This study demonstrated increases in fruit and vegetable consumption, positive changes in motivation to change dietary behaviors, and greater nutrition knowledge in participants in the MSB-N conditions relative to controls. In addition, significant differences were found between intervention and control groups on measures of social support, self-efficacy, and encouragement for dietary change. Barriers and benefits of exercise evidenced change in the intervention groups relative to the control group.
When using the single-item measure of fruit and vegetable consumption, both experimental groups reported significantly higher fruit and vegetable intake than did controls at post-test. We did not find sustained reports of higher F&V consumption, suggesting that in order to maintain dietary changes with college students, more intense efforts are likely needed.
The findings on stage of change were some of the most robust results in the study. Both experimental groups advanced in their perceived readiness to increase fruit and vegetable consumption as well as to decrease dietary fat intake. These results suggest that one important benefit of this Internet-based intervention was to help college students increase their motivation to make dietary changes, which if implemented, could have a significant impact on health (Diclemente et al., 2004
; Hwang, 1999
; Lampe, 1999
; Spencer et al., 2006
; Velicer et al., 2006
In addition to the behavioral and motivational effects, the intervention also appeared to impact measures of encouragement of, and social support for, dietary changes. The positive association between social support and better nutrition has been reported elsewhere (Kelsey et al., 1996
; Lloyd et al., 1995
; Steptoe et al., 2004
; Wolfe, 2004
), and may be particularly important for college students who are transitioning away from family and spending the majority of their time with peers.
Self-efficacy is an important variable in many areas of health change behaviors (Bandura, 2004
; Wangberg, 2007
) and was found to increase in the Experimental I group relative to the control group. Steptoe et al. (2004)
found that dietary self-efficacy was associated with concurrent F&V intake, but did not predict consumption 12 months after the intervention. The methodology employed in this study, i.e., making multiple visits to the website, may have been helpful in increasing self-efficacy because participants had a period in which to try out new behaviors as well as the ability to set goals for themselves that could be updated upon return to the website.
Although behavioral changes in physical activity were not found, the experimental groups did score lower on the barriers to exercise measure at the 3-month follow-up (Experimental I) and the 6-month follow-up (both groups). This minimal impact on physical activity may be due to the fact that fitness was less emphasized on the website than nutrition (i.e., only one main topic area was devoted to fitness whereas three were related to nutrition). Alternatively, there may have been a ceiling effect, as our sample had fairly high levels of physical activity at the start of the study. This suggests that the program might be more beneficial for groups less likely to be physically active, such as minority college students (Blanchard et al., 2008
). That computer use is in fact a sedentary activity makes an online intervention to encourage physical activity challenging (Marks et al., 2006
). It may be that Internet-based programs will need to include use of incentives, sign-up for campus activities, or video games that make use of activity to further increase the efficacy of such an intervention (Lanningham-Foster et al., 2006
Comparisons of our findings to others in the literature is difficult, as many nutrition-and physical activity-related Internet-based programs tend to target specific issues, such as diabetes prevention and care (Long et al., 2006
; Wangberg, 2007
) or weight loss (Gold et al., 2007
, Rothert et al., 2006
). One college-focused intervention combined four stage-based newsletters, one motivational interview, and an individually tailored e-mail follow-up over a 4-month period (Richards, Kattleman, & Ren, 2006
), resulting in an increase in fruit and vegetable consumption in the intervention group of one serving a day compared to 0.4 servings a day in the control group. Woodall et al. (2007)
, in a study using e-mail messages to encourage the use of a nutrition education website with adults in rural settings, found that those who responded to the messages by using the site increased their fruit and vegetable intake by 1.69 servings, relative to the non-responders. Studies that have tested online interventions with adolescents have shown increases in F&V in some cases (e.g., Baranowski et al., 2003
) and no change in others (Haerens et al., 2007; Mangunkusumo et al., 2007
). A recent review of computer-tailored nutrition education programs for children, adolescents and adults (Kroeze, Werkman, & Brug, 2006
) found that 12 of 17 programs reported positive intervention effects, with effect sizes that varied across studies from small (0.14; Winett et al., 1997) to relatively large (0.48; Campbell et al., 1999
). A review of behavioral interventions to modify fruit and vegetable intake reported that 17 or 22 studies found positive results, with an average increase of 0.6 servings per day (Ammerman, Lindquist, Lohr, & Hersey, 2002
). Our finding of an increase of .33 serving per day is less than previous reports, which is likely related to a number of factors that vary among studies, including the amount of time spent using the website, the degree of tailoring available on the site, the addition of in-person contact, the extent to which the program is integrated into classroom activities, and the actual content that makes up the website.
This same review by Kroeze et al. (2006)
also looked at the effectiveness of randomized controlled trials using computer-tailored education for physical activity and found that only 3 of 11 physical activity programs yielded positive results, with effects sizes that ranged from 0.01 (Vandelanotte et al., 2005
) to 0.42 (Marcus et al., 1998
). Similarly, van den Berg and colleagues (2007)
found only 10 eligible studies for their review of Internet-based physical activity interventions, only 5 of which were judged to be of good methodological quality. Of these, 4 compared Internet-based interventions to wait list controls, and only 2 found in favor of the intervention. One of those two studies reported effect sizes, which were small in magnitude (Plotnikoff et al., 2005
). Our null findings regarding physical activity appear to be in keeping with other published reports, emphasizing the difficulty of changing physical activity using online programs and the need to consider adding motivational devices (e.g., pedometers) to increase their effectiveness.
The use of a booster session condition appeared to have little impact, which may have to do with the degree to which participants used the website during the booster session. As participants were requested to return to the site at a remote location (i.e., they did not return to the computer lab), it is not clear how much time was actually spent on the site during this extra session. Use of booster sessions in health promotion programs has been encouraged (Elder et al., 2006
; Sutton, 2007
; Wiehe et al., 2005
), but specific procedures have not been well articulated or evaluated.
The long-term maintenance of our intervention effects on behavioral measures was not strong; however, the attitudinal measures did show some longer-term effects. Long-term maintenance of behavioral changes has been a problem in a number of nutrition education studies (Ahern, 2007
). Our results suggest that in order to enhance and sustain dietary change, college students may need frequent support over time.
The clinical significance of this study is strongest in relation to the findings of participants’ increased readiness to make changes to both F&V and fat intake, relative to controls. Many recent studies have shown that greater readiness to change relates directly to change in dietary behaviors (Campbell et al., 2008
; Di Noia, Schinke, Prochaska, & Contento, 2006
; Henry, Reimer, Smith, & Reicks, 2006
; Nitzke et al., 2007
; Robinson et al., 2008
) and is often a first step toward making difficult behavioral changes. Thus, although we found only a modest increase in fruit and vegetable consumption, we posit that a program that increases participants’ motivation is an important addition to the relatively sparse offerings in online nutrition education available to university students (Cousineau et al., 2004
). The use of this program in combination with university courses and environmental and policy changes may result in improved nutritional behaviors in college students.
Study Strengths and Limitations
There are both strengths and limitations to this study. Strengths include the relatively large sample, low attrition rate, the ease of use and short completion time of the program, and the multiple domains assessed in the outcome measures. Additionally, participants came from geographically diverse groups and no site differences were observed. Over 40% of our participants were ethnic minority students and we used an attention control group to take into account the effect of participation. However, many of our effects were small in magnitude and this raises the question of clinical versus statistical significance. The use of two to three intervention periods is less than is usually recommended in order to effect long-term change in dietary habits. Moreover, our data was self-report, our measures related to fats did not distinguish between types of fat, and we had missing data for a crucial time point on one key measure.
Future studies will be needed to determine whether improvements can be sustained over a longer period, whether self-reported intention to change will translate into behavior, and whether MSB-N
is superior when compared to other nutrition education programs. School-based policies that encourage healthy eating have been studied to a greater extent in middle and high schools (Cullen et al., 2007
; Davee et al., 2005
; Neumark-Sztainer et al., 2005
), than in the college environment (Brown et al., 2005
; Shive & Morris, 2006
). Findings from these studies have indicated that policy changes about the nutrient content of vending machine and a la carte items, social marketing campaigns that provide sample foods and information about healthy eating, and participation in prepaid meal plans have all proved beneficial to sustaining healthy changes in the food environment for students. The current intervention could easily be incorporated into nutrition, health and fitness courses, provided at wellness clinics, and offered in the freshmen orientation or first-year general education courses in an effort to address the poor nutrition and physical activity habits common to college students. In conjunction with broader environmental changes on campuses (e.g., better choices for fresh produce in cafeterias, posted information about the benefits of healthy eating and exercise), such interventions may assist in widespread changes.
In conclusion, MyStudentBody.com-Nutrition appears to be a brief and effective Internet-based program that can promote some dietary changes in knowledge, attitudes, and behaviors in college students. Such a program is likely to have wide applicability on university campuses in the efforts to increase healthy eating in this population.