Promoting physical activity among university students: a systematic review of controlled trials

Objective: University study is often accompanied by a decline in physical activity (PA) levels but can offer the opportunity to promote a lifelong active lifestyle. This review aims to summarize controlled trials of interventions promoting PA among uni- versity students, describing the quality of the evidence, effective strategies, and deficiencies in the interventions employed, to provide directions for future research and for practical implementations. Data Source: PubMed, PsychINFO, Cochrane Library, Education Source, and SPORTDiscus. Study Inclusion Criteria: Randomized or nonrandomized controlled trial, describing an intervention to promote PA in uni- versity students, where PA was one of the outcomes and results were published in English. Data Extraction: Country, study design, participants\u2019 inclusion criteria, participation rate and characteristics, randomization, blinding, theoretical framework, intervention characteristics, participant retention rate and withdrawal reasons, measures employed, data analysis, PA results, and findings regarding PA correlates. Data Synthesis: Data were synthetized considering study characteristics, strategies used, and outcomes. Results: Two thousand five hundred eighty-five articles were identified. Twenty-seven studies met the inclusion criteria. Sixteen studies reported an increase in PA levels. Conclusion: Physical Activity promotion interventions should address a range of behavioral determinants. Personalized approaches and PA sessions should be considered in future studies. The high risk of bias of many studies (mainly due to attrition and poor reporting) and missing information about intervention components limit the strength of conclusions about the most effective strategies and the evidence of effectiveness, highlighting the need for further high-quality studies

A systematic review of digital interventions for improving the diet and physical activity behaviors of adolescents

Many adolescents have poor diet and physical activity behaviors, which can lead to the development of noncommunicable diseases in later life. Digital platforms offer inexpensive means of delivering health interventions, but little is known about their effectiveness. This systematic review was conducted to synthesize evidence on the effectiveness of digital interventions to improve diet quality and increase physical activity in adolescents, to effective intervention components and to assess the cost-effectiveness of these interventions. Following a systematic search, abstracts were assessed against inclusion criteria, and data extraction and quality assessment were performed for included studies. Data were analyzed to identify key features that are associated with significant improvement in behavior. A total of 27 studies met inclusion criteria. Most (n = 15) were Web site interventions. Other delivery methods were text messages, games, multicomponent interventions, emails, and social media. Significant behavior change was often seen when interventions included education, goal setting, self-monitoring, and parental involvement. None of the publications reported cost-effectiveness. Due to heterogeneity of studies, meta-analysis was not feasible.It is possible to effect significant health behavior change in adolescents through digital interventions that incorporate education, goal setting, self-monitoring, and parental involvement. Most of the evidence relates to Web sites and further research into alternate media is needed, and longer term outcomes should be evaluated. There is a paucity of data on the cost-effectiveness of digital health interventions, and future trials should report these data

Advances in Teaching & Learning Day Abstracts 2004

Proceedings of the Advances in Teaching & Learning Day Regional Conference held at The University of Texas Health Science Center at Houston in 2004

Advances in Teaching & Learning Day Abstracts 2005

Proceedings of the Advances in Teaching & Learning Day Regional Conference held at The University of Texas Health Science Center at Houston in 2005

Persuasive system design does matter: a systematic review of adherence to web-based interventions

Background: Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective: This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods: We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results: We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions: Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adher

Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies

A systematic search of the research literature from 1996 through July 2008 identified more than a thousand empirical studies of online learning. Analysts screened these studies to find those that (a) contrasted an online to a face-to-face condition, (b) measured student learning outcomes, (c) used a rigorous research design, and (d) provided adequate information to calculate an effect size. As a result of this screening, 51 independent effects were identified that could be subjected to meta-analysis. The meta-analysis found that, on average, students in online learning conditions performed better than those receiving face-to-face instruction. The difference between student outcomes for online and face-to-face classes—measured as the difference between treatment and control means, divided by the pooled standard deviation—was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. Analysts noted that these blended conditions often included additional learning time and instructional elements not received by students in control conditions. This finding suggests that the positive effects associated with blended learning should not be attributed to the media, per se. An unexpected finding was the small number of rigorous published studies contrasting online and face-to-face learning conditions for K–12 students. In light of this small corpus, caution is required in generalizing to the K–12 population because the results are derived for the most part from studies in other settings (e.g., medical training, higher education)

Native IYG: Improving Psychosocial Protective Factors for HIV/STI and Teen Pregnancy Prevention among Youth in American Indian/Alaska Native Communities

Background: Few HIV/STI and pregnancy prevention programs for youth in American Indian and Alaska Native (AI/AN) communities have been rigorously evaluated despite sexual health disparities in this population. This study reports the evaluation of a culturally adapted Internet-based HIV/STI and pregnancy prevention program for AI/AN youth, Native It’s Your Game (Native IYG). Methods: A randomized study was conducted with 523 youth (12 to 14 years old), recruited from 25 tribal sites in Alaska, Arizona, and the Pacific Northwest. Participants were surveyed at baseline and upon completion of treatment or comparison interventions. Multivariable linear regression models were used to assess impact on short term psychosocial determinants of sexual initiation. Results: A sample of 402 intervention (n=290) and comparison (n=112) youth completed the post-intervention survey (76.9% retention) from 1 to 462 days post-baseline (mean = 114, SD = ±96.67). Participants were 55.5% female, mean age of 13.0 (± 0.97) years with 86.1% self-reporting as AI/AN. Reasons not to have sex, STI knowledge, condom knowledge, condom availability self-efficacy, and condom use self-efficacy were significantly impacted (all P ≤ .01). Limitations included variability in intervention exposure and time between data collection time points. Conclusions: Native IYG demonstrated efficacy to impact short-term psychosocial determinants of sexual behavior in a sample of predominantly AI/AN middle school youth

Why are health care interventions delivered over the internet? : a systematic review of the published literature

Background: As Internet use grows, health interventions are increasingly being delivered online. Pioneering researchers are using the networking potential of the Internet, and several of them have evaluated these interventions. Objective: The objective was to review the reasons why health interventions have been delivered on the Internet and to reflect on the work of the pioneers in this field in order to inform future research. Methods: We conducted a qualitative systematic review of peer-reviewed evaluations of health interventions delivered to a known client/patient group using networked features of the Internet. Papers were reviewed for the reasons given for using the Internet, and these reasons were categorized. Results: We included studies evaluating 28 interventions plus 9 interventions that were evaluated in pilot studies. The interventions were aimed at a range of health conditions. Reasons for Internet delivery included low cost and resource implications due to the nature of the technology; reducing cost and increasing convenience for users; reduction of health service costs; overcoming isolation of users; the need for timely information; stigma reduction; and increased user and supplier control of the intervention. A small number of studies gave the existence of Internet interventions as the only reason for undertaking an evaluation of this mode of delivery. Conclusions: One must remain alert for the unintended effects of Internet delivery of health interventions due to the potential for reinforcing the problems that the intervention was designed to help. Internet delivery overcomes isolation of time, mobility, and geography, but it may not be a substitute for face-to-face contact. Future evaluations need to incorporate the evaluation of cost, not only to the health service but also to users and their social networks. When researchers report the outcomes of Internet-delivered health care interventions, it is important that they clearly state why they chose to use the Internet, preferably backing up their decision with theoretical models and exploratory work. Evaluation of the effectiveness of a health care intervention delivered by the Internet needs to include comparison with more traditional modes of delivery to answer the following question: What are the added benefits or disadvantages of Internet use that are particular to this mode of delivery