JMIR Publications

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  Email Communication, Web-Based...

  Dec 14, 2018

  Pediatric Web-Based Chat Services for Caregivers of Children: Descriptive Study

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  Authors List:

  • Anu Kaskinen  
  • Benjamin Ayeboa-Sallah  
  • Tiina Teivaanmäki  
  • Elina Wärnhjelm  
  • Liisa Korhonen  
  • Otto Helve  

  Abstract:

  Background: Pediatric physician-led Web-based chat services offer a novel, low-threshold communication channel between caregivers and physicians. Objective: Our aim was to describe chat conversations between caregivers and physicians in a Web-based chat service to determine the factors that should be considered when planning a similar chat service. We also aimed to evaluate whether caregivers considered the consultations helpful, whether physicians considered they could answer caregivers’ questions, and whether further face-to-face medical contact was needed. Methods: In September 2015, a private medical center for children in the greater Helsinki area initiated a Web-based chat service, accessible via any device with an internet connection, open from 9 am to 9 pm local time. Four residents in pediatrics, who had performed at least 60% of their 6-year residency program, served as the physicians responsible for chat consultations with caregivers of children. Between October 2015 and March 2016, 343 consecutive consultations were immediately evaluated by a chat physician. On average, caregivers were followed up by email questionnaire 7-14 days later, which 98 caregivers answered a median of 11 (interquartile range, IQR, 7-20) days later. Results: The age of the children whose caregivers contacted the chat service was a median of 2.1 (IQR 0.83-4.69) years, and 29.8% (102/342) of the children were less than 1 year old. The majority (119/343, 34.7%) of the chat conversations took place from 9 am to noon, and infections were the most common concern in over half of cases (189/343, 55.1%). Chat physicians recommended a face-to-face appointment with a physician for that same day in 13.7% (47/343) of the cases. A face-to-face exam was recommended for that same day more often if the chat concerned infection (36/189, 19.0% cases) compared with other reasons (11/154, 7.1%, cases; P=.001). Physicians felt capable of answering caregivers’ questions in 72.6% (249/343) of the cases, whereas 93% (91/98) of caregivers considered physicians’ answers helpful. Whether caregivers had to take their children to see a physician that same day or whether caregivers’ main concern was infection was not found to be associated with whether caregivers considered physicians’ answers helpful or not. However, physicians felt more capable of answering caregivers’ questions when the main concern was infection. Conclusions: Parental consultations via Web-based chat service often take place before noon and focus on infection-related issues as well as on the health and illness of very young children. These factors should be considered when planning or setting up such a service. Based on the high satisfaction with the chat service by both physicians and caregivers, Web-based chat services may be a useful way to help caregivers with concerns about their child’s health or illness.

  • J Med Internet Res 2018;20(12):e10165

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  Web-based and Mobile Health...

  Dec 14, 2018

  Efficacy of a Parent-Based, Indicated Prevention for Anorexia Nervosa: Randomized Controlled Trial

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  Authors List:

  • Corinna Jacobi  
  • Kristian Hütter  
  • Ulrike Völker  
  • Katharina Möbius  
  • Robert Richter  
  • Mickey Trockel  
  • Megan Jones Bell  
  • James Lock  
  • C Barr Taylor  

  Abstract:

  Background: Web-based preventive interventions can reduce risk and incidence of bulimia and binge eating disorders among young high-risk women. However, their specific effects on core symptoms of anorexia nervosa (AN) are rather weak. Objective: The primary objective of this study was to evaluate the efficacy of an indicated, parent-based, Web-based preventive program Eltern als Therapeuten (E@T) in reducing risk factors and symptoms of AN. Methods: Girls aged between 11 and 17 years were screened by selected risk factors and early symptoms of AN. At-risk families were then randomized to E@T or an assessment-only control condition. Assessments took place at pre- and postintervention (6 weeks later) and at 6- and 12-month follow-up (FU). Results: A total of 12,377 screening questionnaires were handed out in 86 German schools, and 3941 including consent returned. Overall, 477 (447/3941, 12.10%) girls were identified as at risk for AN and 256 of those could be contacted. In all, 66 families (66/256, 25.8% of those contacted) were randomized to the E@T or a wait-list control condition, 43 (43/66, 65%) participated in postassessments, and 27 (27/66, 41%) in 12-month FUs. Due to low participation and high dropout rates of parents, recruitment was terminated prematurely. At 12-month FU, girls’ expected body weight (EBW) percentage was significantly greater for intervention participants compared with control participants (group by time interaction beta=21.0 [CI 5.81 to 36.13], P=.007; group by time squared interaction beta=−15.5 [CI −26.6 to −4.49], P=.007; estimated Cohen d=0.42]. No other significant effects were found on risk factors and attitudes of disturbed eating. Conclusions: Despite a significant increase in girls’ EBW percentage, parental participation and adherence to the intervention were low. Overall, parent-based, indicated prevention for children at risk for AN does not seem very promising, although it might be useful for parents who engage in the intervention. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 18614564; http://www.isrctn.com/ISRCTN18614564 (Archived by WebCite at http://www.webcitation.org/74FTV1EpF).

  • J Med Internet Res 2018;20(12):e296

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  Web-based and Mobile Health...

  Dec 14, 2018

  Examining Predictors of Real-World User Engagement with Self-Guided eHealth Interventions: Analysis of Mobile Apps and Websites Using a Novel Dataset

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  Authors List:

  • Amit Baumel  
  • John M Kane  

  Abstract:

  Background: The literature suggests that the product design of self-guided electronic health (eHealth) interventions impacts user engagement. Traditional trial settings, however, do not enable the examination of these relationships in real-world use. Objective: This study aimed to examine whether the qualities of product design, research evidence, and publicly available data predict real-world user engagement with mobile and Web-based self-guided eHealth interventions. Methods: This analysis included self-guided mobile and Web-based eHealth interventions available to the public—with their qualities assessed using the Enlight suite of scales. Scales included Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness, Therapeutic Alliance, Credibility, and Research Evidence. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with websites and mobile apps, based on a time window of 18 months that was set between November 1, 2016 and April 30, 2018. Real-world user engagement variables included average usage time (for both mobile apps and websites) and mobile app user retention 30 days after download. Results: The analysis included 52 mobile apps (downloads median 38,600; interquartile range [IQR] 116,000) and 32 websites (monthly unique visitors median 5689; IQR 30,038). Results point to moderate correlations between Therapeutic Persuasiveness, Therapeutic Alliance, and the 3 user engagement variables (.31≤rs≤.51; Ps≤.03). Visual Design, User Engagement, and Content demonstrated similar degrees of correlation with mobile app engagement variables (.25≤rs≤.49; Ps≤.04) but not with average usage time of Web-based interventions. Positive correlations were also found between the number of reviews on Google Play and average app usage time (r=.58; P<.001) and user retention after 30 days (r=.23; P=.049). Although several product quality ratings were positively correlated with research evidence, the latter was not significantly correlated with real-world user engagement. Hierarchical stepwise regression analysis revealed that either Therapeutic Persuasiveness or Therapeutic Alliance explained 15% to 26% of user engagement variance. Data on Google Play (number of reviews) explained 15% of the variance of mobile app usage time above Enlight ratings; however, publicly available data did not significantly contribute to explaining the variance of the other 2 user-engagement variables. Conclusions: Results indicate that the qualities of product design predict real-world user engagement with eHealth interventions. The use of real-world behavioral datasets is a novel way to learn about user behaviors, creating new avenues for eHealth intervention research.

  • J Med Internet Res 2018;20(12):e11491

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• Quality/Credibility of eHealth...

  Dec 13, 2018

  Elements of Trust in Digital Health Systems: Scoping Review

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  Authors List:

  • Afua Adjekum  
  • Alessandro Blasimme  
  • Effy Vayena  

  Abstract:

  Background: Information and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored. Objective: The objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health. Methods: We performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented. Results: Overall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third—health administrators—was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health. Conclusions: Trust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

  • J Med Internet Res 2018;20(12):e11254

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  Review

  Dec 12, 2018

  Theory-Based Digital Interventions to Improve Asthma Self-Management Outcomes: Systematic Review

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  Authors List:

  • Helen J Lycett  
  • Eva M Raebel  
  • Emilie K Wildman  
  • Jordi Guitart  
  • Thomas Kenny  
  • Jon-Paul Sherlock  
  • Vanessa Cooper  

  Abstract:

  Background: Asthma is a chronic disease requiring effective self-management to control it and prevent mortality. The use of theory-informed digital interventions promoting asthma self-management is increasing. However, there is limited knowledge concerning how and to what extent psychological theory has been applied to the development of digital interventions, or how using theory impacts outcomes. Objective: The study aimed to examine the use and application of theory in the development of digital interventions to enhance asthma self-management and to evaluate the effectiveness of theory-based interventions in improving adherence, self-management, and clinical outcomes. Methods: Electronic databases (CENTRAL, MEDLINE, EMBASE, and PsycINFO) were searched systematically using predetermined terms. Additional studies were identified by scanning references within relevant studies. Two researchers screened titles and abstracts against predefined inclusion criteria; a third resolved discrepancies. Full-text review was undertaken for relevant studies. Those meeting inclusion criteria were assessed for risk of bias using the Cochrane Collaboration tool. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Study outcomes were classified as medication adherence, self-management, asthma control, clinical markers of health, quality of life, other quality of life outcomes, and health care utilization. Effectiveness was calculated as an average outcome score based on the study’s reported significance. The Theory Coding Scheme (TCS) was used to establish the extent to which each intervention had applied theory and which theoretical constructs or behavioral determinants were addressed. Associations between TCS scores and asthma outcomes were described within a narrative synthesis. Results: Fourteen studies evaluating 14 different digital interventions were included in this review. The most commonly cited theories were Social Cognitive Theory, Health Belief Model, and Self-Efficacy Theory. A greater use of theory in the development of interventions was correlated with effective outcomes (r=.657; P=.01): only the 3 studies that met >60% of the different uses of theory assessed by the TCS were effective on all behavioral and clinical outcomes measured. None of the 11 studies that met ≤60% of the TCS criteria were fully effective; however, 3 interventions were partially effective (ie, the intervention had a significant impact on some, but not all, of the outcomes measured). Most studies lacked detail on the theoretical constructs and how they were applied to the development and application of the intervention. Conclusions: These findings suggest that greater use of theory in the development and application of digital self-management interventions for asthma may increase their effectiveness. The application of theory alone may not be enough to yield a successful intervention, and other factors (eg, the context in which the intervention is used) should be considered. A systematic approach to the use of theory to guide the design, selection, and application of intervention techniques is needed.

  • J Med Internet Res 2018;20(12):e293

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  New Methods

  Dec 11, 2018

  Continuous Versus Intermittent Vital Signs Monitoring Using a Wearable, Wireless Patch in Patients Admitted to Surgical Wards: Pilot Cluster Randomized...

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  Authors List:

  • Candice Downey  
  • Rebecca Randell  
  • Julia Brown  
  • David G Jayne  

  Abstract:

  Background: Vital signs monitoring is a universal tool for the detection of postoperative complications; however, unwell patients can be missed between traditional observation rounds. New remote monitoring technologies promise to convey the benefits of continuous monitoring to patients in general wards. Objective: The aim of this pilot study was to evaluate whether continuous remote vital signs monitoring is a practical and acceptable way of monitoring surgical patients and to optimize the delivery of a definitive trial. Methods: We performed a prospective, cluster-randomized, parallel-group, unblinded, controlled pilot study. Patients admitted to 2 surgical wards at a large tertiary hospital received either continuous and intermittent vital signs monitoring or intermittent monitoring alone using an early warning score system. Continuous monitoring was provided by a wireless patch, worn on the patient’s chest, with data transmitted wirelessly every 2 minutes to a central monitoring station or a mobile device carried by the patient’s nurse. The primary outcome measure was time to administration of antibiotics in sepsis. The secondary outcome measures included the length of hospital stay, 30-day readmission rate, mortality, and patient acceptability. Results: Overall, 226 patients were randomized between January and June 2017. Of 226 patients, 140 were randomized to continuous remote monitoring and 86 to intermittent monitoring alone. On average, patients receiving continuous monitoring were administered antibiotics faster after evidence of sepsis (626 minutes, n=22, 95% CI 431.7-820.3 minutes vs 1012.8 minutes, n=12, 95% CI 425.0-1600.6 minutes), had a shorter average length of hospital stay (13.3 days, 95% CI 11.3-15.3 days vs 14.6 days, 95% CI 11.5-17.7 days), and were less likely to require readmission within 30 days of discharge (11.4%, 95% CI 6.16-16.7 vs 20.9%, 95% CI 12.3-29.5). Wide CIs suggest these differences are not statistically significant. Patients found the monitoring device to be acceptable in terms of comfort and perceived an enhanced sense of safety, despite 24% discontinuing the intervention early. Conclusions: Remote continuous vital signs monitoring on surgical wards is practical and acceptable to patients. Large, well-controlled studies in high-risk populations are required to determine whether the observed trends translate into a significant benefit for continuous over intermittent monitoring. Trial Registration: International Standard Randomised Controlled Trial Number ISRCTN60999823; http://www.isrctn.com /ISRCTN60999823 (Archived by WebCite at http://www.webcitation.org/73ikP6OQz)

  • J Med Internet Res 2018;20(12):e10802

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  Demographics of Users, Social &...

  Dec 10, 2018

  Mobile Health, Information Preferences, and Surrogate Decision-Making Preferences of Family Caregivers of People With Dementia in Rural Hispanic Communities:...

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  Authors List:

  • Bo Xie  
  • Jane Dimmitt Champion  
  • Jung Kwak  
  • Kenneth R Fleischmann  

  Abstract:

  Background: Mobile health (mHealth) technology holds promise for promoting health education and reducing health disparities and inequalities in underserved populations. However, little research has been done to develop mHealth interventions for family caregivers of people with dementia, particularly those in rural Hispanic communities, who often serve as surrogate decision makers for their relatives with dementia. Objective: As part of a larger project to develop and test a novel, affordable, and easy-to-use mHealth intervention to deliver individually tailored materials in rural Hispanic communities, in this pilot study, we aimed to examine (1) characteristics of people with dementia and their family caregivers in rural Hispanic communities, (2) caregivers’ preferences for types and amounts of health information and participation in surrogate decision making, and (3) caregivers’ mobile device usage and their desire for receiving information via mobile devices. Methods: This was a cross-sectional survey. A convenience sample of 50 caregivers of people with dementia was recruited from rural health care facilities in Southwest Texas during 3 weeks of April 2017 to May 2017 via word-of-mouth and flyers posted at the facilities. Results: More women than men were in the patient group (χ21=17.2, P<.001) and in the caregiver group (χ21=22.2, P<.001). More patients were on Medicare and Medicaid; more caregivers had private insurance (P<.001 in all cases). Overall, 42% of patients did not have a power of attorney for their health care; 40% did not have a living will or advance directive. Caregivers were interested in receiving all types of information and participating in all types of decisions, although on subscales for diagnosis, treatment, laboratory tests, self-care, and complementary and alternative medicine, their levels of interest for decision-making participation were significantly lower than those for receiving information. On the psychosocial subscale, caregivers’ desire was greater for surrogate decision-making participation than for information. Caregivers did not differ in their interests in information and participation in decision making on the health care provider subscale. All but 1 caregiver (98%) owned a mobile phone and 84% had a smartphone. Two-thirds wanted to receive at least a little dementia-related information via a smartphone or tablet. The amount of dementia-related information caregivers wanted to receive via a mobile device was significantly greater for women than for men (U=84.50, P=.029). Caregivers who owned a tablet were more likely to want to receive dementia-related information via a mobile device than those who did not own a tablet (U=152.0, P=.006). Conclusions: Caregivers in rural Hispanic communities were interested in receiving a wide range of information as well as participating in making decisions for their relatives with dementia. There is much need for effective mHealth interventions that can provide information tailored to the needs and preferences of these caregivers.

  • J Med Internet Res 2018;20(12):e11682

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  Medicine 2.0: Social Media, Open,...

  Dec 10, 2018

  Creating Engaging Health Promotion Campaigns on Social Media: Observations and Lessons From Fitbit and Garmin

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  Authors List:

  • Sarah Edney  
  • Svetlana Bogomolova  
  • Jillian Ryan  
  • Tim Olds  
  • Ilea Sanders  
  • Carol Maher  

  Abstract:

  Background: The popularity and reach of social media make it an ideal delivery platform for interventions targeting health behaviors, such as physical inactivity. Research has identified a dose-response relationship whereby greater engagement and exposure are positively associated with intervention effects, hence enhancing engagement will maximize the potential of these interventions. Objective: This study examined the social media activity of successful commercial activity tracker brands to understand which creative elements (message content and design) they use in their communication to their audience, which social media platforms attract the most engagement, and which creative elements prompted the most engagement. Methods: Posts (n=509) made by Fitbit and Garmin on Facebook, Twitter, and Instagram over a 3-month period were coded for the presence of creative elements. User engagement regarding the total number of likes, comments, or shares per post was recorded. Negative binomial regression analyses were used to identify creative elements associated with higher engagement. Results: Engagement on Instagram was 30-200 times higher than on Facebook, or Twitter. Fitbit and Garmin tended to use different creative elements from one another. A higher engagement was achieved by posts featuring an image of the product, highlighting new product features and with themes of self-improvement (P<.01). Conclusions: Findings suggest that Instagram may be a particularly promising platform for delivering engaging health messaging. Health messages which incorporate inspirational imagery and focus on a tangible product appear to achieve the highest engagement. Fitbit and Garmin employed difference creative elements, which is likely to reflect differences in their target markets. This underscores the importance of market segmentation in health messaging campaigns.

  • J Med Internet Res 2018;20(12):e10911

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  Special Issue on Computing and Mental...

  Dec 7, 2018

  Clinical Feasibility of a Just-in-Time Adaptive Intervention App (iREST) as a Behavioral Sleep Treatment in a Military Population: Feasibility Comparative...

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  Authors List:

  • I Wayan Pulantara  
  • Bambang Parmanto  
  • Anne Germain  

  Abstract:

  Background: Although evidence-based cognitive behavioral sleep treatments have been shown to be safe and effective, these treatments have limited scalability. Mobile health tools can address this scalability challenge. iREST, or interactive Resilience Enhancing Sleep Tactics, is a mobile health platform designed to provide a just-in-time adaptive intervention (JITAI) in the assessment, monitoring, and delivery of evidence-based sleep recommendations in a scalable and personalized manner. The platform includes a mobile phone–based patient app linked to a clinician portal. Objective: The first aim of the pilot study was to evaluate the effectiveness of JITAI using the iREST platform for delivering evidence-based sleep interventions in a sample of military service members and veterans. The second aim was to explore the potential effectiveness of this treatment delivery form relative to habitual in-person delivery. Methods: In this pilot study, military service members and veterans between the ages of 18 and 60 years who reported clinically significant service-related sleep disturbances were enrolled as participants. Participants were asked to use iREST for a period of 4 to 6 weeks during which time they completed a daily sleep/wake diary. Through the clinician portal, trained clinicians offered recommendations consistent with evidence-based behavioral sleep treatments on weeks 2 through 4. To explore potential effectiveness, self-report measures were used, including the Insomnia Severity Index (ISI), the Pittsburgh Sleep Quality Index (PSQI), and the PSQI Addendum for Posttraumatic Stress Disorder. Results: A total of 27 participants completed the posttreatment assessments. Between pre- and postintervention, clinically and statistically significant improvements in primary and secondary outcomes were detected (eg, a mean reduction on the ISI of 9.96, t26=9.99, P<.001). At posttreatment, 70% (19/27) of participants met the criteria for treatment response and 59% (16/27) achieved remission. Comparing these response and remission rates with previously published results for in-person trials showed no significant differences. Conclusion: Participants who received evidence-based recommendations from their assigned clinicians through the iREST platform showed clinically significant improvements in insomnia severity, overall sleep quality, and disruptive nocturnal disturbances. These findings are promising, and a larger noninferiority clinical trial is warranted.

  • J Med Internet Res 2018;20(12):e10124

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  Electronic/Mobile Data Capture,...

  Dec 7, 2018

  Questionnaire Breakoff and Item Nonresponse in Web-Based Questionnaires: Multilevel Analysis of Person-Level and Item Design Factors in a Birth Cohort

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  Authors List:

  • Cauane Blumenberg  
  • Daniela Zugna  
  • Maja Popovic  
  • Costanza Pizzi  
  • Aluisio J D Barros  
  • Lorenzo Richiardi  

  Abstract:

  Background: Web-based questionnaires are increasingly used in epidemiologic studies, as traditional methods are facing a decrease in response rates and an increase in costs. However, few studies have investigated factors related to the level of completion of internet-based epidemiologic questionnaires. Objective: Our objective was to identify person-level characteristics and item design factors associated with breakoff (not finishing the questionnaire) and item nonresponse in a Web-based questionnaire. Methods: This study was a cross-sectional analysis of the baseline questionnaire, applied from 2005 to 2016, of the Italian NINFEA (Nascita e Infanzia: gli Effetti dell’Ambiente) birth cohort. The baseline questionnaire was administered to enrolled women, who could register at any time during pregnancy. We used logistic regression to analyze the influence of person-level factors on questionnaire breakoff, and a logistic multilevel model (first level: items of the questionnaire; second level: sections of the questionnaire; third level: study participants) to analyze the influence of person-level and item design factors on item nonresponse. Since the number of applicable items depended on the respondent’s characteristics and breakoff, we used inverse probability weighting to deal with missing by design. Results: Of 5970 women, 519 (8.69%) did not finish the questionnaire. Older age (adjusted odds ratio 1.40, 95% CI 1.05-1.88), lower educational level (adjusted odds ratio [OR] 1.53, 95% CI 1.23-1.90), and earlier stage of pregnancy (adjusted OR 3.01, 95% CI 2.31-3.92) were positively associated with questionnaire breakoff. Of the 1,062,519 applicable items displayed for the participants, 22,831 were not responded to (overall prevalence of item nonresponse 2.15%). Item nonresponse was positively associated with older age (adjusted OR 1.25, 95% CI 1.14-1.38), being in the first trimester of pregnancy (adjusted OR 1.18, 95% CI 1.06-1.31), and lower educational level (adjusted OR 1.23, 95% CI 1.14-1.33). Dropdown menu items (adjusted OR 1.77, 95% CI 1.56-2.00) and items organized in grids (adjusted OR 1.69, 95% CI 1.49-1.91) were positively associated with item nonresponse. Conclusions: It is important to use targeted strategies to keep participants motivated to respond. Item nonresponse in internet-based questionnaires is affected by person-level and item design factors. Some item types should be limited to reduce item nonresponse.

  • J Med Internet Res 2018;20(12):e11046

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  Infodemiology and Infoveillance

  Dec 6, 2018

  Exploring the Utility of Community-Generated Social Media Content for Detecting Depression: An Analytical Study on Instagram

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  Authors List:

  • Benjamin J Ricard  
  • Lisa A Marsch  
  • Benjamin Crosier  
  • Saeed Hassanpour  

  Abstract:

  Background: The content produced by individuals on various social media platforms has been successfully used to identify mental illness, including depression. However, most of the previous work in this area has focused on user-generated content, that is, content created by the individual, such as an individual’s posts and pictures. In this study, we explored the predictive capability of community-generated content, that is, the data generated by a community of friends or followers, rather than by a sole individual, to identify depression among social media users. Objective: The objective of this research was to evaluate the utility of community-generated content on social media, such as comments on an individual’s posts, to predict depression as defined by the clinically validated Patient Health Questionnaire-8 (PHQ-8) assessment questionnaire. We hypothesized that the results of this research may provide new insights into next generation of population-level mental illness risk assessment and intervention delivery. Methods: We created a Web-based survey on a crowdsourcing platform through which participants granted access to their Instagram profiles as well as provided their responses to PHQ-8 as a reference standard for depression status. After data quality assurance and postprocessing, the study analyzed the data of 749 participants. To build our predictive model, linguistic features were extracted from Instagram post captions and comments, including multiple sentiment scores, emoji sentiment analysis results, and meta-variables such as the number of likes and average comment length. In this study, 10.4% (78/749) of the data were held out as a test set. The remaining 89.6% (671/749) of the data were used to train an elastic-net regularized linear regression model to predict PHQ-8 scores. We compared different versions of this model (ie, a model trained on only user-generated data, a model trained on only community-generated data, and a model trained on the combination of both types of data) on a test set to explore the utility of community-generated data in our predictive analysis. Results: The 2 models, the first trained on only community-generated data (area under curve [AUC]=0.71) and the second trained on a combination of user-generated and community-generated data (AUC=0.72), had statistically significant performances for predicting depression based on the Mann-Whitney U test (P=.03 and P=.02, respectively). The model trained on only user-generated data (AUC=0.63; P=.11) did not achieve statistically significant results. The coefficients of the models revealed that our combined data classifier effectively amalgamated both user-generated and community-generated data and that the 2 feature sets were complementary and contained nonoverlapping information in our predictive analysis. Conclusions: The results presented in this study indicate that leveraging community-generated data from social media, in addition to user-generated data, can be informative for predicting depression among social media users.

  • J Med Internet Res 2018;20(12):e11817

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  Participatory Medicine & E-Patients

  Dec 5, 2018

  eHealth Engagement as a Response to Negative Healthcare Experiences: Cross-Sectional Survey Analysis

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  Authors List:

  • Nicole Senft  
  • Jordan Everson  

  Abstract:

  Background: eHealth provides individuals with new means of accessing health information and communicating with providers through online channels. Prior evidence suggests that patients use eHealth to find information online when they receive care that is low in patient centeredness. However, it is unclear how other problems with the healthcare-delivery system motivate the use of eHealth, how these problems relate to different kinds of eHealth activities, and which populations are most likely to use eHealth when they receive low-quality care. Objective: We aimed to determine how two types of negative care experiences—low patient centeredness and care coordination problems—motivate the use of different eHealth activities, and whether more highly educated individuals, who may find these tools easier to use, are more likely to use eHealth following negative experiences than less highly educated individuals. Methods: Using nationally representative data from the 2017 Health Information National Trends Survey, we used factor analysis to group 25 different eHealth activities into categories based on the correlation between respondents’ reports of their usage. Subsequently, we used multivariate negative binomial generalized linear model regressions to determine whether negative healthcare experiences predicted greater use of these resulting categories. Finally, we stratified our sample based on education level to determine whether the associations between healthcare experiences and eHealth use differed across groups. Results: The study included 2612 individuals. Factor analysis classified the eHealth activities into two categories: provider-facing (eg, facilitating communication with providers) and independent (eg, patient-driven information seeking and communication with non-providers). Negative care experiences were not associated with provider-facing eHealth activity in the overall population (care coordination: P=.16; patient centeredness: P=.57) or among more highly educated respondents (care coordination: P=.73; patient centeredness: P=.32), but respondents with lower education levels who experienced problems with care coordination used provider-facing eHealth more often (IRR=1.40, P=.07). Individuals engaged in more independent eHealth activities if they experienced problems with either care coordination (IRR=1.15 P=.01) or patient-centered communication (IRR=1.16, P=.01). Although care coordination problems predicted independent eHealth activity across education levels (higher education: IRR=1.13 P=.01; lower education: IRR=1.19, P=.07), the relationship between low perceived patient centeredness and independent activity was limited to individuals with lower education levels (IRR=1.25, P=.02). Conclusions: Individuals use a greater number of eHealth activities, especially activities that are independent of healthcare providers, when they experience problems with their healthcare. People with lower levels of education seem particularly inclined to use eHealth when they have negative healthcare experiences. To maximize the potential for eHealth to meet the needs of all patients, especially those who are traditionally underserved by the healthcare system, additional work should be performed to ensure that eHealth resources are accessible and usable to all members of the population.

  • J Med Internet Res 2018;20(12):e11034

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