Mical Kay Shilts

Goal Setting as a Strategy for Dietary and Physical Activity Behavior Change: A Review of the Literature

Objective. Estimate effectiveness of goal setting for nutrition and physical activity behavior change, review the effect of goal-setting characteristics on behavior change, and investigate effectiveness of interventions containing goal setting. Data source. For this review, a literature search was conducted for the period January 1977 through December 2003 that included a Current Contents, Biosis Previews, Medline, PubMed, PsycINFO, and ERIC search of databases and a reference list search. Key words were goal, goal setting, nutrition, diet, dietary, physical activity, exercise, behavior change, interventions, and fitness. Study inclusion and exclusion criteria. The search identified 144 studies, of which 28 met inclusion criteria for being published in a peer reviewed journal and using goal setting in an intervention to modify dietary or physical activity behaviors. Excluded from this review were those studies that (1) evaluated goal setting cross-sectionally without an intervention; (2) used goal setting for behavioral disorders, to improve academic achievement, or in sports performance; (3) were reviews. Data extraction and synthesis. The articles were categorized by target audience and secondarily by research focus. Data extracted included outcome measure, research rating, purpose, sample, sample description, assignment, findings, and goal-setting support. Results. Thirteen of the 23 adult studies used a goal-setting effectiveness study design and eight produced positive results supporting goal setting. No adolescent or child studies used this design. The results were inconclusive for the studies investigating goal-setting characteristics (n = 7). Four adult and four child intervention evaluation studies showed positive outcomes. No studies reported power calculations, and only 32% of the studies were rated as fully supporting goal setting. Conclusions. Goal setting has shown some promise in promoting dietary and physical activity behavior change among adults, but methodological issues still need to be resolved. The literature with adolescents and children is limited, and the authors are not aware of any published studies with this audience investigating the independent effect of goal setting on dietary or physical activity behavior. Although, goal setting is widely used with children and adolescents in nutrition interventions, its effectiveness has yet to be reported.

An Innovative Approach to Goal Setting for Adolescents: Guided Goal Setting

Goal setting has shown promise in promoting positive behavior change in the nutrition and physical activity fields.1-3 When designing the goal-setting strategy for an intervention, a decision about goal type (who develops and chooses the goal) has to be made. Several factors, such as participant’s age, intervention setting, and readiness to change, influence the type of goal to use: (1) self-set, (2) participatory, or (3) assigned.4 This GEM is about the development and use of a fourth type, guided goal setting.This GEM (1) describes the development of the guided goal-setting strategy, (2) shows how guided goal setting was implemented in the EatFit intervention, and (3) provides a step-by-step guide for the practitioner who wishes to duplicate the guided goal-setting strategy (Table).

Pilot Study: EatFit Impacts Sixth Graders' Academic Performance on Achievement of Mathematics and English Education Standards

OBJECTIVE Investigate the impact of a nutrition education program on student academic performance as measured by achievement of education standards. DESIGN Quasi-experimental crossover-controlled study. SETTING California Central Valley suburban elementary school (58% qualified for free or reduced-priced lunch). PARTICIPANTS All sixth-grade students (n = 84) in the elementary school clustered in 3 classrooms. INTERVENTION 9-lesson intervention with an emphasis on guided goal setting and driven by the Social Cognitive Theory. MAIN OUTCOME MEASURE Multiple-choice survey assessing 5 education standards for sixth-grade mathematics and English at 3 time points: baseline (T1), 5 weeks (T2), and 10 weeks (T3). ANALYSIS Repeated measures, paired t test, and analysis of covariance. RESULTS Changes in total scores were statistically different (P < .05), with treatment scores (T3 - T2) generating more gains. The change scores for 1 English (P < .01) and 2 mathematics standards (P < .05; P < .001) were statistically greater for the treatment period (T3 - T2) compared to the control period (T2 - T1). CONCLUSION AND IMPLICATIONS Using standardized tests, results of this pilot study suggest that EatFit can improve academic performance measured by achievement of specific mathematics and English education standards. Nutrition educators can show school administrators and wellness committee members that this program can positively impact academic performance, concomitant to its primary objective of promoting healthful eating and physical activity.

EatFit: A Goal-Oriented Intervention that Challenges Adolescents to Improve Their Eating and Fitness Choices

• Workbook. Each student receives his or her own copy of the full-color, 20-page, magazine-style EatFit workbook (Figure). It contains all worksheets, so no photocopying is necessary. • Web-based assessment (www. eatfit.net). Computer technology is used to assist adolescents in diet assessment. The personalized assessment program is an interactive application that begins with adolescents entering a 24-hour diet record and concludes with personalized dietary feedback, goal setting, and a contract. • Classroom curriculum for the teacher/leader. The curriculum includes 9 experiential lessons that teach skills, provide goal performance feedback, practice behaviors, and motivate. The topics include dietary and physical activity goal setting, reading food labels, eating at fast food outlets, learning the physical activities, and understanding media influence.

Adapting a Diet Analysis Program for an Adolescent Audience

Lytle and Achterberg identified key components to behavior change for youth interventions: (1) self-assessment of eating patterns for adolescents, (2) use of interactive computer technology, and (3) personalized and targeted messages.1 Building on this literature and our interviews with individual middle school students and teachers in California, we decided to include a focused computer component as an important strategy for a nutrition education intervention.The cost of developing a computerized diet analysis application was prohibitive (>

Utilizing the desired results developmental profile as a measure of school readiness: evaluating factor structure and predictors of school readiness

100 000).As a viable alternative, saving time and money, we decided to adapt an existing computer application to meet the needs of our new audience. This adapted Webbased application (www.eatfit.net) starts with the entry of a 24-hour diet record by the adolescent and concludes with the output of a personalized and behaviorally focused goal. Although we believed that our plan was comprehensive, we learned otherwise.This GEM delineates the 6 steps we took to adapt this application. We offer supporting examples from our experiences. These steps might assist others who are considering the inclusion of a computerized diet analysis application into their nutrition education efforts.

My child at mealtime: A visually enhanced self-assessment of feeding styles for low-income parents of preschoolers.

ABSTRACT A disconnect exists between definitions of school readiness used in research and early childhood education (ECE). While researchers often discuss school readiness as a single, multidimensional construct, the majority of studies operationalize it using multiple measures rather than as one outcome. In comparison, in ECE settings a single measurement tool including multiple dimensions is used. The current study attempted to bridge this gap by examining the factor structure of the Desired Results Developmental Profile (DRDP), a measure of school readiness used in Head Start. We considered often-cited predictors of school readiness (parenting, effortful control) to replicate previous research findings. Analyses indicated a single factor was most appropriate for the DRDP. Measures of parenting and children’s effortful control were significant predictors of DRDP scores. Findings from the current study suggest an existing single factor, ECE-based measure of school readiness, such as the DRDP, can also be used as a research tool.

Dose: Comparison of 6 and 12 Nutrition and Physical Activity Sessions Targeting Middle School Adolescents

The importance of caregiver feeding styles on childrens dietary outcomes is well documented. However, the instruments used to assess feeding style are limited by high literacy demands, making selfassessment with low-income audiences challenging. The purpose of the current study is to report on the development of My Child at Mealtime (MCMT), a self-assessment tool with reduced literacy demands, designed to measure feeding styles with parents of preschool-aged children. Cognitive interviews were conducted with 44 Head Start parents of 2-5 year old children to develop question wording and identify appropriate visuals. The resulting tool was administered to 119 ethnically diverse, low-income parents of 2-5 year old children. Factor analysis resulted in a two-factor structure that reflects responsiveness and demandingness in a manner consistent with existing assessment tools. Results indicate the final visually enhanced MCMT self-assessment tool provides a measure of parenting style consistent with existing measures, while reducing the literacy demand.

Vegetable behavioral tool demonstrates validity with MyPlate vegetable cups and carotenoid and inflammatory biomarkers

Determining optimal intervention dose to meet time constraints of the teacher while maximizing behavioral impact for students has proven challenging. This study investigated the influence of intervention dose on 7th & 8th grade participants’ dietary and physical activity (PA) behaviors. Participants were assigned randomly to a: 1) 6 week-12 session nutrition intervention [treatment#1], or 2) 3 week-6 session nutrition intervention [treatment#2] with data collected pre/post intervention. Using ANCOVA, measures assessed dietary and PA self-efficacy and behaviors. Ethnically diverse participants (n=107) were included in the analyses (46% male). All students set two goals: one dietary and one PA regardless of dose. Treatment#1 resulted in similar outcomes compared to treatment#2 with no significant differences between groups. As a result, we recommend that teachers using the 12 week intervention give students the option of setting new goals after the 6th lesson to maintain motivation.

Evaluation of a USDA Nutrition Education Program for Low-income Youth

Young children are not meeting recommendations for vegetable intake. Our objective is to provide evidence of validity and reliability for a pictorial vegetable behavioral assessment for use by federally funded community nutrition programs. Parent/child pairs (n=133) from Head Start and the Special Supplemental Nutrition Program for Women, Infants and Children [WIC] provided parent-administered vegetable tools, three child 24-hour diet recalls, child blood sample and measured heights/weights. The 10-item Focus on Veggies scale, with an alpha of .83 and a stability reliability coefficient of .74, was positively related to vegetables in cup equivalents [p≤.05]; dietary intakes of folate, vitamin C, β-carotene, potassium and magnesium [p≤.05-.01]; and soluble fiber [p≤.001]. The child vegetable scores were related to the parents mediators [p≤.00001] and vegetable behaviors [p≤.00001]. Childrens plasma inflammatory markers were negatively related to the 10 item scale [p≤.05] and are indicators of the childs health status. The positive relationship between the serum carotenoid index and a sub-scale of child vegetable behaviors offered additional support for criterion validity [p≤.05]. Finally, the inverse relationship of BMI-for-age percentile one year post baseline and a sub-scale of child vegetable behaviors supported the predictive validity [p≤.05]. Focus on Veggies, a simple assessment tool, can inform practitioners about the childs health status. A child with a high score, shows a healthful profile with a lower inflammation index, higher carotenoid index, lower BMI and higher vegetable intake. In conclusion, validity of Focus on Veggies has been demonstrated using vegetable cup equivalents and micronutrient intakes, anthropometry and blood biomarkers.