Obesity: Behavioral Interventions that Aim to Reduce Recreational Sedentary Screen Time Among Children

Summary of CPSTF Finding

The Community Preventive Services Task Force (CPSTF) recommends behavioral interventions to reduce recreational sedentary screen time among children ages 13 years and younger. Recreational screen time does not include school- or work-related use.

Intervention

These interventions teach children behavioral self-management skills to help them start or maintain behavior change.

Behavioral screen time interventions are classified into two types:

  1. Screen-time-only interventions focus on reducing recreational sedentary screen time.
  2. Screen-time-plus interventions focus on reducing recreational sedentary screen time and increasing physical activity or improving diet.

Interventions use one or more of the following components:

  • Classroom-based education
  • Tracking and monitoring
  • Coaching or counseling sessions
  • Family-based or peer social support

Interventions also may include one or more additional components such as use of an electronic monitoring device to limit screen time, a TV Turnoff Challenge, screen time contingent on physical activity, or small media.

CPSTF Finding and Rationale Statement

Read the full CPSTF Finding and Rationale Statement for details including implementation issues, possible added benefits, potential harms, and evidence gaps.

About The Systematic Review

The CPSTF finding is based on evidence from a Community Guide systematic review completed in 2008 (7 studies with 9 study arms, search period 1966 July 2007) combined with an updated search for evidence in 2013 (42 studies with 53 study arms, search period April 2007 June 2013).

The systematic review was conducted on behalf of the CPSTF by a team of specialists in systematic review methods, and in research, practice, and policy related to obesity prevention and control.

This finding updates and replaces the 2008 CPSTF findings on Behavioral Interventions to Reduce Screen Time and Mass Media Interventions to Reduce Screen Time and replaces the 2000 review on Behavioral and Social Approaches to Increase Physical Activity: Classroom-Based Health Education to Reduce TV Viewing and Video Game Playing.

Context

Childhood obesity has been positively associated with time spent watching TV (Marshall, et al. 2004, Tremblay, et al. 2011). In the United States, children ages 8 18 years report an average of 7 hours of screen time per day, of which 4.5 hours are spent watching TV content such as TV programs, DVDs, or movies, viewed on a TV, computer, cell phone, or other device (Rideout, et al. 2010). Children ages 5 years and younger spend an average of 2 hours per day with screen media (i.e., TV, DVDs, videos, video/computer games), of which approximately 1.5 hours are spent watching TV or videos (Rideout 2011).

Summary of Results

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement.

The systematic review included 49 studies with 62 study arms.

  • Screen Time Outcomes
    • The amount of time spent on any screen decreased by a median of 26.4 minutes/day (34 study arms)
      • Screen-time-only interventions: median decrease of 82.2 minutes/day (11 study arms)
      • Screen-time-plus interventions: median decrease of 21.6 minutes/day (23 study arms)
  • Physical Activity Outcomes
    • Accelerometer counts measured physical activity through a small monitor worn with a belt clip.
      • Screen-time-only interventions: no study arms
      • Screen-time-plus interventions
        • Screen time contingent on physical activity: median increase of 130.0 counts per day (3 study arms)
        • Screen time not contingent on physical activity: median increase of 66.0 counts per day (4 study arms)
        • Screen time not contingent on physical activity: median increase of 3.6 counts per minute (3 study arms)
      • Small, positive effects were reported for other physical activity outcomes (e.g., pedometer steps of physical activity, score on a fitness test, and duration of physical activity).
    • Dietary Outcomes
      • Total energy intake (kcal/day)
        • Screen-time-only interventions: decrease of 75 calories/day (1 study arm)
        • Screen-time-plus interventions: decrease of 117.9 calories /day (5 study arms)
      • Small, positive effects were reported for other dietary outcomes (e.g., eating meals or snacking with the TV on, daily snack intake, sugar-sweetened beverage intake, and fruit and vegetable intake).
    • Weight-Related Outcomes
      • Body mass index (BMI): median decrease of 0.09 kg/m2 (15 study arms)
      • BMI Z-score: median decrease of 0.13 (14 study arms)
        • BMI Z-score is a standard deviation score that indicates how a child’s BMI compares to the average for their age group and sex.
    • Obesity Prevalence
      • Proportion of participants who are obese: median decrease of 2.3 percentage points (14 study arms)

Summary of Economic Evidence

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement.

The economic review included three models from two studies that were based on randomized controlled trials included in the effectiveness review. A general conclusion about cost-effectiveness could not be determined because results from this small body of evidence were mixed. Monetary values are reported in 2013 U.S. dollars.

Intervention cost:

Intervention cost included the cost of measuring and tracking devices, staff time in counseling and education sessions, training, educational materials, and supplies.

  • The cost per person per year was $43 for a screen-time-plus intervention and $248 for a screen-time-only intervention.
  • The higher cost for the screen-time-only intervention was partially explained by the inclusion of an electronic monitoring device, a greater number of sessions, and labor costs associated with tracking and monitoring outcomes.

Healthcare Cost and QALY:

Healthcare costs are avoided and quality-adjusted life years (QALYs) are saved when the intervention reduces illness and death associated with overweight-related diseases and conditions.

  • The models used in both the screen-time-plus and screen-time-only studies drew from longitudinal data of U.S national surveys to estimate that each prevented case of overweight in adulthood would avert about $4000 in healthcare costs and increase QALYs saved by 0.71.

Cost-effectiveness:

Cost-effectiveness is measured as net cost (intervention cost minus healthcare cost avoided) per QALY saved. An intervention is considered cost-effective when cost-effectiveness is less than or equal to a conservative threshold of $50,000 per QALY saved.

  • Both studies evaluated the models based on a sensitivity analysis of key determinant variables of cost-effectiveness: size of intervention group; intervention effectiveness; transition of weight status to adulthood; intervention cost per person; and 50% relapse to overweight.
  • Both studies modeled the screen-time-plus intervention, finding it to be cost-effective.
    • Cost per QALY saved ranged from $7,500 to $22,900 depending on assumptions made.
  • One study modeled the screen-time-only intervention and found the intervention was not cost-effective.
    • Cost per QALY saved ranged from $26,000 to $115,000 depending on assumptions made.

Applicability

Based on results for interventions in different settings and populations, findings should be applicable to the following:
  • The United States or other high- or medium-income countries
  • Children ages 13 years and younger
  • Males and females
  • Different racial and ethnic populations
  • All socioeconomic levels
  • Normal weight, overweight, and obese populations
  • Urban and suburban settings

Evidence Gaps

The CPSTF identified several areas that have limited information. Additional research and evaluation could help answer the following questions and fill remaining gaps in the evidence base. (What are evidence gaps?)
  • Which combinations of intervention components are most effective? Which components are critical to success?
  • Are interventions effective with teens older than 13 years of age and with adults?
  • Are interventions effective in rural settings?
  • What are other benefits and implications of reduced screen time? For example, does a reduction in screen time mean other sedentary behaviors will be substituted (e.g., reading for leisure, listening to music, time spent on homework)? And, do reductions in screen time lead to other health benefits, such as improved sleep quality?

Study Characteristics

  • Studies included randomized controlled trials (RCT) or group RCTs (37 studies), single group before-after studies (5 studies), before-after with a comparison group (4 studies), and a non-randomized trial (1 study).
  • Studies were conducted in the United States (30 studies), Australia (6 studies), the United Kingdom (4 studies), Canada (2 studies), France (1 study), the Netherlands (1 study), New Zealand (1 study), Sweden (1 study), and Switzerland (1 study).
  • Studies mostly targeted children ages 13 years and younger (46 studies). No studies targeted adolescents ages 14-18 years.
  • Nine studies were conducted among populations with lower economic status. Of these, three studies targeted low-income African-American children, two studies targeted Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participants, one study targeted Head Start program participants, and three studies targeted disadvantaged children.
  • Six studies targeted overweight or obese populations.
  • Family-based social support was the most common intervention component.
  • Evaluated programs were most commonly implemented in schools (20 studies), and of these, 90% were screen-time-plus interventions.

Analytic Framework

Effectiveness Review

Analytic Framework

When starting an effectiveness review, the systematic review team develops an analytic framework. The analytic framework illustrates how the intervention approach is thought to affect public health. It guides the search for evidence and may be used to summarize the evidence collected. The analytic framework often includes intermediate outcomes, potential effect modifiers, potential harms, and potential additional benefits.

Economic Review

No content is available for this section.

Summary Evidence Table

Included Studies

The number of studies and publications do not always correspond (e.g., a publication may include several studies or one study may be explained in several publications).

Effectiveness Review

Screen-Time-Only

Birken CS, Maguire J, Mekky M, Manlhiot C, Beck CE, DeGroot J, et al. Office-based randomized controlled trial to reduce screen time in preschool children. Pediatrics 2012;130(6):1110-1115.

Epstein LH, Roemmich JN, Robinson JL, Paluch RA, Winiewicz DD, Fuerch JH, et al. A randomized trial of the effects of reducing television viewing and computer use on body mass index in young children. Archives of Pediatrics & Adolescent Medicine 2008;162(3):239-45.

Escobar-Chaves SL, Markham CM, Addy RC, Greisinger A, Murray NG, Brehm B. The Fun Families Study: intervention to reduce children’s TV viewing. In: Obesity (Silver Spring, Md.); 2010. p. S99-101.

Ford BS, McDonald TE, Owens AS, Robinson TN. Primary care interventions to reduce television viewing in African-American children. American Journal of Preventive Medicine 2002;22(2):106-9.

Gorin A, Raynor H, Chula Maguire K, Wing R. Decreasing household television time: a pilot study of a combined behavioral and environmental intervention. Behavioral Interventions 2006;21(4):273-280.

*Johnson DB, Birkett D, Evens C, Pickering S. Statewide intervention to reduce television viewing in WIC clients and staff. American Journal of Health Promotion 2005;19(6):418-21.

Ni Mhurchu C, Roberts V, Maddison R, Dorey E, Jiang Y, Jull A, et al. Effect of electronic time monitors on children’s television watching: pilot trial of a home-based intervention. Preventive Medicine 2009;49(5):413-7.

Otten JJ, Jones KE, Littenberg B, Harvey-Berino J. Effects of television viewing reduction on energy intake and expenditure in overweight and obese adults: a randomized controlled trial. Archives of Internal Medicine; 2009. p. 2109-15.

*Robinson TN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA 1999;282(16):1561-7.

Robinson TN, Borzekowski DL. Effects of the SMART classroom curriculum to reduce child and family screen time. Journal of Communication 2006;56(1):1-26.

Todd MK, Reis-Bergan MJ, Sidman CL, Flohr JA, Jameson-Walker K, Spicer-Bartolau T, et al. Effect of a family-based intervention on electronic media use and body composition among boys aged 8–11 years: a pilot study. Journal of Child Health Care 2008;12(4):344-58.

Zimmerman FJ, Ortiz SE, Christakis DA, Elkun D. The value of social-cognitive theory to reducing preschool TV viewing: A pilot randomized trial. Preventive Medicine 2012;54(3-4):212-8.

Screen-Time-Plus

Branscum PW. Designing and evaluating an after-school social cognitive theory based comic book intervention for the prevention of childhood obesity among elementary aged school children. Dissertation Abstracts International Section A: Humanities and Social Sciences 2012;73(1-A):87.

Campbell KJ, Lioret S, McNaughton SA, Crawford DA, Salmon J, Ball K, et al. A parent-focused intervention to reduce infant obesity risk behaviors: A randomized trial. Pediatrics 2013;131(4):652-60.

Davison KK, Jurkowski JM, Li K, Kranz S, Lawson HA. A childhood obesity intervention developed by families for families: Results from a pilot study. International Journal of Behavioral Nutrition and Physical Activity 2013;10(3).

de Silva-Sanigorski AM, Bell AC, Kremer P, Nichols M, Crellin M, Smith M, et al. Reducing obesity in early childhood: results from Romp & Chomp, an Australian community-wide intervention program. American Journal of Clinical Nutrition 2010;91(4):831-40.

*Dennison BA, Russo TJ, Burdick PA, Jenkins PL. An intervention to reduce television viewing by preschool children. Archives of Pediatrics & Adolescent Medicine 2004;158(2):170-6.

*Epstein LH, Paluch RA, Gordy CC, Dorn J. Decreasing sedentary behaviors in treating pediatric obesity. Archives of Pediatrics & Adolescent Medicine 2000;154(3):220-6.

*Epstein LH, Valoski AM, Vara LS, McCurley J, Wisniewski L, Kalarchian MA, et al. Effects of decreasing sedentary behavior and increasing activity on weight change in obese children. Health Psychology 1995;14(2):109-15.

Ezendam NP, Brug J, Oenema A. Evaluation of the web-based computer-tailored FATaintPHAT intervention to promote energy balance among adolescents: results from a school cluster randomized trial. Archives of Pediatrics & Adolescent Medicine 2012;166(3):248-55.

French SA, Gerlach AF, Mitchell NR, Hannan PJ, Welsh EM. Household obesity prevention: take action- a group-randomized trial. Obesity 2011;19(10):2082-8.

Gentile DA, Welk G, Eisenmann JC, Reimer RA, Walsh DA, Russell DW, et al. Evaluation of a multiple ecological level child obesity prevention program: Switch what you do, view, and chew. BMC Medicine 2009;7:49.

Goldfield GS, Mallory R, Parker T, Cunningham T, Legg C, Lumb A, et al. Effects of open-loop feedback on physical activity and television viewing in overweight and obese children: a randomized, controlled trial. Pediatrics 2006(1):e157-66.

*Gortmaker SL, Cheung LWY, Peterson KE, Chomitz G, Cradle JH, Dart H, et al. Impact of a school-based interdisciplinary intervention on diet and physical activity among urban primary school children: Eat well and keep moving. Archives of Pediatrics & Adolescent Medicine 1999;153(9):975-83.

*Gortmaker SL, Peterson K, Wiecha J, Sobol AM, Dixit S, Fox MK, et al. Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health. Archives of Pediatrics & Adolescent Medicine 1999(4):409-18.

Hardy LL, King L, Kelly B, Farrell L, Howlett S. Munch and Move: evaluation of a preschool healthy eating and movement skill program. International Journal of Behavioral Nutrition & Physical Activity 2010;7:80.

Harrison M, Burns CF, McGuinness M, Heslin J, Murphy NM. Influence of a health education intervention on physical activity and screen time in primary school children: ‘Switch Off-Get Active’. Journal of Science and Medicine in Sport 2006;9(5):388-94.

Jago R, Sebire SJ, Turner KM, Bentley GF, Goodred JK, Fox KR, et al. Feasibility trial evaluation of a physical activity and screen-viewing course for parents of 6 to 8 year-old children: Teamplay. International Journal of Behavioral Nutrition and Physical Activity 2013;10(31).

Johnson B, Kremer P, Swinburn B, de Silva-Sanigorski A. Multilevel analysis of the Be Active Eat Well intervention: environmental and behavioural influences on reductions in child obesity risk. International Journal of Obesity 2012;36(7):901-7.

Jouret B, Ahluwalia N, Dupuy M, Cristini C, Negre-Pages L, Grandjean H, et al. Prevention of overweight in preschool children: results of kindergarten-based interventions. International Journal of Obesity 2009;33(10):1075-83.

Lloyd JJ, Wyatt KM, Creanor S. Behavioural and weight status outcomes from an exploratory trial of the Healthy Lifestyles Programme (HeLP): a novel school-based obesity prevention programme. BMJ Open 2012;2(3).

Marcus C, Nyberg G, Nordenfelt A, Karpmyr M, Kowalski J, Ekelund U. A 4-year, cluster-randomized, controlled childhood obesity prevention study: STOPP. International Journal of Obesity 2009;33(4):408-17.

O’Connor T, Hilmers A, Watson K, Baranowski T, Giardino A. Feasibility of an obesity intervention for paediatric primary care targeting parenting and children: Helping HAND. Child: Care, Health and Development 2013;39(1):141-9.

Patrick K, Calfas KJ, Norman GJ, Zabinski MF, Sallis JF, Rupp J, et al. Randomized controlled trial of a primary care and home-based intervention for physical activity and nutrition behaviors: PACE+ for adolescents. Archives of Pediatrics & Adolescent Medicine 2006;160(2):128-36.

Puder JJ, Marques-Vidal P, Schindler C, Zahner L, Niederer I, Burgi F, et al. Effect of multidimensional lifestyle intervention on fitness and adiposity in predominantly migrant preschool children (Ballabeina): cluster randomised controlled trial. BMJ 2011;343:d6195.

Riggs NR, Sakuma K-LK, Pentz MA. Preventing risk for obesity by promoting self-regulation and decision-making skills: Pilot results from the PATHWAYS to health program (PATHWAYS). Evaluation Review 2007;31(3):287-310.

Robinson TN, Killen JD, Kraemer HC, Wilson DM, Matheson DM, Haskell WL, et al. Dance and reducing television viewing to prevent weight gain in African-American girls: the Stanford GEMS pilot study. Ethnicity and Disease 2003;13(1 SUPPL. 1):S1.

Robinson TN, Matheson DM, Kraemer HC, Wilson DM, Obarzanek E, Thompson NS, et al. A randomized controlled trial of culturally tailored dance and reducing screen time to prevent weight gain in low-income African American girls: Stanford GEMS. Archives of Pediatrics & Adolescent Medicine 2010;164(11):995-1004.

Roemmich JN, Gurgol CM, Epstein LH. Open-loop feedback increases physical activity of youth. Medicine and Science in Sports and Exercise 2004(4):668-73.

Roemmich JN, Lobarinas CL, Barkley JE, White TM, Paluch R, Epstein LH. Use of an open-loop system to increase physical activity. Pediatric Exercise Science 2012;24(3):384-98.

Salmon J, Ball K, Hume C, Booth M, Crawford D. Outcomes of a group-randomized trial to prevent excess weight gain, reduce screen behaviours and promote physical activity in 10-year-old children: Switch-play. International Journal of Obesity 2008;32(4):601-12.

Salmon J, Jorna M, Hume C, Arundell L, Chahine N, Tienstra M, et al. A translational research intervention to reduce screen behaviours and promote physical activity among children: Switch-2-Activity. Health Promotion International 2011;26(3):311-21.

Sanigorski AM, Bell AC, Kremer PJ, Cuttler R, Swinburn BA. Reducing unhealthy weight gain in children through community capacity-building: results of a quasi-experimental intervention program, Be Active Eat Well. International Journal of Obesity 2008;32(7):1060-7.

Shapiro JR, Bauer S, Hamer RM, Kordy H, Ward D, Bulik CM. Use of text messaging for monitoring sugar-sweetened beverages, physical activity, and screen time in children: A pilot study. Journal of Nutrition Education and Behavior 2008;40(6):385-91.

Spring B, Schneider K, McFadden HG, Vaughn J, Kozak AT, Smith M, et al. Multiple behavior changes in diet and activity: a randomized controlled trial using mobile technology. Archives Internal Medicine 2012;172(10):789-96.

Spruijt-Metz D, Nguyen-Michel ST, Goran MI, Chou CP, Huang TT. Reducing sedentary behavior in minority girls via a theory-based, tailored classroom media intervention. International Journal of Pediatric Obesity 2008;3(4):240-8.

Taveras EM, Gortmaker SL, Hohman KH, Horan CM, Kleinman KP, Mitchell K, et al. Randomized controlled trial to improve primary care to prevent and manage childhood obesity: the High Five for Kids study. Archives of Pediatrics & Adolescent Medicine 2011;165(8):714-22.

Tucker S, Lanningham-Foster L, Murphy J, Olsen G, Orth K, Voss J, et al. A school based community partnership for promoting healthy habits for life. Journal of Community Health 2011;36(3):414-22.

Warren JM, Henry CJ, Lightowler HJ, Bradshaw SM, Perwaiz S. Evaluation of a pilot school programme aimed at the prevention of obesity in children. Health Promotion International 2003;18(4):287-96.

Whaley SE, McGregor S, Jiang L, Gomez J, Harrison G, Jenks E. A WIC-based intervention to prevent early childhood overweight. Journal of Nutrition Education and Behavior 2010;42(3, Suppl):S47-51.

* Identified in the Original Search Period (1966-July 2007)

Economic Review

Dalziel K, Segal L, Mortimer D. Risk Factor Study – How to reduce the burden of harm from poor nutrition, tobacco smoking, physical inactivity and alcohol misuse: cost-utility analysis of 9 multi-risk factor interventions: Monash University, Centre for Health Economics; 2005.

Wang LY, Yang Q, Lowry R, Wechsler H. Economic analysis of a school-based obesity prevention program. Obesity Research 2003;11(11):1313-24.

Economic Studies Linked with the Effectiveness Review

Gortmaker SL, Peterson K, Wiecha J, Sobol AM, Dixit S, Fox MK, et al. Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health. Arch Pediatr Adolesc Med 1999(4):409-418.

Robinson TN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA 1999;282(16):1561-7.

Additional Materials

Implementation Resource

Rural Health Information Hub, Obesity Prevention Toolkit
This toolkit compiles information, resources, and best practices to support development and implementation of obesity prevention programs in rural communities. Modules include program models, implementation and evaluation resources, and funding and dissemination strategies.

Search Strategies

Effectiveness Review

This literature search was performed to provide a systematic review of the literature to the Guide to Community Preventive Services. The purpose of the search was to review the literature on the effectiveness of reduced screen time for obesity prevention and control.

For the updated search, the following five bibliographic databases were searched between April 2007 and June 2013, using the search terms listed below.

  • CINAHL
  • Cochrane
  • Embase (EBSCO)
  • Medline (OVID)
  • PsycINFO

The databases searched covered publications in medical and social sciences, behavioral sciences, and nursing and allied health. The types of documents retrieved by the search included journal articles, books, book chapters, reports, and conference papers.

Following are search strategies specific for Medline. Search terms and search strategies were adjusted to each database, based on controlled and uncontrolled vocabularies and search software.

Medline (OVID)
  1. (“screen time” or “screen use” or “screen usage”).tw.
  2. television/
  3. video games/
  4. (vcr or dvd$).tw.
  5. ((television or tv) adj (view$ or watch$)).tw.
  6. ((view$ or watch$) adj (television or tv)).tw.
  7. ((video game$ or videogame$) adj play$).tw.
  8. (play$ adj (video game$ or videogame$)).tw.
  9. or/1-8
  10. 9 and health education/
  11. 9 and “health education”.tw.
  12. 9 and exp health promotion/
  13. 9 and intervention studies/
  14. 9 and exp health behavior/
  15. 9 and life style/
  16. 9 and interventions$.mp.
  17. 9 and (trial$ or study or studies).mp.
  18. 9 and program evaluation/
  19. 9 and pc.fs.
  20. or/10-19
  21. 20 and (exp overweight/ or exp obesity/ or body mass index/ or skinfold thickness/ or waist-hip ratio/ or bmi.tw. or obes$.tw. or weight$.hw,tw. or body fat.tw. or overweight.mp.)
  22. 20 and (physical activity.tw. or motor activity/ or exercise$.mp. or physical fitness/ or physical fitness/ or “physical education and training”/ or exp sports/)
  23. 20 and (diet$ or nutrition$ or food$).hw,tw.
  24. 20 and ((reduc$ or restrict$ or decreas$ or limit$) and (television or video$ or screen)).mp.
  25. or/21-24
  26. (computers/ or user-computer interface/ or attitude to computers/ or internet.mp.) and (exp child/ or adolescent/ or exp adult/)
  27. 26 and health education/
  28. 26 and “health education”.tw.
  29. 26 and intervention studies/
  30. 26 and exp health behavior/
  31. 26 and life style/
  32. 26 and intervention$.mp.
  33. 26 and (trial$ or study or studies).mp.
  34. 26 and program evaluation/
  35. 26 and pc.fs.
  36. 26 and exp health promotion/
  37. or/27-36
  38. 37 and (exp overweight/ or exp obesity/ or body mass index/ or skinfold thickness/ or waist-hip ratio/ or bmi.tw. or obes$.tw. or weight$.hw,tw. or body fat.tw. or overweight.mp.)
  39. 37 and (physical activity.tw. or motor activity/ or exercise$.mp. or physical fitness/ or “physical education and training”/ or exp sports/)
  40. 37 and (diet$ or nutrition$ or food$).hw,tw.
  41. 37 and ((reduc$ or restrict$ or decreas$ or limit$) and (computer$ or internet$)).mp.
  42. or/38-41
  43. exp mass media/ or “mass media”.tw. or billboard$.tw. or exp serial publications/
  44. 43 and ((reduc$ or restrict$ or decreas$ or limit$) and (television or video$ or screen or computer$ or internet)).mp.
  45. 44 and (exp overweight/ or exp obesity/ or body mass index/ or skinfold thickness/ or waist-hip ratio/ or bmi.tw. or obes$.tw. or weight$.hw,tw. or body fat.tw. or overweight.mp.)
  46. 44 and (physical activity.tw. or motor activity/ or exercise$.mp. or physical fitness/ or “physical education and training”/ or exp sports/)
  47. 44 and (diet$ or nutrition$ or food$).hw,tw.
  48. or/45-47
  49. 25 or 42 or 48
  50. limit 49 to (English language and yr=”2007 -Current”) 5739

Economic Review

Two bibliographic databases (EconLit and CRD-York) were searched during January 2014, using the search strategies listed below. The years of publication searched were 1966 2014. The databases searched covered publications in economics and evidence-based medicine. The types of documents searched in the databases included journal articles, systematic reviews, economic evaluations, books, book chapters, reports, dissertations, and conference papers.

Database: CRD-York NHS EED NHS EED

CRD assessed economic evaluation
Date Searched: 1/23/2014
Results: 20

Search Strategy:
((tv or television or videogame* or video game or dvd* or video games or screen time or screen usage or screen use or vcr) AND (obese or obesity or fat or body mass or waist or overweight or skinfold or weight* or bmi or obeseness )) and ((Economic evaluation:ZDT and Bibliographic:ZPS) OR (Economic evaluation:ZDT and Abstract:ZPS)) IN NHSEED FROM 1966 TO 2014

Database: EconLit (EBSCOHost)

Date Searched: 1/23/2014
Results: 187

Search Strategy:

S3
S1 AND S2
(187)
S2
( television or “video game” or “video games” or “screen time” or “screen usage” or vcr or dvd or dvds or “screen use” )
Limiters – Published Date: 19660101-20141231
S1
(diet* or nutrition* or food* or obese or obesity or waist or exercise or fitness or skinfold or fat or overweight or weight or “body mass” or bmi or overweight or “physical education” or sports)
Limiters – Published Date: 19660101-20141231
Search modes – Boolean/Phrase

Review References

American Academy of Pediatrics. 2001. American Academy of Pediatrics. Children, adolescents, and television. Pediatrics 107: 423-26

Marshall SJ, Biddle SJ, Gorely T, Cameron N, Murdey I. Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis. Int J Obes Relat Metab Disord 2004;28: 1238-46.

Rideout V. Zero to Eight: Children’s Media Use in America. Common Sense Media; 2011.

Rideout VJ, Foehr UG, Roberts DF. GENERATION M2: Media in the lives of 8- to 18-Year-Olds. Menlo Park (CA): The Henry J. Kaiser Family Foundation; 2010.

Salmon J, Jorna M, Hume C, Arundell L, Chahine N, Tienstra M, et al. A translational research intervention to reduce screen behaviours and promote physical activity among children: Switch-2-Activity. Health Promotion International 2011;26(3):311-321.

Tremblay MS, LeBlanc AG, Kho ME, Saunders TJ, Larouche R, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int J Behav Nutr Phys Act 2011;8:98.

Considerations for Implementation

The following considerations are drawn from studies included in the evidence review, the broader literature, and expert opinion.
  • Family-based social support was the most common intervention component. This highlights the importance of family and parental support in changing sedentary screen time behavior among children.
    • Family-based social support, in combination with electronic monitoring devices, was found to be highly effective, especially in screen-time-only studies. Electronic monitoring devices, which allowed users to set time limits for TV, DVD, and/or videogame use, were distributed across all settings and usually installed at home by parents.
  • Availability of electronic monitoring devices for various digital media has increased in recent years. For example, parents can limit screen time through low-cost apps that can be installed on mobile devices, and some cable providers and e-readers offer time controls.
  • Many studies incorporated intervention materials into regular classroom curricula, and most U.S. programs trained existing classroom teachers to deliver the intervention. The review identified competing demands of other school subjects as a barrier to implementation. Teachers have suggested integrating the intervention into existing curricula (Salmon, et al. 2011).