Planned Missing Design in a School-Based Physical Activity Intervention for Early Adolescence

Christa L. Lilly^1, , Luciana C. Braga², Emily Jones³, Sean Bulger³, Kibum Cho³ and Eloise Elliott³

¹Department of Biostatistics, West Virginia University School of Public Health, Morgantown, WV, USA

²Department of Kinesiology, California State University Chico, Chico, CA, USA

³Department of Physical Education Teacher Education, West Virginia University College of Physical Activity and Sports Sciences, Morgantown, WV, USA

Cite this paper

Christa L. Lilly, Luciana C. Braga, Emily Jones, Sean Bulger, Kibum Cho and Eloise Elliott. Planned Missing Design in a School-Based Physical Activity Intervention for Early Adolescence. American Journal of Sports Science and Medicine. 2016; 4(4):83-93. doi: 10.12691/AJSSM-4-4-1

Abstract

Purpose: The purpose of this study is to present a longitudinal planned missing design used to conduct a physical activity intervention in public middle schools (6th – 8th grades) in a rural Appalachian county. Method: Program outcome measures were collected at 13 points, with 33% participant random selection, and complete measures of demographic and anthropometric variables. Results: Of the 4,621 randomly selected participants over the three-year span, missing after random selection was highest for pedometers (74.68%), but also high for PACER (44.47%) and 3DPAR (41.9%). No differences were found on demographic or anthropometric variables, suggesting missing completely at random (MCAR) data on the planned missing data. Participants with missing data after random selection were more likely to be older, male, and in the 8th grade, suggesting missing at random (MAR) data. Conclusions: Results suggest the use of the planned missing design allowed for the feasible evaluation of the intervention using modern missing data analysis to account for MCAR and MAR data.

Keywords

adolescents, physical activity, method

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Pate RR, Davis MG, Robinson TN, Stone EJ, McKenzie TL, Young JC, et al. Promoting physical activity in children and youth: A leadership role for schools. Circulation. 2006;114(11):1214-24.
[2]	Strong WB, Malina RM, Blimkie CJ, Daniels SR, Dishman RK, Gutin B, et al. Evidence based physical activity for school-age youth. Journal of Pediatrics. 2005;146(6):732-7.
[3]	Trost SG, Loprinzi PD. Exercise-promoting healthy lifestyles in children and adolescents. J Clin Lipidol. 2008;2(3):162-8.
[4]	Sallis JF, McKenzie TL, Beets MW, Beighle A, Erwin H, Lee S. Physical education's role in Public Health: Steps forward and backward over 20 years and HOPE for the future. Res Q Exercise Sport. 2012;83(2):125-35.
[5]	Brown T, Summerbell C. Systematic review of school-based interventions that focus on changing dietary intake and physical activity levels to prevent childhood obesity: An update to the obesity guidance produced by the National Institute for Health and Clinical Excellence. Obes Rev. 2009;10(1):110-41.
[6]	Dumith SC, Gigante DP, Domingues MR, Kohl HW, 3rd. Physical activity change during adolescence: A systematic review and a pooled analysis. International Journal of Epidemiology. 2011;40(3):685-98.
[7]	Sirard JR, Pate RR. Physical activity assessment in children and adolescents. Sports Medicine. 2001;31(6):439-54.
[8]	Scruggs PW. Middle school physical education physical activity quantification: A pedometer steps/min guideline. Res Q Exercise Sport. 2007;78(4):284-92.
[9]	Hohepa M, Schofield G, Kolt GS, Scragg R, Garrett N. Pedometer-determined physical activity levels of adolescents: differences by age, sex, time of week, and transportation mode to school. Journal of Physical Activity and Health. 2008;5 (Suppl. 1):S140-52.
[10]	Zhuang J, Chen P, Wang C, Huang L, Zhu Z, Zhang W, et al. Characteristics of missing physical activity data in children and youth. Res Q Exercise Sport. 2013;84 (Suppl. 2):S41-7.
[11]	Voss C, Sandercock G. Does the twenty meter shuttle-run test elicit maximal effort in 11- to 16-year-olds? Pediatric Exercise Science. 2009;21(1):55-62.
[12]	Pate RR, Ross R, Dowda M, Trost SG, Sirard JR. Validation of a 3-day physical activity recall instrument in female youth. Pediatric Exercise Science. 2003;15(3):257-65.
[13]	Mcmurray RG, Ring KB, Treuth MS, Welk GJ, Pate RR, Schmitz KH, et al. Comparison of two approaches to structured physical activity surveys for adolescents. Med Sci Sport Exer. 2004;36(12):2135-43.
[14]	McNamara E, Hudson Z, Taylor SJ. Measuring activity levels of young people: The validity of pedometers. British Medicine Bulletin. 2010;95:121-37.
[15]	Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581-90.
[16]	Enders CK. The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data. Psychol Methods. 2001;6(4):352-70.
[17]	Berk K. Computing for incomplete repeated measures. Biometrics. 1987;43(2):385-98.
[18]	Little RJ, Raghunathan T. On summary measures analysis of the linear mixed effects model for repeated measures when data are not missing completely at random. Statistics in medicine. 1999;18(17-18):2465-78.
[19]	Graham JW. Missing data analysis: Making it work in the real world. Annu Rev Psychol. 2009;60:549-76.
[20]	Enders CK. Applied missing data analysis. New York, NY: Guilford Press; 2010. xv, 377 p.
[21]	Little RJA, Rubin DB. Statistical analysis with missing data. 2nd ed. Hoboken, N.J.: Wiley; 2002. xv, 381 p. p.
[22]	Little TD, Rhemtulla M. Planned missing data designs for developmental researchers. Child Dev Perspect. 2013;7(4): 199-204.
[23]	Rhemtulla M, Little T. Tools of the trade: Planned missing data designs for research in cognitive development. Journal of Cognitive Development. 2012;13(4).
[24]	Graham JW, Taylor BJ, Olchowski AE, Cumsille PE. Planned missing data designs in psychological research. Psychol Methods. 2006;11(4):323-43.
[25]	Jorgensen TD, Rhemtulla M, Schoemann A, McPherson B, Wu W, Little TD. Optimal assignment methods in three-form planned missing data designs for longitudinal panel studies. Int J Behav Dev. 2014;38(5):397-410.
[26]	Jones E, Bulger S, Braga L, Cho K, Lilly C, Neal W, Elliott, E. Initial findings of a multi-component school-based PEP grant intervention: Greenbrier CHOICES. 2016 SHAPE America Convention; April 2016; Minneapolis, MN.2016.
[27]	Stalter AM, Chaudry RV, Polivka BJ. Facilitating factors and barriers to BMI screening in schools. Journal of School Nursing. 2010;26(4):320-30.
[28]	Buckworth J, Lee RE, Regan G, Schneider LK, DiClemente CC. Decomposing intrinsic and extrinsic motivation for exercise: Application to stages of motivational readiness. Psychology of Sport and Exercise. 2007;8(4):441-61.
[29]	Rhemtulla M, Jia F, Wu W, Little TD. Planned missing designs to optimize the efficiency of latent growth parameter estimates. Int J Behav Dev. 2014;38(5):423-34.
[30]	Little TD, Jorgensen TD, Lang KM, Moore EW. On the joys of missing data. Journal of Pediatric Psychology. 2014;39(2):151-62.