Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

The leading peer-reviewed journal for digital medicine and health and health care in the internet age

Latest Submissions Open for Peer Review

JMIR has been a leader in applying openness, participation, collaboration and other "2.0" ideas to scholarly publishing, and since December 2009 offers open peer review articles, allowing JMIR users to sign themselves up as peer reviewers for specific articles currently considered by the Journal (in addition to author- and editor-selected reviewers).

For a complete list of all submissions across all JMIR journals as well as partner journals, see JMIR Preprints

Note that this is a not a complete list of submissions as authors can opt-out. The list below shows recently submitted articles where submitting authors have not opted-out of open peer-review and where the editor has not made a decision yet. (Note that this feature is for reviewing specific articles - if you just want to sign up as reviewer (and wait for the editor to contact you if articles match your interests), please sign up as reviewer using your profile).

To assign yourself to an article as reviewer, you must have a user account on this site (if you don't have one, register for a free account here) and be logged in (please verify that your email address in your profile is correct).

Add yourself as a peer reviewer to any article by clicking the '+Peer-review Me!+' link under each article. Full instructions on how to complete your review will be sent to you via email shortly after. Do not sign up as peer-reviewer if you have any conflicts of interest (note that we will treat any attempts by authors to sign up as reviewer under a false identity as scientific misconduct and reserve the right to promptly reject the article and inform the host institution).

We now reward completed peer-reviews (all rounds must be completed) with 90 Karma points which can be used as credits towards your own submissions. In addition, you receive karma points at the time of self-assignment, and additional bonus points for nominating other reviewers as well as for excellent reviews. Conditions apply, see Karma Description for details. Note that assigning yourself as reviewer and not delivering a review will lead to negative karma points.

The standard turnaround time for reviews is currently 2 weeks, and the general aim is to give constructive feedback to the authors and/or to prevent publication of uninteresting or fatally flawed articles. Reviewers will be acknowledged by name if the article is published, but remain anonymous if the article is declined.

The abstracts on this page are unpublished studies - please do not cite them (yet). If you wish to cite them/wish to see them published, write your opinion in the form of a peer-review!

Tip: Include the RSS feed of the JMIR submissions on this page on your homepage, blog, or desktop RSS reader to stay informed about current submissions!

JMIR Submissions under Open Peer Review

↑ Grab this Headline Animator

If you follow us on Twitter, we will also announce new submissions under open peer-review there.

Titles/Abstracts of Articles Currently Open for Review:

  • Digital Fever Pharmacies: Establishing Remote Medication Dispensaries in China

    Date Submitted: May 13, 2022
    Open Peer Review Period: May 13, 2022 - Jul 8, 2022

    COVID-19 remains a common problem worldwide. Fever clinics in China have played a very important role in the pandemic, although the pharmacists who ran them experienced a great deal of pressure; there were many problems, such as cross-infections, drug errors caused by burnout, and communication difficulties in the isolated environment. Therefore, we designed and developed a series of medical information circulars, software, and automated equipment and established a digital pharmacy that is operated by remote pharmacists. The goal of having patients obtain medicines and resolve medication problems online was also achieved. The aim of this article is to explain how we solved these problems and the shortage of pharmacists at the same time in hopes of providing a reference for the international pharmacy community.

  • The Role of Serious Video Games in the Treatment of Disordered Eating: A Systematic Review

    Date Submitted: May 13, 2022
    Open Peer Review Period: May 13, 2022 - Jul 8, 2022

    Background: Eating disorders and other forms of disordered eating cause significant complications and comorbidities in patients. However, full remission with current standard treatment remains low. Challenges to treatment include under diagnosis, high dropout rates, as well as difficulties in addressing underlying emotional dysregulation, poor impulse control and personality traits. Serious video games (SVGs) with the advantages of being highly engaging and accessible, may be potential vehicles to deliver various forms of treatment in addressing the underlying psychopathology of disordered eating. Objective: This review aims to provide an overview of the possible mechanisms by which SVGs may affect the clinical course of disordered eating, while evaluating the outcomes of studies that have assessed the role of SVGs in the treatment of disordered eating. Methods: A systematic search was performed on Pubmed, PsychINFO and Embase using keywords related to serious games, disordered eating and eating disorders. A narrative synthesis was subsequently carried out. Results: 2151 papers were identified, from which 11 papers were included. 10 of which were randomized controlled trials (RCTs) while 1 was a quasi-experimental study. The types of SVG interventions varied across the studies and targeted different mechanisms of disorder eating, ranging from addressing problem solving and emotional regulation skills to neurocognitive training for inhibitory control. Most studies showed some benefit of the SVGs in improving certain physical, behavioral or psychological outcomes related to disordered eating. Some studies also showed encouraging evidence of the retention of these benefits at follow-up. Conclusions: The studies included in this review provide collective evidence to suggest the various roles SVGs can play in plugging potential gaps in conventional therapy. Nonetheless, challenges exist in the designing of these games to prevent potential pitfalls such as excessive stress arising from the SVGs themselves or potential gaming addiction. Further studies will also be required to assess the long-term benefits of these SVGs as well as to explore its potential preventive, and not just curative effects on disordered eating. Clinical Trial: Not Applicable

  • Background: Vaping or e-cigarette use has become dramatically more popular in the United States in recent years. Vaping and e-cigarette use-associated lung injury (EVALI) cases caused an increase in hospitalizations and deaths in 2019, and many instances were later linked to unregulated products. Previous literature has leveraged social media data for surveillance of health topics. Individuals are willing to share mental health experiences and other personal stories on social media platforms where they feel a sense of community, reduced stigma, and as space for personal coping and empowerment. Objective: The current paper aims to compare vaping-related content on two popular social media platforms (i.e., Twitter with brief information and Reddit with longer opinion posts) to explore the context surrounding vaping during the 2019 EVALI outbreak and to support the feasibility of using data from both social platforms to develop in-depth and intelligent vaping detection models on social media. Methods: Data were extracted from both Twitter and Reddit from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analysis (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared to computational analysis of content on both platforms. Results: Vaping-related posts and unique users on Twitter and Reddit increased from July to September 2019, with the average post per user increasing from 1.73 to 1.98 on Twitter and 1.25 to 1.56 on Reddit. Computational analyses found the number of positive sentiment posts to be higher than negative ones on both Twitter and Reddit, while content analysis results differed indicating that negative sentiment posts were higher on Twitter based on in-depth manual review. Keywords related to age were more commonly found on Twitter based on computational analysis, while mentions of youth/young adults specifically were higher on Reddit based on clinical content analysis. Further, topics prevalent on both platforms by keywords and based on manual post reviews included marketing/regulation, marijuana/THC, and interest in quitting. Conclusions: Post content and trending topics overlapped on both Twitter and Reddit during the EVALI period in 2019. However crucial differences in user type and content keywords were also found including more frequent mentions of health-related keywords on Twitter and more positive health outcomes from vaping mentioned on Reddit. Utilization of both computational and clinical content analysis are critical to not only identify signals of public health trends among vaping-related social media content but also to provide context on individual-level vaping risks and behaviors. By leveraging the strengths of both Twitter and Reddit as publicly available data sources, this research may provide technical and clinical insights to inform automatic detection of social media users who are vaping and may benefit from digital intervention and proactive outreach strategies on these platforms. Clinical Trial: N/A

  • Helping early obstructive sleep apnea diagnosis with machine learning: A systematic review

    Date Submitted: May 10, 2022
    Open Peer Review Period: May 10, 2022 - Jul 5, 2022

    Background: American Academy of Sleep Medicine guidelines suggests that clinical prediction algorithms can be used to screen obstructive sleep apnea (OSA) patients without replacing polysomnography (PSG) – the gold standard. Objective: We aimed to identify, gather, and analyze existing machine learning approaches that are being used for disease screening in adult patients suspected of OSA. Methods: We searched MEDLINE, Scopus and ISI Web of Knowledge databases for evaluating the validity of different machine learning techniques, with PSG as the gold standard outcome measures. This systematic review was registered in PROSPERO under reference CRD42021221339. Results: Our search retrieved 5479 articles, of which 63 articles were included. We found 23 studies performing diagnostic models’ development alone, 26 with added internal validation, and 14 applying the clinical prediction algorithm to an independent sample (although not all reporting the most common discrimination metrics - sensitivity and/or specificity). Logistic regression was applied in 35 studies, linear regression in 16, support vector machine in 9, neural networks in 8, decision trees in 6, and Bayesian networks in 4. Random forest, discriminant analysis, classification and regression tree, and nomogram were each performed in 2 studies, while Pearson correlation, adaptative neuro-fuzzy inference system, artificial immune recognition system, genetic algorithm, supersparse linear integer models, and k-nearest neighbors’ algorithm each in 1 study. The best AUC was .98 [.96-.99] for age, waist circumference, Epworth somnolence, and oxygen saturation as predictors in a logistic regression. Conclusions: Although high values were obtained, they still lack external validation results in large cohorts and a standard OSA criteria definition.

  • Background: Internalizing, externalizing, and somatoform disorders are the most common and disabling forms of psychopathology. Our understanding of these clinical problems is limited by a reliance on self-report along with research using small samples. Social media has emerged as an exciting avenue in which to collect large sample of longitudinal data from individuals to study psychopathology. Nonetheless, there are concerns regarding whether people who share their social media data for research are significantly different from people who do not. Objective: We report the results of two large ongoing studies in which we collect Twitter data and self-reported clinical screening scales, the Studies of Online Cohorts for Internalizing symptoms and Language (SOCIAL). We categorized individuals based on whether they were deemed to have given a valid Twitter account. We described differences in sociodemographic features, clinical symptoms, and aspects of social media use by whether or not individuals gave valid accounts. Methods: Participants were a nationally representative sample of Twitter-using adults (SOCIAL-I: N= 1,121) as well as a sample of college students in the Midwest (SOCIAL-II: N= 2,015), of which 61% were Twitter users. For all participants who were Twitter users, we asked for access to their Twitter handle which we analyzed with BotOMeter, an online application rating the likelihood the account belongs to a bot. We divided participants into four groups: 1) Twitter users who did not allow access to their account (“No handle”), 2) those who denied being Twitter users (“No Twitter,” only available for SOCIAL-II), 3) Twitter users who gave their handles but whose account had high BotOMeter score (“Bot-like”), and 4) Twitter users who provided their handles and had low BotOMeter scores (“Valid”). Results: n SOCIAL-I, most individuals were classified as valid (n=580) and few were deemed bot-like (n=190). 351 gave no handle. In SOCIAL-II, many individuals were not Twitter users (n = 760). Of the Twitter users in SOCIAL-II (n = 1, 455), most were classified as either invalid (n = 515) or valid (n = 484), with a smaller fraction deemed bot-like (n = 229). Participants reported high rates of mental health diagnoses as well as high levels of symptoms, especially in SOCIAL-II. In general, differences between individuals who provided or did not provide their social media handle were small and not statistically significant Conclusions: Triangulating passively-acquired social media data and self-reported questionnaires offers avenues for large-scale assessment and evaluation of vulnerability to mental disorders. The propensity of participants to share social media handles is not likely a source of sample bias in subsequent social media analytics

  • Association between Telehealth Use and Policy Responses to COVID-19 in Japan: Interrupted Time Series Analysis

    Date Submitted: May 7, 2022
    Open Peer Review Period: May 7, 2022 - May 17, 2022

    Background: Telehealth using telephones or online communication is being promoted as a policy initiative in several countries. However, there is a lack of research on telehealth utilization in a country such as Japan that offers free access to medical care and regulates telehealth provision—particularly with respect to COVID-19. Objective: The present study aimed to clarify telehealth utilization, the characteristics of patients and medical institutions using telehealth, and the changes to telehealth in Japan, in order to support the formulation of policy strategies for telehealth provision. Methods: Using a medical administrative claim database of the National Health Insurance and Advanced Elderly Medical Service System n Mie Prefecture, we investigated patients who used telehealth from January 2017 to September 2021. We examined telehealth utilization with respect to both patients and medical institutions, and we determined their characteristics. Using April 2020 as the reference time point for COVID-19, we conducted an interrupted time-series analysis (ITSA) to assess changes in the monthly proportion of telehealth users to beneficiaries. Results: The number of telehealth users was 13,618 before the reference time point and 28,853 after. Several disease conditions showed an increase with telehealth utilization. Telehealth consultations were mostly conducted by telephone and for prescriptions. The ITSA results showed a sharp increase in the proportion of telehealth use to beneficiaries after the reference time point (rate ratio, 2.97; 95% confidence interval, 2.14–2.31). However, no apparent change in the trend of increasing or decreasing telehealth use was evident after the reference time point (rate ratio,1.00; 95% confidence interval, 1.00–1.01). Conclusions: We observed a sharp increase in telehealth utilization after April 2020, but no change in the trend of telehealth use was evident. We identified changes in the characteristics of patients using telehealth and the providers.

  • Background: Recruitment into clinical trials is a challenging process, with as many as 40% of studies failing to meet their target sample sizes [1]. The principles of direct-to-consumer (DTC) advertising rely upon novel marketing strategies. The ability to reach expansive audiences in the online realm presents a unique opportunity for researchers to overcome various barriers to enrollment in clinical trials. Previous research has investigated the use of individual online platforms to aid in recruitment and accrual into trials, but a gap in the literature exists whereby multiple mass communications platforms have yet to be investigated across a range of clinical trials. Objective: There is a need for research to better understand how individual factors combine to collectively influence trial recruitment. The present study tested whether DTC recruitment of potentially eligible study participants via social media platforms (e.g., Facebook, Twitter) was an effective strategy, or if this process acted as an enhancement to already-existing, traditional (e.g., email via contact registries) recruitment strategies through established clinical research sites. Methods: This study tested multiple direct-to-consumer online recruitment efforts (Facebook, Twitter, email, and patient advocacy group/PAG involvement) across six national and international research studies from five rare disease consortia. Targeted social media messaging, social media management software, and individual study websites complete with pre-screening questions were utilized. Results: A total of 1,465 PRISM website referrals occurred across all six studies. Organic (not paid) Facebook posts (n=676) and RDCRN patient contact registry emails (n=461) represented the most successful forms of engagement. Despite the large number of leads generated from PRISM recruitment efforts, the number of patients that subsequently enrolled in an RDCRN studies was low. Across six studies, three participants ultimately enrolled, meaning that 97.8% of leads dropped off. Females were more responsive to recruitment tactics. Individuals identifying as not of Hispanic or Latino origin were most likely to click on recruitment materials. While there was variance in terms of ages that engaged with online recruitment, those in their 30s were most responsive. Conclusions: Results indicate that although accrual results were low, targeted messaging efforts remain a promising opportunity for engaging individuals in the research process. Key elements to consider include structuring the communicative process (workflow) in such a way that PAG involvement is central to the process, with clinical site coordinators actively involved after an individual consents to share their contact information. Given the high variability in the number of affected individuals across diseases, it is probable that individualized, fine-tuned approaches are needed for each population and research study. As evidenced by lead generation, results suggest that online recruitment efforts, coupled with strategically designed targeted messaging and PAG partnerships, have the potential to help supplement clinical trial accrual. Clinical Trial: NCT02108860; NCT02939573; NCT03531996; NCT03118674; NCT02991807; NCT02523118

  • Background: Mental health apps offer a transformative means to increase access to scalable evidence-based care for college students. Yet low rates of engagement currently preclude the effectiveness of these apps. One promising solution is to make these apps more responsive and personalized through digital phenotyping methods able to predict symptoms and offer tailored interventions. Objective: Following our protocol and utilizing the exact model shared in that paper, in this work we assess the prospective validity of mental health symptom prediction using the mindLAMP app. We also explore secondary aims around app intervention personalization and correlations of engagement with the Technology Acceptance Model (TAM) and Digital Working Alliance Inventory (D-WAI) scale. Methods: The study was 28 days in duration and followed the published protocol with participants collecting digital phenotyping data and being offered optional scheduled as well as algorithm recommend app interventions. Study compensation was tied to the completion of Weekly Surveys and was not otherwise tied to engagement or use of the app. Results: 170 college student participants completed informed consent, of which 108 passed the study trial period, and 74 completed the study. The area under the curve values for the symptom prediction model ranged from 0.58 for the UCLA Loneliness Scale to 0.71 for the Patient Health Questionaire-9. Engagement with the app interventions was high with a study mean of 73% but few participants engaged with the optional recommended interventions. The perceived utility of the app in the TAM was higher among those completing at least one recommended intervention Conclusions: Our results suggest how digital phenotyping methods can be used to create generalizable models that may help create more personalized and engaging mental health apps.

  • Background: A significant technical challenge related to integrating race and ethnicity data across EHR systems is the lack of consistency in how data about race and ethnicity is collected and structured by healthcare organizations. Objective: To evaluate and describe variations in how healthcare systems collect and report information about the race and ethnicity of their patients, and how these data are integrated when it is aggregated into a large clinical database. Methods: At the time of our analysis, the National COVID Cohort Collaborative (N3C) Data Enclave contained records from 6.5 million patients contributed by 56 healthcare institutions. We assessed the quality of race and ethnicity data by analyzing its conformance to federal standards, then drilled into the non-conforming data. Results: “No matching category” was the second largest harmonized racial group in the N3C. 20.7% of the race data did not conform to the federal standard; the largest category was data that were missing. Hispanic or Latino patients were over-represented in the non-conforming racial data, and data from American Indian or Alaska Native patients were obscured. Although only a small proportion of the source data had not been mapped to the correct concepts (0.6%), Black or African-American and Hispanic/Latino patients were over-represented in this category. Conclusions: The impact of data quality issues was not equal across all races and ethnicities, which has the potential to introduce bias in analyses and conclusions drawn from these data.The adverse impact of COVID-19 on marginalized and under-resourced communities of color has highlighted the need for accurate, comprehensive race and ethnicity data. Differences in how race and ethnicity data is conceptualized and encoded by healthcare institutions can affect the quality of the data in aggregated clinical databases. Transparency about how data has been transformed can help users make accurate analyses and inferences, and eventually better guide clinical care and public policy.

  • Patient Design: The Importance Of Including Patients In Designing Healthcare

    Date Submitted: May 2, 2022
    Open Peer Review Period: May 2, 2022 - Jun 27, 2022

    Background: Today, except for the commercial obstacle inserted by paywalls, patients can have access to the same healthcare online resources, studies and data as medical professionals (4). Empowered patients want to get engaged in their health or disease management. Patient scholars have published in prestigious medical journals (7)(8)(9) , , . The #PatientsIncluded movement has led to involving patients in medical events either as speakers or co-hosts. Governments such as the one of New Zealand have started developing digital health policies featuring empowered patients. These examples further underscore that a more patient inclusive design approach is already emerging and will inevitably be the norm. The only thing holding it back is cultural resistance, which is why we say digital health is a cultural transformation. In the 2010s, a myriad of pharmaceutical, medical and healthcare companies started to use patient centricity as a mantra. Each claimed that their company is patient centric thus ahead of the others. Pharmaceutical company executives started making “putting patients first” part of their slogans and internal documents. A 2020 survey revealed that 85% of companies were raising their investment in patient-centric capabilities over the next 18 months (10). Objective: We analyzed the differences between patient centricity and patient design. To drive this paradigm change fully into existence, we are calling for changing "patient centricity” from a relatively passive process, driven by industry’s needs, into a far more active, collaborative process driven by both parties’ needs and preferences. In short, it’s no longer viable for patient centricity to mean “We were thinking about you while we made our decisions.” Methods: - Results: This social movement has already progressed to where examples exist to illustrate the shift in thinking - the paradigm change. In the paper, we show multiple existing examples of patient design and how it can contibute to healthcare. Conclusions: We are at the end of the only period in history where physicians knew important scientific facts and medical insights that patients could not. For healthcare to achieve its potential in this new era, our methods along with our paradigm must change. To build this new world of practice and workflow we simply must engage with patients as true partners. To achieve medicine’s new potential, it must be optimized around the wants and priorities of the ultimate stakeholder - the party that has the most at stake in how it all plays out: the patient. Patient design is the approach that can make it happen.

  • A Revised Hippocratic Oath for The Era of Digital Health

    Date Submitted: May 2, 2022
    Open Peer Review Period: May 2, 2022 - Jun 27, 2022

    Background: Physicians have been taking the Hippocratic Oath for centuries. The Oath contains a set of ethical rules designed to guide physicians through their profession; it articulates a set of true north principles that govern the practice of medicine. Objective: The rise of digital health has dramatically changed the practice of medicine in a way that could not have been easily predicted at the time Hippocrates outlined his ethical principles of medicine. Methods: We reviewed the points of the Oath and suggested revised sections. Results: We believe that it now justified to modify the Hippocratic Oath—even if modestly—to reflect the digital health revolution, advances in patient empowerment, and the evolving role of technology in the everyday practice of medicine. Conclusions: This way, younger physicians below the digital divide can better relate to the Oath, while older physicians above the digital divide can gain further insights and inspiration from the pledge.

  • Background: Digital interventions for health financing, if implemented at scale, bear the potential to improve health system performance by reducing transaction costs and improving data-driven decision making. However, many interventions never reach sustainability and evidence on success factors for scale is scarce. The Insurance Management Information System (IMIS) is a digital intervention for health financing, designed to manage an insurance scheme and already implemented on a national scale in Tanzania. A previous study found that the IMIS claim function was poorly adopted by health care workers, questioning its potential to enable strategic purchasing and succeed at scale. Objective: This study aimed to understand why adoption of the IMIS claim function by health care workers remained low in Tanzania and to assess implications for use at scale. Methods: We conducted 21 semi-structured interviews with health care workers and management staff in 4 districts where IMIS was first implemented. We sampled respondents using a maximum variation strategy. We used the framework method for data analysis, applying a mixture of inductive and deductive coding to organize codes in a socio-ecological model. Finally, we related emerging themes to the framework for digital health interventions for scale developed by Labrique et al. Results: Respondents appreciated IMIS’ intrinsic software characteristics and technical factors and acknowledged IMIS as a valuable tool to simplify claim management. Human factors (e.g., training, workload, support), the extrinsic ecosystem (e.g., internet availability), and the healthcare ecosystem (e.g., financial sustainability of the insurance scheme, stewardship), were considered barriers to widespread adoption. Conclusions: Digital interventions for health financing like IMIS might have the potential for scale if careful consideration is given to the environment in which they are placed. Without a sustainable healthcare (financing) environment, sufficient infrastructure, and human capacity, they cannot unfold their full potential to improve health financing functions and ultimately contribute to UHC.

  • Background: Mobile mindfulness meditation (MMM) is mindfulness meditation intervention implemented by mobile devices like smart phones and apps. MMM has been used to help managing mental health of university students. Objective: The purpose of this study was to evaluate the effectiveness of MMM on mental health of university students in the areas of stress, anxiety, depression, mindfulness, well-being, and resilience. Methods: We conducted a systematic review and meta-analysis of the effectiveness of MMM on mental health of university students. An electronic literature search using the PubMed, Web of Science, EBSCO, Cochrane Library, and EMBASE from inception to July 16, 2021 was conducted to identify studies that reported the effects of MMM on stress, anxiety, depression, mindfulness, well-being, and resilience. Two reviewers retrieved articles, evaluated quality and extracted data independently. The methodological quality of the selected studies was determined using the Cochrane criteria for risk-of-bias assessment. The RevMan Version 5.3 was used to perform meta-analysis. Results: A total of 10 studies, including 958 university students, were selected for meta-analysis. Results showed that MMM was more effective than the control groups in decreasing stress (SMD=-0.41, 95% CI [-0.59, -0.23], P<0.0001), alleviating anxiety (SMD=-0.29, 95% CI [-0.50, -0.09], P=0.004), enhancing well-being (SMD=0.30, 95% CI [0.11, 0.50], P=0.003), and improving mindfulness (SMD=2.66, 95% CI [0.77, 4.55], P=0.006). However, there was no difference between MMM and the control groups in depression (SMD=-0.14, 95% CI [-0.30, 0.03], P=0.11), and resilience (SMD=-0.06, 95% CI [-0.26, 0.15], P=0.59). Conclusions: MMM was an effective method to reduce stress, anxiety, and to increase well-being, mindfulness of university students, further studies are needed to confirm our findings. Clinical Trial: CRD42022303585;

  • Background: Digital-based psychological interventions (DPIs) were suggested to be effective as shown in many randomized controlled trials (RCTs) in dealing with depression in adults. However, the effects of control comparators in these DPI studies were largely overlooked and they may also have potential in terms of depression management. Objective: This meta-analytical study aims to provide a quantitative estimate of the within-subject effects of the control groups across different time intervals and to explore the moderating effects of control types and symptoms severity at baseline. Methods: A systematic literature search was conducted in late September 2021. The control conditions in 107 RCTs with a total of 11,803 adults with depressive symptoms were included in the meta-analysis. Results: The control conditions collectively yielded a small to moderate effect in reducing depressive symptoms within 8 weeks since baseline assessment (g=-.358, 95% CI:-.434 to -.281); The effect grew to moderate within 9 to 24 weeks (g=-.549, 95% CI:-.638 to -.460) and peaked at g=-.810 (95% CI:-.950 to -.670) between 25 to 48 weeks. The effect was maintained at a moderate-to-large range (g=-.769, 95% CI:-1.041 to -.498) beyond 48 weeks. The magnitude of reduction differs across types of control and severity of symptoms. Care as usual (CAU) is the most powerful condition among all that produced a strong effect (g=-.950, 95% CI:-1.161 to -.739) in the medium-term. The finding that waitlist controls (WL) also produced a significant symptomatic reduction in the short-term (g=-.291, 95% CI:-.478 to -.104) refuted previously suspicion of a nocebo effect. Besides, a greater reduction in the long-term (g=-1.091, 95% CI:-1.210 to -.972) was noted among participants with severe symptoms at baseline. Conclusions: The present study provided evidence that depressive symptoms generally reduced over time. Given different control conditions produce variate and significant levels of symptomatic reduction. Future intervention trials must adopt an RCT design and should take into account the procedures of control treatments when examining treatment efficacy. The results of WL confirmed previous findings of spontaneous recovery among people with mild-to-moderate depressive symptoms. They may adopt watchful waiting as they wait for formal digital-based psychological services in the system. Clinical Trial: CRD42021261620 (PROSPERO)

  • Addiction symptoms network of young Internet users: A network analysis

    Date Submitted: Apr 24, 2022
    Open Peer Review Period: Apr 24, 2022 - Jun 19, 2022

    Background: An increasing number of people are becoming addicted to the Internet as a result of overuse. Internet Addiction Test (IAT) is a popular tool for evaluating Internet usage behaviors. The interaction between different symptoms and the relationship between IAT and clinical diagnostic criteria is not well understood. Objective: We recruited 3584 Internet users (14-24 years old) and had them complete the IAT. The final analysis included 2845 participants after screening the submitted questionnaires. Participants were classified into Internet Addiction (IA) group and Non-Internet Addiction (NIA)group. Methods: Using partial correlation with LASSO regularization networks, we identified the core symptoms of IA in each group and compare the group differences in network properties (strength, closeness, and betweenness). Then we analyzed the symptom networks of the DSM-5 diagnostic criteria and IAT scale for Internet addiction. Results: There were 355 in the IA group and 2490 in the NIA group. IAT_06 (school work suffers, strength = 0.511), IAT_08 (job performance suffers, strength = 0.531), IAT_15 (fantasiaze about online, strength = 0.474), IAT_17 (fail to stop online, strength = 0.526), and IAT_12 (fear of boring if offline, strength = 0.502). IA groups have a stronger edge between IAT_09 (defensive or secretive about online) and IAT_18 (hidden online time) than NIA groups. The items in DSM-5 have a stronger association with IAT_12 (weight=-0.066), IAT_15 (weight=-0.081), IAT_17 (weight=-0.106), IAT_9 (weight=-0.198), and IAT_18 (weight=-0.052). Conclusions: The Internet use symptoms network of IA group is significantly different from that of NIA group. Nodes IAT_06 (school work affected) and IAT_08 (work performance affected) are the resulting symptoms affected by other symptoms, node IAT_12 (fear of boredom if offline), IAT_17 (inability to stop online), and IAT_15 (fantasy online) are key symptoms that activate other symptoms of Internet addiction and are strongly linked to inability to control the intention to play games in the DSM-5.

  • Background: Retaining participants in clinical trials is an established challenge. Presently the industry is moving to a technology-mediated, decentralised model for running trials. The shift presents an opportunity for technology design to aid the participant experience and promote retention, but there are many open questions regarding how this can be best supported. We advocate that a stronger theoretical position is required to improve the quality of design decisions for clinical trial technology to promote participant engagement. Objective: This study aims to identify and analyse the types of retention strategies used in published clinical trials that successfully retain participants. Methods: A systematic scoping review was carried out on six electronic databases from 1990 up until September 2020, including Cumulative Index to Nursing and Allied Health Literature (CINAHL), The Cochrane Library, EBSCO, Embase, PsycINFO, and Pub med using the concepts 'retention', 'strategy,' 'clinal trial', and 'clinical research'. This was followed by an analysis of the articles through the lens of Self-Determination Theory (Deci and Ryan 2012), an evidence-based theory of human motivation. Results: Twenty-six articles were included for review. The motivational strategies identified in clinical trials in our sample were categorised into eight themes, including 1. Autonomy, 2. Competence, 3. Relatedness, 4. Controlled Motivation, 5. Branding, communications material, and marketing literature, 6. Contact, tracking, scheduling methods and data collection, 7. Convenience to participate in order to collect data, and 8. Organisational competence. Trials used a wide range of motivational strategies. Notably, trials often relied on controlled motivation interventions and under-utilised strategies to support intrinsic motivation. Also, traditional clinical trials rely heavily on human interaction and ‘relatedness’ to support motivation and retention, which may cause problems in the move to the technology-led decentralised trials. We found inconsistency in data reporting methods and that motivational theory-based approaches were not evident in strategy design. Conclusions: The study offers direction and a framework to guide future decentralised clinical trial (DCT) digital technology design decisions to enhance participant retention during clinical trials. The research defines previous clinical trial retention strategies in terms of participant motivation, identifies motivational strategies and offers a rationale for selecting strategies that will improve retention. The research emphasizes the benefits of using theoretical frameworks to analyse strategic approaches and aid decision making to improve the quality of technology design decisions.

  • Poisoned search engine results redirect European queries to illegal internet pharmacy networks

    Date Submitted: Apr 23, 2022
    Open Peer Review Period: Apr 23, 2022 - Jun 18, 2022

    Background: Illegal online pharmacies function as affiliate networks, in which search engine results pages (SERPs) are “poisoned” by several links redirecting site visitors to unlicensed drug distribution pages by initially clicking on the link of a legitimate, yet irrelevant domain. This unfair online marketing practice is commonly-referred to, search-redirection attack, portraying a decisive role in the illegal internet pharmaceutical marketplace. Objective: In our current study, we describe the mechanism, map and present national and international significance of search redirection attacks. Methods: Notably, our search engine query results regarding four erectile disfunction medications were documented and evaluated using Google with search terminology using “active ingredient” and “buy” in the language of the evaluated country, including Hungary and eleven other European countries, from 2019 through 2021. The final destination website legitimacy was checked at, and the estimated number of monthly unique visitors was obtained from traffic analytics. Compromised links leading to international illegal medicinal product vendors via redirection were analyzed using Gephi graph visualization software. Results: Compromised links redirecting to active online pharmacies were present in search query results of all evaluated countries. The prevalence was highest in Spain (n=62, 18.1%), Hungary (n=52, 15.2%), Italy (n=46, 13.5%) while the lowest in Finland (n=12, 3.5%), Croatia (n=10, 2.9%) and Bulgaria (n=2, 0.6%) recorded in November 2020. A decrease in the number of compromised sites linking visitors to illegitimate medicine sellers were observed in the Hungarian dataset between 2019 and 2021, from 41.3% to 5.0%, respectively. Out of 1920 search results in the international sample, 380 (19.8%) search query results were compromised, with the majority (n=342, 91.1%) of links redirecting individuals to 73 international illegal medicinal product vendors. The majority of these illegal online pharmacies (53.2%) received only one or two compromised links, meanwhile, the top three domains with the highest in-degree link value received more than one-third of all incoming links. Traffic analysis of 35 pharmacy specific domains, accessible via compromised links in search engine queries, showed a total of 473,118 unique visitors in November 2020. Conclusions: Although the prevalence of compromised links in SERPs has shown a decreasing tendency in Hungary, an international search query dataset emphasizes the international significance of search engine poisoning. Our research illustrates that search engine poisoning is a constant threat as illegitimate affiliate networks continue to flourish as uncoordinated interventions by authorities and individual stakeholders remain insufficient. Ultimately, without a dedicated and comprehensive effort on the part of search engine providers to effectively monitor and moderate SERPs, they may never be entirely free of compromised links leading to illegal online pharmacy networks.

  • Background: Given widespread and concerted efforts to propagate health misinformation on social media, particularly centered around vaccination during the pandemic, many groups of clinicians and scientists organized on social media to tackle misinformation and promote vaccination using a national or international lens. While documenting the impact of such social media efforts, particularly at the community level, can be challenging, a more hyperlocal or “place-based approach” for social media campaigns could be effective at tackling misinformation and improving public health outcomes on a community level. Objective: To describe and document the effectiveness of a place-based strategy for a coordinated group of healthcare workers on social media from Chicago to tackle misinformation and improve vaccination rates in their own communities. Methods: The Illinois Medical Professionals Action Collaborative Team (IMPACT) was founded in March 2020 in response to the COVID-19 pandemic with representatives from major academic teaching hospitals in Chicago (University of Chicago, Northwestern University, University of Illinois, Rush University) and community-based organizations. Through crowdsourcing on multiple social media platforms (Facebook, Twitter, Instagram) with a place-based approach, IMPACT engaged grassroots networks of thousands of Illinois healthcare workers and the public to identify gaps, needs, and viewpoints to improve local healthcare delivery during the pandemic. Results: To address vaccine misinformation, IMPACT created 8 “myth debunking” infographics and 14 informational vaccine infographics that have generated >340K impressions and informed the development of vaccine education for the Chicago Public Libraries. IMPACT delivered 13 policy letters focusing on different topics (i.e. healthcare worker personal protective equipment, universal masking, vaccination) with >4000 healthcare workers (HCWs) signatures collected through social media to policymakers, published over 50 op-eds on COVID-19 topics in high impact news outlets, and contributed to >200 local and national news features. Using the crowdsourcing approach on IMPACT social media channels, IMPACT mobilized healthcare and lay volunteers to staff over 400 vaccine events for over 120,000 individuals, many in Chicago’s hardest-hit neighborhoods. The group’s recommendations have influenced public health awareness campaigns and initiatives, research, advocacy, and policy recommendations, and have been recognized with local and national awards. Conclusions: A coordinated group of healthcare workers on social media using a hyperlocal place-based approach can not only work together to address misinformation but can also collaborate to boost vaccination rates in their surrounding communities.

  • Direct and Indirect Effects of an Educational and Communication Skills Intervention to Increase Donor Designation in Latinx Communities: Promotoras de Donación

    Date Submitted: Apr 22, 2022
    Open Peer Review Period: Apr 22, 2022 - Jun 17, 2022

    Background: Latinx populations are severely underrepresented amongst organ donors as compared to non-Hispanic whites. Objective: The Promotoras de Donación eLearning module was developed to train Latinx lay health educators (i.e., promotoras) to discuss deceased organ donation and promote donor registration within their communities. This report describes the results of two studies designed to assess the direct and indirect effects of the module. Methods: Forty promotoras affiliated with four partnering community based organizations completed the module. Brief surveys were administered before and after module completion to assess changes in organ donation knowledge and support, and communication confidence (Study 1). Promotoras participating in the first study were then asked to hold at least 2 group conversations about organ donation and donor designation with mature Latinas (Study 2). Fifty-two group discussions were held with 375 attendees. Descriptive statistics, means and standard deviations and counts and percents, were used as appropriate, to categorize the samples. The Paired Sample t-test statistic was used to assess changes in knowledge of and support for organ donation, and confidence discussing donation and promoting donor designation from pre- to post-test. Results: Increases in knowledge and support were observed from pre- to post-test, however these changes did not reach statistical significance. A statistically significant increase in communiation confidence was found (692.1 (pre) to 852.3 (post); p=.01). The module was well-received, with most participants deeming it well-organized, presenting new information, and providing realistic and helpful portrayals of donation conversations (Study 1). The trained promotora-led group discussion about organ donation resulted in increased support of organ donation in promotoras and mature Latinas from pre- to post-test. Knoweldge of the steps to become an organ donor and belief that the process is easy to do increased in mature Latinas from pre- to post-test 30.7% and 15.2% respectively (Study 2). Twenty-one attendees (0.06%) submitted completed organ donation registration forms. Conclusions: This evaluation provides preliminary support for the module’s direct and indirect impact. The need for additional modifications to and future evaluations of the module are discussed.

  • Bibliometric Analysis of Published Research on COVID-19 in the Eastern Mediterranean Region

    Date Submitted: Apr 22, 2022
    Open Peer Review Period: Apr 22, 2022 - Jun 17, 2022

    Background: The challenges presented by the COVID-19 pandemic have led to unprecedented global research activity. The Eastern Mediterranean Region (EMR) continues to contribute to COVID-19 research driven by the unique challenges of the region, including the protracted conflicts, already stressed health systems, and serious health and social inequalities. Objective: This study aimed to provide an overview of the publication activities and trends of COVID-19 research in EMR from the onset of the disease to early 2022, using bibliometric methods. Methods: A literature search using Scopus was conducted from 2019 to January 31, 2022, using keywords relevant to COVID-19 and the World Health Organization (WHO) EMR countries list. Data were exported and analyzed using Microsoft Excel and The Citation Overview function on Scopus. The quality of journals was determined using SCImago Journal Rank and CiteScore. VOSviewer software was used to visualize the relationships between authors, countries, and key terms used in the retrieved documents. Results: Kingdom of Saudi Arabia (KSA) and 1782/6880 (25.90%) from Iran, followed by Pakistan, Egypt, and Jordan. Most published documents were affiliated with EMR universities, primarily Tehran University of Medical Sciences in Iran and King Saud University in KSA, 5.76% (396/6880) and 5.4% (370/6880), respectively, while only 5.92% (407/6880) were associated with universities outside the EMR. For most of the identified publications (72.97%), no funding source was reported, while King Saud University contributed the largest share (282/1860, 15.16%) of funded publications. Retrieved documents were cited 53,516 times, with an average of 7.78 (SD 34.30). Iran was the EMR country with the most links to other countries (77 links and total link strength of 1279). The 5 authors with the most publications were from KSA, Qatar, and Jordan. There were 290 high-frequency keywords that occurred ≥ 10 times and were linked in 7 different clusters. The cluster with the most linked keywords was related to epidemiology and mortality. Recent topics included vaccines, vaccination, machine learning, and online learning. Conclusions: This is the first study to show trends and project future developments of COVID-19 research activity in the EMR. Authors and institutions who led research on COVID-19 in the region were from Iran and KSA. There were multiple regional collaborative efforts, however, international collaboration was limited. Output focused on COVID -19 epidemiology, mortality as well as anxiety and depression. Recently, interest has been shifting towards topics related to vaccination, machine learning, and online learning.

  • Predicting Publication of Clinical Trials Using Structured and Unstructured Data

    Date Submitted: Apr 19, 2022
    Open Peer Review Period: Apr 19, 2022 - Jun 14, 2022

    Background: Publication of registered clinical trials is a critical step in the timely dissemination of trial findings, which can improve healthcare and advance medical research. However, a significant proportion of completed clinical trials are never published, motivating the need to analyse the factors behind success or failure to publish. This could inform study design, help regulatory decision making, and improve resource allocation. It could also enhance our understanding of bias in publication of trials, and publication trends based on the research direction or strength of the findings. While publication of clinical trials has been addressed in several descriptive studies at an aggregate level, there is a lack of research on predictive analysis of a trial’s publishability given an individual (planned) clinical trial description. Objective: To carry out a study that combines structured and unstructured (textual) features relevant to the clinical trial publication status in a single predictive approach. Established natural language processing (NLP) techniques as well as recent advances in using pretrained language models as textual encoders enable us to incorporate information from the textual descriptions of clinical trials into a machine learning approach. We are particularly interested in whether and which textual features can improve the classification accuracy for publication outcome. Methods: In this study, we use pre-recorded metadata from (a registry of clinical trials) and MEDLINE (a bibliographic database of academic journal articles) to build a dataset of clinical trials (N=76,950) that contains the description of a registered trial and its publication outcome (36% published, 64% unpublished). This is the largest dataset of its kind, which we release as part of this work. The publication outcome in the dataset was identified from MEDLINE based on clinical trial identifiers. We carried out a detailed descriptive analysis and predicted the publication outcome using two approaches: a neural network that represents the text using a large domain-specific language model, and a random forest classifier using a weighted “bag-of-words” representation of text. Results: First, our analysis of the newly-created dataset corroborates several findings from the existing literature about attributes associated with a higher publication rate (e.g. the phase of a clinical trial). Second, a crucial observation from our predictive modelling is that the addition of textual features (e.g. eligibility criteria) offers consistent improvements over approaches that only use structured data (F1 =.62–.64 vs. F1 =.61 without textual features). Both pretrained language models and more basic word-based representations provide high-utility text representations, with no significant empirical difference between the two. Conclusions: Different factors affect whether a registered clinical trial is published or not. Our approach to predictive modelling combines heterogeneous features, both structured and unstructured (textual). We show that methods from NLP can provide effective textual features to enable more accurate prediction of publication success, which has not been explored for this task in previous work.

  • Background: Studies show that lung ultrasound (LUS) can accurately diagnose pneumonia in children, but intelligent diagnosis hasn’t been explored in this area. Objective: To construct deep learning (DL) models based on transfer learning (TL) to explore the feasibility of ultrasound image diagnosis and grading in community-acquired pneumonia (CAP) of children. Methods: From September 2021 to February 2022, 89 inpatients who were expected to receive a diagnosis of CAP in the pediatric ward of local hospital were prospectively enrolled. Clinical data were collected, a LUS images database was established, and the diagnostic values of LUS in CAP were analyzed. We constructed DL models using AlexNet, ResNet-18 and ResNet-50 to perform CAP diagnosis and grading on the LUS database and evaluated the performance of each model. The models were trained separately with transfer learning. Results: 1. Among the 89 children, 24 were in the non-CAP group, and 65 were finally diagnosed with CAP, including 44 in the mild group and 21 in the severe group. 2. LUS was highly consistent with clinical diagnosis, CXR and chest CT (kappa values = 0.943, 0.837, 0.835). 3. In the task of diagnosing CAP in children, different ratios of training and test sets (5:5; 8:2; 9:1) affected the performance of the model. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve of the AlexNet model ranged from 87.6%–89.5%, 93.2%–97.1%, 68.4%–73.6%, 89.5%–90.7%, 79.5%–89.9%, and 0.820–0.841; for the ResNet-18 model, these values were 87.3%–92.4%, 94.4%–98.3%, 64.6%–76.1%, 89.4%–91.8%, 83.7%–94.9%, and 0.795–0.972; moreover, for the ResNet-50 model, these values were 88.2%–90.9%, 94.0%–97.9%, 70.8%–72.1%, 90.2%–91.0%, 81.3%–92.6%, and 0.824–0.850. 4. When the training set and test set ratio was 8:2, the AlexNet, ResNet-18, and ResNet-50 models were highly consistent with the manual diagnosis CAP (kappa values = 0.832, 0.848, and 0.847 respectively), which was comparable to CXR and chest CT, and the ResNet-18 model performed better than manual ultrasound diagnosis (P=0.021). 5. In the task of grading, the accuracy of all three models increased with additions to the training set. When the ratio was 9:1, the accuracy of the ResNet-18 model reached 96%. Conclusions: LUS is a reliable method for diagnosing CAP in children. The transfer learning-based DL models AlexNet, ResNet-18 and ResNet-50 perform well in children’s CAP diagnosis in the database we established; of these, the ResNet-18 model achieves the best performance and may serve as a tool for the further research and development of AI automatic diagnosis LUS system in clinical applications. Clinical Trial: This study was a prospective case-control clinical diagnostic study, which was reviewed by the clinical trial registration website and obtained the registration number ChiCTR2200057328.

  • Background: Intensive longitudinal (IL) measurement, which involves prolonged self-monitoring, may have important clinical applications but is also burdening. This raises the question who takes part in, and successfully completes IL measurements. Objective: This study investigated which demographic, personality, economic, social, psychological, or physical participant characteristics are associated with participation and compliance in an IL study conducted in young adults at enhanced risk for psychopathology. Methods: Young adults enrolled in the clinical cohort of the Tracking Adolescents’ Individual Lives Survey (TRAILS) were invited to a six-month daily diary study. Participant characteristics came from five earlier TRAILS assessment waves collected from age 11 onwards. To evaluate participation, we compared diary study participants (N=134) to non-participants (N=309) and a sex-matched subsample (N=1926) of individuals from the general population cohort of TRAILS. To evaluate compliance, we analyzed which characteristics were related to the proportion of completed diary entries. Results: Participants (mean age 23.6 years; SD=0.7) were largely similar to non-participants. In addition, compared to the general population, participants reported more negative scores on nearly all characteristics. Internalizing problems predicted higher compliance. Externalizing problems, antisocial behavior and daily smoking predicted lower compliance. Conclusions: In at-risk young adults, who scored lower on nearly every positive characteristic and higher on every negative characteristic relative to the general population, participation in a diary study is unbiased. Small biases in compliance occur, of which researchers should be aware. IL measurement is thus suitable in at-risk populations, which is a requirement for its usefulness in clinical practice.

  • Background: Emotions are central to recognizing, responding, and recovering from an exposure to misinformation in social media. However, older adults are highly susceptible to misinformation in social media, due to the emotions involved with several key factors related to aging. Objective: Research is needed to speculate about the unknown unknown ethical, legal, and social implications (ELSI) associated with technologies that help older adults to recognize, respond, and recover from an exposure to misinformation in social media. Designing for older adult use of social media is challenging, because they exhibit different patterns of use and have limited access to digital literacy training. Additionally, there is a risk that some system designs might further disenfranchise already vulnerable populations. Methods: The paper presents research on a design fiction-based approach to speculate about the ELSIs related to a fictitious application called the “Digital News Navigator” (DN2) service. The DN2 was applied as a probe to reflect on potential unintended consequences of system design, reviewing a broad range of academic literature. To guide future research, the Digital Health Checklist for Researchers (DHC-R) was applied to contribute specific considerations related to ELSIs. Results: Together, the Author Statement and Discussion sections draw attention to how features of the fictitious DN2 service raise concerns about access and usability, privacy, risks & benefits, and data management. Our analysis also demonstrates how the design fiction method might be combined with frameworks for ethical thinking to generate insights about not-yet-possible technologies. Conclusions: There are potential ELSIs associated with system designs intended to assist older adults as they are exposed to misinformation through social media. Design fiction and the DHC-R offer a structured approach for identifying and speculating about these risks.

  • We consider the prevalence of misinformation online before and during the Covid 19 pandemic and the effect that has on health practitioners’ practice. The pressures and distractions that health professionals face in attempting to mitigate the impacts of this misinformation are discussed. By reviewing the available literature, we are able to draw conclusions regarding the impact on both health professionals' and patients' understanding of health information, especially in under represented communities, during and before the pandemic. The aim is to illustrate the impact of online social media in introducing additional sources of misinformation that impact health practitioners' ability to communicate effectively with their patients. In addition, the level of knowledge held by practitioners in order to mitigate the effect of misinformation is considered as well as the additional stress factors associated with dealing with the outbreak, which in turn affect communication with patients.

  • Examining how ethics in relation to health technology is described in the research literature: A Scoping Review

    Date Submitted: Apr 14, 2022
    Open Peer Review Period: Apr 14, 2022 - Jun 9, 2022

    Background: Given the increased use of technology in healthcare, both in extent and application, the importance of understanding the ethical implications of new health technologies increases. Profound insight into the possible ethical implications of new health technologies enhances research and development of such technologies and the likelihood of eventual successful implementation in clinical practice. Objective: The objective of this study was to gain an understanding of how and if researchers focused on health technologies describing actual or possible ethical aspects of their research findings. Methods: An established framework for Scoping reviews was used to guide the methodology. Studies published in PubMed over the last ten years were included if studying or referring to ethics in relation to health technology as defined by established frameworks. In total, 14532 articles were screened, 692 were retained for full-text evaluation, and 227 were included for data extraction. Results: Most studies were conducted in North America and Europe; literature review studies were dominant. Most studies had no direct reference to any of the four basic ethical principles: beneficence, non-maleficence, autonomy, and justice. In those cases where studies referenced ethical theory, consequentialism dominated. Conclusions: When research about technology is published, the predominant focus is on its intent rather than its actual effect on patients. This lack of insight is problematic considering the vast advancement of technology in which ethics cannot keep up with understanding and offer insights on addressing ethical issues. This finding has implications for practice, research, and education.

  • Background: The early access to prenatal care and high-cost technologies for pregnancy dating challenge the early neonatal risks assessment at birth in resource-constrained settings. To overcome the absence or low accuracy of postnatal gestational age, we developed a frugal innovation based on the photobiological properties of the newborn's skin and predictive models. Objective: This study aims to validate the photobiological model of skin maturity adjusted to the clinical data to promptly detect gestational age and determine its accuracy in detecting prematurity. Methods: A multicenter single-blinding and single-arm clinical trial intention-to-diagnosis evaluated the accuracy of a novel device to detect gestational age and preterm newborns. The first-trimester ultrasound (US), a second comparator US, and the last menstrual period (LMP) data from antenatal reports were the references for gestational age at birth. A portable multiband reflectance photometer assessed 781 newborns’ skin maturity and used machine learning models to predict gestational age, adjusted to birth weight and antenatal corticosteroid therapy exposure. Results: As the primary outcome, the predicted gestational by the new test had high agreement with the reference gestational age calculated with the intraclass correlation coefficient (0.970 [95%CI: 0.965, 0.974]) similar values to the comparator-US and better than the comparator-LMP gestational ages. As secondary outcomes, the new test achieved 97.7% (95%CI: 96.5%, 98.6%) agreement with the reference gestational age within one-week error. This value surpassed those of comparator-US (91.3% [95%CI: 89.2%, 93.1%]), and of comparator-LMP gestational ages (64.1% [60.7% to 67.5%]). Bland-Altman limits of the new test were -7.1 to 4.7 days. Prematurity discrimination with the novel device had the area under the receiver operating characteristic curve (AUROC) (0.998 [95%CI: 0.997, 1.000]), similar to comparator-US (0.996 [95% CI: 0.993, 0.999)]; and superior to comparator-LMP gestational ages (0.957 [95%CI:0.941, 0.974]). In newborns with absent or unreliable LMP (n=451), the intent-to-discriminate analysis showed correct classifications with the new test of 96.5% (95%CI: 94.3%, 98.0%), while with the comparator-LMP gestational age was 69.6% (95% CI: 65.3%, 73.7%). Conclusions: The assessment of the newborn's skin maturity adjusted by learning models promises accurate pregnancy dating at birth even without the antenatal ultrasound reference. Clinical Trial: WHO’s International Clinical Trial Platform - Brazilian Clinical Trials Registry RBR-3f5bm5.

  • Background: Seasonal influenza affects 5%-15% of Americans annually, resulting in preventable deaths and significant economic impact. Influenza infection is particularly dangerous for people with cardiovascular disease, who therefore represent a priority group for vaccination campaigns. Objective: We aimed to assess the effects of digital intervention messaging on self-reported rates of seasonal influenza vaccination. Methods: This was a randomized, controlled, single-blind decentralized trial conducted at individual locations throughout the United States over the 2020-2021 influenza season. Adults with self-reported cardiovascular disease who were members of the mobile Achievement platform were randomized to receive or not receive a series of 6 patient-centered digital intervention messages promoting influenza vaccination. The primary endpoint was the between-group difference in self-reported vaccination rates at 6 months after randomization. Secondary outcomes included levels of engagement with messages and the relationship between vaccination rates and engagement with messages. Subgroup analyses examined variation in intervention effects by race. Controlling for randomization group, we examined the impact of other predictors of vaccination status, including cardiovascular condition type, vaccine drivers/barriers, and vaccine knowledge. Results: Of the 49,138 randomized participants, responses on the primary endpoint were available for 11,237 (23%; 5575 in the intervention group and 5662 in the control group). The vaccination rate was significantly higher in the intervention group than among controls: 3418/5575 (61.31%) vs. 3355/5662 (59.25%), respectively; relative risk 1.03 [95% CI 1.004-1.066]; P=.027). Participants who were older, more educated, and White or Asian were more likely to report being vaccinated. The intervention was effective among White participants (P=.004) but not among people of color (P=.422). The vaccination rate was 15 percentage points higher among participants who completed all 6 intervention messages versus none, and at least 2 completed messages appeared to be needed for effectiveness. Participants who reported a diagnosis of COVID-19 were more likely to be vaccinated for influenza regardless of treatment assignment. Conclusions: This personalized, evidence-based digital intervention was effective in increasing vaccination rates in this population of high-risk people with cardiovascular disease. Clinical Trial: NCT04584645;

  • Background: Following the third week of March 2020, states and agencies of the Women, Infants and Children (WIC) program were granted temporary waivers to secondary contact requirements for clients seeking to receive or recertify WIC benefits given the emerging COVID-19 global pandemic. By April 1, 2020, four COVID-19 specific educational resources were launched on the dashboard page where users land after logging onto Wichealth, an online nutrition education behavior change program. This investigation compared users who accessed these resources to users with no access to any COVID-19 resources during April 1, 2020 through October, 31, 2021. User engagement with emergency response embedded in an online health education system has not previously been investigated due to a paucity of opportunities and a lack of the ability to evaluate relevant users at scale. Objective: This investigation sought to understand differences between Wichealth users who accessed at least one COVID-19 specific response resource and Wichealth users who recorded no use during the entire the period the resources were active. Methods: A comparative cross-sectional study was completed evaluating differences between Wichealth lesson completion and performance statistics between 29,979 unique WIC clients who accessed COVID-19 resources and 555,861 unique users who did not access the resources over the same period. Odds ratios and binomial 95% confidence intervals using normal approximation were calculated for both groups across all measures stratified by available socio-demographic characteristics. Results: Overall, Wichealth COVID-19 resources were utilized by 6.5% of system users with access to them, much lower than expected given historical Wichealth resource usage rates. A significantly greater level of COVID-19 resource access was observed for Latino users (P<.05; OR=1.15, 95% CI 1.13,1.18) and Spanish language version users (P<.05; OR=1.73, 95% CI 1.61,1.86), compared to overall Wichealth system usage for these groups. Further, compared to Wichealth system users with no COVID-19 resource utilization, individuals who accessed these resources were more likely to engage with Wichealth lesson resources during lesson completion (P<.05, OR=1.3; 95% CI 1.25,1.35). However, users who accessed COVID-19 resources were slightly less likely to recommend Wichealth lesson resources to others and believe in their ability to make healthy changes using information they learned from completing the lesson, but these differences were not statistically significant overall or by any socio-demographic strata. Conclusions: Wichealth COVID-19 response resource use was limited among system users and associated with those most likely to engage with other Wichealth resources. The relatively low access and lack of reach across all user socio-demographic characteristics suggests that separate, COVID-19 specific resources may not be the most effective way of addressing user concerns of an existing online educational system. Rather, integration of COVID-19 messaging within existing resources may be more effective at reaching more users.

  • Background: As of 2021, 89% of the Australian population are active internet users. Although the internet is widely used, there are concerns about the quality, accuracy, and credibility of health-related websites. A 2015 systematic assessment of infant feeding websites and apps available in Australia found that 61% of websites were of poor quality and readability with minimal coverage of infant feeding topics and lack of author credibility. Objective: This study aimed to systematically assess quality, interactivity, readability, and comprehensibility of information targeting infant feeding, active play, screen time and sleep behaviours on websites globally; and provide an update of the 2015 systematic assessment. Methods: Similar methods to the 2015 assessment were used. Key words related to infant milk feeding behaviours, solid feeding behaviours, active play, screen time and sleep were used to identify websites targeting infant health behaviours on Safari Google search engine. The websites were evaluated between July 2021 and February 2022 and assessed for information content based on the Australian Infant Feeding Guidelines and National Physical Activity Recommendations. The Suitability Assessment of Materials (SAM), Quality Component Scoring System (QCSS), the Health-Related Website Evaluation Form (HRWEF), and the adherence to the Health on the Net code (HONcode) were used to evaluate the suitability and quality of information respectively. Readability was assessed used three online readability tools. Results: Of the 450 websites screened, 66 were included based on the selection criteria and evaluated. Overall, the quality of websites was mostly adequate. Media- related sources, Non-Governmental Organisations, hospital, and privately owned websites had the highest median quality scores while university websites received the lowest median score (35%). The information covered within the websites was predominantly poor: 91% of the websites received an overall score of ≤74% (mean 53%). Suitability of health information was mostly rated adequate for literacy demand, layout, and learning and motivation of readers. The median readability score for the websites was grade 8.5 which is higher than the Government recommendations (< grade 8). Overall, 74% of websites obtained a poor rating for interactivity measuring active control, two-way communication, and synchronicity. The most common features found on websites were social media links (92%), frequently asked questions (73%), and videos (67%). Only 14% of websites presented information that addressed culture in texts or images. Conclusions: Quality, content, readability, and interactivity of websites promoting health behaviours during infancy ranged between poor to adequate. Since the 2015 systematic assessment, there was a slight improvement in quality of websites but no difference in the SAM rating and readability of information. There is a need for researchers and healthcare providers to leverage innovative web-based platforms to provide culturally competent evidence-based information based on Government guidelines that are accessible to those with limited English proficiency.

  • Antecedent factors of information security behavior in health care providers: a systematic review

    Date Submitted: Apr 10, 2022
    Open Peer Review Period: Apr 10, 2022 - Jun 5, 2022

    Background: Most data breaches in health care organizations are caused by human factors. The medical environment has specific characteristics that might impact the decision and behavior of their employee, including in performing security practices. Objective: This study aims to review the literature on antecedent factors of information security behavior in health care organizations based on various stakeholders’ perspectives (clinical staff, non-clinical staff, medical students, and patients) and different types of health care entities (hospital, clinic, medical center, and others). Methods: This review searched academic articles on five online databases (Scopus, PubMed/MedLine, IEEE Xplore, Science Direct, SAGE) using specific keywords until 2022. Studies are selected following the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) protocol. Results: The result identifies antecedent factors that significantly influence the information security behavior of health information system users in various health care organizations. The factors are classified into individual and organizational factors. Top-three frequent individual factors are self-efficacy, perceived severity, and attitude, while frequent organizational factors are management support, cues to action, and organizational culture. Each factor is mapped on two types of security behavior, desirable and undesirable security behavior. Conclusions: More individual factors are found significantly influence security behavior in health care organization. Previous studies in this field are still dominated by security compliance behavior. The researcher, manager of health care providers, and government should consider those factors to improve information security in health information system implementation.

  • Background: Evidence regarding the analgesic effect of distraction through immersion in virtual reality (VR) for care-induced pain, has been documented in several phase II trials but comparison with standard treatments in large-randomized studies are needed. Objective: In this open-label multicenter randomized phase III trial ( identifier: NCT 03483194), we evaluated the safety and efficacy of a novel VR therapy solution for distraction in the context of bone marrow (BM) biopsy. Methods: Bliss© is a VR software with four imaginary interactive environments in three dimensions with a binaural sound (head-mounted display). Efficacy was evaluated on pain intensity using a visual analog scale (score from 0-10) immediately after the biopsy. The primary endpoint was patient-assessed pain intensity after BM procedure, with a visual analog scale (VAS). Secondary endpoints were anxiety and tolerance. Overall, 126 patients with previously documented untreated or suspected malignant hemopathy between September 6, 2018, and May 18, 2020, were randomly assigned in a 1:1 ratio to receive pain prevention with a mixture of nitrous oxide/oxygen (MEOPA) (n=63) or VR (n=63) before and during BM biopsy. All patients received local anesthesia (lidocaine) before biopsy. Modified intention-to-treat analysis was performed. Results: Participants’ median age was 65.5 (range 18-87) years and 54.2% of patients were male. The average pain intensity was 3.5 (SD 2.6) for the MEOPA group and 3.0 (SD 2.4) for the VR group without any significant difference in age, sex, center or hemopathy (P=.26). Concerning anxiety, 67.5% of patients were afraid before the biopsy and anxiety scores were moderate to very high in 26.3% of patients before the biopsy (fear of pain and revised STAI questionnaires) and 9.0% after the biopsy for all patients without any significant difference between the 2 groups (P=.83). Immersion in VR was well tolerated by the majority of patients in the VR group. Conclusions: The intensity of pain and did not significantly differ between both arms. VR was well tolerated, and satisfaction of patients, nurses and physicians was very high. Virtual reality could be an alternative treatment in case of contraindication or intolerance to MEOPA. Clinical Trial: identifier: NCT 03483194

  • Background: The overloading of health care systems is an international problem. In this context, new tools such as symptom checker (SC) are emerging to improve patient orientation and triage. Several studies have attempted to evaluate the accuracy of these tools, but they tend to use a small number or specific to the evaluated tool vignettes, that reduces their reproducibility. Objective: The main objective was to evaluate the diagnostic performance of a SC compared to a gold standard in the diagnosis of frequent unscheduled care pathologies, using the interrogation of simulated patients. Methods: We explored a method to evaluate a symptom checker with simulation. A panel of medical experts wrote 220 simulated patients. Each situation was played twice by an actor trained to the role, once in front of the SC, once in front of a physician. We performed a prospective diagnostic non-inferiority study. If primary analysis failed to detect non-inferiority, we have planned a superiority analysis Results: We cannot conclude if the SC is non-inferior. However, the emergency physician was superior compared to the SC in terms of principal diagnosis (81% versus 30%) and association of principal and secondary diagnosis (92% versus 52%). In terms of patient triage (vital emergency or not), there is still a medical superiority (96% versus 71%). There is also a non-inferiority of the SC compared to the physician in terms of interviewing time. Conclusions: This method could provide solid evidence on the evaluation of SC. In an exploratory way, we have shown that SC seems to be relevant for patient triage and orientation in emergency department. A larger study with this method could provide more accurate results to increase the value of the SC. Clinical Trial: N/A

  • Digital Health Interventions for Depression and Anxiety Among People with Chronic Conditions: Scoping Review

    Date Submitted: Apr 7, 2022
    Open Peer Review Period: Apr 7, 2022 - Jun 2, 2022

    Background: Chronic conditions are characterized by their long duration (1 year or more), need for ongoing medical attention, and limitations on activities of daily living. These can often co-occur, with depression and anxiety as particularly common and detrimental comorbidities among the growing population living with chronic conditions. Digital health interventions (DHIs) hold promise in overcoming barriers to accessing mental health support for these individuals; however, the design and implementation of DHIs for depression and/or anxiety for people with chronic conditions is yet to be explored. Objective: To explore what is known in the literature about DHIs for the prevention, detection, or treatment of depression and/or anxiety among people with chronic conditions. Methods: A scoping review of the literature was conducted using the Arksey & O’Malley framework. Searches of the literature published in five databases between 1990 and 2019 were conducted in April 2019 and updated in March 2021. To be included, studies must have described a DHI tested with, or designed for, the prevention, detection, or treatment of depression and/or anxiety in people with common chronic conditions (arthritis, asthma, diabetes mellitus, heart disease, chronic obstructive pulmonary disease, cancer, stroke, Alzheimer’s disease and/or dementia). Studies were independently screened by two reviewers against the inclusion and exclusion criteria. Both quantitative and qualitative data were extracted, charted, and synthesized to provide a descriptive summary of the trends and considerations for future research. Results: Database searches yielded a total of 11,422 articles across the initial and update searches, 53 of which were included in this review. DHIs predominantly sought to provide treatment (n=44), followed by detection (n=5) and prevention (n=4). Most DHIs were focused on depression (n=36), guided (n=32), tailored to the chronic physical condition (n=19), and delivered through web-based platforms (n=20). Only two studies described the implementation of a DHI. Conclusions: As a growing research area, DHIs offer the potential to address the gap in care for depression and anxiety among people with chronic conditions; however, their implementation in standard care is scarce. While stepped care was identified as a promising model to implement efficacious DHIs, few studies have investigated the use of DHIs for depression and anxiety among chronic conditions with such models. In developing stepped care, we outline DHI tailoring, guidance, and intensity as key considerations requiring further research.

  • Background: Aim2Be is a gamified lifestyle app designed to promote lifestyle behaviour change among Canadian adolescents and their families. Objective: Our primary aim was to test the efficacy of the Aim2Be app with support from a live coach to reduce weight outcomes (Body Mass Index Z-score (zBMI)) and improve lifestyle behaviours among adolescents with overweight and obesity and their parents versus a waitlist control group over 3 months. Secondary aims were to compare health trajectories among waitlist control participants over 6 months (before and after receiving access to the app), assess whether support from a live coach enhanced intervention impact, and evaluate app usage influenced changes among intervention participants. Methods: A 2-arm parallel randomized control trial was conducted from November 2018 to June 2020. Adolescents aged 10-17 years with overweight or obesity and their parents were randomized into an intervention group (Aim2Be with live coach for 6 months) or a waitlist control group (Aim2Be with no live coach; accessed after 3 months). Adolescents’ assessments at baseline, 3- and 6- months included measured height and weight, 24-hour dietary recalls, and daily step counts measured with a Fitbit. Self-reported physical activity, screen time, fruit and vegetable intake, and sugary beverage intake of adolescents and parents were also collected. Results: A total of 214 parent-child participants were randomized. In our primary analyses, there were no significant differences in zBMI or any of the health behaviours between the intervention and control groups at 3 months. Secondary analyses revealed that among waitlist control participants, zBMI (mean difference between phases: -0.10; P=0.023) and discretionary calories (mean difference between phases: -5.8%; P=0.033) declined after receiving app access compared to before receiving app access. Adolescents randomized to Aim2Be with coaching reported more time being active outside of school compared to adolescents who used Aim2Be with no coaching over 3 months (P=0.001). App utilization did not modify any changes in outcomes among adolescents in the intervention group. Conclusions: The Aim2Be app did not improve zBMI and lifestyle behaviours in adolescents with overweight and obesity vs. a waitlist control group over 3 months. Future studies should explore the potential mediators of change in zBMI and lifestyle behaviours as well as predictors of engagement. Clinical Trial: The trial was prospectively registered at (NCT03651284) on 29 August 2018.

  • Supporting Autonomous Motivation for Physical Activity with Chatbots during COVID-19: A Factorial Experiment

    Date Submitted: Apr 20, 2022
    Open Peer Review Period: Apr 5, 2022 - May 31, 2022

    Background: While physical activity can mitigate disease trajectories, and improve and sustain mental health, many people have become less physically active during the COVID-19 pandemic. Personal information technology, such as activity trackers and chatbots, can technically converse with people and possibly enhance their autonomous motivation to undertake physical activity. The literature suggests that for an effective design of such interactions, adopting Behavioural Change Techniques (BCTs) based on Self-Determination Theory (SDT) seems promising, but this remains untested. Objective: The objectives of our study are (1) to test whether autonomous motivation for walking can be increased when a chatbot in combination with an activity tracking smartphone application (app) is used, (2) to confirm the underlying theoretical mechanisms, and (3) to evaluate the effectiveness of various BCT implementations. Methods: We employed a 2x2x3 factorial field experiment, using 12 variations of a chatbot which differed in three BCTs: goal setting, experimenting, and action planning. In total, 102 participants used a variation of the chatbot together with the Google Fit app over the course of three weeks. Each week, participants were asked to have a conversation with the chatbot and to complete a questionnaire capturing their perceived app/chatbot support, need-satisfaction, and physical activity levels. Motivation was measured before and after the three-week period. Results: On average, across all variations of the chatbot, participants reported significant increases in autonomous motivation (P<.001). Motivation was associated with need-satisfaction (P<.001) and need-satisfaction was associated with perceived app/chatbot support (P=.002). In terms of the different BCT implementations no significant differences were found. While many participants (49%) would have preferred to interact with a human instead of the chatbot, 46% of the participants stated that the chatbot helped them to become more active, and 42% of the participants decided to keep using the chatbot for an additional week. Furthermore, a majority thought that a more advanced chatbot could be very helpful. Conclusions: The results provide evidence that a chatbot in combination with a physical activity tracking app such as Google Fit can increase autonomous motivation by supporting the needs of competence and autonomy. Our study also clarifies a need to further study how the corresponding Behavioural Change Techniques are best implemented, and how other BCTs could be studied.

  • Background: Dry eye (DE) and hay fever show synergistic exacerbation of each other’s pathology through inflammatory pathways. Objective: We aimed to investigate the association between hay fever symptoms and DE comorbidity as well as the related risk factors. Methods: This cross-sectional observational study was conducted using crowdsourced multidimensional integrative data of individuals who downloaded the smartphone application, AllerSearch, in Japan between February 1, 2018, and May 1, 2020. Hay fever was defined by the participants’ responses to the questionnaire: hay fever, non-hay fever, and unknown. Symptomatic DE was defined as a Japanese version of Ocular Surface Disease Index total score of ≥ 13. We conducted a multivariable regression analysis examining the association between the severity of DE symptoms and hay fever symptoms. We then conducted a multivariable logistic regression analysis to identify factors associated with symptomatic DE (vs. non-symptomatic DE) among individuals with hay fever. Results: Among 11284 participants, 9041 were classified into the experiencing hay fever, 720 into the non-hay fever, and 1523 into the unknown groups. There was a significant positive association between the severity of DE symptoms and hay fever symptoms. The prevalence of symptomatic DE was 49.0% (4429/9041) among individuals with hay fever. There were personal and contextual risk factors for comorbid symptomatic DE among individuals with hay fever. Conclusions: This crowdsourced research suggests a significant association between severe DE and hay fever symptoms. Detecting DE among individuals with hay fever could allow effective prevention and interventions through complementary treatment for ocular surface management along with hay fever treatment.

  • Validity and Sources of WhatsApp Health Messages Used by the Public in Saudi Arabia: An Observational Study

    Date Submitted: Apr 5, 2022
    Open Peer Review Period: Apr 4, 2022 - May 30, 2022

    Background: Social media is a platform that allows users to communicate and share information or ideas and experiences. Health information found on social media is written and shared by people from different educational and credibility levels. Objective: To estimate the validity and safety of Arabic language health information messages circulated on WhatsApp and to classify them into different categories based on their credibility and sources. Methods: A descriptive-analytical, cross-sectional study was conducted from Feb-April 2021. A convenience sampling technique was used. Students from Common First Preparatory Year College at King Saud University participated through sharing three health-related WhatsApp messages that they or their relatives have read recently. Four Board-certified physicians reviewed and classified the messages into categories based on their credibility and sources. Results: Two hundred eighty-two (282) students filled out a socio-demographic characteristics questionnaire and 63% of them were female students. Out of the 326 messages, 86% were either invalid or inaccurate. Most messages (83.7%) were from unknown sources. 8.3% of the messages were obtained from known sources but written by unqualified persons represented 8.3% of the messages. Written by qualified persons (5.8%) or trusted scientific sources (2.1%) represented only 8% of the total messages. There was a significant association between the sources and the validity of the message’s information. Most of the messages from unknown sources or unqualified persons were either invalid or invalid with potential risk. Conclusions: This study showed a high percentage of inaccurate and invalid health-related messages on WhatsApp. Invalid with potential risk messages were mainly from unknown sources or unqualified persons. Most of the health messages written by trusted authorities and qualified persons were valid. Trusted scientific authorities should be more active in social media platforms, and they should advise the community on how to discern the validity of such messages. More efforts are needed to guide the patients from where to get accurate and valid health information.

  • Background: Primary care providers are regarded as trustworthy sources of information about COVID-19 vaccines, but little is known about whether primary care practices provide information about COVID-19 vaccines on their practice websites. Objective: To identify the prevalence and correlates of COVID-19 vaccine information on family medicine practice website homepages in the United States. Methods: Between September 20 and October 8, 2021, we examined 964 U.S.-based family medicine practice websites and extracted data on the availability of COVID-19 vaccine information. We estimated prevalence of COVID-19 vaccine information on practice website homepages and used Poisson regression with robust error variances to estimate crude and adjusted prevalence ratios for correlates of COVID-19 vaccine information, including practice size, practice region, university affiliation, and presence of information about seasonal influenza vaccines. Results: Of 964 websites, 550 (57%) mentioned COVID-19 vaccines on their practice website homepage. As practice size increased, the likelihood of finding COVID-19 vaccine information on the homepage increased (28% among single-location practices compared to 78% among practices with 20 or more locations, p<0.01). Compared to clinics in the Northeast, clinics in the West and Mid-west had a similar prevalence of COVID-19 vaccine information on website homepages, but clinics in the South had a lower prevalence (adjusted prevalence ratio 0.8, 95% CI: 0.7 to 1.0, p=0.02). Conclusions: Given the ongoing COVID-19 pandemic, primary care practitioners who promote and provide vaccines should strongly consider utilizing their existing practice websites to share COVID-19 vaccine information. These existing platforms can serve as an extension of providers’ influence on established and prospective patients who search online for information about COVID-19 vaccines.

  • Background: The Covid-19 vaccine remains central to the UK government’s plan for tackling the Covid-19 pandemic. Average uptake of 3 doses in the UK stands at 66.7% as of March 2022, however this rate varies across localities. Understanding the views of groups who have low vaccine uptake is crucial to guide efforts to improve vaccine uptake. Objective: A qualitative social media analysis of social media posts from Nottinghamshire based profiles and data sources to understand vaccine hesitancy in Nottingham and make intervention recommendations to increase vaccination uptake. Methods: A manual search strategy was used to search the Nottingham Post website, and local Facebook and Twitter accounts from September to October 2021. Only comments in the public domain and in English were included in the analysis. A total of 3508 comments from 1238 users on Covid-19 vaccine posts by 10 different local organisations were analysed. Results: 6 over-arching themes were identified: lack of trust in vaccine information, information sources including the media, and the government; belief that the vaccine is not safe due to the speed of development and approval process, the severity of side effects and belief that the ingredients are harmful; belief that the vaccine is not effective as people can still become infected and spread the virus, and that the vaccine may increase transmission through shedding; belief that the vaccine is not necessary due to low perceived risk of death and severe outcomes, and use of other protective measures such as natural immunity, ventilation, testing, face coverings and self-isolation; individual rights and freedoms to be able to choose to have the vaccine or not without judgement or discrimination; and barriers to physical access. Conclusions: The findings reveal a wide range of beliefs and attitudes towards the Covid-19 vaccination. Implications for the vaccine programme in Nottingham include communication strategies delivered by trusted sources to address the gaps in knowledge identified, whilst acknowledging some negatives such as side effects alongside emphasising the benefits. These strategies should avoid perpetuating myths and avoid using scare tactics when addressing risk perceptions. Accessibility should also be considered with a review of current vaccination site locations, opening hours and transport links. Additional research may benefit from using qualitative interviews or focus groups to further probe on the themes identified and explore the acceptability of the recommended interventions.

  • Background: HIV self-testing is preferred by many Chinese for its convenience and confidentiality. However, most studies on HIV self-testing (HIVST) uptake in China over-focused on men who have sex with men (MSM) and over-relied on obtrusive methods such as surveys and interviews to collect data. Objective: The current study aims to explore Chinese HIVST-kit users’ authentic experience via their feedback comments posted on e-commerce platforms from an unobtrusive approach. Methods: In total, 21018 feedback comments about buying and using HIVST kits posted on Chinese e-commerce platforms (Tmall and Pinduoduo) were collected. An inductive thematic analysis based on a random sample of 367 comments were conducted and yielded several thematic features. These thematic features were developed into coding categories for a quantitative content analysis of another random sample of 1857 comments. Results: Four themes were identified in the first study including expression of positive and negative emotions after and before getting test respectively, calling for living a clean and moral life in the future, comments on the sellers and HIVST kits, and narratives about the reasons for buying HIVST kits. The results from the second study suggested that there were significant associations between different platforms and several thematic features. Nearly 50% of the comments were related to the product itself and the disclosures of HIV negative test results. More than 25% of the comments showed users’ feelings of gratefulness after receiving negative test results such as “thank heavens for sparing my life”. Conclusions: The results suggested that Chinese users relied on HIVST kits to reduce and prevent HIV infection while they also considered getting HIV infection uncontrollable or dependent on one’s morality. The traditional Chinese health belief in which health is influenced by one’s morality still persists among some Chinese users. Many users also lacked appropriate knowledge about HIV transmission and self-testing kits. Clinical Trial: Not applicable.

  • Public health communication ethics theories and their application in COVID-19 infodemic: a narrative review

    Date Submitted: Mar 31, 2022
    Open Peer Review Period: Mar 30, 2022 - May 25, 2022

    Background: Public health communication plays an important role in all stages of a public health emergency. Effective communication is essential for encouraging people to follow preventive measures and mitigation strategies. Objective: The objective of this study was to provide an overview of the ethical theories related to public health communication in the context of COVID-19. Methods: Electronic databases were searched for relevant literature in English language published between 2020 and 2022 using a custom search strategy. Screening of the title-abstract and full texts of the included records was carried out by two reviewers in single. Results: The review identified nine key principles and three theories that were widely used in public health communication ethics. The nine principles for authorities to ethically communicate information included: evidence, participation, equity, transparency, precaution, proportionality, flexibility, testing and uncertainty. In order to be ethical, the information in public health communication should be reliable, trustworthy, accurate, clear, evidence-based, and advise the public to make informed choices based on these. Epistemic humility, Kant’s categorical imperative, and utilitarian theory were found to be applied for decision-making during the pandemic. Conclusions: Theories and principles of public health communication ethics can be applied for decision-making during the COVID-19 infodemic. Governments and public health organizations should work towards empowering the communities by equipping them with trustworthy, reliable and evidence-based information to make informed decisions. Transparent and honest communication to the public, especially relating to uncertainties, can increase the public’s trust in authorities and public health efforts.

  • Background: Financial incentive interventions for improving physical activity have proven to be effective but costly. Deposit contracts (a type of incentive in which participants pledge their own money) could be an affordable alternative. In addition, deposit contracts may have superior effects by exploiting the power of loss aversion. Previous research often operationalized deposit contracts through framing a financial reward as a loss (without requiring a deposit) to mimic the feelings of loss involved in a deposit contract. Objective: This study aims to disentangle the effects of incurring actual losses (through self-funding a deposit contract) and loss framing. We investigated (1) whether incentive conditions are more effective than a no-incentive control condition, (2) whether deposit contracts have lower uptake than financial rewards, (3) whether deposit contracts are more effective than financial rewards, and (4) whether loss frames are more effective than gain frames. Methods: Healthy participants (N = 126) with an average age of 22.7 years participated in a 20-day physical activity intervention. They downloaded a smartphone application that provided them with a personalised physical activity goal and either required a €10 deposit upfront (which could be lost) or provided €10 as a reward, contingent on performance. Daily feedback on incentive earnings was provided and framed as either a loss or a gain. We employed a 2 (incentive type: deposit vs reward) x 2 (feedback frame: gain vs loss) between-subjects factorial design with a no incentive control condition. Our primary outcome was the number of days participants achieved their goal. Uptake of the intervention was a secondary outcome. Results: Overall, financial incentive conditions (M = 13.10 days) had higher effectiveness than the control condition (M = 8.00 days), p = .002, ηp2 = .147. Deposit contracts had lower uptake (61.7%) than rewards (100%), p = <.001, V = .492. Furthermore, two-way ANCOVA showed that deposit contracts (M = 14.88 days) were not significantly more effective than rewards (M = 12.13 days), p = .166. Unexpectedly, loss frames (M = 10.50 days) were significantly less effective than gain frames (M = 14.67 days), p = .007, ηp2 = .155. Conclusions: We found that financial incentives help increase physical activity, but deposit contracts were not more effective than rewards. Although self-funded deposit contracts can be offered at low cost, low uptake is an important obstacle for large scale implementation. Unexpectedly, loss framing was less effective than gain framing. Therefore, we urge for more research on their boundary conditions before using loss framed incentives in practice. Clinical Trial: OSF Registries,

  • #DataSavesLives: Exploring how the hashtag is used on Twitter.

    Date Submitted: Mar 24, 2022
    Open Peer Review Period: Mar 24, 2022 - May 19, 2022

    Background: The #DataSavesLives Data Saves Lives is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area. Objective: Exploring how the #DataSavesLives is utilised on Twitter. We focused on the period when the campaign has expanded outside the United Kingdom and was relaunched around Europe. Methods: Public tweets published between 19th April and 15th July 2021, using the hashtag #DataSavesLives were saved using NCapture for NVivo. All tweets were coded twice. Firstly, each tweet was assigned a positive, neutral or negative attitude towards the campaign. Secondly, inductive thematic analysis was conducted. Results: Of 1026 unique tweets available for qualitative analysis, discussion around #DataSavesLives was largely positive (n=716) or neutral (n=276) towards the campaign with limited negative attitudes (n=34). Themes derived from the #DataSavesLives debate included: ethical data sharing; the importance of how to proactively engage the public, harnessing the potential of big data; and sharing ideas. The Twitter discourse remains mostly positive towards the campaign. The hashtag is predominantly used by similarly-minded Twitter users to share information about big data projects and to spread positive messages about big data research when there are public controversies. The hashtag usage is mostly by organisation and people supportive of big data research. Tweet authors recognise that the public should be proactively engaged and involved in big data projects. The campaign remains UK centric. The results indicate that the communication around big data research is driven by the professional community and remains one-way as the public rarely use the hashtag. Conclusions: The results demonstrate the potential of social media but draws attention to hashtag usage being generally confined to ‘Twitter bubbles’; groups of similarly-minded Twitter users.