Costs and difficulties of recruiting patients to provide e-health support: pilot study in one primary care trust

<p>Abstract</p> <p>Background</p> <p>Better use of e-health services by patients could improve outcomes and reduce costs but there are concerns about inequalities of access. Previous research in outpatients suggested that anonymous personal email support may help patients with long term conditions to use e-health, but recruiting earlier in their 'journey' may benefit patients more. This pilot study explored the feasibility and cost of recruiting patients for an e-health intervention in one primary care trust.</p> <p>Methods</p> <p>The sample comprised 46 practices with total patient population of 250,000. We approached all practices using various methods, seeking collaboration to recruit patients via methods agreed with each practice. A detailed research diary was kept of time spent recruiting practices and patients. Researcher time was used to estimate costs. Patients who consented to participate were offered email support for their use of the Internet for health.</p> <p>Results</p> <p>Eighteen practices agreed to take part; we recruited 27 patients, most (23/27) from five practices. Practices agreed to recruit patients for an e-health intervention via waiting room leaflets (16), posters (16), practice nurses (15), doctors giving patients leaflets (5), a study website link (7), inclusion in planned mailshots (2), and a special mailshot to patients selected from practice computers (1). After low recruitment response we also recruited directly in five practices through research assistants giving leaflets to patients in waiting rooms. Ten practices recruited no patients. Those practices that were more difficult to recruit were less likely to recruit patients. Leaving leaflets for practice staff to distribute and placing posters in the practice were not effective in recruiting patients. Leaflets handed out by practice nurses and website links were more successful. The practice with lowest costs per patient recruited (£70) used a special mailshot to selected patients.</p> <p>Conclusion</p> <p>Recruitment via general practice was not successful and was therefore expensive. Direct to consumer methods and recruitment of patients in outpatients to offer email support may be more cost effective. If recruitment in general practice is required, contacting practices by letter and email, not following up non-responding practices, and recruiting patients with selected conditions by special mailshot may be the most cost-effective approach.</p

Long term effects of self-determination theory and motivational interviewing in a web-based physical activity intervention: randomized controlled trial

Background: Our main objective in the current study was to evaluate the long-term effectiveness (12 months from baseline) of I Move (a web-based computer tailored physical activity intervention, based on self-determination theory and motivational interviewing). To this end, we compared I Move to a web-based computer tailored physical activity intervention based on traditional health behavior theories (Active Plus), and to a no-intervention control group. As a secondary objective, the present study aimed to identify participant characteristics that moderate the long term effects of I Move and Active Plus. Methods: A randomized controlled trial was conducted, comparing three research conditions: 1) the I Move condition, participants in this condition received I Move; 2) the Active Plus condition, participants in this condition received Active Plus; 3) the control condition; participants in this condition received no intervention and were placed on a waiting list. Main outcome measures were weekly minutes of moderate to vigorous physical activity and weekly days with minimal 30 min of physical activity. All measurements were taken by web-based questionnaires via the study website. Intervention effects were analyzed using multilevel linear regression analyses. Results: At 12 months from baseline, I Move was found to be effective in increasing weekly minutes of moderate to vigorous physical activity (ES = .13), while Active Plus was not. In contrast, Active Plus was found to be effective in increasing weekly days with >= 30 min PA at 12 months (ES = .11), while I Move was not. No moderators of the effects of I Move were found. Conclusions: The results suggest that web-based computer tailored physical activity interventions might best include elements based on both self-determination theory/motivational interviewing and traditional health behavioral theories. To be more precise, it is arguable that the focus of the theoretical foundations, used in new web-based PA interventions should depend on the intended program outcome. In order to draw firm conclusions, however, more research on the effects of self-determination theory and motivational interviewing in web-based physical activity promotion is needed