Full report available at:

Slides:



Advertisements
Similar presentations
V v Measuring Pedometer Accuracy in Free Living Conditions L. Paige Perilli, Erin Siebert, Caitlyn Elliott, & Joonkoo Yun COLLEGE OF PUBLIC HEALTH AND.
Advertisements

Stand-Out Sport Athletes’ Attitudes Toward Physical Education Timothy M. Church Department of Physical Education and Health Education INTRODUCTION Assumptions.
Amber S. Emanuel 1, James A. Shepperd 2, Virginia J. Dodd 1 & Henrietta Logan 1 1 Department of Behavioral Sciences & Community Dentistry, University of.
Predictors of change in children's physical activity: potential targets for intervention Esther van Sluijs, Chris Craggs, Kirsten Corder, Alison McMinn,
Implication of Gender and Perception of Self- Competence on Educational Aspiration among Graduates in Taiwan Wan-Chen Hsu and Chia- Hsun Chiang Presenter.
JENNY SMITH CAROLINE SMITH GEORGE SANDERS AMELIA THORNTON EMMA CLYDE-SMITH The Impact of Financial Circumstances on Student Health Jessop, Herberts, &
Helen Bland, PhD, Health & Kinesiology, Georgia Southern University Bridget Melton, EdD, Health & Kinesiology, GSU Elaine S. Marshall, RN, PhD, Nursing,
Quality Of Life, Health And Well Being Of Highly Active Individuals Louisa Raisbeck, Jeanne Johnston, Joel Stager, Francoise Benay Human Performance Laboratory,
THE RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND MENTAL HEALTH Focus: Physical Activity and self esteem.
DEVELOPEMENT OF A HOLISTC WELLNESS MODEL FOR MANAGERS IN TERTIARY INSTITUTIONS Petrus Albertus Botha Tshwane University of Technology Polokwane Delivery.
Self-assessment Accuracy: the influence of gender and year in medical school self assessment Elhadi H. Aburawi, Sami Shaban, Margaret El Zubeir, Khalifa.
National Physical Activity Guidelines
ACKNOWLEDGMENTS BACKGROUND Funded by: American Cancer Society MRSGT CPPB (Dunton, PI) and National Cancer Institute R01-CA (Pentz,
ABSTRACT The purpose of the present study was to investigate the test-retest reliability of force-time derived parameters of an explosive push up. Seven.
Ryoichi J. P. Noguchi, Michael M. Knepp, Sheri L. Towe, Chad L. Stephens, Jared A. Rowland, Christopher S. Immel, & David W. Harrison, Ph.D. INTRODUCTION.
The U.Va. Center to Promote Effective Youth Development Promoting Physical Activity and Well-Being The Youth-Nex Inaugural Conference FORWARD THINKING.
Project VIABLE - Direct Behavior Rating: Evaluating Behaviors with Positive and Negative Definitions Rose Jaffery 1, Albee T. Ongusco 3, Amy M. Briesch.
Test-Retest Reliability of the Work Disability Functional Assessment Battery (WD-FAB) Dr. Leighton Chan, MD, MPH Chief, Rehabilitation Medicine Department.
Wendy L. Wolfe, Kaitlyn Patterson, & Hannah Towhey
Progress and future developments
Kaitlyn Patterson & Wendy Wolfe
Physical activity levels in England
Contribution of Physical Education to Physical Activity of Children
Spearman Rho Correlation
Comparison of Four "Time in Intensity“ Physical Activity Indices as
Healthy Eating Similarities and Differences
Patterns and trends in adult physical activity
Patterns and trends in adult physical activity
Reliability and validity of the BREQ-2 for measuring high school students’ motivation for physical education Stuart Forsyth¹, David Rowe¹, and Nanette.
The University of Alabama, Tuscaloosa, AL
Day-to-day variability in older adults' physical activity:
Statin use in adults at high risk of cardiovascular disease mortality: cross-sectional analysis of baseline data from the Irish Longitudinal Study on Ageing.
Structured PA exercises
Associations between Total Daily Step Counts and
Family Paradigm Assessment Scale (F-PAS) Test-Retest Reliability
METHODS AND PARTICIPANTS ANALYSES AND STUDY QUESTIONS
Parental Status and Emergency Preparedness:
Effects of Educating URI General Education Students on Physical Activity, Exercise, and Disease Prevention and Maintenance Julie Gastall, Department.
Number of Days of Monitoring Needed with Accelerometers and Pedometers to Obtain Reliable Estimates of Habitual Physical Activity in Adults T. S. Robinson,
University of Michigan
Brotherson, S., Kranzler, B., & Zehnacker, G.
DESCRIPTIVES AND CORRELATIONS
Introduction Results Hypotheses Discussion Method
DISCUSSION AND CONCLUSIONS
The Relationship among Leisure Involvement and Happiness of Elementary Schoolteachers in Tainan County Chia-Hsin Cheng1* Chao-Chien Chen2  1 Department.
Effectiveness of support to increase physical activity
The University of Alabama, Tuscaloosa, AL
The University of Alabama, Tuscaloosa, AL
CURRENT STUDY OVERVIEW
Relationship between Physical Activities with Body Mass Index (BMI), among first year and second year medical students of Faculty of Medicine Session.
Making Every Contact Count
Examination of the Relationship Between Nutrition Media Literacy and Soft Drink Consumption Among Adolescents – Preliminary Findings Martin H. Evans*,
CONCLUSIONS AND DISCUSSION
Spearman Rho Correlation
DEVELOPING A FIT.GREEN.HAPPYTM CAMPUS: A DESCRIPTIVE STUDY OF
Natalie Robinson Centre for Evidence-based Veterinary Medicine
Validation of the Portuguese DSM-IV-MR-J
Measuring Sedentary Behavior: Epoch- and Hour-level
Jackie Eul Major: Outdoor Studies and Tourism
Kenneth Jim Joseph Jimeno, MHSS, RN
Examining the Effectivenesses of the IMPACT Program
2University of Virginia
University of Virginia1 & James Madison University2
A presentation of the latest data on child physical activity
Emily A. Davis & David E. Szwedo James Madison University Introduction
The Results from Estonian’s 2018 Report Card on Physical Activity for Children and Youth Mäestu E, Kull M, Mooses K, Mäestu J, Pihu M, Koka A, Raudsepp.
A. GBADAMOSI, A. CLARKE-CORNWELL, P. SINDALL1 and M. GRANAT1
A.M. CLARKE-CORNWELL1, P.A. COOK1 and M.H.GRANAT1
Objectively measured distributions of moderate to vigorous physical activity (MVPA), light intensity physical activity (LIPA) and sedentary time during.
Presentation transcript:

Full report available at: The validity and reliability of three self-report instruments for assessing compliance with physical activity guidelines amongst Irish university students. Murphy, J. Murphy, N. MacDonncha, C. Murphy, M. Woods, C. Dublin City University, Waterford Institute of Technology, Ulster University, University of Limerick. Introduction Third level education students comprise a large portion of the population and may wield a sizable degree of future influence in society through their post-graduation roles (1). These students spend a considerable amount of time in educational environments - which promote sedentary behaviour and in addition, they are largely being educated for sedentary occupations (2). Environments which promote sedentary behaviour or physical inactivity are likely to contribute to shaping long-term physical inactivity patterns (3,4,5). In order to assess the levels of physical activity (PA) in this population, a set of valid and reliable measurements are needed and self-report questionnaires are the most commonly used method for population studies. The purpose of this study was to examine the reliability and validity of three separate short physical activity measurement tools for assessing physical activity guidelines (PAGL) in Irish students. Methods Students (N = 463; 53% male; mean age 22.15 ± 4.5) from five institutions across Ireland completed an online questionnaire containing a single item measure (SIM) (8), an adapted PACE (PACE+) measure (7), and the IPAQ-SF (6). Physical activity was objectively measured for seven days, eight hours per day, using the Actigraph GT1M and the GT3X. After nine days, participants were instructed to complete an identical questionnaire containing each of the physical activity measures. Spearman Rho correlations and levels of agreement analysis between measures was used to assess validity. Test-retest reliability was performed for each self-report measure through an intra-class correlation (ICC). Results After data cleaning 190 participants (45.8% male, 22.86 ± 5.36 years) were available for analyses. Participants were undergraduate (89.1%) and postgraduate students spread across different years including 1st (27.4%), 2nd (42.7%), 3rd (11.3%), and 4th (18.5%). Across all participants the proportion meeting the 30 minute PAGL was 32.1% using the SIM and 31.1 % using PACE+, but was higher with accelerometry using an all days method (71.6%). A higher proportion met the 150 minute PAGL with the IPAQ-SF (77.4%) and accelerometry (95.8%) using the total minutes method. Males had significantly higher values (p<0.05) than females for moderate to vigorous physical activity (MVPA) mins/day, counts per minute (CPM), and self-reported PA using the SIM, PACE+, and IPAQ-SF. Spearman Rho correlations between self-reported and accelerometry recorded physical activity levels. Agreement, sensitivity and specificity between self-reported physical activity and accelerometer data for compliance with 30 minute or 150 minute physical activity guidelines. Intraclass correlation coefficients showing the reliability of each self-report measure in 133 participants.   MVPA (mins/day)a Total PA (CPM)b SIM (mins/day) N Total 190 0.26** 0.31** Male 87 0.12 0.21* Female 103 0.36** 0.39** PACE+ (mins/day) 0.27** 0.35** 0.16 0.23* 0.44**  IPAQ-SF (mins/day) 0.32** 0.28** 0.34** 0.30** 30 minute PAGL a   N Agreement Sensitivity Specificity PPVc NPVd SIM 190 45.8 % 34.6 % 74.1 % 77.0 % 31.0 % Males 87 42.5 % 37.9 % 57.1 % 73.5 % 22.6 % Females 103 48.5% 31.4 % 84.8 % 81.5 % 36.8 % PACE+ 33.8 % 75.9 % 78.0 % 31.3 % 43.7 % 61.9 % 75.8 % 24.1 % 47.6 % 30.0 % 84.9 % 80.8 % 36.4 % 150 minute PAGL b PPV NPV IPAQ-SF 77.9 % 78.6 % 50.0 % 97.3 % 9.3 % 80.5 % 82.1 % 33.3 % 97.2 % 6.7 % 75.7 % 75.5 % 60.0 % 97.4 % 11.1 %   ICCa 95% CIb SIM 0.67 0.54 – 0.77 PACE + 0.7 0.66 – 0.83 IPAQ-SF 0.52 0.33 – 0.66 a: Intraclass correlation coefficients b: 95 % confidence intervals a: Accelerometer derived average MVPA mins/day b: Accelerometer counts per minute * p < 0.05 ** p < 0.01 a: Proportion achieving 30 minutes of MVPA on 5 days or more b: Proportion achieving 150 minutes of MVPA over a week c: Positive Predictive Value d: Negative Predictive Value Discussion Correlations for each self-report measure with accelerometer data in terms of MVPA mins/day and accelerometer CPM were poor to moderate (0.26 - 0.35, p<0.01). The IPAQ-SF was the only measure found to have a significant association with accelerometer derived MVPA for males and females, replicating results from past research (6). Unlike previous research (9), only females reported significant correlations between accelerometer derived MVPA and the SIM. Levels of agreement reported for the SIM and the PACE+ were low (45.8%), while stronger for the IPAQ-SF (77.9%). The results of previous studies showed percentage agreement values ranging from 58% (for the SIM against accelerometry in adults) (9) to 66% (for IPAQ-SF against accelerometry in adults) (10). Nine day test-retest reliability showed the PACE+ score a strong ICC (0.70), followed by the SIM (0.67) and finally the IPAQ-SF (0.52). Reliability scores reported in this study were lower than research suggests for both the SIM (ICC = 0.86) (8) and the IPAQ-SF (ICC = 0.71 – 0.89) (11). This paper would recommend that when assessing levels of high active third level students achieving the PAGL, the IPAQ-SF is the most suitable. It is important to ensure that suitable measures are selected in future studies, depending on the population and the outcome measure of the studies. References (1) Hussain, R. et al., 2013. Physical and mental health perspectives of first year undergraduate rural university students. BMC public health, 13(1), p.848. (2) Fotheringham, M., Wonnacott, R. & Owen, N., 2000. Computer use and physical inactivity in young adults: public health perils and potentials of new information technologies. Annals of Behavioral Medicine, 22(4), pp.269–75. (3) Owen, N. et al., 2000. Environmental determinants of physical activity and sedentary behavior. Exercise and sport sciences reviews, 28(4), pp.153–8. (4) Lesliephillip, E. et al., 1999. Insufficiently active Australian college students: perceived personal, social, and environmental influences. Preventive medicine, 28(1), pp.20–7. (5) Sallis, J.F., Bauman, A. & Pratt, M., 1998. Environmental and policy interventions to promote physical activity. American Journal of Preventive Medicine, 15(4), pp.379–97. (6) Craig, C.L. et al., 2003. International physical activity questionnaire: 12-country reliability and validity. Medicine and science in sports and exercise, 35(8), pp.1381–95. (7) Hardie Murphy, M. et al., 2015. Validity of a two-item physical activity questionnaire for assessing attainment of physical activity guidelines in youth. BMC public health, 15(1), p.1080. (8) Milton, K., Bull, F.C. & Bauman, a, 2011. Reliability and validity testing of a single-item physical activity measure. British journal of sports medicine, 45(3), pp.203–8. (9) Milton, K., Clemes, S. & Bull, F., 2013. Can a single question provide an accurate measure of physical activity? British journal of sports medicine, 47(1), pp.44–8. (10) Ekelund, U. et al., 2006. Criterion-related validity of the last 7-day, short form of the International Physical Activity Questionnaire in Swedish adults. Public Health Nutrition, 9(2), pp.258–65. (11) Dinger, M.K., Behrens, T.K. & Han, J.L., 2006. Validity and Reliability of the International Physical Activity Questionnaire in College Students. American Journal of Health Education, 37(6), pp.337–343. Acknowledgements The SASSI study (2016) was funded by Student Sport Ireland. Full report available at: www.studentsport.ie Presented at ISBNPA 2016 Contact: joseph.murphy222@mail.dcu.ie or Catherine.Woods@dcu.ie