Lizzy Pope

When do gain-framed health messages work better than fear appeals?

Past literature reviews of gain-framed versus loss-based health messages have been inconsistent and inconclusive. To resolve this and provide a clearer pattern, this review focuses on the individual or person-specific characteristics of target audiences. The results indicate that by answering the following four questions about a target audience, one can predict whether a gain-framed or a loss-based health message will be more effective. 1) Is there a low (versus high) level of involvement in the issue? 2) Is there a high (versus low) certainty of the outcome? 3) Is there a low (versus high) preference for risk? 4) Is there a heuristic (versus piecemeal) processing style? The profiling of audiences on these factors has two distinct benefits; it resolves many of the seeming inconsistencies in past positive-negative and gain-loss message research (such as fear appeals working better with experts than nonexperts) and it helps predict which type of message will be most effective with a given audience.

Burn and earn: a randomized controlled trial incentivizing exercise during fall semester for college first-year students.

OBJECTIVE To examine the viability of monetary incentives to increase fitness-center use and maintain/improve the Body Mass Indexes (BMIs) of first-year students over the fall semester. METHOD Randomized-controlled trial with no-treatment and incentive conditions involving 117 first-year students. For 12 weeks, students in the incentive condition received monetary payments ranging from

Undergrad and Overweight: An Online Behavioral Weight Management Program for College Students

10 to

New Year’s Res-Illusions: Food Shopping in the New Year Competes with Healthy Intentions

38.75 for meeting researcher-set fitness-center use goals that were identical across conditions. Fitness-center use was monitored through electronic ID-card check-in and check-out records at the campus fitness center. RESULTS 63% of incentive-condition participants met the weekly fitness-center use goals on average compared to only 13% of control-condition participants, a significant difference, p<0.001. Goal achievement significantly decreased over time, p<0.01 and at roughly the same rate in the control and incentive conditions, p=0.23. Average BMI increases over the fall semester in the control (24.2 (0.6) to 24.6 (0.6)kg/m(2)) versus incentive condition (23.1 (0.4) to 23.5 (0.4)kg/m(2)) were not significantly different (p=0.70). CONCLUSION Weekly monetary incentives resulted in significantly more first-year students meeting weekly fitness-center use goals. However, the increased fitness-center use by the incentive condition did not prevent an increase in BMI during fall semester.

The Impact of Incentives on Intrinsic and Extrinsic Motives for Fitness-Center Attendance in College First-Year Students

OBJECTIVE Explore the feasibility of an online behavioral weight management program for college students. METHODS The program focused on behavioral strategies to modify eating and exercise behaviors of students interested in losing weight and/or developing a healthy lifestyle. Specific tools included weekly chat meetings with a facilitator, calorie and fat gram recommendations, daily food logs, and exercise guidance. RESULTS Three hundred thirty-six students participated from 2 northeastern universities. Overweight/obese students wanting to lose weight had a mean body mass index of 30.6 kg/m(2) at baseline and lost an average of 5.1 ± 6.0 lbs. Those of healthy weight wanting to lose weight had a mean body mass index of 22.0 kg/m(2) at baseline and lost an average of 1.8 ± 3.2 lbs. Twenty-three percent of students lost > 5% of their baseline weight. CONCLUSIONS AND IMPLICATIONS Use of an online behavioral weight management program may be a feasible way to help college students develop healthy eating and exercise behaviors.

Food Neophiles: Profiling the Adventurous Eater

Objective How do the holidays – and the possible New Year’s resolutions that follow – influence a household’s purchase patterns of healthier foods versus less healthy foods? This has important implications for both holiday food shopping and post-holiday shopping. Methods 207 households were recruited to participate in a randomized-controlled trial conducted at two regional-grocery chain locations in upstate New York. Item-level transaction records were tracked over a seven-month period (July 2010 to March 2011). The cooperating grocer’s proprietary nutrient-rating system was used to designate “healthy,” and “less healthy” items. Calorie data were extracted from online nutritional databases. Expenditures and calories purchased for the holiday period (Thanksgiving-New Year’s), and the post-holiday period (New Year’s-March), were compared to baseline (July-Thanksgiving) amounts. Results During the holiday season, household food expenditures increased 15% compared to baseline (

You can’t “nudge” nuggets: An investigation of college late-night dining with behavioral economics interventions

105.74 to

Viewers vs. Doers: The Relationship between Watching Food Television and BMI

121.83; p<0.001), with 75% of additional expenditures accounted for by less-healthy items. Consistent with what one would expect from New Year’s resolutions, sales of healthy foods increased 29.4% (

The impact of high-calorie-expenditure exercise on quality of life in older adults with coronary heart disease.

13.24/week) after the holiday season compared to baseline, and 18.9% (

“Don’t eat so much:” how parent comments relate to female weight satisfaction

9.26/week) compared to the holiday period. Unfortunately, sales of less-healthy foods remained at holiday levels (