Reduce Recreational Screen Time among Children – Healthy Eating and Active Living Fall 2016

Needs Assessment

In 2012, approximately 32% of U.S. youth aged 2-19 years were either overweight or obese, with nearly 17% of youth and 35% of adults falling into the obese category (Ogden, Carroll, Kit, & Flegal, 2014). Though the portion of children who were overweight or obese has remained steady over the last decade, the overall rate is nonetheless disconcerting and has been associated with a number of related cardiovascular diseases and unfavorable metabolic conditions (Katzmarzyk, Church, Craig, & Bouchard, 2009). Heart disease and Type 2 diabetes are among the most prevalent conditions among obese individuals, and, specifically, with increased obesity rates among youth since 1970, health scientists have also observed even earlier onset of these illnesses (Tremblay, LeBlanc, Kho, et al. 2011), as well as earlier onset of puberty and menarche in girls (Biro & Wien, 2010). Thus, it is a public health challenge to increase the health of children and reduce the likelihood that they will remain obese or overweight into adolescence and adulthood. As Biro and Wien (2010) note, perhaps the most important factors underlying the obesity epidemic are the current opportunities for energy intake (i.e., food) coupled with limited energy expenditure (i.e., sedentary lifestyle).

Not surprisingly, childhood obesity has been positively associated with time spent watching TV and other sedentary screen time, such as iPad use (Marshall, et al. 2004, Tremblay, et al. 2011). Longitudinal studies have shown that sedentary screen time, especially TV viewing, increases the risk of children being overweight and obese (Buchanan, 2016). The American Academy of Pediatrics (AAP) recommends no more than 2 hours per day of screen time for children 2 years and older, and none for children younger than 2 years (American Academy of Pediatrics, 2001). Nonetheless, despite this recommendation, U.S. children between ages 8-18 years report an average of 7.5 hours of screen time per day, of which 4.5 hours are spent watching TV content, i.e., TV programs, DVDs, or movies, viewed on a TV, computer, cell phone, or other device (Rideout, et al. 2010). Among U.S. children under 5 years of age, an average of 2 hours was spent with screen media (Rideout et al., 2010). It should be noted that this data is at least 7 years old, and, since its publication, devices have become even more ubiquitous and TV programming almost universally accessible from any device, at any time, in any place where there is cellular signal available. Thus, it would not be surprising if the number of total hours spent watching screens has increased among younger and older children alike.

While children’s screen times far surpass what the AAP recommends, their overall physical activity does not (Tremblay et al., 2011). In fact, recreational time spent viewing TV and/or or other screen media is positively associated with overweight and obesity in children. (Hancox et al. 2004), such that greater screen time correlates with worse physical condition. The Community Preventive Services Task Force (2016) recommends behavioral interventions to reduce recreational sedentary screen time among children aged 13 years and younger. Several behavioral interventions have shown positive effects on children’s energy expenditure, as well as small but positive impacts on their diets (Task Force, 2016).

According to 2015 census data, over 25 percent of Athens-Clarke County residents under the age of 18 live in poverty, because of the association between poverty and obesity as well as poverty and increased screen time, this intervention would be implemented multiple elementary schools in the Athens-Clarke County school district. The target population would include children ages 4 to 8 in an effort to focus on early intervention. Early intervention that promotes effective parenting in children at high risk is an innovative and promising approach to obesity prevention (Brotman, 2012).

Stakeholder	Role in Intervention	Questions from Stakeholder	Effect on Stakeholder of a Successful Program	Effect on Stakeholder of an Unsuccessful Program
Children	Participants	*What to do instead of watch tv	Reduced sedentary screen-time Increased physical activity Reduced risk of associated disease Reduced BMI	No change in behavior No change in attitude
Caregivers	Administer / monitor	What new schedules will be needed Effect on daily routine *Effect on behavior of the child	Change in attitude Change in behavior *Increase knowledge	No change in attitude No change in behavior
counselors / coaches	Administer / monitor	How long will it take How to administer *What are the outcome goals	*meeting goals	not meeting goals Negative evaluation
School/Educational Systems	Partner and collaborate with counselors	How will it effect student behavior Will programs effect instructional time *Will it effect budgets	*less heath related absences among students	*no change in student population

Part 2: Intervention Identification

State and define the intervention strategy – what does it mean? What populations has this strategy been used with? What settings has it been used in? How are your community characteristics similar or different to those of the communities in which the strategy has been effective? (20 points)

The present intervention strategy has a primary aim to reduce Recreational (non work or school related) Sedentary Screen Time in youth and, indirectly, secondarily aims to improve or maintain weight-related outcomes, increase physical activity, and improve diet in youth populations. Sedentary screen time refers to activities such as TV viewing, non school or work related computer, and tablet or phone use. The behavioral intervention sample included mostly children aged 13 years and younger across nine countries, The intervention also consisted of two main methods of delivery with differing intensities: screen time only, which comprised 90% of the studies; and screen time plus. Screen time only interventions focused only on the reduction of sedentary screen time, whereas screen time plus included a focus dually on increasing physical activity and improving diet. The interventions were most commonly delivered in classrooms and included classroom-based education, tracking and monitoring, coaching and counseling, and family or social support. In addition, some studies incorporated the use of electronic monitoring devices, motivational challenges, making screen time contingent on physical activity, or small media.

Nine of the 49 studies examined in this intervention targeted low-income populations. Three studies focused specifically on African American individuals from low-income backgrounds.The proposed intervention focuses specifically on children ages 4 to 8 from low socio-economic households living in Athens-Clarke County. According to 2015 census data, over 37% of the total Athens-Clarke County population lives in poverty. Among those residents those under the age of 18, 25% are living in poverty. This is particularly striking because low socio-economic status has been associated with both higher instances of obesity, as well as increased screen time. In a nationally representative sample, rates of severe obesity were approximately 1.7 times higher among poor children aged 2 to 19 (Skelton et al,. 2009). One study, Screen Time at Home and School among Low-Income Children Attending Head Start (2014), found over one in eight low income children had more than four hours per weekday of at-home screen time. By targeting children at a younger age, the proposed intervention will have a greater likelihood of creating behavior changes. In addition, the proposed intervention will attend to parent education and involvement to increase the impact and permanence of the changed behaviors.

Is the strategy recommended by the Task Force? Why or why not? (10 points)

The strategy is clearly recommended by the Task Force. After a review of 49 studies, the task force found sufficient evidence that both screen time only and screen time plus studies were effective in reducing recreational sedentary screen time, increasing physical activity, improving diet, and maintaining or improving weight-related outcomes.

Provide at least 3 examples from existing articles (peer-reviewed preferably, but could come from other places). These should be different than the research-tested intervention programs(RTIP) listed already. You can include or link to this information, but you should provide different examples. (45 points total)
1. Describe the intervention – what did the authors do? What was the procedure? How long was the intervention? Please describe individual components as well as the broader intervention plan.
2. What were the outcomes measured?
3. What amount of change did they find?

Hip-Hop to Health Jr. Randomized Effectiveness Trial: 1-Year Follow-up Results (1)

618 children, primarily African American aged 3-5 from low-income households were randomly assigned to either a control group who received a general health curriculum or intervention group. The intervention consisted of a 14 week teacher delivered healthy lifestyle behavior curriculum. In addition to improved diet and physical activity, the intervention aimed to reduce television viewing. The intervention consisted of culturally specific materials that were delivered twice a week for 14 weeks. Sessions were themed and included a 20 minute lesson on healthy eating or physical activity as well as a 20 minute interactive physical activity component. Parent participation was encouraged through a homework assignment that mirrored the intervention curriculum. Parents were paid $5.00 for each completed assignment. The control group received only general health curriculum with no information specific to diet, physical activity, or screen time.
The outcomes measured included BMI, nutrition, and screen time. The height and weight of the children were measured at baseline, post-intervention, and one year follow-up. A portable stadiometer was used to measure height and a digital scale was used to measure weight. BMI percentiles and z-scores were calculated using and a CDC developed SAS program. In addition, dietitians were able to obtain information on food consumption by collecting a 24-hour recall at each time point for every enrolled child. Meal observations were also done by trained observers during school meal periods. Food consumption was measured by weighing uneaten food and calculating the difference between the food served and the food left unconsumed. Diet quality was also measuring using the healthy eating index. At each time point parents were also asked to report the amount of screen time use their child engaged in on a typical school day and weekend day.
There was no significant difference between the intervention group and the control group in zBMI scores (-.01, p=.83) There was also no difference found in total screen time (.14, p=.22) time spent viewing television (.18, p=.15) between the intervention or control group. Significant differences were found, however, between groups in their diet quality. The total Healthy Eating Index score remained stable among the intervention group while the control group decreased significantly (mean change, –3.0; SE=1.1; p=0.02).

Sport participation, screen time, and personality trait development during childhood (2)

This intervention looked at the relationship between participation in extracurricular sport activities and screen time as it relates to personality trait stability and change during childhood. Two independent samples were taken, including 3,956 children age 6 and 3,862 children age 10. Sports participation, personality traits, and screen time were measured through parent report, one at baseline and again at 24 months. At baseline, the short temperament scale for children was used to measure introversion, persistence, and reactivity among the 6-year old group. At 24 months, both groups were assessed through parent report using 12 items from the school-aged temperament inventory measuring the same three traits, introversion, persistence, and reactivity. In addition, a composite score was created by using parent report to measure the amount of minutes the child spent watching television and playing electronic games on an average weekday and weekend.
n the younger cohort there was a change in screen time between baseline and the second 24 months. Mean-level changes in child personality traits were associated with total screen time (Table 4). In the younger cohort, screen time at Time 1 (b = .08, p < .01) and the change in screen time between Time 1 and Time 2 (b = .05, p < .01) were negatively associated with change in persistence. The change in screen time between Time 1 and Time 2 was also associated with change in introversion (b = .04, p < .05) – An effect that was conditioned by screen time estimates at Time 1 (interaction term, b = .04, p < .01). Moreover, the change in screen time was non-significant between 0.00 and 1.37 standard deviations in the mean level of Time 1 screen time, meaning that an increase in screen time between Time 1 and Time 2 was positively associated with mean-level change in introversion, but only for children recording fewer than 946.4 min of screen time (per week) at Time 1.
In the older cohort, screen time at Time 1 (b = .04, p < .05) and the change in screen time between Time 1 and Time 2 (b = .04, p < .05) were positively associated with mean- level change in introversion. Screen time at Time 1 (b = .06, p < .01) and the change in screen time between Time 1 and Time 2 (b = .06, p < .01) were also negatively associated with mean-level change in persistence. Intra-individual stability of personality was unrelated to screen time estimates in the younger and older cohorts (Table 5).

Screen-Time Weight-loss Intervention Targeting Children at Home (SWITCH): a randomized controlled trial (3)

The present study was a randomized, controlled trial of children age 9-12 and their primary care giver in the home setting. Their aim was to assess the effect of a home-based, family-delivered intervention designed to reduce screen-based sedentary behavior among overweight and obese children, while also measuring body composition, sedentary behavior, physical activity, and diet. The intervention was delivered over a 20-week period. The content was delivered via face-to-face meetings with the parent or caregiver and the child. During this time, the families were given training and education on specific strategies to use to reduce their child’s screen time. TV monitoring devices were used to assist in allocation of screen time. In addition, activity packages that promoted alternatives to screen time, and online support were also provided as part of the study.
The primary outcome measure was the children’s BMI. This was measured at baseline and, again, at a 24-month follow-up. Height and weight data were used to convert to z-scores. Secondary outcomes included: Waist circumference and percentage of body fat assessed using a bioelectrical impedance monitor; self-reported measures of physical activity, total sedentary time, and sleep. Children’s activity and sedentary time were measured with the Multimedia Activity Recall for Children and Adolescents (MARCA). The MARCA tracks the time spent in each activity and determines the amount of total time spent and the intensity levels of physical activity, including self-reported measures of daily physical activity (PA; including minutes of total PA, light intensity PA [LPA] and moderate-to-vigorous PA [MVPA]), total sedentary time (minutes), and sleep. Dietary intake was also measured using the Food Frequency Questionnaire (FFQ), which asks children to report how often and how much they have eaten of foods over the prior 4-week period. Finally, enjoyment of physical activity and sedentary behavior were also measured and the 14-item Physical Activity Enjoyment Scale was used to measure these.
At 24 weeks, the mean change in the primary outcome, zBMI, was .03 in the intervention group and .05 in the control group. This difference was not significant (p=0.64).There was also no significant difference found among secondary outcomes, of BMI, weight circumference, fat free mass, fat mass, and percentage of body fat, sedentary behavior, or sleep. Though not significant, both groups reported decreased sedentary time at 24 weeks. Perhaps most interestingly, nearly half (46%) of the study participants reported never using the intervention to budget their child’s screen time. It is not surprising, then, that children’s behaviors did not change when there was little observed change in their parents’ behaviors.

Citations:

Kong, A., & Buscemi, J. (2016). Hip-Hop to Health Jr. Randomized Effectiveness Trial: 1-Year Follow-up Results. American Journal of Preventative Medicine, 50(2), 136-144. http://dx.doi.org/10.1016/j.amepre.2015.07.008

Allen, M.S., & Vella, S.A. (2015). Sport participation, screen time, and personality trait development during childhood. British Journal of Developmental Psychology, 33, 375-390. Retrieved from: http://web.a.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=476b08f7-f117-4424-9446-9af5378993d7%40sessionmgr4009&vid=6&hid=4201

Madison, R., Marsh, S. (2014) Screen-Time Weight-loss Intervention Targeting Children at Home (SWITCH): a randomized controlled trial. International Journal of Behavioral Nutrition and Physical Activity, 11(111). Retrieved from: http://download.springer.com/static/pdf/31/art%253A10.1186%252Fs12966-014-0111-2.pdf?originUrl=http%3A%2F%2Fijbnpa.biomedcentral.com%2Farticle%2F10.1186%2Fs12966-014-0111-2&token2=exp=1475546970~acl=%2Fstatic%2Fpdf%2F31%2Fart%25253A10.1186%25252Fs12966-014-0111-2.pdf*~hmac=388d6e2c10f9d064df26cc6fb7ceecdbe8628bfb76a51fc56034cfc6c70ed79a

Part 3: Intervention Fit

SMART Objectives

Children aged 4-8 years in the Athens-Clark County school district will show reduced sedentary screen time by 20% or less than 1.5 hours per day by the end of the intervention period.
Participants will increase daily intake of fruits and vegetables by 20% by the completion of the intervention
Parents/caregivers will demonstrate increased knowledge of healthy eating, physical activity, and screen time habits through completion of a self-assement at the conclusion of the six-month program.
The percentage of participants in the obese or overweight condition will be reduced by 15% at the 6-month follow-up.
By month four of the intervention, 80% of parents will read the weekly newsletter.
80% of children will engage in 60 minutes of moderate to vigorous physical activity five days per week by the end of the intervention period.
75% of parents will attend 2 out of 3 parent education sessions over the course of the intervention period.


Inputs/Resources	Activities	Outputs	Short-term outcomes	Intermediate Outcomes	Long-term Outcomes
Training manuals/Curriculum Educator and parent trainers Media (posters encouraging active alternatives to screen-time) Federal/ local grants Parent newsletters promoting healthy behaviors	Classroom based education Family social support / education Train teachers in curriculum	24, 20 minute in school educational lessons 3 trained parent educators/ teacher trainers goal setting /monitoring workbooks 3 parent education sessions	Increased knowledge among parents and caregivers Motivation to make behavior changes	Reduced screen-time Increase in activity levels Increase in consumption of healthy foods	Improvement or maintenance of BMI Improved diet and exercise habits Improved aerobic fitness

This model will be effective because its focus is early education and intervention during a developmental phase when individuals are more open to change. Education is the first step in making sustainable change. Children aged 4 to 8 are still forming habits and routines, and, thus, may be more pliant when it comes to changing nutritional and exercise habits. These routines will shape their actions and attitudes surrounding behaviors. By reaching parents through both regular educational sessions and newsletters, they will develop or improve on existing habits that will translate to positive behavior changes. In addition to parent education, in school lessons will target children directly. To put it simply, when you know better, you do better. Educating children through hands-on, interactive lessons will empower them to make better decisions regarding screen time, physical activity, and eating habits. According to the CDC, School Health Guidelines to Promote Healthy Eating and Physical Activity, schools have a critical role in establishing policies and practices to support healthy behaviors and to provide students with opportunities to learn and practice these healthy behaviors. By targeting both children and their caregivers using multiple strategies for delivery, this intervention is designed to impact multiple contexts of the developing child’s environment

Citation:

School Health Guidelines to Promote Healthy Eating and Physical Activity. (2011).

Retrieved December 03, 2016, from

http://www.cdc.gov/MMWR/preview/mmwrhtml/rr6005a1.htm

Limitations

This intervention focuses on reducing sedentary screen time and improving healthy eating and physical activity habits among Athens-Clarke County students aged 4 – 8. Due to the age of the participants, as well as the target demographic and geographic area, this intervention has several potential limitations. First, caregiver participation is crucial for success, as caregivers have direct control over their child’s access to screen time and diet, as well as the majority of control over physical activity. Athens-Clarke County is a Title 1 school district with a disproportionate number of low income families – over 35% according to US Census data. Over 60% of Athens-Clarke County students fall into the category of low socio-economic status. This might present parents with the challenge of access to and affordability of healthy food options. In addition, students from low-SES backgrounds are at higher risk for overweight in part because of higher levels of television viewing (Morgenstern, 2009). The target population may experience higher than normal television viewing at baseline and, therefore, might be more resistant to modify current habits. Not knowing what barriers caregivers might be facing is another limitation. Are primary caregivers in control of screen time and healthy eating and physical activity habits, or are the children being monitored by older siblings or relatives after school and on the weekends? Not knowing these answers may limit the interpretation of our findings.Another limitation might be delivery of curriculum. Although teachers will be given training on implementation, there could be inconsistency in delivery. Delivering the newsletters via email will allow for tracking to measure what amount of parents open (and read) the emails, however, this delivery method might not be ideal for all caregivers as limited access to computers might be a factor.

Data

Information to be collected :

Number of student lessons delivered
Number of newsletter views
Number of parent education sessions delivered
Hours of daily screen time
Hours of daily physical activity
Height, weight / BMI

Process Evaluation:

To be certain that the intervention was delivered as intended teachers will be responsible for tracking the 24, 20 minutes lessons delivered, by reporting the date and length of each lesson. In addition instructional sessions will be observed through random selection to assess that they are being delivered as designed. Software used to track newsletter views will be utilized in delivering weekly newsletters to ensure parents are opening the email. Sign-in for three parent education sessions will be required to determine the number of attendees and if the goal of 75% participation was achieved. A self-assessment exit interview will be given to assess the level of understanding and comprehension of the material covered. Program fidelity will be assessed by determining the degree to which the instructors delivered the workshops as intended. This will be done through observational measures as well as an assessment of outcomes through the particpant self-assement. Goal setting and monitoring work books will track and measure screen time, diet and physical activity. These will be utilized not only as a tool for behavior change, but also will be turned in and reviewed to assess the effectiveness of the program delivery. If effective, we expect participants would experience at least 20% reduction in screen time, coupled with a 20% increase in fruit and vegetable consumption. Furthermore, we expect an effective intervention will result in 80% of participants engaging in 60 minutes of moderate to vigorous physical activity five days per week. Prior to implementation (baseline), children will be weighed using a digital scale and measured using a stadiometer to determine their starting BMI. Children will be measured and weighed again at three months to monitor progress and finally at six month follow up to determine if there was a change in BMI.

Part 4: Reflection

Oftentimes when working with communities, the initial plan is not what ultimately happens. What would your second choice strategy be for your identified behavior and community? Why would you choose this strategy? In other words, in what ways would this strategy also address the needs of the community based on your assessment for Part 1? (25 points)

The initial intervention aimed to reduce recreational sedentary screen time, increase physical activity, improve diet, and improve or maintain weight-related outcomes among children. The proposed intervention focused on low-income schools in Athens-Clarke county where the perceived need is high. If this intervention failed to elicit the desired outcomes in this population, I would narrow the focus to strictly school-based nutrition and exercise education.

There is evidence that well-designed nutrition education programs effectively increase consumption of fruits and vegetables at home (Long, 2013). With this in mind, I would implement a school-based program that provides dedicated instruction time for 20 minutes twice per week for one year on topics in nutrition and exercise. An interactive curriculum delivered by classroom teachers would include age-appropriate nutrition guidelines with workbook-based activities for student participation. In addition, physical activity guidelines and ideas would be discussed and demonstrated to encourage physically active time and reduce sedentary time. Physical Education classes are only offered once per week in Athens-Clarke County. By providing students with additional strategies for how to be active outside of scheduled, structured activities, they will be more likely to experience behavioral changes.

This intervention would serve the community by continuing to promote healthy habits and educate children about the importance of healthy nutrition and exercise routines.

Long, V. (2013). Supplemental Nutrition Assistance Program Education And Evaluation Study.

United States Department of Agriculture. Retrieved From:

http://www.fns.usda.gov/sites/default/files/SNAPEdWaveII_Summary.pdf

Reflect on how you may use the Community Guide, Nutrition Education Library, and other resources in the future. What did you like about these resources? What didn’t you like? Provide suggestions on how you would make the sites easier for practitioners to use. (20 points)

I found The Community Guide to be very user-friendly and accessible. The information was well-organized by topic, making it very easy to locate information that was associated with my areas of interest. Additionally, the search filters provide an accessible and comprehensive way to locate specific results, making it easy to narrow down the topic search.

I also really found it useful to have the capability of filtering by strategy. This allows the user to determine where the information might be most useful and applicable without having to sift through all of it. As a new user of this tool, I found it to be intuitive and reasonably easy to navigate.

If I were to recommend changes to this resource, I would add a searchable index or glossary of terms that includes technical definitions. This would enable those with minimal expertise to enjoy greater use and potentially greater application of the information in broader audiences. For example, high school students or community leaders without technical training but who may have interest in health intervention topics might make better use of the information if they have verifiable and accessible definitions of the more technical terminology from the Guide.