Background: Using technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored. Objective: The purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes. Methods: A retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of ≥25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome. Results: Participants in the Retrofit Program lost a mean –5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R2=.197, P<0.001) identified the following measures as significant predictors of weight loss at 6 months: number of weigh-ins per week (P<.001), number of steps per day (P=.02), highly active minutes per week (P<.001), number of food log days per week (P<.001), and the percentage of weeks with five or more food logs (P<.001). Weighing in at least three times per week, having a minimum of 60 highly active minutes per week, food logging at least three days per week, and having 64% (16.6/26) or more weeks with at least five food logs were associated with clinically significant weight loss for both male and female participants. Conclusions: The self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention. Journal of Medical Internet Research
Background: The capacity to advertise via the Internet continues to contribute to the shifting dynamics in adult commercial sex work. eHealth interventions have shown promise to promote Internet-based sex workers’ health and safety internationally, yet minimal attention has been paid in Canada to developing such interventions. Understanding the information communicated in Internet-based sex work advertisements is a critical step in knowledge development to inform such interventions. Objective: The purpose of this content analysis was to increase our understanding of the health and safety information within the Internet advertisements among women, men, and transgender sex workers and to describe how this information may be utilized to inform eHealth service development for this population. Methods: A total of 75 Internet-based sex worker advertisements (45 women, 24 men, and 6 transgender persons) were purposefully selected from 226 advertisements collected as part of a larger study in Western Canada. Content analysis was employed to guide data extraction about demographic characteristics, sexual services provided, service restrictions, health practices and concerns, safety and security, and business practices. Frequencies for each variable were calculated and further classified by gender. Thematic analysis was then undertaken to situate the communications within the social and commercialized contexts of the sex industry. Results: Four communications themes were identified: (1) demographic characteristics; (2) sexual services; (3) health; and (4) safety and security. White was the most common ethnicity (46/75, 61%) of advertisements. It was found that 20-29 years of age accounted for 32 of the 51 advertisements that provided age. Escort, the only legal business title, was the most common role title used (48/75, 64%). In total, 85% (64/75) of advertisements detailed lists of sexual services provided and 41% (31/75) of advertisements noted never offering uncovered services (ie, no condom). Gender and the type of Web-based platform mattered for information communicated. It was found that 35 of the 45 women’s advertisements were situated in personal websites and hosted details about nonsexual aspects of an appointment. Men and transworkers used Internet classified advertisement platforms with predetermined categories. Communications about sexually transmitted infections (STIs) occurred in only 16% (12/75) of advertisements with men accounting for 7. Women’s advertisements accounted for 26 of the 37 advertisements noting safety restrictions. Zero men or transpersons restricted alcohol or drug use. In total, 75% (56/75) of advertisements offered out-call services and the average minimal hourly rate ranged from Can $ 140/h to Can $ 200/h. Conclusions: The study findings contribute to understandings about the diverse platforms used in commercial sex advertisements, and how sex workers frame information for potential clients. This information affords health care providers and policy makers insights to how they might assist with promoting the health of Internet-based sex workers and their clients.
Journal of Medical Internet Research
Background: Expansion of virtual health care—real-time video consultation with a physician via the Internet—will continue as use of mobile devices and patient demand for immediate, convenient access to care grow. Objective: The objective of the study is to analyze the care provided and the cost of virtual visits over a 3-week episode compared with in-person visits to retail health clinics (RHC), urgent care centers (UCC), emergency departments (ED), or primary care physicians (PCP) for acute, nonurgent conditions. Methods: A cross-sectional, retrospective analysis of claims from a large commercial health insurer was performed to compare care and cost of patients receiving care via virtual visits for a condition of interest (sinusitis, upper respiratory infection, urinary tract infection, conjunctivitis, bronchitis, pharyngitis, influenza, cough, dermatitis, digestive symptom, or ear pain) matched to those receiving care for similar conditions in other settings. An episode was defined as the index visit plus 3 weeks following. Patients were children and adults younger than 65 years of age without serious chronic conditions. Visits were classified according to the setting where the visit occurred. Care provided was assessed by follow-up outpatient visits, ED visits, or hospitalizations; laboratory tests or imaging performed; and antibiotic use after the initial visit. Episode costs included the cost of the initial visit, subsequent medical care, and pharmacy. Results: A total of 59,945 visits were included in the analysis (4635 virtual visits and 55,310 nonvirtual visits). Virtual visit episodes had similar follow-up outpatient visit rates (28.09%) as PCP (28.10%, P=.99) and RHC visits (28.59%, P=.51). During the episode, lab rates for virtual visits (12.56%) were lower than in-person locations (RHC: 36.79%, P<.001; UCC: 39.01%, P<.001; ED: 53.15%, P<.001; PCP: 37.40%, P<.001), and imaging rates for virtual visits (6.62%) were typically lower than in-person locations (RHC: 5.97%, P=.11; UCC: 8.77%, P<.001; ED: 43.06%, P<.001; PCP: 11.26%, P<.001). RHC, UCC, ED, and PCP were estimated to be $ 36, $ 153, $ 1735, and $ 162 more expensive than virtual visit episodes, respectively, including medical and pharmacy costs. Conclusions: Virtual care appears to be a low-cost alternative to care administered in other settings with lower testing rates. The similar follow-up rate suggests adequate clinical resolution and that patients are not using virtual visits as a first step before seeking in-person care. Journal of Medical Internet Research
Biowebspin, October 14th, 2016
Innovation without corporate R&D? An analysis of the Italian case and implications for policy
by Pietro MONCADA-PATERNÒ-CASTELLO and Nicola GRASSANO, 2016
This paper analyses the status of private R&D investment in Italy based on a collection of recent evidences and indicates possible policy actions to boost private R&D investment. Our analysis relies on microdata from an unbalanced 10 years’ panel data-set (2004-2013), built using several waves of the European Industrial R&D Investment Scoreboard and on other sources of quantitative and qualitative information (e.g. OECD, ISTAT, EUROSTAT, ERAWATCH Country Report – Italy, 2013, State of the Innovation Union, 2014). We also took into account recent academic literature on the topic. Based on all this, we argue that: i) innovation in firms’ without their engagement in R&D activities is not sustainable in the medium and long term to reach higher levels of innovation, competitiveness and growth; ii) the Italian R&D and innovation (and competitiveness) gap is due to ‘systemic’/structural reasons and thus targeted high quality policies are needed to address these issues; iii) such policy interventions will have little positive impact without comprehensive reform aimed at improving the innovation environment as a whole. Careful design of an ‘innovation strategy’ that includes support for R&D is needed. This strategy should be fine-tuned to tackle the actual specificities of the Italian economic context and its R&D-led innovation difficulties.
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Biowebspin, December 19th, 2016
Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays
by Jonathan Lawson, Rupesh J Robinson-Vyas, Janette P McQuillan, Andy Paterson, Sarah Christie, Matthew Kidza-Griffiths, Leigh-Anne McDuffus, Karwan A Moutasim, Emily C Shaw, Anne E Kiltie, William J Howat, Andrew M Hanby, Gareth J Thomas and Peter Smittenaar in British Journal of Cancer, 2016
Background: Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples. Methods: We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants’ accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. Results: We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (40.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/ EGFR and bladder/p53 samples, respectively). Conclusions: These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains.
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Background: Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market. Objective: The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation). Methods: We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis. Results: The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated. Conclusions: When health care services are delivered online, the market will be more concentrated (known as the “Superstar” effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors. Journal of Medical Internet Research
Background: Analyzing content generated by users of social network sites has been shown to be beneficial across a number of disciplines. Such analysis has revealed the precise behavior of users that details their distinct patterns of engagement. An issue is evident whereby without direct engagement with end users, the reasoning for anomalies can only be the subject of conjecture. Furthermore, the impact of engaging in social network sites on quality of life is an area which has received little attention. Of particular interest is the impact of online social networking on older users, which is a demographic that is specifically vulnerable to social isolation. A review of the literature reveals a lack of knowledge concerning the impact of these technologies on such users and even less is known regarding how this impact varies across different demographics. Objective: The objective of our study was to analyze user interactions and to survey the attitudes of social network users directly, capturing data in four key areas: (1) functional usage, (2) behavioral patterns, (3) technology, and (4) quality of life. Methods: An online survey was constructed, comprising 32 questions. Each question directly related to a research question. Respondents were recruited through a variety of methods including email campaigns, Facebook advertisements, and promotion from related organizations. Results: In total, data was collected from 919 users containing 446 younger and 473 older users. In comparison to younger users, a greater proportion of older users (289/473, 61.1% older vs 218/446, 48.9% younger) (P<.001) stated that Facebook had either a positive or huge impact on their quality of life. Furthermore, a greater percentage of older users strongly agreed that Facebook strengthened their relationship with other people (64/473, 13.5% older vs 40/446, 9.0%younger) (P=.02). In comparison to younger users, a greater proportion of older users had more positive emotions—classified as slightly better or very good—during their engagement with Facebook (186/473, 39.3% older vs 120/446, 26.9% younger) (P<.001). Conclusions: The results reveal that despite engaging at considerably lower rates with significantly fewer connections, older users gain a greater quality-of-life benefit. Results disclose how both cohorts vary in their use, interactions, and rationale for engaging with Facebook. Journal of Medical Internet Research
Background: Suicidal ideation (SI) is a common mental health problem. Variability in intensity of SI over time has been linked to suicidal behavior, yet little is known about the temporal course of SI. Objective: The primary aim was to identify prototypical trajectories of SI in the general population and, secondarily, to examine whether receiving Web-based self-help for SI, psychiatric symptoms, or sociodemographics predicted membership in the identified SI trajectories. Methods: We enrolled 236 people, from the general Dutch population seeking Web-based help for SI, in a randomized controlled trial comparing a Web-based self-help for SI group with a control group. We assessed participants at inclusion and at 2, 4, and 6 weeks. The Beck Scale for Suicide Ideation was applied at all assessments and was included in latent growth mixture modeling analysis to empirically identify trajectories. Results: We identified 4 SI trajectories. The high stable trajectory represented 51.7% (122/236) of participants and was characterized by constant high level of SI. The high decreasing trajectory (50/236, 21.2%) consisted of people with a high baseline SI score followed by a gradual decrease to a very low score. The third trajectory, high increasing (12/236, 5.1%), also had high initial SI score, followed by an increase to the highest level of SI at 6 weeks. The fourth trajectory, low stable (52/236, 22.0%) had a constant low level of SI. Previous attempted suicide and having received Web-based self-help for SI predicted membership in the high decreasing trajectory. Conclusions: Many adults experience high persisting levels of SI, though results encouragingly indicate that receiving Web-based self-help for SI increased membership in a decreasing trajectory of SI.
Journal of Medical Internet Research