Journal of Medical Internet Research

The leading peer-reviewed journal for health and healthcare in the Internet age.

JMIR's Thomson Reuter Impact Factor of 4.7 for 2013

MELLO: MEdical Life-Log Ontology

Background: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic consistency among lifelog terms and related ontologies. Objective: MEdical Life-Log Ontology (MELLO) was developed by identifying lifelog concepts and relationships between concepts, and it provides clear definitions by following ontology development methods. MELLO aims to support the classification and semantic mapping of lifelog data from diverse health self-tracking devices. Methods: MELLO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of lifelog data, (2) identifying lifelog concepts, (3) assigning relationships among MELLO concepts, (4) developing MELLO properties (e.g., synonyms, preferred terms, and definitions) for each MELLO concept, and (5) evaluating representative layers of the ontology content. An evaluation was performed by classifying 11 devices into 3 classes by subjects, and performing pairwise comparisons of lifelog terms among 5 devices in each class as measured using the Jaccard similarity index. Results: MELLO represents a comprehensive knowledge base of 1,980 lifelog concepts, with 4,596 synonyms for 1,193 (61%) concepts and 1,395 definitions for 923 (48%) concepts. The Web-based MELLO Browser and MELLO Mapper provide convenient access and annotating non-standard proprietary terms with MELLO (http://www.snubi.org/software/mello). MELLO covers 88.1% of lifelog terms from 11 health self-tracking devices and uses simple string matching to match semantically similar terms provided by various devices that are not yet integrated. The results from the comparisons of Jaccard similarities between simple string matching and MELLO matching revealed increases of 2.5-fold for the physical activity class, 2.2-fold for the body measure class, and 5.7-fold for the sleep class. Conclusions: MELLO is the first ontology for representing health-related lifelog data with rich contents including definitions, synonyms, and semantic relationships. MELLO fills the semantic gaps among heterogeneous lifelog terms that are generated by diverse health self-tracking devices. The unified representation of lifelog terms facilitated by MELLO can help describe an individual’s lifestyle and environmental factors, which can be included with user-generated data for clinical research and thereby enhance data integration and sharing.

2014-10-04

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Recent Articles:

  • Screenshot of the laboratory results and treatment goals of the patient Web portal.

    Reasons and Barriers for Using a Patient Portal: Survey Among Patients With Diabetes Mellitus

    Abstract:

    Background: The use of a Web portal for patients with diabetes mellitus to access their own personal health record may result in improved diabetes outcomes. However, the adoption by patients is slow. This may be caused by patient characteristics, but also by the content, layout, and promotion of the portal. Detailed knowledge about this could help increase patients’ participation in Web portals. Objective: The aim was to study the opinions of patients with diabetes and identify perceived barriers to using a Web portal to optimize its use. Methods: We conducted a survey among patients with type 1 and type 2 diabetes mellitus from 62 primary care practices and 1 outpatient hospital clinic in the central area of the Netherlands who all used the same electronic health record with a Web portal. Questionnaires about patient characteristics, opinions about reasons for use or nonuse, and about portal content were sent to 1500 patients with a login and 3000 patients without a login to the Web portal. Patient groups were stratified according to login frequency. Demographic and diabetes-related variables were analyzed with multivariable regression analysis. Results: The total response rate was 66.63% (2391/4399); 1390 of 4399 patients (31.60%) were eligible for analysis. There were 413 regular users (login frequency more than once) and 758 nonusers (no login). Most nonusers (72.4%) stated that the main reason for not requesting a login was that they were unaware of the existence of the portal. Other barriers reported by patients were disinterest in managing their own disease (28.5%, 216/758) and feelings of inadequacy with the use of computers and Internet (11.6%, 88/758). Patients treated by a general practitioner were more frequently nonusers compared to patients treated by an internist (78.8%, 666/846 vs 28.3%, 92/325; P<.001) and more users than nonusers became aware of the Web portal through their physician (94.9%, 392/413 vs 48.8%, 102/209; P<.001). Nonusers perceived specific portal content as not as useful as regular users did, especially access to laboratory values (71.7%, 383/534 vs 92.3%, 372/403), rereading clinic visits (61.3%, 320/522 vs 89.6%, 360/402), e-messaging (52.0%, 262/504 vs 74.6%, 299/401), and uploading results to the glucose diary (45.3%, 229/506 vs 74.0%, 288/400; all P<.001). Conclusions: Our study shows that unawareness of the patient portal is the main barrier of enrollment. Users and nonusers perceive the usefulness of the portal differently and do not have the same recommendations for additional functionalities. To increase patients’ participation in a Web portal, the unawareness of its existence and its possibilities need to be addressed by their health care professionals.
  • Screenshot of Healthcare Access San Antonio (HASA).

    Characteristics of Patient Portals Developed in the Context of Health Information Exchanges: Early Policy Effects of Incentives in the Meaningful Use Program...

    Abstract:

    Background: In 2014, the Centers for Medicare & Medicaid Services in the United States launched the second stage of its Electronic Health Record (EHR) Incentive Program, providing financial incentives to providers to meaningfully use their electronic health records to engage patients online. Patient portals are electronic means to engage patients by enabling secure access to personal medical records, communication with providers, various self-management tools, and administrative functionalities. Outcomes of patient portals have mainly been reported in large integrated health systems. This may now change as the EHR Incentive Program enables and supports the use of patient portals in other types of health systems. In this paper, we focus on Health Information Exchanges (HIE): entities that facilitate data exchange within networks of independent providers. Objective: In response to the EHR Incentive Program, some Health Information Exchanges in the United States are developing patient portals and offering them to their network of providers. Such patient portals hold high value for patients, especially in fragmented health system contexts, due to the portals’ ability to integrate health information from an array of providers and give patients one access point to this information. Our aim was to report on the early effects of the EHR incentives on patient portal development by HIEs. Specifically, we describe the characteristics of these portals, identify factors affecting adoption by providers during the 2013-2014 time frame, and consider what may be the primary drivers of providers’ adoption of patient portals in the future. Methods: We identified four HIEs that were developing patient portals as of spring 2014. We collected relevant documents and conducted interviews with six HIE leaders as well as two providers that were implementing the portals in their practices. We performed content analysis on these data to extract information pertinent to our study objectives. Results: Our findings suggest that there are two primary types of patient portals available to providers in HIEs: (1) portals linked to EHRs of individual providers or health systems and (2) HIE-sponsored portals that link information from multiple providers’ EHRs. The decision of providers in the HIEs to adopt either one of these portals appears to be a trade-off between functionality, connectivity, and cost. Our findings also suggest that while the EHR Incentive Program is influencing these decisions, it may not be enough to drive adoption. Rather, patient demand for access to patient portals will be necessary to achieve widespread portal adoption and realization of potential benefits. Conclusions: Optimizing patient value should be the main principle underlying policies intending to increase online patient engagement in the third stage of the EHR Incentive Program. We propose a number of features for the EHR Incentive Program that will enhance patient value and thereby support the growth and sustainability of patient portals provided by Health Information Exchanges.
  • Screenshot of the intervention.

    Web-Enhanced Tobacco Tactics With Telephone Support Versus 1-800-QUIT-NOW Telephone Line Intervention for Operating Engineers: Randomized Controlled Trial

    Abstract:

    Background: Novel interventions tailored to blue collar workers are needed to reduce the disparities in smoking rates among occupational groups. Objective: The main objective of this study was to evaluate the efficacy and usage of the Web-enhanced “Tobacco Tactics” intervention targeting operating engineers (heavy equipment operators) compared to the “1-800-QUIT-NOW” telephone line. Methods: Operating engineers (N=145) attending one of 25 safety training sessions from 2010 through 2012 were randomized to either the Tobacco Tactics website with nurse counseling by phone and access to nicotine replacement therapy (NRT) or to the 1-800-QUIT-NOW telephone line, which provided an equal number of phone calls and NRT. The primary outcome was self-reported 7-day abstinence at 30-day and 6-month follow-up. The outcomes were compared using chi-square tests, t tests, generalized mixed models, and logistic regression models. Results: The average age was 42 years and most were male (115/145, 79.3%) and white (125/145, 86.2%). Using an intent-to-treat analysis, the Tobacco Tactics website group showed significantly higher quit rates (18/67, 27%) than the 1-800-QUIT NOW group (6/78, 8%) at 30-day follow-up (P=.003), but this difference was no longer significant at 6-month follow-up. There were significantly more positive changes in harm reduction measures (quit attempts, number of cigarettes smoked per day, and nicotine dependence) at both 30-day and 6-month follow-up in the Tobacco Tactics group compared to the 1-800-QUIT-NOW group. Compared to participants in the 1-800-QUIT NOW group, significantly more of those in the Tobacco Tactics website group participated in the interventions, received phone calls and NRT, and found the intervention helpful. Conclusions: The Web-enhanced Tobacco Tactics website with telephone support showed higher efficacy and reach than the 1-800-QUIT-NOW intervention. Longer counseling sessions may be needed to improve 6-month cessation rates. Trial Registration: Clinicaltrials.gov NCT01124110; http://clinicaltrials.gov/ct2/show/NCT01124110 (Archived by WebCite at http://www.webcitation.org/6TfKN5iNL).
  • Screenshot of the patient portal.

    The Effect of a Patient Portal With Electronic Messaging on Patient Activation Among Chronically Ill Patients: Controlled Before-and-After Study

    Abstract:

    Background: It has been suggested that providing patients with access to their medical records and secure messaging with health care professionals improves health outcomes in chronic care by encouraging and activating patients to manage their own condition. Objectives: The aim was to evaluate the effect of access to a patient portal on patient activation among chronically ill patients. Further, the relationship between temporal proximity of a severe diagnosis and patient activation were assessed. Methods: A total of 876 chronically ill patients from public primary care were allocated to either an intervention group receiving immediate access to a patient portal that included their medical records, care plan, and secure messaging with a care team, or to a control group receiving usual care. Patient Activation Measure (PAM) at baseline and at 6-month follow-up was obtained from 80 patients in the intervention group and 57 patients in the control group; thus, a total of 137 patients were included in the final analysis. Results: No significant effect of access to patient portal on patient activation was detected in this study (F1,133=1.87, P=.17, η2=0.01). Patients starting at a lower level of activation demonstrated greater positive change in activation compared to patients starting at higher levels of activation in both the intervention and control groups. Further, patients diagnosed with a severe diagnosis during the intervention showed greater positive change in patient activation compared to patients whose last severe diagnosis was made more than 2 years ago. The results also suggest that the intervention had greatest effect on patients starting at the highest level of patient activation (difference in change of patient activation=4.82, P=.13), and among patients diagnosed within a year of the intervention (difference in change of patient activation=7.65, P=.12). Conclusions: Time since last severe diagnosis and patient activation at baseline may affect changes in patient activation, suggesting that these should be considered in evaluation of activating chronic care interventions and in the specification of possible target groups for these interventions. This may be relevant in designing services for a heterogeneous group of patients with a distinct medical history and level of activation.
  • Composite of our Figure 10 and a sample (fake, generic) sexual network application profile.

    Using a Geolocation Social Networking Application to Calculate the Population Density of Sex-Seeking Gay Men for Research and Prevention Services

    Abstract:

    Background: In the United States, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) continues to have a heavy impact on men who have sex with men (MSM). Among MSM, black men under the age of 30 are at the most risk for being diagnosed with HIV. The US National HIV/AIDS strategy recommends intensifying efforts in communities that are most heavily impacted; to do so requires new methods for identifying and targeting prevention resources to young MSM, especially young MSM of color. Objective: We piloted a methodology for using the geolocation features of social and sexual networking applications as a novel approach to calculating the local population density of sex-seeking MSM and to use self-reported age and race from profile postings to highlight areas with a high density of minority and young minority MSM in Atlanta, Georgia. Methods: We collected data from a geographically systematic sample of points in Atlanta. We used a sexual network mobile phone app and collected application profile data, including age, race, and distance from each point, for either the 50 closest users or for all users within a 2-mile radius of sampled points. From these data, we developed estimates of the spatial density of application users in the entire city, stratified by race. We then compared the ratios and differences between the spatial densities of black and white users and developed an indicator of areas with the highest density of users of each race. Results: We collected data from 2666 profiles at 79 sampled points covering 883 square miles; overlapping circles of data included the entire 132.4 square miles in Atlanta. Of the 2666 men whose profiles were observed, 1563 (58.63%) were white, 810 (30.38%) were black, 146 (5.48%) were another race, and 147 (5.51%) did not report a race in their profile. The mean age was 31.5 years, with 591 (22.17%) between the ages of 18-25, and 496 (18.60%) between the ages of 26-30. The mean spatial density of observed profiles was 33 per square mile, but the distribution of profiles observed across the 79 sampled points was highly skewed (median 17, range 1-208). Ratio, difference, and distribution outlier measures all provided similar information, highlighting areas with higher densities of minority and young minority MSM. Conclusions: Using a limited number of sampled points, we developed a geospatial density map of MSM using a social-networking sex-seeking app. This approach provides a simple method to describe the density of specific MSM subpopulations (users of a particular app) for future HIV behavioral surveillance and allow targeting of prevention resources such as HIV testing to populations and areas of highest need.
  • AIDS-denialists online community structure.

    An AIDS-Denialist Online Community on a Russian Social Networking Service: Patterns of Interactions With Newcomers and Rhetorical Strategies of Persuasion

    Abstract:

    Background: The rise of social media proved to be a fertile ground for the expansion of the acquired immune deficiency syndrome (AIDS)-denialist movement (in the form of online communities). While there is substantial literature devoted to disproving AIDS-denialist views, there is a lack of studies exploring AIDS-denialists online communities that interact with an external environment. Objective: We explored three research areas: (1) reasons for newcomers to come to an AIDS-denialist community, (2) the patterns of interactions of the community with the newcomers, and (3) rhetorical strategies that denialists use for persuasion in the veracity of their views. Methods: We studied the largest AIDS-denialist community on one of the most popular social networking services in Russia. We used netnography as a method for collecting data for qualitative analysis and observed the community for 9 months (at least 2-3 times a week). While doing netnography, we periodically downloaded community discussions. In total, we downloaded 4821 posts and comments for analysis. Grounded theory approach was used for data analysis. Results: Most users came to the community for the following reasons: their stories did not fit the unitary picture of AIDS disease progression translated by popular medical discourse, health problems, concern about HIV-positive tests, and desire to dissuade community members from false AIDS beliefs. On the basis of strength in AIDS-denialist beliefs, we constructed a typology of the newcomers consisting of three ideal-typical groups: (1) convinced: those who already had become denialists before coming to the group, (2) doubters: those who were undecided about the truth of either human immunodeficiency virus (HIV) science theory or AIDS-denialist theory, and (3) orthodox: those who openly held HIV science views. Reception of a newcomer mainly depended on the newcomer’s belief status. Reception was very warm for the convinced, cold or slightly hostile for the doubters, and extremely hostile or derisive for the orthodox. We identified seven main rhetorical strategies of persuasion used by the denialists on the “undecided”. Conclusions: Contrary to the widespread public health depiction of AIDS denialists as totally irrational, our study suggests that some of those who become AIDS denialists have sufficiently reasonable grounds to suspect that “something is wrong” with scientific theory, because their personal experience contradicts the unitary picture of AIDS disease progression. Odd and inexplicable practices of some AIDS centers only fuel these people’s suspicions. We can conclude that public health practitioners’ practices may play a role in generating AIDS-denialist sentiments. In interactions with the newcomers, the experienced community members highlighted the importance of personal autonomy and freedom of choice in decision making consistent with the consumerist ideology of health care. The study findings suggest that health care workers should change a one-size-fits-all mode of counseling for a more complex and patient-tailored approach, allowing for diversity of disease progression scenarios and scientific uncertainty.
  • The use of Twitter is already ubiquitous, and its use as a method of influenza surveillance in the United States is investigated further in this study.

    The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance

    Abstract:

    Background: Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. Objective: There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. Methods: Tweets containing the keyword “flu” were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was “valid”, or from a user who was likely ill with the flu. Results: Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. Conclusions: Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.
  • Cropped Figure 3.

    Analyzing Engagement in a Web-Based Intervention Platform Through Visualizing Log-Data

    Abstract:

    Background: Engagement has emerged as a significant cross-cutting concern within the development of Web-based interventions. There have been calls to institute a more rigorous approach to the design of Web-based interventions, to increase both the quantity and quality of engagement. One approach would be to use log-data to better understand the process of engagement and patterns of use. However, an important challenge lies in organizing log-data for productive analysis. Objective: Our aim was to conduct an initial exploration of the use of visualizations of log-data to enhance understanding of engagement with Web-based interventions. Methods: We applied exploratory sequential data analysis to highlight sequential aspects of the log data, such as time or module number, to provide insights into engagement. After applying a number of processing steps, a range of visualizations were generated from the log-data. We then examined the usefulness of these visualizations for understanding the engagement of individual users and the engagement of cohorts of users. The visualizations created are illustrated with two datasets drawn from studies using the SilverCloud Platform: (1) a small, detailed dataset with interviews (n=19) and (2) a large dataset (n=326) with 44,838 logged events. Results: We present four exploratory visualizations of user engagement with a Web-based intervention, including Navigation Graph, Stripe Graph, Start–Finish Graph, and Next Action Heat Map. The first represents individual usage and the last three, specific aspects of cohort usage. We provide examples of each with a discussion of salient features. Conclusions: Log-data analysis through data visualization is an alternative way of exploring user engagement with Web-based interventions, which can yield different insights than more commonly used summative measures. We describe how understanding the process of engagement through visualizations can support the development and evaluation of Web-based interventions. Specifically, we show how visualizations can (1) allow inspection of content or feature usage in a temporal relationship to the overall program at different levels of granularity, (2) detect different patterns of use to consider personalization in the design process, (3) detect usability issues, (4) enable exploratory analysis to support the design of statistical queries to summarize the data, (5) provide new opportunities for real-time evaluation, and (6) examine assumptions about interactivity that underlie many summative measures in this field.
  • Screenshot from A Patient's View of OpenNotes  https://www.youtube.com/watch?v=V41bhSWtQbI#t=39.

    Patients Who Share Transparent Visit Notes With Others: Characteristics, Risks, and Benefits

    Abstract:

    Background: Inviting patients to read their primary care visit notes may improve communication and help them engage more actively in their health care. Little is known about how patients will use the opportunity to share their visit notes with family members or caregivers, or what the benefits might be. Objective: Our goal was to evaluate the characteristics of patients who reported sharing their visit notes during the course of the study, including their views on associated benefits and risks. Methods: The OpenNotes study invited patients to access their primary care providers’ visit notes in Massachusetts, Pennsylvania, and Washington. Pre- and post-intervention surveys assessed patient demographics, standardized measures of patient-doctor communication, sharing of visit notes with others during the study, and specific health behaviors reflecting the potential benefits and risks of offering patients easy access to their visit notes. Results: More than half (55.43%, 2503/4516) of the participants who reported viewing at least one visit note would like the option of letting family members or friends have their own Web access to their visit notes, and 21.70% (980/4516) reported sharing their visit notes with someone during the study year. Men, and those retired or unable to work, were significantly more likely to share visit notes, and those sharing were neither more nor less concerned about their privacy than were non-sharers. Compared to participants who did not share clinic notes, those who shared were more likely to report taking better care of themselves and taking their medications as prescribed, after adjustment for age, gender, employment status, and study site. Conclusions: One in five OpenNotes patients shared a visit note with someone, and those sharing Web access to their visit notes reported better adherence to self-care and medications. As health information technology systems increase patients’ ability to access their medical records, facilitating access to caregivers may improve perceived health behaviors and outcomes.
  • Graphic illustrating how to address unreliable research. Figure courtesy of Kai-ou Tang.

    Beyond Open Big Data: Addressing Unreliable Research

    Abstract:

    The National Institute of Health invests US $30.9 billion annually in medical research. However, the subsequent impact of this research output on society and the economy is amplified dramatically as a result of the actual medical treatments, biomedical innovations, and various commercial enterprises that emanate from and depend on these findings. It is therefore a great concern to discover that much of published research is unreliable. We propose extending the open data concept to the culture of the scientific research community. By dialing down unproductive features of secrecy and competition, while ramping up cooperation and transparency, we make a case that what is published would then be less susceptible to the sometimes corrupting and confounding pressures to be first or journalistically attractive, which can compromise the more fundamental need to be robustly correct.
  • Screenshot of online partnership timing module.

    Assessment of a New Web-Based Sexual Concurrency Measurement Tool for Men Who Have Sex With Men

    Abstract:

    Background: Men who have sex with men (MSM) are the most affected risk group in the United States’ human immunodeficiency virus (HIV) epidemic. Sexual concurrency, the overlapping of partnerships in time, accelerates HIV transmission in populations and has been documented at high levels among MSM. However, concurrency is challenging to measure empirically and variations in assessment techniques used (primarily the date overlap and direct question approaches) and the outcomes derived from them have led to heterogeneity and questionable validity of estimates among MSM and other populations. Objective: The aim was to evaluate a novel Web-based and interactive partnership-timing module designed for measuring concurrency among MSM, and to compare outcomes measured by the partnership-timing module to those of typical approaches in an online study of MSM. Methods: In an online study of MSM aged ≥18 years, we assessed concurrency by using the direct question method and by gathering the dates of first and last sex, with enhanced programming logic, for each reported partner in the previous 6 months. From these methods, we computed multiple concurrency cumulative prevalence outcomes: direct question, day resolution / date overlap, and month resolution / date overlap including both 1-month ties and excluding ties. We additionally computed variants of the UNAIDS point prevalence outcome. The partnership-timing module was also administered. It uses an interactive month resolution calendar to improve recall and follow-up questions to resolve temporal ambiguities, combines elements of the direct question and date overlap approaches. The agreement between the partnership-timing module and other concurrency outcomes was assessed with percent agreement, kappa statistic (κ), and matched odds ratios at the individual, dyad, and triad levels of analysis. Results: Among 2737 MSM who completed the partnership section of the partnership-timing module, 41.07% (1124/2737) of individuals had concurrent partners in the previous 6 months. The partnership-timing module had the highest degree of agreement with the direct question. Agreement was lower with date overlap outcomes (agreement range 79%-81%, κ range .55-.59) and lowest with the UNAIDS outcome at 5 months before interview (65% agreement, κ=.14, 95% CI .12-.16). All agreements declined after excluding individuals with 1 sex partner (always classified as not engaging in concurrency), although the highest agreement was still observed with the direct question technique (81% agreement, κ=.59, 95% CI .55-.63). Similar patterns in agreement were observed with dyad- and triad-level outcomes. Conclusions: The partnership-timing module showed strong concurrency detection ability and agreement with previous measures. These levels of agreement were greater than others have reported among previous measures. The partnership-timing module may be well suited to quantifying concurrency among MSM at multiple levels of analysis.
  • eHealth Literacy Interventions for Older Adults: A Systematic Review of the Literature

    Authors List:

    Abstract:

    Background: eHealth resources offer new opportunities for older adults to access health information online, connect with others with shared health interests, and manage their health. However, older adults often lack sufficient eHealth literacy to maximize their benefit from these resources. Objective: This review evaluates the research design, methods, and findings of eHealth literacy interventions for older adults. Methods: A systematic review of peer-reviewed research articles from 28 databases in 9 fields was carried out in January 2013. Four rounds of screening of articles in these databases resulted in a final sample of 23 articles. Results: Findings indicated a significant gap in the literature for eHealth literacy interventions evaluating health outcomes as the outcome of interest, a lack of theory-based interventions, and few studies applied high-quality research design. Conclusions: Our findings emphasize the need for researchers to develop and assess theory-based interventions applying high-quality research design in eHealth literacy interventions targeting the older population.

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  • MELLO: MEdical Life-Log Ontology

    Date Submitted: Nov 24, 2014

    Open Peer Review Period: Nov 25, 2014 - Jan 20, 2015

    Background: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has b...

    Background: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic consistency among lifelog terms and related ontologies. Objective: MEdical Life-Log Ontology (MELLO) was developed by identifying lifelog concepts and relationships between concepts, and it provides clear definitions by following ontology development methods. MELLO aims to support the classification and semantic mapping of lifelog data from diverse health self-tracking devices. Methods: MELLO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of lifelog data, (2) identifying lifelog concepts, (3) assigning relationships among MELLO concepts, (4) developing MELLO properties (e.g., synonyms, preferred terms, and definitions) for each MELLO concept, and (5) evaluating representative layers of the ontology content. An evaluation was performed by classifying 11 devices into 3 classes by subjects, and performing pairwise comparisons of lifelog terms among 5 devices in each class as measured using the Jaccard similarity index. Results: MELLO represents a comprehensive knowledge base of 1,980 lifelog concepts, with 4,596 synonyms for 1,193 (61%) concepts and 1,395 definitions for 923 (48%) concepts. The Web-based MELLO Browser and MELLO Mapper provide convenient access and annotating non-standard proprietary terms with MELLO (http://www.snubi.org/software/mello). MELLO covers 88.1% of lifelog terms from 11 health self-tracking devices and uses simple string matching to match semantically similar terms provided by various devices that are not yet integrated. The results from the comparisons of Jaccard similarities between simple string matching and MELLO matching revealed increases of 2.5-fold for the physical activity class, 2.2-fold for the body measure class, and 5.7-fold for the sleep class. Conclusions: MELLO is the first ontology for representing health-related lifelog data with rich contents including definitions, synonyms, and semantic relationships. MELLO fills the semantic gaps among heterogeneous lifelog terms that are generated by diverse health self-tracking devices. The unified representation of lifelog terms facilitated by MELLO can help describe an individual’s lifestyle and environmental factors, which can be included with user-generated data for clinical research and thereby enhance data integration and sharing.

  • The effect of telemonitoring and telephone-based health coaching on health-related quality of life and clinical measures among Finnish diabetic and heart disease patients: a randomized controlled trial

    Date Submitted: Nov 24, 2014

    Open Peer Review Period: Nov 25, 2014 - Jan 20, 2015

    Background: There is a strong will and need to find alternative models of health care delivery driven by the ever-increasing burden of chronic diseases. Objective: The purpose of this one-year trial w...

    Background: There is a strong will and need to find alternative models of health care delivery driven by the ever-increasing burden of chronic diseases. Objective: The purpose of this one-year trial was to study whether a structured telephone-based health coaching programme, which was supported by a remote monitoring system, could be used to improve the health-related quality of life (HRQL) and/or the clinical measures of type 2 diabetes and heart disease patients. Methods: A randomized controlled trial was conducted among type 2 diabetes patients and heart disease patients of the South Karelia Social and Health Care District. Patients were recruited by sending invitation to randomly selected patients using electronic health records system. Health coaches called patients every four to six weeks and patients were encouraged to self-monitor their weight, blood pressure, blood glucose (diabetics) and steps (heart disease patients) once in a week. The primary outcome was the self-assessed HRQL measured by SF-36 and HbA1c among diabetic patients. The clinical measures assessed were blood pressure, weight, waist circumference, and lipid levels. Results: 267 heart patients and 250 diabetes patients started in the trial, of which 246 and 225 patients concluded the end point assessments, respectively. The withdrawal was associated with the patients’ unfamiliarity with mobile phones: of the 41 dropouts, 85% (11 heart disease patients ) and 88% (14 diabetes patients) were familiar with mobile phones whereas the corresponding percentages were 97.1% (231) and 99% (208), respectively, among the rest of the patients (P=0.019 and P=0.004). Withdrawal was also associated with heart disease patients’ comorbidities: 40% (8) of the dropouts had at least one comorbidity whereas the corresponding percentage was 19% (47) among the rest of the patients (P=0.024). The intervention showed no statistically significant benefits over the current practice with regard to the health-related quality of life (heart disease patients: β=0.730, P=0.358 for physical component score and β=-0.608,P=0.616 for mental component score, diabetes patients: β=0.875, P=0.853 for physical component score, β=-0.770, P=0.523 for mental component score). There was a significant difference in waist in the type 2 diabetes group (β=-1.711, P=0-012. There were no differences in any other outcome variables. Conclusions: Health coaching programme supported with telemonitoring did not improve heart disease patients' or diabetes patients’ quality of life or their clinical condition. We found indications that the intervention had differential effect between heart patients and diabetes patients. Diabetes patients may be more prone to benefit from this kind of intervention. This should not be neglected when developing new ways for self-management of chronic diseases. Clinical Trial: clinicaltrials.gov Identifier: NCT01310491

  • Wikipedia and Medicine: Quantifying Readership, Editors, and the Significance of Natural Language

    Date Submitted: Nov 23, 2014

    Open Peer Review Period: Nov 24, 2014 - Jan 19, 2015

    Background: Wikipedia is a collaboratively edited encyclopedia. One of the most popular websites on the Internet, it is known to be a frequently used source of healthcare information by both professio...

    Background: Wikipedia is a collaboratively edited encyclopedia. One of the most popular websites on the Internet, it is known to be a frequently used source of healthcare information by both professionals and the lay public. Objective: This document quantifies: 1. The amount of medical content on Wikipedia a. By number of articles b. By number of bytes 2. The reliability of Wikipedia’s medical content (using references as a proxy) 3. The readership of medical content a. Comparison between Wikipedia and other healthcare websites b. Comparison between Wikipedia’s natural language editions c. Correlation of Wikipedia article traffic and disease prevalence 4. The quantity/characteristics of Wikipedia’s medical contributors a. Year-over-year analysis of editor numbers b. Contributor demographics/background via survey Methods: Using a well-defined tagging infrastructure we identify medically pertinent English Wikipedia articles and links to their foreign language equivalents (Objective 1). With these, Wikipedia’s API can be queried to produce metadata and full texts for entire article histories (Objective 1-2). Wikipedia also makes available hourly reports that aggregate reader traffic at per-article granularity (Objective 3). An online survey was used to determine the background of contributors (Objective 4). Standard mining/analysis techniques are applied to each of these datasets. Data focuses on year-end 2013, but historical data permits some longitudinal analysis. Results: Wikipedia’s medical content (at the end of 2013) is made up of more than 155,000 articles and 1 billion bytes of text across 255+ languages. This content is supported by more than 950,000 references. Content was viewed more than 4.88 billion times in 2013. This makes it one of -- if not the most viewed -- medical resource(s) globally. The core editor community numbers less than 300 and has declined over the past 5 years. The members of this community are half health care providers and 85% have a university education. Conclusions: While Wikipedia has a considerable volume of multi-lingual medical content that is extensively read and well-referenced, the core group of editors that contribute and maintain that content is small and shrinking in size.

  • Nursing performance during concurrent smartphone use: are nurses aware of their performance decrements?

    Date Submitted: Nov 22, 2014

    Open Peer Review Period: Nov 24, 2014 - Dec 1, 2014

    Background: Background Prior research has documented the effect of concurrent smartphone use on medical care. This current study examined the extent of hospital registered nurses’ awareness of thei...

    Background: Background Prior research has documented the effect of concurrent smartphone use on medical care. This current study examined the extent of hospital registered nurses’ awareness of their smartphone-associated performance decrements. Objective: Objective The objective of this study was to compare self-reported performance with reported observed performance of others related to smartphone use by hospital registered nurses. Methods: Methods In March 2014, a previously validated survey was emailed to the 10,978 members of the Academy of Medical Surgical Nurses. Eight hundred and twenty-five respondents met the inclusion criteria of in-patient care. Results: Results A significant difference was found between registered nurses’ self-reported and observed rates of errors associated with concurrent smartphone use in three categories: work performance (Z = –26.6142, P < 0.01), missing important clinical information (Z = −13.9882, p < 0.01) and making a medical error (Z = −9.6798, P < 0.01). Conclusions: Conclusions Many hospitals are drawing up policies that allow workers to decide how to use their devices at work. This study found that nurses express a disproportionately high confidence in their ability to manage the risk associated with the use of smartphones and may not be able to accurately assess when it is appropriate to use their smartphones at work.

  • Picture Me Smokefree: A Qualitative Feasibility Study Using Social Media and Digital Photography to Engage Young Adults in Tobacco Reduction and Cessation

    Date Submitted: Nov 20, 2014

    Open Peer Review Period: Nov 21, 2014 - Nov 28, 2014

    Background: Young adults have high rates of tobacco use compared to other sub-populations, yet there are relatively few tobacco interventions specifically targeted to this group. In this article we re...

    Background: Young adults have high rates of tobacco use compared to other sub-populations, yet there are relatively few tobacco interventions specifically targeted to this group. In this article we report findings from a qualitative feasibility study Picture Me Smokefree (PMSF), an online tobacco reduction and cessation intervention for young adults employing digital photography and social networking. Objective: The main goal of the project was to determine the feasibility of engaging young adults to participate in user-driven, online forums intended to provide peer support and motivate critical reflection about tobacco use and cessation among this high-use, hard-to-reach population. A related aim was to explore the influence of gender-related factors on participation, to determine the need for online interventions to be tailored to the specific gender preferences reflecting young men and women’s participation styles. Methods: Sixty young adults ages 19 to 24 who self-identified as current cigarette smokers or who had quit within the last year were recruited from across British Columbia, Canada and participated in an online photo-group on Facebook over a period of 12 consecutive weeks. A variety of data collection methods were used including tracking online activity, surveys and interviews. Data analysis involved both quantitative measures (e.g., frequencies, crosstabs) and qualitative (e.g., narrative analysis, synthesis of feedback) feedback about participant engagement. Results: Findings from this study suggest good potential for Facebook as an accessible, low cost platform for engaging young adults to reflect on the reasons for their tobacco use, the benefits of quitting or reducing, and the best strategies for tobacco reduction. Young adults’ frequent use of smartphone and mobile devices to access social networking permitted ease of access and facilitated real time peer-to-peer support across a diverse group of participants. However, our experience of conducting the study suggests that working with young tobacco users can be accompanied by considerable recruitment, participation and retention challenges. Our findings also pointed to differences in how young women and men engaged the photo-group intervention that should be considered bearing in mind that in follow up interviews participants indicated their preference for a mixed gender and “gender neutral” group format. Conclusions: Tobacco interventions for youth and young adults should be embedded within the existing social networking platforms they access most frequently, rather than designing a stand-alone online prevention or intervention resource. This sub-population would likely benefit from tobacco reduction interventions that are gender-sensitive rather than gender-specific.

  • Behaviour change techniques in popular alcohol reduction apps

    Date Submitted: Nov 20, 2014

    Open Peer Review Period: Nov 20, 2014 - Jan 15, 2015

    Background: Smartphone apps have the potential to reduce excessive alcohol consumption cost-effectively. Although hundreds of alcohol-related apps are available there is little information about the b...

    Background: Smartphone apps have the potential to reduce excessive alcohol consumption cost-effectively. Although hundreds of alcohol-related apps are available there is little information about the behaviour change techniques (BCTs) they contain, or the extent to which they are based on evidence or theory and how this relates to their popularity and user ratings. Objective: To assess the proportion of popular alcohol-related apps available in the UK that focus on alcohol reduction, identify the BCTs they contain and assess whether BCTs or the mention of theory or evidence is associated with app popularity and user ratings. Methods: The iTunes and Google Play stores were searched with the terms ‘alcohol’ and ‘drink’ and the first 800 results were classified into: alcohol reduction, entertainment or blood alcohol content measurement. Of those classified as alcohol reduction, all free apps and the top 10 paid apps were coded for BCTs and for reference to evidence or theory. Measures of popularity and user ratings were extracted. Results: Of the 800 apps identified, 662 were unique. Of these, 13.7% were classified as alcohol reduction (n=91, 95% CI: 11.3 – 16.6), 53.9% entertainment (n=357, 95% CI: 50.1 – 57.7), 18.9% blood alcohol content measurement (n=125, 95% CI: 16.1 – 22.0) and 13.4% other (n=89, 95% CI: 11.1 – 16.3). The 51 free alcohol reduction apps and the top 10 paid apps contained a mean of 3.6 BCTs (SD=3.4), with approximately 12% (7/61) not including any BCTs. The BCTs used most often were: ‘facilitate self-recording’ (54.1%), ‘provide information on consequences of excessive alcohol use and drinking cessation’ (42.6%), ‘provide feedback on performance’ (41.0%), ‘give options for additional and later support’ (24.6%) and ‘offer/direct towards appropriate written materials’ (23.0%). These apps also rarely included any of the 22 BCTs frequently used in other health behaviour change interventions (mean: 2.46, SD = 2.06). Evidence was mentioned by 16.4% of apps and theory was not mentioned by any app. Multivariable regression showed that apps including advice on environmental restructuring were associated with lower user ratings (Β = -46.61, p = .04, 95% CI: -91.77 – -1.45) and that both the techniques of ‘advise on/facilitate the use of social support’ (Β = 2549.21, p = .04, 95% CI: 96.75 – 5001.67) and the mention of evidence (Β = 1376.74, p = .02, 95%, CI: 208.62 – 2544.86) were associated with the popularity of the app. Conclusions: Only a minority of alcohol-related apps promoted health while the majority implicitly or explicitly promoted the use of alcohol. Alcohol-related apps that promoted health contained few BCTs and none referred to theory. The mention of evidence was associated with more popular apps, but popularity and user ratings were only weakly associated with the BCT content.