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 3.4 for 2014

India thanks Doctors by trending #ThankYouDoctor on twitter

Twitter trends are said to be one of the important methods to sense the mood of the people in social media. In India, #ThankYouDoctor was trending on Twitter, on July 1st 2015. This is a very significant point to note, as social media is usually flooded with more negativity than positivity on several issues, including medical profession. Negativity about medical profession is usually due to an incident or a particular organization. Positivity about medical profession is usually about a particular doctor or a successful operation. The twitter trend on July 1st 2015, to honour all the doctors, comes as a clear message about the public sentiments. It is noteworthy fact that many a doctors are not using twitter when compared to other professionals. The author has not seen such a trend before, on twitter, thanking other professionals the way doctors were thanked on July 1st. It is indeed heartening. India observes National Doctors' Day on July 1st every year on the birthday of Dr Bidhan Chandra Roy. Dr Roy was honoured with the country's highest civilian award, Bharat Ratna,for being a legendary physician and a popular politician from of West Bengal, India.


Thomson Reuters has published the Journal Citation Reports (JCR) with its Journal Impact Factors for 2015. The Journal Impact Factor 2015 is defined as the number of citations in 2014 to the citations to articles published in the previous 2 years (2012-2013), divided by the number of articles published during that time. The Journal Impact Factor is a metric of excellence for a journal, it is not an article-level metric.

The Impact Factor is an increasingly controversial metric due its frequent misuse, e.g. administrators comparing the "raw" impact factor score across disciplines. This disadvantages journals in smaller disciplines such as medical informatics, which traditionally have less citations than for example multidisciplinary or general medicine journals. As one innovation, Thomson Reuters is now ranking journals by quartile (Q1, Q2, Q3, Q4), within their discipline.

While we at JMIR discourage obsession over the journal impact factor (in particular if abused as proxy to assess the quality of individual articles), our ranking in the JCR is an important validation that even as small open access publisher we can compete with journals published by publishing giants.

JMIR continues to be ranked in the first quartile (Q1) in both of it's disciplines, medical informatics (Q1) and health services research (Q1).

However, even these category-specific rankings are sometimes questionable, in particular for multidisciplinary journals such as JMIR which fit into more than the categories selected by the JCR editors. Moreover, the current JCR categories sometimes lump together journals which do not belong together, for example statistics journals are part of the medical informatics category, and oddly enough, the journal Statistical Methods in Medical Research is now suddenly the top-ranked journal in the medical informatics category.

It may therefore make more sense to compare JMIR against other leading multidisciplinary open access journals, as shown below. However, once again, the impact factor should not be the only determining factor when submitting an article. The journal scope and audience (who reads the journal) are equally important if one wants to maximize impact and influence of an article on key stakeholders and researchers, which is not measurable by citations (perhaps better measured with social media uptake and altmetrics).

We continue to encourage our authors to consider the full range of JMIR journals when submitting an article and consider the scope of the journal and the topic of the article.

Quiz: Which of the following #openaccess journals has the highest impact factor:

1) PloS One,

2) PeerJ,


4) BMJ Open,

5) JMIR 

(scroll down for the answer)

Journal Quartile (in their category)   Impact Factor 2015
1. JMIR Q1, Q1 3.428
2. PloS One Q1 3.234
3. BMJ Open Q2 2.271
4. PeerJ Q1 2.112
5. BMC Med Inform Med Dec Mk Q2 1.830

Beyond the Journal Impact Factor

Authors care (and should care) about other metrics/ratings such as author satisfaction with reviews and turnaround times, as for example evaluated by SciRevJMIR is ranked highly here as well (compare for example against PlosOne ratings).

scirev ranking of JMIR vs PlosOne

Other metrics to look at are the twimpact factor (social media impact) as well as post-publication dissemination activies by the publisher (JMIR is using TrendMD to promote published articles across other publishers such as BMJ and the JAMA network).

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  • This image was purchased from Shutterstock. Image ID: 94930510 Copyright: Maryna Pleshkun.

    Allowing Physicians to Choose the Value of Compensation for Participation in a Web-Based Survey: Randomized Controlled Trial


    Background: Survey response rates among physicians are declining, and determining an appropriate level of compensation to motivate participation poses a major challenge. Objective: To estimate the effect of permitting intensive care physicians to select their preferred level of compensation for completing a short Web-based survey on physician (1) response rate, (2) survey completion rate, (3) time to response, and (4) time spent completing the survey. Methods: A total of 1850 US intensivists from an existing database were randomized to receive a survey invitation email with or without an incentive available to the first 100 respondents. The incentive could be instantly redeemed for an amount chosen by the respondent, up to a maximum of US $50. Results: The overall response rate was 35.90% (630/1755). Among the 35.4% (111/314) of eligible participants choosing the incentive, 80.2% (89/111) selected the maximum value. Among intensivists offered an incentive, the response was 6.0% higher (95% CI 1.5-10.5, P=.01), survey completion was marginally greater (807/859, 94.0% vs 892/991, 90.0%; P=.06), and the median number of days to survey response was shorter (0.8, interquartile range [IQR] 0.2-14.4 vs 6.6, IQR 0.3-22.3; P=.001), with no difference in time spent completing the survey. Conclusions: Permitting intensive care physicians to determine compensation level for completing a short Web-based survey modestly increased response rate and substantially decreased response time without decreasing the time spent on survey completion.

  • Screenshot of the Bite Back website.

    A Web-Based Adolescent Positive Psychology Program in Schools: Randomized Controlled Trial


    Background: Adolescent mental health is characterized by relatively high rates of psychiatric disorders and low levels of help-seeking behaviors. Existing mental health programs aimed at addressing these issues in adolescents have repeated inconsistent results. Such programs have generally been based on techniques derived from cognitive behavioral therapy, which may not be ideally suited to early intervention among adolescent samples. Positive psychology, which seeks to improve well-being rather than alleviate psychological symptoms, offers an alternative approach. A previous community study of adolescents found that informal engagement in an online positive psychology program for up to 6 weeks yielded significant improvements in both well-being and depression symptoms. However, this approach had not been trialed among adolescents in a structured format and within a school setting. Objective: This study examines the feasibility of an online school-based positive psychology program delivered in a structured format over a 6-week period utilizing a workbook to guide students through website content and interactive exercises. Methods: Students from four high schools were randomly allocated by classroom to either the positive psychology condition, "Bite Back", or the control condition. The Bite Back condition consisted of positive psychology exercises and information, while the control condition used a series of non-psychology entertainment websites. Both interventions were delivered online for 6 hours over a period of 4-6 weeks during class time. Symptom measures and measures of well-being/flourishing and life satisfaction were administered at baseline and post intervention. Results: Data were analyzed using multilevel linear modeling. Both conditions demonstrated reductions in depression, stress, and total symptom scores without any significant differences between the two conditions. Both the Bite Back and control conditions also demonstrated significant improvements in life satisfaction scores post intervention. However, only the control condition demonstrated significant increases in flourishing scores post intervention. Conclusions: Results suggest that a structured online positive psychology program administered within the school curriculum was not effective when compared to the control condition. The limitations of online program delivery in school settings including logistic considerations are also relevant to the contradictory findings of this study. Clinical Trial: Australian New Zealand Clinical Trials Registry: ACTRN1261200057831; (Archived by Webcite at

  • This is a royalty free image by hywards (

    Secure Cloud-Based Solutions for Different eHealth Services in Spanish Rural Health Centers


    Background: The combination of eHealth applications and/or services with cloud technology provides health care staff—with sufficient mobility and accessibility for them—to be able to transparently check any data they may need without having to worry about its physical location. Objective: The main aim of this paper is to put forward secure cloud-based solutions for a range of eHealth services such as electronic health records (EHRs), telecardiology, teleconsultation, and telediagnosis. Methods: The scenario chosen for introducing the services is a set of four rural health centers located within the same Spanish region. iCanCloud software was used to perform simulations in the proposed scenario. We chose online traffic and the cost per unit in terms of time as the parameters for choosing the secure solution on the most optimum cloud for each service. Results: We suggest that load balancers always be fitted for all solutions in communication together with several Internet service providers and that smartcards be used to maintain identity to an appropriate extent. The solutions offered via private cloud for EHRs, teleconsultation, and telediagnosis services require a volume of online traffic calculated at being able to reach 2 Gbps per consultation. This may entail an average cost of €500/month. Conclusions: The security solutions put forward for each eHealth service constitute an attempt to centralize all information on the cloud, thus offering greater accessibility to medical information in the case of EHRs alongside more reliable diagnoses and treatment for telecardiology, telediagnosis, and teleconsultation services. Therefore, better health care for the rural patient can be obtained at a reasonable cost.

  • Photoaged image of a 17 year old woman showing the consequences of smoking one pack a day for one year (vs. non-smoking).

    Photoaging Mobile Apps: A Novel Opportunity for Smoking Cessation?


    Most smokers start smoking during their early adolescence with the idea that smoking is glamorous; the problems related to lung cancer, vascular disease, and chronic pulmonary disease are too far in the future to fathom. In contrast, most adolescents view their image in a mirror as an important component of their personal life. A recent randomized controlled trial by Burford et al published in the Journal of Medical Internet Research demonstrated an increased quit rate of 21% in 18-30-year-old young adults by the help of photoaging desktop programs, in which an image is altered to predict future appearance [1]. Furthermore, the photoaging software has been shown to increase the motivation of 14-18-year-old females to quit [2]. However, the investigated programs only reach a small audience and are not freely available. We took advantage of the widespread availability of mobile phones and adolescents´ interest in appearance to develop a free mobile phone app which requires the user to take a self portrait (ie, a selfie), which is then displayed by the photoaging software as four images: consequences of (non-)smoking one pack a day for a year (Figure 1) or 15 years (Figure 2). Afterwards, the app explains the visual results and offers many sharing options with family and friends. By this means, the social network of the user may also be informed about the various beauty reducing effects of smoking, potential health consequences, and learn about the app. The underlying aging algorithms take into account the user’s current age and are based on publications showing an increased risk for acne and pale skin due to declined capillary perfusion (after one pack-year), as well as connective tissue changes and wrinkles in the longer term (after 15 pack-years) [3,4]. Unfortunately, the app cannot demonstrate yellowing of teeth. The app has been installed on over 50,000 Android and 27,000 iOS mobile phones within seven months after its release in Germany (10/27/2014 to 4/26/2015). As mobile phone use in Germany declines with age, the largest fraction of the app’s users are assumed to be 30 years or younger. Based on the publication from Burford et al, it is reasonable to speculate that the app could motivate smokers to quit. Taking into account that the smoking prevalence in the general German population is approximately 25% (approximately 19,250 of the 77,000 app users were smokers), about 4000 users (21%) would have quit after using the app. Further research is needed to investigate the effectiveness of app-based photoaging interventions to increase quit rates and to prevent smoking initiation.

  • The It's LiFe! activity monitor and mobile phone app.

    It's LiFe! Mobile and Web-Based Monitoring and Feedback Tool Embedded in Primary Care Increases Physical Activity: A Cluster Randomized Controlled Trial


    Background: Physical inactivity is a major public health problem. The It’s LiFe! monitoring and feedback tool embedded in the Self-Management Support Program (SSP) is an attempt to stimulate physical activity in people with chronic obstructive pulmonary disease or type 2 diabetes treated in primary care. Objective: Our aim was to evaluate whether the SSP combined with the use of the monitoring and feedback tool leads to more physical activity compared to usual care and to evaluate the additional effect of using this tool on top of the SSP. Methods: This was a three-armed cluster randomised controlled trial. Twenty four family practices were randomly assigned to one of three groups in which participants received the tool + SSP (group 1), the SSP (group 2), or care as usual (group 3). The primary outcome measure was minutes of physical activity per day. The secondary outcomes were general and exercise self-efficacy and quality of life. Outcomes were measured at baseline after the intervention (4-6 months), and 3 months thereafter. Results: The group that received the entire intervention (tool + SSP) showed more physical activity directly after the intervention than Group 3 (mean difference 11.73, 95% CI 6.21-17.25; P<.001), and Group 2 (mean difference 7.86, 95% CI 2.18-13.54; P=.003). Three months after the intervention, this effect was still present and significant (compared to Group 3: mean difference 10.59, 95% CI 4.94-16.25; P<.001; compared to Group 2: mean difference 9.41, 95% CI 3.70-15.11; P<.001). There was no significant difference in effect between Groups 2 and 3 on both time points. There was no interaction effect for disease type. Conclusions: The combination of counseling with the tool proved an effective way to stimulate physical activity. Counseling without the tool was not effective. Future research about the cost-effectiveness and application under more tailored conditions and in other target groups is recommended. Trial Registration: NCT01867970, (archived by WebCite at

  • (cc) Frederix et al. CC-BY-SA-2.0, please cite as (

    Medium-Term Effectiveness of a Comprehensive Internet-Based and Patient-Specific Telerehabilitation Program With Text Messaging Support for Cardiac Patients:...


    Background: Cardiac telerehabilitation has been introduced as an adjunct or alternative to conventional center-based cardiac rehabilitation to increase its long-term effectiveness. However, before large-scale implementation and reimbursement in current health care systems is possible, well-designed studies on the effectiveness of this new additional treatment strategy are needed. Objective: The aim of this trial was to assess the medium-term effectiveness of an Internet-based, comprehensive, and patient-tailored telerehabilitation program with short message service (SMS) texting support for cardiac patients. Methods: This multicenter randomized controlled trial consisted of 140 cardiac rehabilitation patients randomized (1:1) to a 24-week telerehabilitation program in combination with conventional cardiac rehabilitation (intervention group; n=70) or to conventional cardiac rehabilitation alone (control group; n=70). In the telerehabilitation program, initiated 6 weeks after the start of ambulatory rehabilitation, patients were stimulated to increase physical activity levels. Based on registered activity data, they received semiautomatic telecoaching via email and SMS text message encouraging them to gradually achieve predefined exercise training goals. Patient-specific dietary and/or smoking cessation advice was also provided as part of the telecoaching. The primary endpoint was peak aerobic capacity (VO2 peak). Secondary endpoints included accelerometer-recorded daily step counts, self-assessed physical activities by International Physical Activity Questionnaire (IPAQ), and health-related quality of life (HRQL) assessed by the HeartQol questionnaire at baseline and at 6 and 24 weeks. Results: Mean VO2 peak increased significantly in intervention group patients (n=69) from baseline (mean 22.46, SD 0.78 mL/[min*kg]) to 24 weeks (mean 24.46, SD 1.00 mL/[min*kg], P<.01) versus control group patients (n=70), who did not change significantly (baseline: mean 22.72, SD 0.74 mL/[min*kg]; 24 weeks: mean 22.15, SD 0.77 mL/[min*kg], P=.09). Between-group analysis of aerobic capacity confirmed a significant difference between the intervention group and control group in favor of the intervention group (P<.001). At 24 weeks, self-reported physical activity improved more in the intervention group compared to the control group (P=.01) as did the global HRQL score (P=.01). Conclusions: This study showed that an additional 6-month patient-specific, comprehensive telerehabilitation program can lead to a bigger improvement in both physical fitness (VO2 peak) and associated HRQL compared to center-based cardiac rehabilitation alone. These results are supportive in view of possible future implementation in standard cardiac care.

  • This image is from the public domain.

    Online Recruitment Methods for Web-Based and Mobile Health Studies: A Review of the Literature


    Background: Internet and mobile health (mHealth) apps hold promise for expanding the reach of evidence-based health interventions. Research in this area is rapidly expanding. However, these studies may experience problems with recruitment and retention. Web-based and mHealth studies are in need of a wide-reaching and low-cost method of recruitment that will also effectively retain participants for the duration of the study. Online recruitment may be a low-cost and wide-reaching tool in comparison to traditional recruitment methods, although empirical evidence is limited. Objective: This study aims to review the literature on online recruitment for, and retention in, mHealth studies. Methods: We conducted a review of the literature of studies examining online recruitment methods as a viable means of obtaining mHealth research participants. The data sources used were PubMed, CINAHL, EbscoHost, PyscINFO, and MEDLINE. Studies reporting at least one method of online recruitment were included. A narrative approach enabled the authors to discuss the variability in recruitment results, as well as in recruitment duration and study design. Results: From 550 initial publications, 12 studies were included in this review. The studies reported multiple uses and outcomes for online recruitment methods. Web-based recruitment was the only type of recruitment used in 67% (8/12) of the studies. Online recruitment was used for studies with a variety of health domains: smoking cessation (58%; 7/12) and mental health (17%; 2/12) being the most common. Recruitment duration lasted under a year in 67% (8/12) of the studies, with an average of 5 months spent on recruiting. In those studies that spent over a year (33%; 4/12), an average of 17 months was spent on recruiting. A little less than half (42%; 5/12) of the studies found Facebook ads or newsfeed posts to be an effective method of recruitment, a quarter (25%; 3/12) of the studies found Google ads to be the most effective way to reach participants, and one study showed better outcomes with traditional (eg in-person) methods of recruitment. Only one study recorded retention rates in their results, and half (50%; 6/12) of the studies recorded survey completion rates. Conclusions: Although online methods of recruitment may be promising in experimental research, more empirical evidence is needed to make specific recommendations. Several barriers to using online recruitment were identified, including participant retention. These unique challenges of virtual interventions can affect the generalizability and validity of findings from Web-based and mHealth studies. There is a need for additional research to evaluate the effectiveness of online recruitment methods and participant retention in experimental mHealth studies.

  • (c) Care Innovations.

    Overcoming Clinical Inertia: A Randomized Clinical Trial of a Telehealth Remote Monitoring Intervention Using Paired Glucose Testing in Adults With Type 2...


    Background: Type 2 diabetes mellitus is a worldwide challenge. Practice guidelines promote structured self-monitoring of blood glucose (SMBG) for informing health care providers about glycemic control and providing patient feedback to increase knowledge, self-efficacy, and behavior change. Paired glucose testing—pairs of glucose results obtained before and after a meal or physical activity—is a method of structured SMBG. However, frequent access to glucose data to interpret values and recommend actions is challenging. A complete feedback loop—data collection and interpretation combined with feedback to modify treatment—has been associated with improved outcomes, yet there remains limited integration of SMBG feedback in diabetes management. Incorporating telehealth remote monitoring and asynchronous electronic health record (EHR) feedback from certified diabetes educators (CDEs)—specialists in glucose pattern management—employ the complete feedback loop to improve outcomes. Objective: The purpose of this study was to evaluate a telehealth remote monitoring intervention using paired glucose testing and asynchronous data analysis in adults with type 2 diabetes. The primary aim was change in glycated hemoglobin (A1c)—a measure of overall glucose management—between groups after 6 months. The secondary aims were change in self-reported Summary of Diabetes Self-Care Activities (SDSCA), Diabetes Empowerment Scale, and Diabetes Knowledge Test. Methods: A 2-group randomized clinical trial was conducted comparing usual care to telehealth remote monitoring with paired glucose testing and asynchronous virtual visits. Participants were aged 30-70 years, not using insulin with A1c levels between 7.5% and 10.9% (58-96 mmol/mol). The telehealth remote monitoring tablet computer transmitted glucose data and facilitated a complete feedback loop to educate participants, analyze actionable glucose data, and provide feedback. Data from paired glucose testing were analyzed asynchronously using computer-assisted pattern analysis and were shared with patients via the EHR weekly. CDEs called participants monthly to discuss paired glucose testing trends and treatment changes. Separate mixed-effects models were used to analyze data. Results: Participants (N=90) were primarily white (64%, 56/87), mean age 58 (SD 11) years, mean body mass index 34.1 (SD 6.7) kg/m2, with diabetes for mean 8.2 (SD 5.4) years, and a mean A1c of 8.3% (SD 1.1; 67 mmol/mol). Both groups lowered A1c with an estimated average decrease of 0.70 percentage points in usual care group and 1.11 percentage points in the treatment group with a significant difference of 0.41 percentage points at 6 months (SE 0.08, t159=–2.87, P=.005). Change in medication (SE 0.21, t157=–3.37, P=.009) was significantly associated with lower A1c level. The treatment group significantly improved on the SDSCA subscales carbohydrate spacing (P=.04), monitoring glucose (P=.001), and foot care (P=.02). Conclusions: An eHealth model incorporating a complete feedback loop with telehealth remote monitoring and paired glucose testing with asynchronous data analysis significantly improved A1c levels compared to usual care. Trial Registration: NCT01715649; (Archived by WebCite at

  • Source:  Tony Alter, Licensed under cc-by 2.0.

    Evaluation of Internet-Based Interventions on Waist Circumference Reduction: A Meta-Analysis


    Background: Internet-based interventions are more cost-effective than conventional interventions and can provide immediate, easy-to-access, and individually tailored support for behavior change. Waist circumference is a strong predictor of an increased risk for a host of diseases, such as hypertension, diabetes, and dyslipidemia, independent of body mass index. To date, no study has examined the effect of Internet-based lifestyle interventions on waist circumference change. Objective: This study aimed to systematically review the effect of Internet-based interventions on waist circumference change among adults. Methods: This meta-analysis reviewed randomized controlled trials (N=31 trials and 8442 participants) that used the Internet as a main intervention approach and reported changes in waist circumference. Results: Internet-based interventions showed a significant reduction in waist circumference (mean change –2.99 cm, 95% CI −3.68 to −2.30, I2=93.3%) and significantly better effects on waist circumference loss (mean loss 2.38 cm, 95% CI 1.61-3.25, I2=97.2%) than minimal interventions such as information-only groups. Meta-regression results showed that baseline waist circumference, gender, and the presence of social support in the intervention were significantly associated with waist circumference reduction. Conclusions: Internet-based interventions have a significant and promising effect on waist circumference change. Incorporating social support into an Internet-based intervention appears to be useful in reducing waist circumference. Considerable heterogeneity exists among the effects of Internet-based interventions. The design of an intervention may have a significant impact on the effectiveness of the intervention.

  • EBM library guide. Screenshot of

    A Cost-Effectiveness Analysis of Blended Versus Face-to-Face Delivery of Evidence-Based Medicine to Medical Students


    Background: Blended learning describes a combination of teaching methods, often utilizing digital technologies. Research suggests that learner outcomes can be improved through some blended learning formats. However, the cost-effectiveness of delivering blended learning is unclear. Objective: This study aimed to determine the cost-effectiveness of a face-to-face learning and blended learning approach for evidence-based medicine training within a medical program. Methods: The economic evaluation was conducted as part of a randomized controlled trial (RCT) comparing the evidence-based medicine (EBM) competency of medical students who participated in two different modes of education delivery. In the traditional face-to-face method, students received ten 2-hour classes. In the blended learning approach, students received the same total face-to-face hours but with different activities and additional online and mobile learning. Online activities utilized YouTube and a library guide indexing electronic databases, guides, and books. Mobile learning involved self-directed interactions with patients in their regular clinical placements. The attribution and differentiation of costs between the interventions within the RCT was measured in conjunction with measured outcomes of effectiveness. An incremental cost-effectiveness ratio was calculated comparing the ongoing operation costs of each method with the level of EBM proficiency achieved. Present value analysis was used to calculate the break-even point considering the transition cost and the difference in ongoing operation cost. Results: The incremental cost-effectiveness ratio indicated that it costs 24% less to educate a student to the same level of EBM competency via the blended learning approach used in the study, when excluding transition costs. The sunk cost of approximately AUD $40,000 to transition to the blended model exceeds any savings from using the approach within the first year of its implementation; however, a break-even point is achieved within its third iteration and relative savings in the subsequent years. The sensitivity analysis indicates that approaches with higher transition costs, or staffing requirements over that of a traditional method, are likely to result in negative value propositions. Conclusions: Under the study conditions, a blended learning approach was more cost-effective to operate and resulted in improved value for the institution after the third year iteration, when compared to the traditional face-to-face model. The wider applicability of the findings are dependent on the type of blended learning utilized, staffing expertise, and educational context.

  • Image credit: Dave Di Biase/Freeimages,

    Characterizing the Processes for Navigating Internet Health Information Using Real-Time Observations: A Mixed-Methods Approach


    Background: Little is known about the processes people use to find health-related information on the Internet or the individual characteristics that shape selection of information-seeking approaches. Objective: Our aim was to describe the processes by which users navigate the Internet for information about a hypothetical acute illness and to identify individual characteristics predictive of their information-seeking strategies. Methods: Study participants were recruited from public settings and agencies. Interested individuals were screened for eligibility using an online questionnaire. Participants listened to one of two clinical scenarios—consistent with influenza or bacterial meningitis—and then conducted an Internet search. Screen-capture video software captured Internet search mouse clicks and keystrokes. Each step of the search was coded as hypothesis testing (etiology), evidence gathering (symptoms), or action/treatment seeking (behavior). The coded steps were used to form a step-by-step pattern of each participant’s information-seeking process. A total of 78 Internet health information seekers ranging from 21-35 years of age and who experienced barriers to accessing health care services participated. Results: We identified 27 unique patterns of information seeking, which were grouped into four overarching classifications based on the number of steps taken during the search, whether a pattern consisted of developing a hypothesis and exploring symptoms before ending the search or searching an action/treatment, and whether a pattern ended with action/treatment seeking. Applying dual-processing theory, we categorized the four overarching pattern classifications as either System 1 (41%, 32/78), unconscious, rapid, automatic, and high capacity processing; or System 2 (59%, 46/78), conscious, slow, and deliberative processing. Using multivariate regression, we found that System 2 processing was associated with higher education and younger age. Conclusions: We identified and classified two approaches to processing Internet health information. System 2 processing, a methodical approach, most resembles the strategies for information processing that have been found in other studies to be associated with higher-quality decisions. We conclude that the quality of Internet health-information seeking could be improved through consumer education on methodical Internet navigation strategies and the incorporation of decision aids into health information websites.

  • (cc) Levy et al. CC-BY-SA-2.0, please cite as (

    The Mobile Insulin Titration Intervention (MITI) for Insulin Adjustment in an Urban, Low-Income Population: Randomized Controlled Trial


    Background: Diabetes patients are usually started on a low dose of insulin and their dose is adjusted or “titrated” according to their blood glucose levels. Insulin titration administered through face-to-face visits with a clinician can be time consuming and logistically burdensome for patients, especially those of low socioeconomic status (SES). Given the wide use of mobile phones among this population, there is the potential to use short message service (SMS) text messaging and phone calls to perform insulin titration remotely. Objective: The goals of this pilot study were to (1) evaluate if our Mobile Insulin Titration Intervention (MITI) intervention using text messaging and phone calls was effective in helping patients reach their optimal insulin glargine dose within 12 weeks, (2) assess the feasibility of the intervention within our clinic setting and patient population, (3) collect data on the cost savings associated with the intervention, and (4) measure patient satisfaction with the intervention. Methods: This was a pilot study evaluating an intervention for patients requiring insulin glargine titration in the outpatient medical clinic of Bellevue Hospital Center in New York City. Patients in the intervention arm received weekday SMS text messages from a health management platform requesting their fasting blood glucose values. The clinic’s diabetes nurse educator monitored the texted responses on the platform website each weekday for alarm values. Once a week, the nurse reviewed the glucose values, consulted the MITI titration algorithm, and called patients to adjust their insulin dose. Patients in the usual care arm continued to receive their standard clinic care for insulin titration. The primary outcome was whether a patient reached his/her optimal insulin glargine dose within 12 weeks. Results: A total of 61 patients consented and were randomized into the study. A significantly greater proportion of patients in the intervention arm reached their optimal insulin glargine dose than patients in the usual care arm (88%, 29/33 vs 37%, 10/27; P<.001). Patients responded to 84.3% (420/498) of the SMS text messages requesting their blood glucose values. The nurse reached patients within 2 attempts or by voicemail 91% of the time (90/99 assigned calls). When patients traveled to the clinic, they spent a median of 45 minutes (IQR 30-60) on travel and 39 minutes (IQR 30-64) waiting prior to appointments. A total of 61% (37/61) of patients had appointment copays. After participating in the study, patients in the intervention arm reported higher treatment satisfaction than those in the usual care arm. Conclusions: MITI is an effective way to help low-SES patients reach their optimal insulin glargine dose using basic SMS text messaging and phone calls. The intervention was feasible and patients were highly satisfied with their treatment. The intervention was cost saving in terms of time for patients, who were able to have their insulin titrated without multiple clinic appointments. Similar interventions should be explored to improve care for low-SES patients managing chronic disease. Trial Registration: NCT01879579; (Archived by WebCite at

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  • India thanks Doctors by trending #ThankYouDoctor on twitter

    Date Submitted: Jul 24, 2015

    Open Peer Review Period: Jul 28, 2015 - Sep 22, 2015

    Twitter trends are said to be one of the important methods to sense the mood of the people in social media. In India, #ThankYouDoctor was trending on Twitter, on July 1st 2015. This is a very signif...

    Twitter trends are said to be one of the important methods to sense the mood of the people in social media. In India, #ThankYouDoctor was trending on Twitter, on July 1st 2015. This is a very significant point to note, as social media is usually flooded with more negativity than positivity on several issues, including medical profession. Negativity about medical profession is usually due to an incident or a particular organization. Positivity about medical profession is usually about a particular doctor or a successful operation. The twitter trend on July 1st 2015, to honour all the doctors, comes as a clear message about the public sentiments. It is noteworthy fact that many a doctors are not using twitter when compared to other professionals. The author has not seen such a trend before, on twitter, thanking other professionals the way doctors were thanked on July 1st. It is indeed heartening. India observes National Doctors' Day on July 1st every year on the birthday of Dr Bidhan Chandra Roy. Dr Roy was honoured with the country's highest civilian award, Bharat Ratna,for being a legendary physician and a popular politician from of West Bengal, India.

  • Translation of Evidence into a mHealth Chronic Disease Platform Supporting Mobile App Design

    Date Submitted: Jul 28, 2015

    Open Peer Review Period: Jul 28, 2015 - Sep 22, 2015

    Background: A design structure, process and tools are important to translate clinical and behavioral evidence, user interface, experience design and technical capabilities into scalable, replicable, e...

    Background: A design structure, process and tools are important to translate clinical and behavioral evidence, user interface, experience design and technical capabilities into scalable, replicable, evidence–based mobile health (mHealth) solutions to drive outcomes. Objective: This paper proposes an approach for systematic design of different types of mHealth apps to facilitate delivery of interventions and evaluation of mobile technologies to answer the questions of when, where and for whom mHealth apps are effective in the real-world. Methods: The process of developing the platform and its frameworks was conducted between June 2012 and June 2014. Informed by clinical guidelines, standards of care, clinical practice recommendations, evidence-based research, best practices and translated by subject matter experts, the mobile strategic framework (mSF) and mobile integrated clinical behavioral framework (mICBF) were developed. Application and refinement of the frameworks across three implementation models allowed for development of the mobile chronic disease platform (mCDP). Results: One platform, its two corresponding frameworks, and its application to seven chronic diseases across three implementation models are described. The platform is the design structure that enables replicable product development. The frameworks allowed for the integration of clinical and behavioral evidence for intervention and feature design. The application to different diseases and implementation models allowed for designing mHealth solutions to support varying levels of chronic disease management. Conclusions: As a result, a comprehensive ontology and associated taxonomies, cataloging the critical components of integrated clinical and behavioral mHealth solution design, was developed to support consistent product development. Implications for policy, practice and research for chronic disease management are discussed.

  • Online prediction of the future 6-month healthcare utilization in Maine State: a prospective patient study

    Date Submitted: Jul 24, 2015

    Open Peer Review Period: Jul 24, 2015 - Sep 18, 2015

    Background: The increasing rate of healthcare expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future healthcare utilization of patients can prov...

    Background: The increasing rate of healthcare expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future healthcare utilization of patients can provide useful information to better understand and manage overall healthcare deliveries and clinical resource allocation. Objective: This study developed an EMR-based (electronic-medical-record-based) online risk model predictive of future 6-month resource utilization for patients in Maine, across all payers, all diseases and all demographic groups. Methods: In the HealthInfoNet (HIN), Maine’s Health Information Exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient’s future 6-month (between January 1, 2013 and June 30, 2013) healthcare resource utilization was retrospectively scored ranging from 0 to 100, and a decision-tree based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their future 6-month risks of resource utilization between July 1, 2013 and December 31, 2013. Results: Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the future 6-month resource utilization distributions as well as the clinical patterns at the population level. A case study demonstrating the strong correlation between its care resource utilization and our risk scores supports the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and care-givers in the State of Maine. Conclusions: The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for healthcare resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

  • Personal Health Record Use in the U.S.: Forecasting Future Adoption Levels

    Date Submitted: Jul 23, 2015

    Open Peer Review Period: Jul 24, 2015 - Sep 18, 2015

    Background: PHRs offer a tremendous opportunity to generate consumer support in pursing the triple aim of reducing costs, increasing access, and improving care quality. Moreover, surveys indicate that...

    Background: PHRs offer a tremendous opportunity to generate consumer support in pursing the triple aim of reducing costs, increasing access, and improving care quality. Moreover, surveys indicate that consumers want online access to their medical records. However, concerns that consumers’ low health information literacy levels and physicians’ resistance to sharing notes will limit PHRs utility to a relatively small portion of the population have reduced both the product innovation and policy imperatives. Objective: The purpose of this study is threefold. First, to report on consumers’ current level of Personal Health Record (PHR) activity; second, we describe the imitation and innovation influence factors roles in determining PHR adoption rates, and; third, we forecast future PHR diffusion uptake among U.S. consumers under three scenarios. Methods: Secondary data from the Health Information National Tracking Survey (HINTS: Survey Years: 2008, 2011, and 2013) of U.S. citizens are used. Applying technology diffusion theory and Bass modeling, we evaluate three future PHR adoption scenarios by varying the introduction dates. Results: All models display the characteristic diffusion S-curve indicative that the PHR technology is likely to achieve significant market penetration ahead of MU goals. The best performing model indicates that PHR adoption will exceed 75 percent by 2020. Therefore, the MU program targets for PHR adoption are below the rates likely to occur without an intervention. Conclusions: The promise of improved care quality and cost savings through better consumer engagement prompted the Institute of Medicine to call for universal PHR adoption in 1999. The PHR products available as of 2014 are likely to meet and exceed MU Stage 3 targets prior to 2020 without any incentive. Therefore, more ambitious uptake and functionality availability should be incorporated into future goals. Clinical Trial: N/A

  • Communication and value of virtual peer support: An explorative study of virtual community threads about prenatal diagnoses of fetal anomalies

    Date Submitted: Jul 18, 2015

    Open Peer Review Period: Jul 24, 2015 - Sep 18, 2015

    Background: A prenatal diagnosis of a fetal anomaly during pregnancy triggers psychological distress. The Internet has the potential to provide virtual support following the diagnosis. Objective: The...

    Background: A prenatal diagnosis of a fetal anomaly during pregnancy triggers psychological distress. The Internet has the potential to provide virtual support following the diagnosis. Objective: The overall aim was to explore how Swedish posters communicate in threads about prenatal diagnoses of fetal anomalies. The following research questions were addressed: 1) How is affirmational, emotional, informational and instrumental virtual support communicated and how is it distributed among posters with different backgrounds, 2) How is appreciation of virtual support distributed among posters with differents backgrounds and how is the value of the support described, 3) What reactions are expressed regarding the decision to continue or terminate the pregnancy and how do others respond to these reactions? Methods: Following searches on, 117 threads from three host websites were identified. By purposeful sampling, 15 were included, involving 349 posters, of which 176/349 (50.4%) presented experience of congenital anomalies. The majority of the posters presented themselves as females (n=229/349, 65.6%) and one (0.3%) as a male. Content analysis was used to categorize meaning units that described and interpreted patterns in the data. Identified meaning units were analyzed using descriptive statistics. Results: The virtual support, described as comforting and empowering, included mainly emotional (meaning units n=1,992/3,688, 54.0%) support. Informational (meaning units n=812/3,688, 22.0%) and affirmational (meaning units n=807/3,688, 21.9%) were also expressed, whereas instrumental support was expressed less frequently (meaning units n=77/3,688, 2.1%). Posters with experience of a prenatal diagnosis appreciated the virtual support (meaning units n=325), including the opportunity to gain insight into other cases, which eased loneliness, and to write about one’s own experience. Critique of the decision to continue or terminate the pregnancy was identified (meaning units n=36), primarily toward termination of pregnancy (meaning units n=30/36, 83.3%), which was met with defence (meaning units n=142). The norm in the threads was to not question the decision to continue or terminate the pregnancy. Conclusions: Virtual communities mainly provide emotional support, but also affirmational and informational support and are described as being appreciated and beneficial for women writing in the threads. The threads provide an allowing and protective environment where the decision to continue or terminate the pregnancy is not to be questioned. It could be hypothesized that virtual peer support facilitates psychosocial function following the diagnosis. However, this needs to be investigated in future experimental and longitudinal studies.

  • Do Patients Treated for Colorectal Cancer Benefit from General Practitioner Support? A Video Vignette Study

    Date Submitted: Jul 17, 2015

    Open Peer Review Period: Jul 24, 2015 - Sep 18, 2015

    Background: Introduction Colorectal cancer is the second most commonly diagnosed adult cancer in Australia [1]. One in 12 people in Australia will develop colorectal cancer in their lifetime [2]. Mos...

    Background: Introduction Colorectal cancer is the second most commonly diagnosed adult cancer in Australia [1]. One in 12 people in Australia will develop colorectal cancer in their lifetime [2]. Most people with colorectal cancer survive more than five years and die of unrelated causes [3]. The treatment of colorectal cancer may include surgery, radiotherapy, and chemotherapy. In the months and years following treatment, people may experience a number of troublesome side effects or symptoms and signs related to cancer recurrence. Many patients may experience bowel dysfunction, sexual dysfunction, urinary dysfunction and fatigue, among other difficulties [4]. Post-treatment follow-up is provided in secondary settings in some instances; however, this follow-up may only be for a short period of time for some patients, after which they are encouraged to see their GP about any ongoing problems [5]. Previous studies have demonstrated that cancer patients consult a GP routinely in the months and years after treatment for colorectal cancer, even for patients with scheduled follow-up visits at the hospital [6]. Colorectal cancer patients may contact their GP for a range of symptoms, such as radiation proctitis, urinary incontinence/urgency, fatigue, erectile dysfunction and symptoms of recurrence [7]. In order to address the needs of patients treated for colorectal cancer, the GP needs to be knowledgeable about the recommended treatment for side effects of colorectal cancer treatment and the signs and symptoms that merit referral for further specialist treatment. Objective: In this pilot video vignette study, we aim to explore the impact of a variety of clinical and respondent characteristics of GPs’ decisions to treat colorectal cancer patients experiencing treatment side effects or symptoms of recurrence of their cancer. Methods: Methods Participants Ethics approval was obtained from the Curtin Human Research Ethics Committee (HR 42/2012). Participants were then recruited from a network of 100 GPs across Australia. GPs were emailed invitations and the initial emails were supplemented with follow-up personal invitations to the invitees who did not initially respond. Participants were remunerated with AUD $50 for their contribution. Video Vignettes Six video vignettes were developed, each presenting a potential side effect related to treatment for colorectal cancer or features of cancer recurrence (see multimedia Appendix 1 for an example). The range of scenarios was based on the most common side effects reported by colorectal cancer patients (see Appendix 2). The identification and validation of these side effects was reported in a different phase of this project [8]. Each vignette depicted a patient with clear indications for specific management, including referral, prescription, reassurance, and/or investigation. The vignettes were developed by four GPs, a radiation therapist, a medical oncologist and a surgeon. This expert panel also suggested the management of each case, with details of prescription, referral for specialist treatment and laboratory investigations (see Appendix 3). The vignettes were then prepared as a short video monologue by an actor-patient. The video included an off-camera commentary by an actor-doctor describing relevant signs to be found on clinical examination. Participation in the study was via the internet. Information on the actor-patient’s medical history, family history, medication history and physical assessment were offered at the onset of each video. Participants were asked four questions after watching each video vignette: (1) ‘What is your diagnosis?’ (2) ‘Would you prescribe something? If so, what would you prescribe?’ (3) ‘Would you refer the patient? If so, to whom?’, and (4) ‘Would you order tests? If so, which tests?’ Sample Size and Statistical Analysis The main aim of this study was to evaluate the treatment GPs offer to standardised patients presenting with side effects of colorectal cancer treatment or symptoms of recurrence. Each GP reviewed the same set of six video vignettes and responded to the four binary (Yes/No response) questions above regarding their diagnosis, prescription of medication, referral for further treatment or ordering of tests. Each of these four questions was analysed in a separate General Estimating Equation (GEE) model, with the binary response as the dependent variable, and the subject named as the random effect. The GEE model is appropriate to this design as it takes into account the correlation between responses from the same GP across the six vignettes. The estimated sample size required to give adequate power to detect associations with the independent variables is difficult to estimate, but depends on the expected response proportions (proportions of positive responses) and the correlations between responses belonging to the same respondent. In the absence of pilot data on which these quantities might have been estimated, a sample of 40 GPs was sought (who would provide 240 observations in total). This projected number cannot be mathematically justified in the absence of pilot data. However, in a standard regression model, a sample of 120 uncorrelated measurements should be adequate to identify an independent variable exhibiting a moderate effect size with 80% power [9]. It was assumed that doubling the number of observations would be adequate to compensate for the internal correlations in the dataset. Each of the GEE models initially included the following independent variables: age, years of GP experience, recognised speciality qualification with the Royal Australian College of General Practitioners (FRACGP), number of patients consultations per week and patient consultations hours per week. A backwards elimination method was used to arrive at the final model. This method involved dropping the least significant variable, one at a time, until all variables remaining in the model were significantly associated with the outcome. SPSS Version 21 software was used to perform the analysis. Following convention, a p-value <0.05 was taken to indicate a statistically significant association in all tests. Results: Results Demographics In total, 52 general practitioners consented to participate in the project, and 40 GPs completed the study. Those who participated in the study were younger than Australian GPs generally (mean age 36.9 years vs 50.5 years), and a greater proportion were females (58% vs 39.1%). The demographic details of the respondents are shown in Table 1. Table 1: Participant demographic information (N=52) Characteristics Study sample National populationa Mean / % Demographics Age (years), mean (SD) 36.9 (10.5) 50.5 Years of GP experience, mean (SD) 7.0 (9.7) Gender, n (%) Male 22 (42) 60.9 Female 30 (58) 39.1 Registrars (GPs in training), n (%) 17(32.7) 3.8 FRACGP, n (%) 28 (53.8) 56.8 Practice demographics Practice accredited, n (%) 52(100%) 88.6 Clinic remoteness, n (%) Major city 36 (69.2) 71.1 Non-major city 16 (30.8) 28.9 Clinic location, n (%)b Capital 27 (51.9) Other metropolitan 14 (26.9) Large rural 6 (11.5) Small rural 4 (7.7) Remote centre 1(1.9) GP position in the practice, n (%) Principal 8 (15.4) Non-principal 35 (67.3) Others 9 (17.3) Patient consultations Patient consultations per week, n (%) <100 22 (42.3) 100–149 21(40.4) ≥150 9 (17.3) Patient consultations hours per week, n (%) <11 10 (19.2) 1.2 11–20 4 (7.7) 12.2 21–40 24 (46.2) 53 41–60 14 (26.9) 33.5 Non-English consultations, n (%) No 45(86.5) Yes, <25% 7 (13.5) 24.5 aSourced from national data when available [18] bClassification based on Rural, Remote and Metropolitan Area classification (RRMA) [19] Diagnosis Consistent with Expert Opinion The colorectal cancer video vignettes were presented 240 times in the study (40 GPs x 6 vignettes). Of the 240 diagnoses made by the GPs, an average of 70% (range 35–95%) were consistent with the expert diagnosis. This consistency was observed more for erectile dysfunction (38/40, 95%), peripheral neuropathy (36/40, 90%) and tumour recurrence (31/40, 76%), compared to urinary dysfunction (23/40, 58%) and cancer-related fatigue (14/40, 35%). A higher proportion of correct diagnoses were made by GPs who worked more than 60 patient care hours per week (15/18, 83%), those who held a GP fellowship (101/138, 73%), and those who had less than 10 years of experience (1–2 years 71/96, 74%; 3–10 years 53/72, 74%). A multivariate GEE analysis was carried out to determine whether a correct diagnosis depended on the case itself, or characteristics of the GP. There were some statistically significant differences in the diagnosis of the cases. Compared to radiation proctitis, GPs were more likely to identify cases with chemotherapy-induced peripheral neuropathy [OR 4.43, 95% CI 1.41–13.96, p=0.01] or erectile dysfunction [OR 9.70, 95% CI 2.48–38.03, p=0.001], but were less likely to recognise chemotherapy-induced fatigue [OR 0.19, 95% CI 0.08–0.44, p=0001]. Also, younger GPs (<30 years of age) [OR 2.64, 95% CI 1.12–6.22, p=0.03] and those who held a GP fellowship [OR 3.26, 95% CI 1.62–6.62, p=0.000] were more likely to identify cases consistent with the expert opinion. The demographic characteristics of the GP did not have any significant influence on their ability to recognise colorectal cancer treatment side effects or symptoms of recurrence. Details of the factors associated with correct diagnosis are displayed in Table 2. Table 2: Factors associated with correct diagnosis (consistent with expert opinion) Outcome Variable n/N (%) Odds ratio 95% CI p-value Diagnosis Age 31 or older 103/156 (66) 1 (reference) 30 or younger 67/84 (80) 2.64 1.12–6.22 0.0262 Years of practice 1–5 101/132 (77) 1 (reference) 5 or more 69/108 (64) 0.42 0.20–0.87 0.0189 GP holds a fellowship No 69/102 (68) 1 (reference) Yes 101/138 (73) 3.26 1.62–6.54 0.0009 Case vignette <0.0001* 1: Peripheral neuropathy 36/40 (90) 4.43 1.41–13.96 0.0110 2: Erectile dysfunction 38/40 (95) 9.70 2.48–38.03 0.0011 3: Urinary dysfunction 23/40 (58) 0.54 0.20–1.46 0.2227 4: Tumour recurrence 31/40 (78) 1.55 0.48–5.06 0.4663 5: Cancer-related fatigue 14/40 (35) 0.19 0.08–0.44 0.0001 6: Radiation proctitis 28/40 (70) 1 (reference) *p-value for the variable as a whole. Note: the dependent variable was a correct response. For example, in the first analysis, respondents who were aged 30 or younger were significantly more likely (OR 2.64) to give a correct diagnosis than the older participants. The numbers in the third column show the number and percentage of correct responses within the group defined by the row. For example, 80% of the diagnoses from people aged 30 or under were correct, vs 66% for the older group. Management Consistent with Expert Opinion Management of the cases according to the expert opinion was categorised into three domains: 1) refer, 2) prescribe and 3) order tests. Refer Only five of the six cases were deemed by the experts to require referral. The analysis of this variable used only the records relating to these vignettes (n=200 observations), as it was far more important that the GP should refer when a referral was considered important than they should do so when it was considered unimportant. Of these 200 observations, only 43% (range 18–60%) were consistent with the expert opinion (so 57% did not refer, when it was considered appropriate to do so). This inconsistency occurred more frequently for the cases of erectile dysfunction, radiation proctitis and peripheral neuropathy, with only18% (7/40), 36 % (15/40) and 43% (17/40) of these cases correctly referred, respectively. Similarly, only 38% (15/40) of the referrals made by GPs who worked more than 60 patient care hours per week and 33% (26/80) of those made by GPs who had 1–2 years of experience were consistent with expert opinion. The results of the regression analysis revealed that the number of patient contact hours done by a GP per week and years of practice influenced GPs’ decisions to refer. Compared to GPs who worked up to 40 hours, GPs who worked more than 40 hours per week were more likely [OR 0.38, 95% CI 0.17–0.84, p=0.02] to refer the patient, in agreement with the expert opinion. GPs with 1 year of experience [OR 0.30, 95% CI 0.13–0.66, p=0.003] were less likely to refer according to expert opinion. Details of the factors associated with correct referrals are displayed in Table 3. Prescribe Of the 160 observations made by the GPs to correctly prescribe, only 39% (range 29-70%) of the prescriptions were consistent with the expert opinion. The only cases with higher proportion of GPs who gave prescriptions that were consistent with expert opinion were, erectile dysfunction (28/40, 70%). The results of the regression analysis show that, compared to radiation proctitis, GPs were more likely to offer a prescription for erectile dysfunction that was consistent with expert opinion [OR 1.27 95% CI 0.47-3.42, p=0.63]. However this association was not statistically significant Details of the factors associated with correct prescription are displayed in Table 3. Order tests Of the 160 observations made by the GPs to order tests, at least 50% were consistent with the expert opinion (average 36, range 10–85%). This consistency was observed more for chemotherapy-induced fatigue (33/40, 83%) and tumour recurrence (32/40, 80%) compared to radiation proctitis (4/40, 10%) and urinary dysfunction (16/40, 40%). Sixty-four per cent (23/36) of tests ordered by GPs who had more than 150 patient consultations per week [OR 2.48, 95% CI 1.16–5.30, p=0.02] were consistent with the expert opinion. Regression analysis results showed that compared ordering tests for radiation proctitis, GPs were more likely to order tests for urinary dysfunction [OR 6.33, 95% CI 1.58–25.42, p=0.01], tumour recurrence [OR 40.02, 95% CI 10.29–155.68, p<0.001] and chemotherapy-induced fatigue [OR 47.29, 95% CI 11.47–195.00, p<0.001]. Details of the factors associated with correct ordering of tests by GPs are displayed in Table 3.   Table 3: Factors associated with management that is consistent with expert opinion Outcome Variable n/N (%) Odds ratio 95% CI p-value Prescribe FRACGP No 33/68 (49) 1 (reference) Yes 32/92 (35) 0.41 0.17–1.00 0.0508 Case vignette <0.0001* 1: Peripheral neuropathy 11/40 (28) 0.19 0.08–0.47 0.0003 2: Erectile dysfunction 28/40 (70) 1.27 0.47–3.42 0.6388 6: Radiation proctitis 26/40 (65) 1 (reference) Refer Years of practice 1 15/55 (27) 0.30 0.13–0.66 0.0027 2 or more 71/145 (49) 1 (reference) Hours of patient contact per week Up to 40 69/145 (48) 1 (reference) 41 or more 17/55 (31) 0.38 0.17–0.84 0.0165 Case vignette 0.0005* 1: Peripheral neuropathy 17/40 (43) 1.26 0.58–2.71 0.5632 2: Erectile dysfunction 7/40 (18) 0.33 0.10–1.04 0.0582 3: Urinary dysfunction 23/40 (58) 2.44 0.94–6.35 0.0680 4: Tumour recurrence 24/40 (60) 2.73 0.98–7.60 0.0542 6: Radiation proctitis 15/40 (38) 1 (reference) Order tests No. of patients seen per week Less than 150 62/124 (50) 1 (reference) 150 or more 23/36 (64) 2.48 1.16–5.30 0.0191 Case vignette <0.0001* 3: Urinary dysfunction 16/40 (40) 6.33 1.58–25.42 0.0092 4: Tumour recurrence 32/40 (80) 40.02 10.29–155.68 <.0001 5: Cancer-related fatigue 33/40 (83) 47.29 11.47–195.00 <.0001 6: Radiation proctitis 4/40 (10) 1 (reference) *p-value for the variable as a whole Note: The table shows the results of three GEE models. For each analysis, the dependent variable was a correct response. The numbers in the third column show the number and percentage of correct responses within the group defined by the row. Conclusions: Discussion In this study, we have explored the impact of a variety of clinical and respondent characteristics on GPs’ decisions to treat patients with treatment side effects or symptoms of recurrence of colorectal cancer. Peripheral neuropathy, fatigue, bowel dysfunction, urinary dysfunction, tumour recurrence, and sexual dysfunction are common presentations of patients with colorectal cancer in general practice [10]. Our data indicate that GPs correctly diagnosed most of these conditions, with the exception of chemotherapy-induced fatigue. This would be expected, as in most cases, fatigue presents as a manifestation of other underlying conditions and it is also difficult to diagnose [11]. Although participating GPs did not recognise fatigue, the regression results showed that they ordered tests to explore underlying conditions that were consistent with the expert suggestions. Suggestions for management plans for these conditions were, however, not consistent with expert opinion in all the applicable categories of management (refer, prescribe and order tests) for the specific cases. From the regression analysis, we were able to conclude that compared to radiation proctitis, tumour recurrence, fatigue and urinary dysfunction were more likely to be managed as per the experts. There were marked deviations from the experts’ suggestions for the cases of erectile dysfunction and peripheral neuropathy. For example, for erectile dysfunction practitioners were less likely to refer back to the specialist, but offered appropriate medication. Similarly, there were deviations from expert management for peripheral neuropathy and urinary dysfunction. Such deviations from expert opinion have been reported previously in similar studies with prostate cancer patients [12]. The differences in management between the participants and the expert panel were less marked for the management of tumour recurrence. This may be expected, as most patients first present to a GP before the cancer diagnosis [13] or with symptoms of recurrence even with ongoing management by their specialist [6]. It is therefore plausible that the GPs were well experienced in recognising and making appropriate decisions related to tumour recurrence. Regression analysis also suggested that there were other influential variables impacting on the management of these conditions. These were some of the demographic characteristics of the participants; specifically, the number of patient contact hours and years of experience. GPs with less than one year of experience were less likely to manage patients according to expert opinion. This was expected for patients treated for colorectal cancer, because many of these problems are likely to present infrequently when patients are still being followed by their specialist. Few doctors will have encountered them previously unless they work full-time and/or have been practising for a longer period. A number of approaches have been reported in the literature to promote consistent and reliable management of chronic conditions in primary care [6, 12, 14]. A few of these have focused specifically on the knowledge of GPs [12], and others have reported that attitudes and beliefs are important in the context of a cancer diagnosis [6]. These issues were not evaluated in this study. For example, we were unable to report on the participants’ attitude to the management of patients following treatment and whether they felt this role extended to investigating and treating conditions that may have resulted from specialist treatment. Finally, we could not identify any practitioners who had any specialist training in colorectal cancer. However, all participants were working as GPs when they participated in this study and it is reasonable to assume that there were a negligible number with specialist training in a specific cancer. This pilot study had a modest sample size of 240 observations, which was chosen on the basis that this number would be adequate to estimate the proportion of occasions on which at least one problem was correctly identified or managed with a reasonable precision (approximately ±10%). This was not true of all management modalities. In some cases the number of observations was very low, as evidenced by very wide confidence limits, as shown in Table 3. Therefore, a much larger randomised study would be required to robustly test our objectives. Conclusions In this pilot study, years of experience and direct patient contact hours had a more significant and positive impact on the management of patients. This study also showed promising results that management of the common side effects of cancer colorectal treatment could be delegated to general practice. Such an intervention could support the application of shared care models of care. However, a larger study, including the management of side effects in real patients, needs to be conducted before it can be safely recommended. Clinical Trial: n/a