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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 ± 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, ± 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 ( , 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., 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., 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., Environmental determinants of physical activity and sedentary behavior. Exercise and sport sciences reviews, 28(4), pp.153–8. (4) Lesliephillip, E. et al., 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., Environmental and policy interventions to promote physical activity. American Journal of Preventive Medicine, 15(4), pp.379–97. (6) Craig, C.L. et al., 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., Validity of a two-item physical activity questionnaire for assessing attainment of physical activity guidelines in youth. BMC public health, 15(1), p (8) Milton, K., Bull, F.C. & Bauman, a, 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., 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., 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., 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.
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