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

Baseline adherence, socio-demographic, clinical, immunological, virological and anthropometric characteristics of 242 HIV positive patients on ART in Malaysia

Background: Adherence to ARVs prevents disease progression, and the emergence of resistant mutations, thereby reducing morbidity, and the necessity for more frequent, complicated regimens which are also relatively more expensive. According to WHO, minimum adherence levels of 95% are required for treatment success. Poor adherence to treatment (clinic visits and medication adherence) remains a stumbling block to the success of treatment programs and generates major concerns about possible resistance of the HIV virus to the currently available ARVs. Objective: The objective of this study was to investigate whether the introduction of mobile phone technology (SMS and telephone call reminders) can significantly improve adherence and treatment outcomes of HIV positive patients on ART in Malaysia. Methods: Baseline characteristics of 242 Malaysian patients involved in a Randomized Controlled Clinical Trial between January and December, 2014 was collected and analyzed. Data on socio-demographic factors, clinical symptoms and adherence behavior of respondents was collected using modified, pre-validated AACTG adherence questionnaires. Baseline CD4 count, viral load, weight, full blood count, blood pressure, Liver function and renal profile tests were also conducted and recorded. Data was analyzed using SPSS version 21 and R software. Results: Patients consisted of 215 (89%) males and 27 (11%) females. 117 (48%) were Malays, 98 (40%) were Chinese, 22 (9%) were Indians while 5 (2%) were of other ethnic minorities. The mean age for the intervention group was 32.1 ± 8.7 years while the mean age for the control group was 34.7 ± 9.5 years. Mean baseline adherence was 80.1 ± 19.6 and 85.1 ± 15.8 for the intervention and control groups respectively. Overall mean baseline CD4 count of patients was 222.97 ± 143.7 cells/mm³ while overall mean viral load was 255237.85 ± 470618.9. Patients had a mean weight of 61.55 ± 11.0 kg and 61.47 ± 12.3 kg in the intervention and control groups, respectively. Conclusions: Males account for about 90% of those initiating ART in the HIV clinic, at a relatively low CD4 count, high viral load and sub-optimal medication adherence levels at baseline. Clinical Trial: N/A

2015-02-10

We are pleased to announce our forthcoming new journals, all of which have currently no submission or publication fees, and all of which focus on emerging technologies and patient-centered innovations in specific areas, going beyond Internet/webbased interventions: * JMIR Cancer (http://cancer.jmir.org) * JMIR Medical Education (http://mededu.jmir.org) * JMIR Public Health and Surveillance (http://publichealth.jmir.org) We welcome submissions for the inaugural issues of these journals. The following journals have already published articles and are still free of charge to publish in (no submission or publication fees): * JMIR Human Factors (http://humanfactors.jmir.org) * JMIR Rehabilitation and Assistive Technologies (http://rehab.jmir.org) * JMIR Mental Health (http://mental.jmir.org) (APF after March 1st, 2015) To submit to these journals, simply append /author to the URLs above (e.g. http://cancer.jmir.org/author), or submit to the main JMIR journal and use the dropdown-box in step 1 to change the journal name. All journals offer careful copyediting and typesetting of manuscripts, and submission to PubMed and PubMed Central (being new journals it may however take a few month until they appear in PubMed). We are also happy to announce that JMIR Medical Informatics and JMIR Serious Games are now indexed in PubMed.

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Recent Articles:

  • Air quality word cloud.

    Social Media as a Sensor of Air Quality and Public Response in China

    Abstract:

    Background: Recent studies have demonstrated the utility of social media data sources for a wide range of public health goals, including disease surveillance, mental health trends, and health perceptions and sentiment. Most such research has focused on English-language social media for the task of disease surveillance. Objective: We investigated the value of Chinese social media for monitoring air quality trends and related public perceptions and response. The goal was to determine if this data is suitable for learning actionable information about pollution levels and public response. Methods: We mined a collection of 93 million messages from Sina Weibo, China’s largest microblogging service. We experimented with different filters to identify messages relevant to air quality, based on keyword matching and topic modeling. We evaluated the reliability of the data filters by comparing message volume per city to air particle pollution rates obtained from the Chinese government for 74 cities. Additionally, we performed a qualitative study of the content of pollution-related messages by coding a sample of 170 messages for relevance to air quality, and whether the message included details such as a reactive behavior or a health concern. Results: The volume of pollution-related messages is highly correlated with particle pollution levels, with Pearson correlation values up to .718 (n=74, P<.001). Our qualitative results found that 67.1% (114/170) of messages were relevant to air quality and of those, 78.9% (90/114) were a firsthand report. Of firsthand reports, 28% (32/90) indicated a reactive behavior and 19% (17/90) expressed a health concern. Additionally, 3 messages of 170 requested that action be taken to improve quality. Conclusions: We have found quantitatively that message volume in Sina Weibo is indicative of true particle pollution levels, and we have found qualitatively that messages contain rich details including perceptions, behaviors, and self-reported health effects. Social media data can augment existing air pollution surveillance data, especially perception and health-related data that traditionally requires expensive surveys or interviews.

  • Partial screenshot of the Healthy Past 50 website.

    A Web-Based Health Promotion Program for Older Workers: Randomized Controlled Trial

    Abstract:

    Background: Recent evidence supports the efficacy of programs that promote improvements in the health practices of workers 50 years and older who are at higher risk for chronic diseases than younger workers are. Internet-based programs that promote healthy practices have also shown promise and, therefore, should be especially appropriate for workers aged 50 years and older. Objective: The purpose of the research was to evaluate the effectiveness of HealthyPast50, a fully automated Web-based health promotion program based on social cognitive theory and aimed specifically at workers 50 years and older. Methods: The randomized controlled trial was conducted across multiple US offices of a large global information technology company. The sample included 278 employees aged 50 to 68 who were recruited online and randomly assigned to the Web-based HealthyPast50 program or to a wait-list control condition. Self-report measures of diet, physical activity, stress, and tobacco use were collected online before and 3 months after the program group was given access to the program. Use data included number of log-ins and number of pages accessed. The primary analysis was multiple linear regression, following intent-to-treat principles with multiple imputation using the Markov chain Monte Carlo (MCMC) approach for nonmonotone missing data. Potential moderators from demographic characteristics and program dosage effects were assessed using multiple linear regression models. Additional analyses were conducted on complete (nonimputed) cases, excluding program participants who used the program for less than 30 minutes. Results: Retention rates were good for both groups: 80.4% (111/138) for the program group and 94.3% (132/140) for the control group. Program group participants spent a mean of 102.26 minutes in the program (SD 148.32), logged in a mean of 4.33 times (SD 4.28), and viewed a mean of 11.04 pages (SD 20.08). In the analysis of the imputed dataset, the program group performed significantly better than the control group on diet behavioral change self-efficacy (estimated adjusted difference [Δ]=0.16, P=.048), planning healthy eating (Δ=0.17, P=.03), and mild exercise (Δ=1.03, P=.01). Moderator and dosage analyses of the dataset found no significant program effects. Analyses of the nonimputed dataset comparing program users with controls found additional significant program effects on eating practices (Δ=0.09, P=.03), exercise self-efficacy (Δ=0.12, P=.03), exercise planning (Δ=0.18, P=.03), and aging beliefs (Δ=0.17, P=.01). Moderator analysis of this dataset also found significant moderator effects of gender on multiple measures of exercise. Conclusions: A Web-based health promotion program showed promise for making a significant contribution to the short-term dietary and exercise practices of older working adults. Gender effects suggest that the program effects on exercise are due mainly to improvements among women.

  • Mountain visualization of biclustering of highly frequent major MeSH terms and articles on Internet health information seeking behavior.

    Mapping Publication Trends and Identifying Hot Spots of Research on Internet Health Information Seeking Behavior: A Quantitative and Co-Word Biclustering...

    Abstract:

    Background: The Internet has become an established source of health information for people seeking health information. In recent years, research on the health information seeking behavior of Internet users has become an increasingly important scholarly focus. However, there have been no long-term bibliometric studies to date on Internet health information seeking behavior. Objective: The purpose of this study was to map publication trends and explore research hot spots of Internet health information seeking behavior. Methods: A bibliometric analysis based on PubMed was conducted to investigate the publication trends of research on Internet health information seeking behavior. For the included publications, the annual publication number, the distribution of countries, authors, languages, journals, and annual distribution of highly frequent major MeSH (Medical Subject Headings) terms were determined. Furthermore, co-word biclustering analysis of highly frequent major MeSH terms was utilized to detect the hot spots in this field. Results: A total of 533 publications were included. The research output was gradually increasing. There were five authors who published four or more articles individually. A total of 271 included publications (50.8%) were written by authors from the United States, and 516 of the 533 articles (96.8%) were published in English. The eight most active journals published 34.1% (182/533) of the publications on this topic. Ten research hot spots were found: (1) behavior of Internet health information seeking about HIV infection or sexually transmitted diseases, (2) Internet health information seeking behavior of students, (3) behavior of Internet health information seeking via mobile phone and its apps, (4) physicians’ utilization of Internet medical resources, (5) utilization of social media by parents, (6) Internet health information seeking behavior of patients with cancer (mainly breast cancer), (7) trust in or satisfaction with Web-based health information by consumers, (8) interaction between Internet utilization and physician-patient communication or relationship, (9) preference and computer literacy of people using search engines or other Web-based systems, and (10) attitude of people (especially adolescents) when seeking health information via the Internet. Conclusions: The 10 major research hot spots could provide some hints for researchers when launching new projects. The output of research on Internet health information seeking behavior is gradually increasing. Compared to the United States, the relatively small number of publications indexed by PubMed from other developed and developing countries indicates to some extent that the field might be still underdeveloped in many countries. More studies on Internet health information seeking behavior could give some references for health information providers.

  • (cc) Agree et al. CC-BY-SA-2.0, please cite as (http://www.jmir.org/article/viewFile/3352/1/52521).

    “It’s Got to Be on This Page”: Age and Cognitive Style in a Study of Online Health Information Seeking

    Abstract:

    Background: The extensive availability of online health information offers the public opportunities to become independently informed about their care, but what affects the successful retrieval and understanding of accurate and detailed information? We have limited knowledge about the ways individuals use the Internet and the personal characteristics that affect online health literacy. Objective: This study examined the extent to which age and cognitive style predicted success in searching for online health information, controlling for differences in education, daily Internet use, and general health literacy. Methods: The Online Health Study (OHS) was conducted at Johns Hopkins School of Public Health and Stanford University School of Medicine from April 2009 to June 2010. The OHS was designed to explore the factors associated with success in obtaining health information across different age groups. A total of 346 men and women aged 35 years and older of diverse racial and ethnic backgrounds participated in the study. Participants were evaluated for success in searching online for answers to health-related tasks/questions on nutrition, cancer, alternative medicine, vaccinations, medical equipment, and genetic testing. Results: Cognitive style, in terms of context sensitivity, was associated with less success in obtaining online health information, with tasks involving visual judgment most affected. In addition, better health literacy was positively associated with overall success in online health seeking, specifically for tasks requiring prior health knowledge. The oldest searchers were disadvantaged even after controlling for education, Internet use, general health literacy, and cognitive style, especially when spatial tasks such as mapping were involved. Conclusions: The increasing availability of online health information provides opportunities to improve patient education and knowledge, but effective use of these resources depends on online health literacy. Greater support for those who are in the oldest cohorts and for design of interfaces that support users with different cognitive styles may be required in an age of shared medical decision making.

  • Research assistants conducting clinical trial of SMS-based laboratory results communication intervention in Mbarara, Uganda.

    Know Your Audience: Predictors of Success for a Patient-Centered Texting App to Augment Linkage to HIV Care in Rural Uganda

    Abstract:

    Background: Despite investments in infrastructure and evidence for high acceptability, few mHealth interventions have been implemented in sub-Saharan Africa. Objective: We sought to (1) identify predictors of uptake of an mHealth application for a low-literacy population of people living with HIV (PLWH) in rural Uganda and (2) evaluate the efficacy of various short message service (SMS) text message formats to optimize the balance between confidentiality and accessibility. Methods: The trial evaluated the efficacy of a SMS text messaging app to notify PLWH of their laboratory results and request return to care for those with abnormal test results. Participants with a normal laboratory result received a single SMS text message indicating results were normal. Participants with an abnormal test result were randomized to 1 of 3 message formats designed to evaluate trade-offs between clarity and privacy: (1) an SMS text message that stated results were abnormal and requested return to clinic (“direct”), (2) the same message protected by a 4-digit PIN code (“PIN”), and (3) the message “ABCDEFG” explained at enrollment to indicate abnormal results (“coded”). Outcomes of interest were (1) self-reported receipt of the SMS text message, (2) accurate identification of the message, and (3) return to care within 7 days (for abnormal results) or on the date of the scheduled appointment (for normal results). We fit regression models for each outcome with the following explanatory variables: sociodemographic characteristics, CD4 count result, ability to read a complete sentence, ability to access a test message on enrollment, and format of SMS text message. Results: Seventy-two percent (234/385) of participants successfully receiving a message, 87.6% (219/250) correctly identified the message format, and 60.8% (234/385) returned to clinic at the requested time. Among participants with abnormal tests results (138/385, 35.8%), the strongest predictors of reported message receipt were the ability to read a complete sentence and a demonstrated ability to access a test message on enrollment. Participants with an abnormal result who could read a complete sentence were also more likely to accurately identify the message format (AOR 4.54, 95% CI 1.42-14.47, P=.01) and return to clinic appropriately (AOR 3.81, 95% CI 1.61-9.03, P=.002). Those who were sent a PIN-protected message were less likely to identify the message (AOR 0.11, 95% CI 0.03-0.44, P=.002) or return within 7 days (AOR 0.26, 95% CI 0.10-0.66, P=.005). Gender, age, and socioeconomic characteristics did not predict any outcomes and there were no differences in outcomes between those receiving direct or coded messages. Conclusions: Confirmed literacy at the time of enrollment was a robust predictor of SMS text message receipt, identification, and appropriate response for PLWH in rural Uganda. PIN-protected messages reduced odds of clinic return, but coded messages were as effective as direct messages and might augment privacy. Trial Registration: Clinicaltrials.gov NCT 01579214; https://clinicaltrials.gov/ct2/show/NCT01579214 (Archived by WebCite at http://www.webcitation.org/6Ww8R4sKq).

  • This image is from the public domain by cooldesign (http://www.freedigitalphotos.net/images/medical-stethoscope-on-a-laptop-computer-photo-p198234).

    Systems Medicine 2.0: Potential Benefits of Combining Electronic Health Care Records With Systems Science Models

    Abstract:

    Background: The global burden of disease is increasingly dominated by non-communicable diseases.These diseases are less amenable to curative and preventative interventions than communicable disease. This presents a challenge to medical practice and medical research, both of which are experiencing diminishing returns from increasing investment. Objective: Our aim was to (1) review how medical knowledge is generated, and its limitations, (2) assess the potential for emerging technologies and ideas to improve medical research, and (3) suggest solutions and recommendations to increase medical research efficiency on non-communicable diseases. Methods: We undertook an unsystematic review of peer-reviewed literature and technology websites. Results: Our review generated the following conclusions and recommendations. (1) Medical knowledge continues to be generated in a reductionist paradigm. This oversimplifies our models of disease, rendering them ineffective to sufficiently understand the complex nature of non-communicable diseases. (2) Some of these failings may be overcome by adopting a “Systems Medicine” paradigm, where the human body is modeled as a complex adaptive system. That is, a system with multiple components and levels interacting in complex ways, wherein disease emerges from slow changes to the system set-up. Pursuing systems medicine research will require larger datasets. (3) Increased data sharing between researchers, patients, and clinicians could provide this unmet need for data. The recent emergence of electronic health care records (EHR) could potentially facilitate this in real-time and at a global level. (4) Efforts should continue to aggregate anonymous EHR data into large interoperable data silos and release this to researchers. However, international collaboration, data linkage, and obtaining additional information from patients will remain challenging. (5) Efforts should also continue towards “Medicine 2.0”. Patients should be given access to their personal EHR data. Subsequently, online communities can give researchers the opportunity to ask patients for direct access to the patient’s EHR data and request additional study-specific information. However, selection bias towards patients who use Web 2.0 technology may be difficult to overcome. Conclusions: Systems medicine, when combined with large-scale data sharing, has the potential to raise our understanding of non-communicable diseases, foster personalized medicine, and make substantial progress towards halting, curing, and preventing non-communicable diseases. Large-scale data amalgamation remains a core challenge and needs to be supported. A synthesis of “Medicine 2.0” and “Systems Science” concepts into “Systems Medicine 2.0” could take decades to materialize but holds much promise.

  • Term clouds for top 95 percentile ADRs (A) and bottom 5 percentile (B). Term size is proportionate to the relative number of reports in the FDA AERS.

    Ranking Adverse Drug Reactions With Crowdsourcing

    Abstract:

    Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  • Child killed by a car bomb in Kirkuk, Iraq, July 2011. Source:

    Web-Based Psychotherapy for Posttraumatic Stress Disorder in War-Traumatized Arab Patients: Randomized Controlled Trial

    Abstract:

    Background: In recent years, armed conflicts in the Middle East have resulted in high rates of exposure to traumatic events. Despite the increasing demand of mental health care provision, ongoing violence limits conventional approaches of mental health care provision. Internet-based interventions for posttraumatic stress disorder (PTSD) have proved feasible and effective in Western countries, but their applicability and efficacy in war and conflict regions remains unknown. Objective: This study investigated the efficacy of a cognitive behavioral Internet-based intervention for war-traumatized Arab patients, with focus on Iraq. Methods: A total of 159 individuals with PTSD participated in a parallel group randomized trial. Participants were randomly allocated by a computer-generated sequence to a treatment group (n=79) or a waiting list control group (n=80). The treatment group received 2 weekly 45-minute cognitive behavioral interventions via Internet over a 5-week period (10 sessions in total). The primary outcome was recovery from posttraumatic stress symptoms. Results: Posttraumatic stress symptoms were significantly reduced from baseline to posttreatment (intention-to-treat analysis) in the treatment group relative to the control group (F1,157=44.29, P<.001, d=0.92). Treatment effects were sustained at 3-month follow-up. Completer analysis indicated that 29 of 47 patients (62%) in the treatment group had recovered from posttraumatic stress symptoms at posttreatment (reliable change and Posttraumatic Stress Diagnostic Scale score <20) versus 1 patient (2%) in the control group (OR 74.19, 95% CI 9.93-585.8, P<.001) indicating that the chance of recovering was 74.19 times higher in the treatment than in the control group. Conclusions: The results indicate, even in unstable and insecure settings with ongoing exposure to human rights violations through war and dictatorships, people with posttraumatic stress symptoms benefit from a cognitive behavioral treatment provided entirely through the Internet. This method of delivery could improve patients’ access to humanitarian aid in the form of e-mental health services. Trial Registration: Australian New Zealand Clinical Trial Registry, ACTRN12611001019998; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347505 (Archived by WebCite at http://www.webcitation.org/6Wto4HCdH).

  • Image courtesy of Ambro at FreeDigitalPhotos.net.

    Do Web-Based and Clinic Samples of Gay Men Living With HIV Differ on Self-Reported Physical and Psychological Symptoms? A Comparative Analysis

    Abstract:

    Background: Although the Internet is commonly used to recruit samples in studies of human immunodeficiency virus (HIV)-related risk behaviors, it has not been used to measure patient-reported well-being. As the burden of long-term chronic HIV infection rises, the Internet may offer enormous potential for recruitment to research and interventions. Objective: This study aimed to compare two samples of gay men living with HIV, one recruited via the Web and the other recruited in outpatient settings, in terms of self-reported physical and psychological symptom burden. Methods: The Internet sample was recruited from a UK-wide Web-based survey of gay men with diagnosed HIV. Of these, 154 respondents identified themselves as resident in London and were included in this analysis. The HIV clinic sample was recruited from five HIV outpatient clinics. Of these participants, 400 gay men recruited in London clinics were included in this analysis. Results: The Web-based sample was younger than the clinic sample (37.3 years, SD 7.0 vs 40.9 years, SD 8.3), more likely to be in paid employment (72.8%, 99/136 vs 60.1%, 227/378), less likely to be on antiretroviral therapy (ART) (58.4%, 90/154 vs 68.0%, 266/391), and had worse mean psychological symptom burden compared to the clinic sample (mean scores: 1.61, SD 1.09 vs 1.36, SD 0.96) but similar physical symptom burden (mean scores: 0.78, SD 0.65 vs 0.70, SD 0.74). In multivariable logistic regression, for the physical symptom burden model, adjusted for age, ethnicity, employment status, and ART use, the recruitment setting (ie, Web-based vs clinic) was not significantly associated with high physical symptom score. The only variable that remained significantly associated with high physical symptom score was employment status, with those in employment being less likely to report being in the upper (worst) physical symptom tertile versus the other two tertiles (adjusted OR 0.41, 95% CI 0.28-0.62, P<.001). For the psychological symptom burden model, those recruited via the Web were significantly more likely to report being in the upper (worst) tertile (adjusted OR 2.20, 95% CI 1.41-3.44, P=.001). In addition, those in employment were less likely to report being in the upper (worst) psychological symptom tertile compared to those not in employment (adjusted OR 0.32, 95% CI 0.21-0.49, P<.001). Conclusions: Our data have revealed a number of differences. Compared to the clinic sample, the Web-based sample had worse psychological symptom burden, younger average age, higher prevalence of employment, and a lower proportion on ART. For future research, we recommend that Web-based data collection should include the demographic variables that we note differed between samples. In addition, we recognize that each recruitment method may bring inherent sampling bias, with clinic populations differing by geographical location and reflecting those accessing regular medical care, and Web-based sampling recruiting those with greater Internet access and identifying survey materials through specific searches and contact with specific websites.

  • Web-Based Physical Activity Record System available on the smartphone, the tablet and the Personal computer. (cc) Namba et al. CC-BY-SA-2.0, please cite as (http://www.jmir.org/article/viewFile/3923/1/54866).

    Use of a Web-Based Physical Activity Record System to Analyze Behavior in a Large Population: Cross-Sectional Study

    Abstract:

    Background: The use of Web-based physical activity systems has been proposed as an easy method for collecting physical activity data. We have developed a system that has exhibited high accuracy as assessed by the doubly labeled water method. Objective: The purpose of this study was to collect behavioral data from a large population using our Web-based physical activity record system and assess the physical activity of the population based on these data. In this paper, we address the difference in physical activity for each urban scale. Methods: In total, 2046 participants (aged 30-59 years; 1105 men and 941 women) participated in the study. They were asked to complete data entry before bedtime using their personal computer on 1 weekday and 1 weekend day. Their residential information was categorized as urban, urban-rural, or rural. Participant responses expressed the intensity of each activity at 15-minute increments and were recorded on a Web server. Residential areas were compared and multiple regression analysis was performed. Results: Most participants had a metabolic equivalent (MET) ranging from 1.4 to 1.8, and the mean MET was 1.60 (SD 0.28). The median value of moderate-to-vigorous physical activity (MVPA, ≥3 MET) was 7.92 MET-hours/day. A 1-way ANCOVA showed that total physical activity differed depending on the type of residential area (F2,2027=5.19, P=.006). The urban areas (n=950) had the lowest MET-hours/day (mean 37.8, SD, 6.0), followed by urban-rural areas (n=432; mean 38.6, SD 6.5; P=.04), and rural areas (n=664; mean 38.8, SD 7.4; P=.002). Two-way ANCOVA showed a significant interaction between sex and area of residence on the urban scale (F2,2036=4.53, P=.01). Men in urban areas had the lowest MET-hours/day (MVPA, ≥3 MET) at mean 7.9 (SD 8.7); men in rural areas had a MET-hours/day (MVPA, ≥3 MET) of mean 10.8 (SD 12.1, P=.002). No significant difference was noted in women among the 3 residential areas. Multiple regression analysis showed that physical activity consisting of standing while working was the highest contributor to MVPA, regardless of sex. Conclusions: We were able to compile a detailed comparison of physical activity because our Web-based physical activity record system allowed for the simultaneous evaluation of physical activity from 2046 Japanese people. We found that rural residents had greater total physical activity than urban residents and that working and transportation behaviors differed depending on region type. Multiple regression analysis showed that the behaviors affected MVPA. People are less physically active while working, and sports and active transportation might be effective ways of increasing physical activity levels.

  • Screenshot of the Web questionnaire.

    Web-Based Self-Reported Height, Weight, and Body Mass Index Among Swedish Adolescents: A Validation Study

    Abstract:

    Background: Web-collected height and weight are increasingly used in epidemiological studies; however, the validity has rarely been evaluated. Objective: The aim of the study was to validate self-reported height, weight, and corresponding body mass index (BMI) among Swedish adolescents aged approximately 16 years. A secondary aim was to investigate possible prediction factors for validity of self-reported BMI. Methods: The study included 1698 adolescents from the population-based cohort BAMSE. Height and weight were collected through a Web-based questionnaire and subsequently measured using standard procedures. Differences between reported and measured height, weight, and corresponding BMI were compared by t tests and agreement was evaluated by Pearson correlation and Bland-Altman plots. Multivariable linear regression analysis was used to investigate whether lifestyle and demographic factors predicted validity of self-reported BMI. Results: On average, weight was underestimated by 1.1 kg and height was overestimated by 0.5 cm, leading to an underestimation of BMI by 0.5 kg/m2. Correlation coefficients were .98 for height, .97 for weight, and .94 for BMI, and highly significant. Females underestimated weight to a higher extent than males and overweight and obese participants underestimated weight to a higher extent than normal-weight participants, which resulted in higher underestimation of BMI. Underweight participants, on the contrary, overestimated weight and correspondingly BMI. Overall, a high proportion of participants were classified into the correct BMI category; however, among overweight and obese participants, only 60.2% (139/231) and 46% (20/44) were correctly classified, respectively. In the multivariable prediction model, only gender and BMI status significantly predicted discrepancy between reported and measured BMI. Conclusions: Web-collected BMI may be used as a valid, quick, and cost-effective alternative to measured BMI among Swedish adolescents. The accuracy of self-reported BMI declines with increasing BMI and self-reported BMI should not be used to estimate the prevalence of overweight or obesity.

  • Possible Image #1. I will upload three potential images that we located; please use the one that you feel will be best for promotional purposes. Thank you.

    eHealth Literacy and Web 2.0 Health Information Seeking Behaviors Among Baby Boomers and Older Adults

    Abstract:

    Background: Baby boomers and older adults, a subset of the population at high risk for chronic disease, social isolation, and poor health outcomes, are increasingly utilizing the Internet and social media (Web 2.0) to locate and evaluate health information. However, among these older populations, little is known about what factors influence their eHealth literacy and use of Web 2.0 for health information. Objective: The intent of the study was to explore the extent to which sociodemographic, social determinants, and electronic device use influences eHealth literacy and use of Web 2.0 for health information among baby boomers and older adults. Methods: A random sample of baby boomers and older adults (n=283, mean 67.46 years, SD 9.98) participated in a cross-sectional, telephone survey that included the eHealth literacy scale (eHEALS) and items from the Health Information National Trends Survey (HINTS) assessing electronic device use and use of Web 2.0 for health information. An independent samples t test compared eHealth literacy among users and non-users of Web 2.0 for health information. Multiple linear and logistic regression analyses were conducted to determine associations between sociodemographic, social determinants, and electronic device use on self-reported eHealth literacy and use of Web 2.0 for seeking and sharing health information. Results: Almost 90% of older Web 2.0 users (90/101, 89.1%) reported using popular Web 2.0 websites, such as Facebook and Twitter, to find and share health information. Respondents reporting use of Web 2.0 reported greater eHealth literacy (mean 30.38, SD 5.45, n=101) than those who did not use Web 2.0 (mean 28.31, SD 5.79, n=182), t217.60=−2.98, P=.003. Younger age (b=−0.10), more education (b=0.48), and use of more electronic devices (b=1.26) were significantly associated with greater eHealth literacy (R2 =.17, R2adj =.14, F9,229=5.277, P<.001). Women were nearly three times more likely than men to use Web 2.0 for health information (OR 2.63, Wald= 8.09, df=1, P=.004). Finally, more education predicted greater use of Web 2.0 for health information, with college graduates (OR 2.57, Wald= 3.86, df =1, P=.049) and post graduates (OR 7.105, Wald= 4.278, df=1, P=.04) nearly 2 to 7 times more likely than non-high school graduates to use Web 2.0 for health information. Conclusions: Being younger and possessing more education was associated with greater eHealth literacy among baby boomers and older adults. Females and those highly educated, particularly at the post graduate level, reported greater use of Web 2.0 for health information. More in-depth surveys and interviews among more diverse groups of baby boomers and older adult populations will likely yield a better understanding regarding how current Web-based health information seeking and sharing behaviors influence health-related decision making.

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  • Baseline adherence, socio-demographic, clinical, immunological, virological and anthropometric characteristics of 242 HIV positive patients on ART in Malaysia

    Date Submitted: Mar 25, 2015

    Open Peer Review Period: Mar 26, 2015 - May 21, 2015

    Background: Adherence to ARVs prevents disease progression, and the emergence of resistant mutations, thereby reducing morbidity, and the necessity for more frequent, complicated regimens which are al...

    Background: Adherence to ARVs prevents disease progression, and the emergence of resistant mutations, thereby reducing morbidity, and the necessity for more frequent, complicated regimens which are also relatively more expensive. According to WHO, minimum adherence levels of 95% are required for treatment success. Poor adherence to treatment (clinic visits and medication adherence) remains a stumbling block to the success of treatment programs and generates major concerns about possible resistance of the HIV virus to the currently available ARVs. Objective: The objective of this study was to investigate whether the introduction of mobile phone technology (SMS and telephone call reminders) can significantly improve adherence and treatment outcomes of HIV positive patients on ART in Malaysia. Methods: Baseline characteristics of 242 Malaysian patients involved in a Randomized Controlled Clinical Trial between January and December, 2014 was collected and analyzed. Data on socio-demographic factors, clinical symptoms and adherence behavior of respondents was collected using modified, pre-validated AACTG adherence questionnaires. Baseline CD4 count, viral load, weight, full blood count, blood pressure, Liver function and renal profile tests were also conducted and recorded. Data was analyzed using SPSS version 21 and R software. Results: Patients consisted of 215 (89%) males and 27 (11%) females. 117 (48%) were Malays, 98 (40%) were Chinese, 22 (9%) were Indians while 5 (2%) were of other ethnic minorities. The mean age for the intervention group was 32.1 ± 8.7 years while the mean age for the control group was 34.7 ± 9.5 years. Mean baseline adherence was 80.1 ± 19.6 and 85.1 ± 15.8 for the intervention and control groups respectively. Overall mean baseline CD4 count of patients was 222.97 ± 143.7 cells/mm³ while overall mean viral load was 255237.85 ± 470618.9. Patients had a mean weight of 61.55 ± 11.0 kg and 61.47 ± 12.3 kg in the intervention and control groups, respectively. Conclusions: Males account for about 90% of those initiating ART in the HIV clinic, at a relatively low CD4 count, high viral load and sub-optimal medication adherence levels at baseline. Clinical Trial: N/A

  • Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use

    Date Submitted: Mar 25, 2015

    Open Peer Review Period: Mar 26, 2015 - May 21, 2015

    Background: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years, in part fueled by marketing and word-...

    Background: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years, in part fueled by marketing and word-of-mouth communications via social media platforms, such as Twitter. Objective: This study examines Twitter posts about e-cigarettes between 2008 and 2013 to gain insights into (1) marketing trends for selling and promoting e-cigarettes and (2) locations where people use e-cigarettes. Methods: We used keywords to gather tweets about e-cigarettes between July 1, 2008, and February 28, 2013. A randomly selected subset of tweets was manually coded as advertising (e.g., marketing, advertising, sales, promotion) or non-advertising (e.g., individual users, consumers), and classification algorithms were trained to code the remaining data into these two categories. A combination of manual coding and Natural Language Processing methods was used to indicate locations where people used e-cigarettes. Additional metadata were used to generate insights about users who tweeted most frequently about e-cigarettes. Results: We identified ~1.7 million tweets about e-cigarettes between 2008 and 2013, with the majority of these tweets being advertising (94%). Tweets about e-cigarettes increased more than tenfold between 2009 and 2010, suggesting a rapid increase in the popularity of e-cigarettes and marketing efforts. The Twitter handles tweeting most frequently about e-cigarettes were a mixture of e-cigarette brands, affiliate marketers, and resellers of e-cigarette products. Of the 471 e-cigarette tweets mentioning a specific place, most mentioned e-cigarette use in class (39%), followed by home/room/bed (13%), school (12%), public (9%), the bathroom (6%), and at work (5%). Conclusions: Our results demonstrate that Twitter is being used to promote e-cigarettes and that the online marketplace is more diverse than offline product offerings and advertising strategies. Monitoring and regulating these entities online will be a challenge should the Food and Drug Administration issue a ruling to regulate e-cigarettes. Our results also underscore the need to address the growing use of e-cigarettes in public places.

  • A Critical Analysis of behaviour change techniques present in wearable activity trackers and their potential for use with older adults

    Date Submitted: Mar 25, 2015

    Open Peer Review Period: Mar 26, 2015 - May 21, 2015

    Background: Wearable activity trackers are promising interventions that offer guidance and support for increasing physical activity and health-focused tracking. The extent to which they implement evid...

    Background: Wearable activity trackers are promising interventions that offer guidance and support for increasing physical activity and health-focused tracking. The extent to which they implement evidence or theory-informed behaviour change strategies is not currently known, and has the potential to offer significant insight towards adoption, and improved user health. Most older adults are not meeting their recommended daily activity guidelines, and wearable fitness trackers are increasingly cited as having great potential to improve the physical activity levels of older adults. Taking into consideration the behaviour change techniques present within physical activity trackers has not as of yet been considered as it relates to older adults. Objective: The goal of this study was to characterize the behaviour change techniques embedded in wearable activity trackers or their associated platforms that are relevant to older adults uptake of physical activity trackers as a tool to improve their health. Methods: Two independent raters used the Coventry, Aberdeen and London-Refined (CALO-RE) taxonomy to code the behaviour change strategies in seven wearable activity trackers. Two independent coders assessed the seven trackers that were commercially available in Canada as of March 2014, including Fitbit Flex, Misfit Shine, Withings Pulse, Jawbone Up24, SparkPeople, Nike Fuelband and Polar Loop. We calculated interrater reliability using Cohen’s kappa. Results: Interrater reliability was high and the average number of behaviour change techniques identified was 16.3. This total is greater than the average number of behaviour change techniques found in physical activity apps and face-to-face interventions. The Withings Pulse had the greatest number of behaviour change techniques and the Misfit Shine had the fewest. The majority of techniques identified centred around self-monitoring and self-regulation, all of which have been associated with greater physical activity. Techniques related to planning and providing instructions were scarce in wearable activity trackers. Conclusions: Overall, wearable activity trackers contained a moderate number of behaviour change techniques, conferring promise toward their effectiveness. While more research and development must be done, the current wearable trackers offer significant potential with regards to behaviour change techniques relevant to uptake by older adults.

  • Analyzing older users’ home telehealth services acceptance behavior – applying an Extended UTAUT model

    Date Submitted: Mar 26, 2015

    Open Peer Review Period: Mar 26, 2015 - May 21, 2015

    Background: Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally c...

    Background: Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally conservative users pose a big challenge to the successful implementation of innovative telehealth services. Objective: The objective of this study was to develop and empirically test a model for predicting the factors affecting older users’ acceptance of Home Telehealth Services (HTS). Methods: A survey instrument was administered to 400 participants aged 50 years and above from both rural and urban environments in Slovenia. Structural equation modeling was applied to analyze the causal effect of seven hypothesized predicting factors. HTS were introduced as a bundle of functionalities, representing future services that currently do not exist. This enabled users’ perceptions to be measured on the conceptual level, rather than attitudes to a specific technical solution. Results: Six relevant predictors were confirmed in older users’ HTS acceptance behavior, with Performance Expectancy (r=0.30), Effort Expectancy (r=0.49), Facilitating Conditions (r=0.12), and Perceived Security (r=0.16) having a direct impact on behavioral intention to use HTS. In addition, Computer Anxiety is positioned as an antecedent of Effort Expectancy with a strong negative influence (r=-0.61), and Doctor’s Opinion influence showed a strong impact on Performance Expectancy (r=0.31). The results also indicate Social Influence as an irrelevant predictor of acceptance behavior. The model of six predictors yielded 77% of the total variance explained in the final measured Behavioral Intention to Use HTS by older adults. Conclusions: The level at which HTS are perceived as easy to use and manage is the leading acceptance predictor in elderly HTS acceptance. Together with Perceived Usefulness and Perceived Security, these three factors represent the key influence on older people’s HTS acceptance behavior. When promoting HTS, interventions should focus to portray it as secure. Marketing interventions should focus also on promoting HTS among health professionals, using them as social agents to frame the services as useful and beneficial. The important role of computer anxiety may result in a need to use different equipment such as a tablet computer to access HTS. Finally, this paper introduces important methodological guidelines for measuring perceptions on a conceptual level of future services that currently do not exist

  • How Consumers and Physicians View New Medical Technology

    Date Submitted: Mar 23, 2015

    Open Peer Review Period: Mar 24, 2015 - May 19, 2015

    Background: As an outgrowth of the digital revolution coming to medicine, there are a number of new tools that are becoming available and starting to be introduced in clinical practice. Objective: To...

    Background: As an outgrowth of the digital revolution coming to medicine, there are a number of new tools that are becoming available and starting to be introduced in clinical practice. Objective: To assess healthcare professional and consumer attitudes toward new medical technology Methods: We performed a survey with 1,406 healthcare providers and 1,102 consumers responders. Results: Consumers were more likely to prefer new technologies for a medical diagnosis (437 out of 1102%) compared with providers (194 out of 1406; P<.001), with more providers (393 out of 1406) than consumers (175 out of 1102; P=.007) reporting feeling uneasy about using technology for a diagnosis. Both providers and consumers supported genetic testing for various purposes, with providers (1234 out of 1406) being significantly more likely than consumers (806 out of 1102) to support genetic testing when planning to have a baby (87.77% vs. 73.14% respectively; P<.001). Similarly, 1289 providers and 895 consumers supported diagnosing problems in a fetus (91.68% vs. 81.22%; p<.001). Ninety-percent of providers (1270 out of 1406) were concerned that patients would experience anxiety after accessing health records and 81.72% (1149 out of 1406) felt it would lead to requests for unnecessary medical evaluations, but only 34.30% (378 out of 1102; P <.001) and 24.59% (271 out of 1102; P <.001) of consumers expressed the same concerns, respectively. Physicians (137 out of 827) reported less concern about the use of technology for diagnosis compared to 21 medical students (16.57% versus 8.94%, respectively; P =.049), and also more frequently felt that patients owned their medical record (323 doctors out of 827 versus 30 students out of 235; p<.001). Conclusions: Consumers and health professionals differ significantly and broadly in their views of emerging medical technology, with more enthusiasm and support expressed by consumers.

  • If You Build It, Will They Come? Patterns of Online and Face-to-face Participation in a Parenting Program for Military Families.

    Date Submitted: Mar 19, 2015

    Open Peer Review Period: Mar 20, 2015 - May 15, 2015

    Background: Some evidence suggests parents are drawn to media-based interventions over face-to-face interventions, but little is known about the factors associated with parents’ use of Internet-base...

    Background: Some evidence suggests parents are drawn to media-based interventions over face-to-face interventions, but little is known about the factors associated with parents’ use of Internet-based or Internet-enhanced programs. Research is needed to understand characteristics of parents who may be most likely to use online components or attend face-to-face meetings in order to ensure maximum engagement among parents likely to participate in Internet-enhanced programs. Objective: In this study, we examine characteristics that predict various patterns of online use and face-to-face attendance in a parenting program designed for military families. Methods: An ecological framework guided analysis of differences in patterns of online use and face-to-face attendance by parents’ demographic characteristics (gender, education, income, number of children), number of months the parent was deployed, incentives offered, and partner’s participation both online and face-to-face. We reported differences in the total number of online components completed over the 14 modules, total number of face-to-face sessions attended, and the use of different types of online components accessed (videos, downloadable handouts, mindfulness exercises, knowledge checks, and downloadable summaries). Then, we computed multinomial logistic regression to predict patterns of engagement (use of online components and attendance at face-to-face sessions). Results: Just over half (52.2%) of the participants used the online components at least once, and 48.4% used at least four online components. The majority of participants (73.2%) attended at least one face-to-face session, and 61.6% attended at least four face-to-face sessions. The first online modules had the heaviest use, and video components were the most accessed. An examination of different patterns of participation revealed that compared to parents who did not use online components but attended face-to-face sessions, parents who engaged online and attended the face-to-face parenting program regularly were more likely to be mothers (reference category males; 95% CI 0.2 – 0.8) and more likely to have received incentives to access the online components (95% CI 3.0 – 29.5). Highly engaged mothers were also more likely to have a higher household income than less engaged mothers (95% CI 1.0 – 1.3). Compared to those who participated primarily in face-to-face sessions, parents who participated online but had less face-to-face participation were more likely have fewer (95% CI 0.4 – 1.0) and older children (95% CI 1.0 – 1.5), be married (reference category single; 95% CI 0.0 – 0.9), and to have a partner who did not attend face-to-face sessions (95% CI 0.0 – 0.2). Conclusions: Results imply that parents may be drawn to different delivery options of a parenting program (online components versus face-to-face sessions) depending on their needs and family circumstances. For example, parents who have several children may prefer a face-to-face setting with childcare available. Results suggest potential directions for tailoring online interventions.