baseline risks and covariate effects and also relax the assumption of proportional hazards. Within the proposed framework, data with arbitrary random censoring patterns can be handled. The accompanying $\textsf{R}$ package tramME utilizes the Laplace approximation and automatic differentiation to perform efficient maximum likelihood estimation and inference in mixed-effects transformation models. We compare several variants of our model to predict the survival of patients with chronic obstructive pulmonary disease using a large data set of prognostic studies. Finally, a simulation study is presented that verifies the correctness of the implementation and highlights its efficiency compared to an alternative approach.

Variation in SARS-CoV-2 seroprevalence across districts, schools and classes: baseline measurements from a cohort of primary and secondary school children in Switzerland.

OBJECTIVES: To determine the variation in SARS-CoV-2 seroprevalence in school children and the relationship with self-reported symptoms. DESIGN: Baseline measurements of a longitudinal cohort study (Ciao Corona) from June to July 2020. SETTING: 55 schools stratified by district in the canton of Zurich, Switzerland. PARTICIPANTS: 2585 children (1339 girls; median age: 11 years, age range: 6-16 years), attending grades 1-2, 4-5 and 7-8. MAIN OUTCOME MEASURES: Variation in seroprevalence of SARS-CoV-2 in children across 12 cantonal districts, schools and grades, assessed using Luminex-based test of four epitopes for IgG, IgA and IgM (Antibody Coronavirus Assay,ABCORA 2.0). Clustering of cases within classes. Association of seropositivity and symptoms. Comparison with seroprevalence in adult population, assessed using Luminex-based test of IgG and IgA (Sensitive Anti-SARS-CoV-2 Spike Trimer Immunoglobulin Serological test). RESULTS: Overall seroprevalence was 2.8% (95% CI 1.5% to 4.1%), ranging from 1.0% to 4.5% across districts. Seroprevalence in grades 1-2 was 3.8% (95% CI 2.0% to 6.1%), in grades 4-5 was 2.4% (95% CI 1.1% to 4.2%) and in grades 7-8 was 1.5% (95% CI 0.5% to 3.0%). At least one seropositive child was present in 36 of 55 (65%) schools and in 44 (34%) of 131 classes where ≥5 children and ≥50% of children within the class were tested. 73% of children reported COVID-19-compatible symptoms since January 2020, with the same frequency in seropositive and seronegative children for all symptoms. Seroprevalence of children and adults was similar (3.2%, 95% credible interval (CrI) 1.7% to 5.0% vs 3.6%, 95% CrI 1.7% to 5.4%). The ratio of confirmed SARS-CoV-2 cumulative incidence-to-seropositive cases was 1:89 in children and 1:12 in adults. CONCLUSIONS: SARS-CoV-2 seroprevalence was low in children and similar to that in adults by the end of June 2020. Very low ratio of diagnosed-to-seropositive children was observed. We did not detect clustering of SARS-CoV-2-seropositive children within classes, but the follow-up of this study will shed more light on transmission within schools. TRIAL REGISTRATION NUMBER: NCT04448717.

[Cancer Screening - Prerequesites for a Successful and Meaningful Screening Program]. / Krebs Screening.

Cancer Screening - Prerequesites for a Successful and Meaningful Screening Program Abstract. Benefits and harms of cancer screening should be carefully assessed based on evidence, put into local context and weighed against each other. The success of cancer screening programs depends on many factors beyond the evidence, such as participation rates, the organization and the quality of the program. This article highlights the epidemiologic prerequisites for a cancer screening and explains how a successful screening program is designed.

Toward a Working Definition of eCohort Studies in Health Research: Narrative Literature Review.

BACKGROUND: The wide availability of internet-connected devices and new sensor technologies increasingly infuse longitudinal observational study designs and cohort studies. Simultaneously, the costly and time-consuming nature of traditional cohorts has given rise to alternative, technology-driven designs such as eCohorts, which remain inadequately described in the scientific literature. OBJECTIVE: The aim of this study was to outline and discuss what may constitute an eCohort, as well as to formulate a first working definition for health researchers based on a review of the relevant literature. METHODS: A two-staged review and synthesis process was performed comparing 10 traditional cohorts and 10 eCohorts across the six core steps in the life cycle of cohort designs. RESULTS: eCohorts are a novel type of technology-driven cohort study that are not physically linked to a clinical setting, follow more relaxed and not necessarily random sampling procedures, are primarily based on self-reported and digitally collected data, and systematically aim to leverage the internet and digitalization to achieve flexibility, interactivity, patient-centeredness, and scalability. This approach comes with some hurdles such as data quality, generalizability, and privacy concerns. CONCLUSIONS: eCohorts have similarities to their traditional counterparts; however, they are sufficiently distinct to be treated as a separate type of cohort design. The novelty of eCohorts is associated with a range of strengths and weaknesses that require further exploration.

Drivers of Acceptance of COVID-19 Proximity Tracing Apps in Switzerland: Panel Survey Analysis.

BACKGROUND: Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved. OBJECTIVE: This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases. METHODS: We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively. RESULTS: Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or

Nocturnal Cough and Sleep Quality to Assess Asthma Control and Predict Attacks.

INTRODUCTION: Objective markers for asthma, that can be measured without extra patient effort, could mitigate current shortcomings in asthma monitoring. We investigated whether smartphone-recorded nocturnal cough and sleep quality can be utilized for the detection of periods with uncontrolled asthma or meaningful changes in asthma control and for the prediction of asthma attacks. METHODS: We analyzed questionnaire and sensor data of 79 adults with asthma. Data were collected in situ for 29 days by means of a smartphone. Sleep quality and nocturnal cough frequencies were measured every night with the Pittsburgh Sleep Quality Index and by manually annotating coughs from smartphone audio recordings. Primary endpoint was asthma control assessed with a weekly version of the Asthma Control Test. Secondary endpoint was self-reported asthma attacks. RESULTS: Mixed-effects regression analyses showed that nocturnal cough and sleep quality were statistically significantly associated with asthma control on a between- and within-patient level (p < 0.05). Decision trees indicated that sleep quality was more useful for detecting weeks with uncontrolled asthma (balanced accuracy (BAC) 68% vs 61%; Δ sensitivity -12%; Δ specificity -2%), while nocturnal cough better detected weeks with asthma control deteriorations (BAC 71% vs 56%; Δ sensitivity 3%; Δ specificity -34%). Cut-offs using both markers predicted asthma attacks up to five days ahead with BACs between 70% and 75% (sensitivities 75 - 88% and specificities 57 - 72%). CONCLUSION: Nocturnal cough and sleep quality have useful properties as markers for asthma control and seem to have prognostic value for the early detection of asthma attacks. Due to the limited study duration per patient and the pragmatic nature of the study, future research is needed to comprehensively evaluate and externally validate the performance of both biomarkers and their utility for asthma self-management.

Characteristics of Asthma-related Nocturnal Cough: A Potential New Digital Biomarker.

INTRODUCTION: The nature of nocturnal cough is largely unknown. It might be a valid marker for asthma control but very few studies characterized it as a basis for better defining its role and its use as clinical marker. This study investigated prevalence and characteristics of nocturnal cough in asthmatics over the course of four weeks. METHODS: In two centers, 94 adult patients with physician-diagnosed asthma were recruited. Patient-reported outcomes and nocturnal sensor data were collected by a smartphone with a chat-based study app. RESULTS: Patients coughed in 53% of 2212 nights (range: 0-345 coughs/night). Median coughs per hour were 0 (IQR 0-1). Nocturnal cough rates showed considerable inter-individual variance. The highest counts were measured in the first 30 min in bed (4.5-fold higher than rest of night). Eighty-six percent of coughs were part of a cough cluster. Clusters consisted of a median of two coughs (IQR 2-4). Nocturnal cough was persistent within patient. CONCLUSION: To the best of the authors' knowledge, this study is the first to describe prevalence and characteristics of nocturnal cough in asthma over a period of one month, demonstrating that it was a prevalent symptom with large variance between patients and high persistence within patients. Cough events in asthmatics were 4.5 times more frequent within the first 30 min in bed indicating a potential role of positional change, and not more frequent during the early morning hours. An important next step will investigate the association between nocturnal cough and asthma control.

Self-Monitoring App Preferences for Sun Protection: Discrete Choice Experiment Survey Analysis.

BACKGROUND: The availability and use of health apps continues to increase, revolutionizing the way mobile health interventions are delivered. Apps are increasingly used to prevent disease, improve well-being, and promote healthy behavior. On a similar rise is the incidence of skin cancers. Much of the underlying risk can be prevented through behavior change and adequate sun protection. Self-monitoring apps have the potential to facilitate prevention by measuring risk (eg, sun intensity) and encouraging protective behavior (eg, seeking shade). OBJECTIVE: Our aim was to assess health care consumer preferences for sun protection with a self-monitoring app that tracks the duration and intensity of sun exposure and provides feedback on when and how to protect the skin. METHODS: We conducted an unlabeled discrete choice experiment with 8 unique choice tasks, in which participants chose among 2 app alternatives, consisting of 5 preidentified 2-level attributes (self-monitoring method, privacy control, data sharing with health care provides, reminder customizability, and costs) that were the result of a multistep and multistakeholder qualitative approach. Participant preferences, and thus, the relative importance of attributes and their levels were estimated using conditional logit modeling. Analyses consisted of 200 usable surveys, yielding 3196 observations. RESULTS: Our respondents strongly preferred automatic over manually operated self-monitoring (odds ratio [OR] 2.37, 95% CI 2.06-2.72) and no cost over a single payment of 3 Swiss francs (OR 1.72, 95% CI 1.49-1.99). They also preferred having over not having the option of sharing their data with a health care provider of their choice (OR 1.66, 95% CI 1.40-1.97), repeated over single user consents, whenever app data are shared with commercial thirds (OR 1.57, 95% CI 1.31-1.88), and customizable over noncustomizable reminders (OR 1.30, 95% CI 1.09-1.54). While most participants favored thorough privacy infrastructures, the attribute of privacy control was a relatively weak driver of app choice. The attribute of self-monitoring method significantly interacted with gender and perceived personal usefulness of health apps, suggesting that female gender and lower perceived usefulness are associated with relatively weaker preferences for automatic self-monitoring. CONCLUSIONS: Based on the preferences of our respondents, we found that the utility of a self-monitoring sun protection app can be increased if the app is simple and adjustable; requires minimal effort, time, or expense; and has an interoperable design and thorough privacy infrastructure. Similar features might be desirable for preventive health apps in other areas, paving the way for future discrete choice experiments. Nonetheless, to fully understand these preference dynamics, further qualitative or mixed method research on mobile self-monitoring-based sun protection and broader preventive mobile self-monitoring is required. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/16087.

Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review.

INTRODUCTION: Advances in wearable sensor technology now enable frequent, objective monitoring of real-world walking. Walking-related digital mobility outcomes (DMOs), such as real-world walking speed, have the potential to be more sensitive to mobility changes than traditional clinical assessments. However, it is not yet clear which DMOs are most suitable for formal validation. In this review, we will explore the evidence on discriminant ability, construct validity, prognostic value and responsiveness of walking-related DMOs in four disease areas: Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and proximal femoral fracture. METHODS AND ANALYSIS: Arksey and O'Malley's methodological framework for scoping reviews will guide study conduct. We will search seven databases (Medline, CINAHL, Scopus, Web of Science, EMBASE, IEEE Digital Library and Cochrane Library) and grey literature for studies which (1) measure differences in DMOs between healthy and pathological walking, (2) assess relationships between DMOs and traditional clinical measures, (3) assess the prognostic value of DMOs and (4) use DMOs as endpoints in interventional clinical trials. Two reviewers will screen each abstract and full-text manuscript according to predefined eligibility criteria. We will then chart extracted data, map the literature, perform a narrative synthesis and identify gaps. ETHICS AND DISSEMINATION: As this review is limited to publicly available materials, it does not require ethical approval. This work is part of Mobilise-D, an Innovative Medicines Initiative Joint Undertaking which aims to deliver, validate and obtain regulatory approval for DMOs. Results will be shared with the scientific community and general public in cooperation with the Mobilise-D communication team. REGISTRATION: Study materials and updates will be made available through the Center for Open Science's OSFRegistry (https://osf.io/k7395).