JMIR Publications

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  New Methods

  Nov 11, 2019

  The Service of Research Analytics to Optimize Digital Health Evidence Generation: Multilevel Case Study

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  Authors List:

  • Quynh Pham  
  • James Shaw  
  • Plinio P Morita  
  • Emily Seto  
  • Jennifer N Stinson  
  • Joseph A Cafazzo  

  Abstract:

  Background: The widespread adoption of digital health interventions for chronic disease self-management has catalyzed a paradigm shift in the selection of methodologies used to evidence them. Recently, the application of digital health research analytics has emerged as an efficient approach to evaluate these data-rich interventions. However, there is a growing mismatch between the promising evidence base emerging from analytics mediated trials and the complexity of introducing these novel research methods into evaluative practice. Objective: This study aimed to generate transferable insights into the process of implementing research analytics to evaluate digital health interventions. We sought to answer the following two research questions: (1) how should the service of research analytics be designed to optimize digital health evidence generation? and (2) what are the challenges and opportunities to scale, spread, and sustain this service in evaluative practice? Methods: We conducted a qualitative multilevel embedded single case study of implementing research analytics in evaluative practice that comprised a review of the policy and regulatory climate in Ontario (macro level), a field study of introducing a digital health analytics platform into evaluative practice (meso level), and interviews with digital health innovators on their perceptions of analytics and evaluation (microlevel). Results: The practice of research analytics is an efficient and effective means of supporting digital health evidence generation. The introduction of a research analytics platform to evaluate effective engagement with digital health interventions into a busy research lab was ultimately accepted by research staff, became routinized in their evaluative practice, and optimized their existing mechanisms of log data analysis and interpretation. The capacity for research analytics to optimize digital health evaluations is highest when there is (1) a collaborative working relationship between research client and analytics service provider, (2) a data-driven research agenda, (3) a robust data infrastructure with clear documentation of analytic tags, (4) in-house software development expertise, and (5) a collective tolerance for methodological change. Conclusions: Scientific methods and practices that can facilitate the agile trials needed to iterate and improve digital health interventions warrant continued implementation. The service of research analytics may help to accelerate the pace of digital health evidence generation and build a data-rich research infrastructure that enables continuous learning and evaluation.

  • J Med Internet Res 2019;21(11):e14849

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  Peer-to-Peer Support and Online...

  Nov 11, 2019

  Effects of Three Antecedents of Patient Compliance for Users of Peer-to-Peer Online Health Communities: Cross-Sectional Study

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  Authors List:

  • Anne-Françoise Audrain-Pontevia  
  • Loick Menvielle  
  • Myriam Ertz  

  Abstract:

  Background: Over the past 50 years, patient noncompliance has appeared as a major public health concern and focus of a great deal of research because it endangers patient recovery and imposes a considerable financial burden on health care systems. Meanwhile, online health communities (OHCs) are becoming more common and are commonly used by individuals with health problems, and they may have a role in facilitating compliance. Despite this growing popularity, little is known about patient compliance predictors for OHCs’ users. Objective: This study aimed to investigate the extent to which participating in OHCs may trigger higher levels of compliance. It identified 3 interrelated predictors that may affect patient compliance: patient empowerment gained through peer-to-peer OHCs, satisfaction with the physician, and commitment to the physician. Methods: A Web-based survey tested the conceptual model and assessed the effects of patient empowerment gained through OHCs on patient satisfaction and commitment to the physician, as well as the effects of these 3 predictors on patient compliance with the proposed treatment. Members of peer-to-peer OHCs were asked to answer an online questionnaire. A convenience sample of 420 patients experiencing chronic illness and using peer-to-peer OHCs was surveyed in August 2018 in Québec, Canada. A path analysis using structural equation modeling tested the proposed relationships between the predictors and their respective paths on patient compliance. The mediation effects of these predictor variables on patient compliance were estimated with the PROCESS macro in SPSS. Results: The findings indicated that patient empowerment gained through OHCs was positively related to patient commitment to the physician (beta=.69; P<.001) and patient compliance with the proposed treatment (beta=.35; P<.001). Patient commitment also positively influenced patient compliance (beta=.74; P<.001). Patient empowerment did not exert a significant influence on patient satisfaction with the physician (beta=.02; P=.76), and satisfaction did not affect compliance (beta=−.07; P=.05); however, patient satisfaction was positively related to patient commitment to the physician (beta=.14; P<.01). The impact of empowerment on compliance was partially mediated by commitment to the physician (beta=.32; 95% CI 0.22-0.44) but not by satisfaction. Conclusions: This study highlights the importance of peer-to-peer OHCs for two main reasons. The primary reason is that patient empowerment gained through peer-to-peer OHCs both directly and indirectly enhances patient compliance with the proposed treatment. The underlying mechanisms of these effects were shown. Second, commitment to the physician was found to play a more critical role than satisfaction with the physician in determining patient-physician relationship quality. Overall, our findings support the assumption that health care stakeholders should encourage the use of peer-to-peer OHCs to favor patient empowerment and patient commitment to the physician to increase patient compliance with the proposed treatment.

  • J Med Internet Res 2019;21(11):e14006

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  Information Retrieval

  Nov 11, 2019

  Patients’ Use of the Internet to Find Reliable Medical Information About Minor Ailments: Vignette-Based Experimental Study

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  Authors List:

  • Joyce Kwakernaak  
  • Just AH Eekhof  
  • Margot WM De Waal  
  • Elisabeth AM Barenbrug  
  • Niels H Chavannes  

  Abstract:

  Background: Little is known about the exact process of how patients search for medical information on the internet and what they retrieve. There is especially a paucity of literature on browsing for information on minor ailments, a term used for harmless diseases that are very common in the general population and thus have a significant impact on health care. Objective: This vignette-based experimental study aimed to explore what kind of Web-based search strategies are applied and how search strategies, demographic characteristics, and the quality of the visited websites relate to finding the right diagnosis. Additional goals were to describe how searching on the Web influences one’s perception of the severity of the potential diagnosis and whether or not the participants would discuss the information they found on the internet with their doctors. Methods: Out of 1372 survey participants, 355 were randomly sampled, and 155 of them were recruited and assigned to one of four clinical scenarios. Each search term they used was classified as one of three search strategies: (1) hypothesis testing, (2) narrowing within the general hypothesis area, and (3) symptom exploration. The quality of the websites used was determined by using the DISCERN instrument. To compare the diagnostic accuracy of the participants before and after the internet search, a McNemar test was used. Chi-square tests were used to describe which factors are related to the chosen search strategy. A multivariate binary logistic regression model was constructed to predict which factors are related to finding a sound diagnosis after searching the internet for health information. Results: Most participants (65.8%, 102/155) used the symptom exploration strategy. However, this depends on the assigned scenario (P<.001) and the self-estimated severity score of the symptoms before the internet search (P=.001). A significant relation was found between choosing an accurate diagnosis and age (odds ratio [OR] 0.94, 95% CI 0.90 to 0.98) and the clinical scenario, as well as the use of high-quality websites (OR 7.49, 95% CI 1.85 to 30.26). Browsing the internet did not lead to a statistically significant change in participants’ beliefs about the severity of the condition (McNemar test, P=.85). Most participants (65%) shared their retrieved information with their physician and most of them (75%) received a positive response. Conclusions: Our findings suggest that most patients use a symptom-based approach; however, if patients expect the potential diagnosis to be severe, they tend to use a hypothesis verification strategy more often and are therefore prone to certain forms of bias. In addition, self-diagnosing accuracy is related to younger age, the symptom scenario, and the use of high-quality websites. We should find ways to guide patients toward search strategies and websites that may more likely lead to accurate decision making.

  • J Med Internet Res 2019;21(11):e12278

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  Quality/Credibility of eHealth...

  Nov 11, 2019

  A Revised Model of Trust in Internet-Based Health Information and Advice: Cross-Sectional Questionnaire Study

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  Authors List:

  • Elizabeth Sillence  
  • John Matthew Blythe  
  • Pam Briggs  
  • Mark Moss  

  Abstract:

  Background: The internet continues to offer new forms of support for health decision making. Government, charity, and commercial websites increasingly offer a platform for shared personal health experiences, and these are just some of the opportunities that have arisen in a largely unregulated arena. Understanding how people trust and act on this information has always been an important issue and remains so, particularly as the design practices of health websites continue to evolve and raise further concerns regarding their trustworthiness. Objective: The aim of this study was to identify the key factors influencing US and UK citizens’ trust and intention to act on advice found on health websites and to understand the role of patient experiences. Methods: A total of 1123 users took part in an online survey (625 from the United States and 498 from the United Kingdom). They were asked to recall their previous visit to a health website. The online survey consisted of an updated general Web trust questionnaire to account for personal experiences plus questions assessing key factors associated with trust in health websites (information corroboration and coping perception) and intention to act. We performed principal component analysis (PCA), then explored the relationship between the factor structure and outcomes by testing the fit to the sampled data using structural equation modeling (SEM). We also explored the model fit across US and UK populations. Results: PCA of the general Web trust questionnaire revealed 4 trust factors: (1) personal experiences, (2) credibility and impartiality, (3) privacy, and (4) familiarity. In the final SEM model, trust was found to have a significant direct effect on intention to act (beta=.59; P<.001), and of the trust factors, only credibility and impartiality had a significant direct effect on trust (beta=.79; P<.001). The impact of personal experiences on trust was mediated through information corroboration (beta=.06; P=.04). Variables specific to electronic health (eHealth; information corroboration and coping) were found to substantially improve the model fit, and differences in information corroboration were found between US and UK samples. The final model accounting for all factors achieved a good fit (goodness-of-fit index [0.95], adjusted goodness-of-fit index [0.93], root mean square error of approximation [0.50], and comparative fit index [0.98]) and explained 65% of the variance in trust and 41% of the variance in intention to act. Conclusions: Credibility and impartiality continue to be key predictors of trust in eHealth websites. Websites with patient experiences can positively influence trust but only if users first corroborate the information through other sources. The need for corroboration was weaker in the United Kingdom, where website familiarity reduced the need to check information elsewhere. These findings are discussed in relation to existing trust models, patient experiences, and health literacy.

  • J Med Internet Res 2019;21(11):e11125

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  Theme issue 2019: 20th Anniversary Issue

  Nov 8, 2019

  Unlocking the Power of Artificial Intelligence and Big Data in Medicine

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  Authors List:

  • Christian Lovis  

  Abstract:

  unstructured: Data-driven science and its corollaries in machine learning and the wider field of artificial intelligence have the potential to drive important changes in medicine. However, medicine is not a science like any other: It is deeply and tightly bound, with a large and wide network of legal, ethical, regulatory, economical, and societal dependencies. As a consequence, the scientific and technological progresses in handling information and its further processing and cross-linking for decision support and predictive systems must be accompanied by parallel changes in the global environment, with numerous stakeholders, including citizen and society. What can be seen at the first glance as a barrier and mechanism slowing down the progression of data science must, however, be considered an important asset. Only global adoption can transform the potential of big data and artificial intelligence into an effective breakthroughs in handling health and medicine. This requires science and society, scientists and citizens, to progress together.

  • J Med Internet Res 2019;21(11):e16607

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  Theme issue 2019: 20th Anniversary Issue

  Nov 8, 2019

  The Last Mile: Where Artificial Intelligence Meets Reality

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  Authors List:

  • Enrico Coiera  

  Abstract:

  Although much effort is focused on improving the technical performance of artificial intelligence, there are compelling reasons to focus more on the implementation of this technology class to solve real-world applications. In this “last mile” of implementation lie many complex challenges that may make technically high-performing systems perform poorly. Instead of viewing artificial intelligence development as a linear one of algorithm development through to eventual deployment, there are strong reasons to take a more agile approach, iteratively developing and testing artificial intelligence within the context in which it finally will be used.

  • J Med Internet Res 2019;21(11):e16323

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  New Methods

  Nov 8, 2019

  Validation of an Independent Web-Based Tool for Measuring Visual Acuity and Refractive Error (the Manifest versus Online Refractive Evaluation Trial):...

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  Authors List:

  • Robert P L Wisse  
  • Marc B Muijzer  
  • Francesco Cassano  
  • Daniel A Godefrooij  
  • Yves F D M Prevoo  
  • Nienke Soeters  

  Abstract:

  Background: Digital tools provide a unique opportunity to increase access to eye care. We developed a Web-based test that measures visual acuity and both spherical and cylindrical refractive errors. This test is Conformité Européenne marked and available on the Easee website. The purpose of this study was to compare the efficacy of this Web-based tool with traditional subjective manifest refraction in a prospective open-label noninferiority clinical trial. Objective: The aim of this study was to evaluate the outcome of a Web-based refraction compared with a manifest refraction (golden standard). Methods: Healthy volunteers from 18 to 40 years of age, with a refraction error between –6 and +4 diopter (D), were eligible. Each participant performed the Web-based test, and the reference test was performed by an optometrist. An absolute difference in refractive error of <0.5 D was considered noninferior. Reliability was assessed by using an intraclass correlation coefficient (ICC). Both uncorrected and corrected visual acuity were measured. Results: A total of 200 eyes in 100 healthy volunteers were examined. The Web-based assessment of refractive error had excellent correlation with the reference test (ICC=0.92) and was considered noninferior to the reference test. Uncorrected visual acuity was similar with the Web-based test and the reference test (P=.21). Visual acuity was significantly improved using the prescription obtained by using the Web-based tool (P<.01). The Web-based test provided the best results in participants with mild myopia (ie, <3 D), with a mean difference of 0.02 (SD 0.49) D (P=.48) and yielding a corrected visual acuity of >1.0 in 90% (n=77) of participants. Conclusions: Our results indicate that Web-based eye testing is a valid and safe method for measuring visual acuity and refractive error in healthy eyes, particularly for mild myopia. This tool can be used for screening purposes, and it is an easily accessible alternative to the subjective manifest refraction test. Clinical Trial: Clinicaltrials.gov NCT03313921; https://clinicaltrials.gov/ct2/show/NCT03313921.

  • J Med Internet Res 2019;21(11):e14808

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  Physician and Health Services Rating...

  Nov 8, 2019

  Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study

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  Authors List:

  • Jill S Borchert  
  • Bo Wang  
  • Muzaina Ramzanali  
  • Amy B Stein  
  • Latha M Malaiyandi  
  • Kirk E Dineley  

  Abstract:

  Background: Patient online drug reviews are a resource for other patients seeking information about the practical benefits and drawbacks of drug therapies. Patient reviews may also serve as a source of postmarketing safety data that are more user-friendly than regulatory databases. However, the reliability of online reviews has been questioned, because they do not undergo professional review and lack means of verification. Objective: We evaluated online reviews of hypnotic medications, because they are commonly used and their therapeutic efficacy is particularly amenable to patient self-evaluation. Our primary objective was to compare the types and frequencies of adverse events reported to the Food and Drug Administration Adverse Event Reporting System (FAERS) with analogous information in patient reviews on the consumer health website Drugs.com. The secondary objectives were to describe patient reports of efficacy and adverse events and assess the influence of medication cost, effectiveness, and adverse events on user ratings of hypnotic medications. Methods: Patient ratings and narratives were retrieved from 1407 reviews on Drugs.com between February 2007 and March 2018 for eszopiclone, ramelteon, suvorexant, zaleplon, and zolpidem. Reviews were coded to preferred terms in the Medical Dictionary for Regulatory Activities. These reviews were compared to 5916 cases in the FAERS database from January 2015 to September 2017. Results: Similar adverse events were reported to both Drugs.com and FAERS. Both resources identified a lack of efficacy as a common complaint for all five drugs. Both resources revealed that amnesia commonly occurs with eszopiclone, zaleplon, and zolpidem, while nightmares commonly occur with suvorexant. Compared to FAERS, online reviews of zolpidem reported a much higher frequency of amnesia and partial sleep activities. User ratings were highest for zolpidem and lowest for suvorexant. Statistical analyses showed that patient ratings are influenced by considerations of efficacy and adverse events, while drug cost is unimportant. Conclusions: For hypnotic medications, online patient reviews and FAERS emphasized similar adverse events. Online reviewers rated drugs based on perception of efficacy and adverse events. We conclude that online patient reviews of hypnotics are a valid source that can supplement traditional adverse event reporting systems.

  • J Med Internet Res 2019;21(11):e13371

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  Chatbots and Conversational Agents

  Nov 7, 2019

  The Personalization of Conversational Agents in Health Care: Systematic Review

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  Authors List:

  • Ahmet Baki Kocaballi  
  • Shlomo Berkovsky  
  • Juan C Quiroz  
  • Liliana Laranjo  
  • Huong Ly Tong  
  • Dana Rezazadegan  
  • Agustina Briatore  
  • Enrico Coiera  

  Abstract:

  Background: The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. Objective: The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in health care and characterize the methods of its implementation. Methods: We searched on PubMed, Embase, CINAHL, PsycInfo, and ACM Digital Library using a predefined search strategy. The studies were included if they: (1) were primary research studies that focused on consumers, caregivers, or health care professionals; (2) involved a conversational agent with an unconstrained natural language interface; (3) tested the system with human subjects; and (4) implemented personalization features. Results: The search found 1958 publications. After abstract and full-text screening, 13 studies were included in the review. Common examples of personalized content included feedback, daily health reports, alerts, warnings, and recommendations. The personalization features were implemented without a theoretical framework of customization and with limited evaluation of its impact. While conversational agents with personalization features were reported to improve user satisfaction, user engagement and dialogue quality, the role of personalization in improving health outcomes was not assessed directly. Conclusions: Most of the studies in our review implemented the personalization features without theoretical or evidence-based support for them and did not leverage the recent developments in other domains of personalization. Future research could incorporate personalization as a distinct design factor with a more careful consideration of its impact on health outcomes and its implications on patient safety, privacy, and decision-making.

  • J Med Internet Res 2019;21(11):e15360

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  Special Issue: Analysis of Randomized...

  Nov 7, 2019

  Electronic Screening for Alcohol Use and Brief Intervention by Email for University Students: Reanalysis of Findings From a Randomized Controlled Trial Using...

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  Authors List:

  • Marcus Bendtsen  

  Abstract:

  Background: Almost a decade ago, Sweden became the first country to implement a national system enabling student health care centers across all universities to routinely administer (via email) an electronic alcohol screening and brief intervention to their students. The Alcohol email assessment and feedback study dismantling effectiveness for university students (AMADEUS-1) trial aimed to assess the effect of the student health care centers’ routine practices by exploiting the lack of any standard timing for the email invitation and by masking trial participation from students. The original analyses adopted the conventional null hypothesis framework, and the results were consistently in the expected direction. However, since for some tests the P values did not pass the conventional .05 threshold, some of the analyses were necessarily inconclusive. Objective: The outcomes of the AMADEUS-1 trial were derived from the first 3 items of the Alcohol Use Disorders Identification Test (AUDIT-C). The aim of this paper was to reanalyze the two primary outcomes of the AMADEUS-1 trial (AUDIT-C scores and prevalence of risky drinking), using the same models used in the original publication but applying a Bayesian inference framework and interpretation. Methods: The same regression models used in the original analysis were employed in this reanalysis (linear and logistic regression). Model parameters were given uniform priors. Markov chain Monte Carlo was used for Bayesian inference, and posterior probabilities were calculated for prespecified thresholds of interest. Results: Where the null hypothesis tests showed inconclusive results, the Bayesian analysis showed that offering an intervention at baseline was preferable compared to offering nothing. At follow-up, the probability of a lower AUDIT-C score among those who had been offered an intervention at baseline was greater than 95%, as was the case when comparing the prevalence of risky drinking. Conclusions: The Bayesian analysis allows for a more consistent perspective of the data collected in the trial, since dichotomization of evidence is not looked for at some arbitrary threshold. Results are presented that represent the data collected in the trial rather than trying to make conclusions about the existence of a population effect. Thus, policy makers can think about the value of keeping the national system without having to navigate the treacherous landscape of statistical significance. Clinical Trial: ISRCTN Registry ISRCTN28328154; http://www.isrctn.com/ISRCTN28328154

  • J Med Internet Res 2019;21(11):e14419

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  Web-based and Mobile Health...

  Nov 7, 2019

  A New Mental Health Mobile App for Well-Being and Stress Reduction in Working Women: Randomized Controlled Trial

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  Authors List:

  • Cássia Canha Coelhoso  
  • Patricia Renovato Tobo  
  • Shirley Silva Lacerda  
  • Alex Heitor Lima  
  • Carla Regina Camara Barrichello  
  • Edson Amaro Jr  
  • Elisa Harumi Kozasa  

  Abstract:

  Background: Although the availability and use of mobile mental health apps has grown exponentially in recent years, little data are available regarding their efficacy. Objective: This study aimed to evaluate the effectiveness of an app developed to promote stress management and well-being among working women compared with a control app. Methods: Female employees at a private hospital were invited to participate in the study via mailing lists and intranet ads. A total of 653 individuals self-enrolled through the website. Eligible participants were randomized between control (n=240) and intervention (n=250) groups. The well-being mobile app provides an 8-week program with 4 classes per week (including a brief theoretical portion and a 15-min guided practice). The active control app also provided 4 assessments per week that encouraged participants to self-observe how they were feeling for 20 min. We also used the app to conduct Web-based questionnaires (10-item Perceived Stress Scale and 5-item World Health Organization Well-Being Index) and ask specific questions to assess subjective levels of stress and well-being at baseline (t₁), midintervention (t₄=4 weeks after t₁) and postintervention (t₈=8 weeks after t₁). Both apps were fully automated without any human involvement. Outcomes from the control and intervention conditions at the 3 time points were analyzed using a repeated measures analysis of variance. Results: Among the randomized participants (n=490), 185 participants were excluded at the 4-week follow-up and another 79 at the 8-week follow-up because of noncompliance with the experimental protocol. Participants who did not complete t₄ and t₈ assessments were equally distributed between groups (t₄: control group=34.6% [83/240] and intervention group=40.8% [102/250]; P=.16; t₈: control group=29.9% [47/157] and intervention group=21.6% [32/148]; P=.10). Both groups showed a significant increase in general well-being as a function of time (F_2,426=5.27; P=.006), but only the intervention group presented a significant increase in work-related well-being (F_2,426=8.92; P<.001), as well as a significant reduction in work-related and overall stress (F_2,426=5.50; P=.004 and F_2,426=8.59; P<.001, respectively). Conclusions: The well-being mobile app was effective in reducing employee stress and improving well-being. Clinical Trial: Clinicaltrials.gov NCT02637414; https://clinicaltrials.gov/ct2/show/NCT02637414.

  • J Med Internet Res 2019;21(11):e14269

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  Theme issue 2019: 20th Anniversary Issue

  Nov 6, 2019

  Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research...

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  Authors List:

  • Scott Barnett  
  • Kit Huckvale  
  • Helen Christensen  
  • Svetha Venkatesh  
  • Kon Mouzakis  
  • Rajesh Vasa  

  Abstract:

  unstructured: In this viewpoint we describe the architecture of, and design rationale for, a new software platform designed to support the conduct of digital phenotyping research studies. These studies seek to collect passive and active sensor signals from participants' smartphones for the purposes of modelling and predicting health outcomes, with a specific focus on mental health. We also highlight features of the current research landscape that recommend the coordinated development of such platforms, including the significant technical and resource costs of development, and we identify specific considerations relevant to the design of platforms for digital phenotyping. In addition, we describe trade-offs relating to data quality and completeness versus the experience for patients and public users who consent to their devices being used to collect data. We summarize distinctive features of the resulting platform, InSTIL (Intelligent Sensing to Inform and Learn), which includes universal (ie, cross-platform) support for both iOS and Android devices and privacy-preserving mechanisms which, by default, collect only anonymized participant data. We conclude with a discussion of recommendations for future work arising from learning during the development of the platform. The development of the InSTIL platform is a key step towards our research vision of a population-scale, international, digital phenotyping bank. With suitable adoption, the platform will aggregate signals from large numbers of participants and large numbers of research studies to support modelling and machine learning analyses focused on the prediction of mental illness onset and disease trajectories.

  • J Med Internet Res 2019;21(11):e16399

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