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David Rowe Physical Activity for Health Research Group University of Strathclyde.

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Presentation on theme: "David Rowe Physical Activity for Health Research Group University of Strathclyde."— Presentation transcript:

1 David Rowe Physical Activity for Health Research Group University of Strathclyde

2  Brief rationale  Description of the intervention  Description of the study design and methods  Results  Active commuting and daily physical activity  Intention and Habit  Take-forward messages 2

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4  Curricular intervention (6 weeks)  Aimed at P5 (8-9 years old)  Teachers’ resource handbook:  Introductory activities  Write and draw activities, target setting, etc.  13 Lesson plans  e.g., the local environment, mapping skills, road safety, healthy lifestyles, etc.  Variety of methods – class and small-group discussions, worksheets, practical tasks, take- home activities 4

5  Other resources:  Classroom poster to record daily travel mode  Pupil pack (used at home):  Guides for parents  “My travel challenge”  Progress chart  Fluorescent stickers 5

6  McKee et al. (2007)  Quasi-experiment, two schools (n = 55)  Distance walked and distance by car, measured via self-report (route mapping)  Walking:  Intervention 198  772 m/day  Control 242  285 m/day  Car:  Intervention 2018  933 m/day  Control 933  947m/day 6

7  SE-CAT study added:  Objective measures of physical activity  Stratified sample (high and low SES)  Assess variety of theoretical model parameters (Barriers, Motivations, Self-Efficacy, Theory of Planned Behavior, Habit)  Follow-up (maintenance) measures (5-mth, 12- mth)  Assessment of parent perceptions  Process evaluation (teacher chceklist)  Pilot (McMinn et al., 2012, BMC Public Health) 7

8  Physical activity measures (main behavioral outcome)  Total daily, morning commute, afternoon commute  Route characteristics  Actigraph GT1M, NL-1000, Trackstick (GPS)  Travel diary (home journey)  Mode  Arrival time 8

9  Parent and child questionnaires  Socioeconomic (car ownership, income, home ownership, home SIMD, etc.)  Stage of Change  Barriers, facilitators, benefits  Self-efficacy  Theory of Planned Behavior Attitude, subjective norms, perceived behavioral control, intention  Habit Walking Car/bus 9

10  Active commuting/physical activity  Actigraph-determined steps  To school (a.m. commute), from school (p.m. commute), and total day  Psychological predictors  Theory of Planned Behavior components  Habit (Walk, Car/Bus) 10

11 1)What are the immediate, medium- and long-term effects of the Travelling Green intervention on children’s active commuting?  and on determinants of active commuting? 2)How does season of the year moderate the effect of the Travelling Green intervention on children’s active commuting?  and on determinants of active commuting? 3)What are the personal and environmental determinants of active commuting in children  and of their response to the intervention? 4)What is the role of habit in explaining children’s active commuting  and their response to the intervention? 5)Moderating effect of SES 6)Role of parents 11

12  163 children (P5; 8-9 yr) in 5 schools  Intervention schools (I; n = 79)  Comparison schools (C; n = 84)  Actigraph GT1M accelerometer steps during one school week  4 measurement points:  Baseline (fall)  Immediate post-intervention (winter)  5 months post-intervention (spring)  12 months post-intervention (fall).  Travelling Green intervention delivered by teachers 12

13 InterventionComparisonTime Data collection Aug/Sept 2009 Data collection TG Oct/Nov 2009 March-May 2010 June 2010 Oct/Nov 2010 June 2011 McMinn et al. (2012) Preventive Medicine 13

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15 15 Significant Group*Time interaction for a.m. commute steps (p <.05, η 2 =.02) The I and C groups diverged following the I group intervention for 5 months, and converged following the C group intervention d = 0.03 d = 0.25 d = 0.49 d = 0.17

16 16 Nonsignificant Group*Time interaction for p.m. commute steps (p >.05, η 2 =.00) Main effects tests indicated significantly higher (p Winter < Spring = Fall). d = 0.28 d = 0.19 d = 0.23 d = 0.20

17 17 Significant Group*Time interaction for daily steps (p <.001, η 2 =.05). For daily steps, the I and C groups diverged following the I group intervention for 5 months, and converged following the C group intervention. d = -0.37 d = 0.13 d = 0.30 d = 0.00

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19 Attitude Subjective Norm Perceived Behavioral Control IntentionBehaviour Walking Habit Habit Murtagh et al. 2012, IJBNPA 19 (?)

20 20 Nonsignificant Group*Time interaction (p >.05, η 2 =.00) Main effects tests indicated significantly higher (p.05, η 2 =.01). d = 0.37 d = 0.41 d = 0.53 d = 0.40

21 21 Nonsignificant Group*Time interaction (p >.05, η 2 =.00) Main effects tests indicated significantly higher (p.05, η 2 =.01). d = 0.76d = 0.55d = 0.49 d = 0.59

22 22 Nonsignificant Group*Time interaction (p >.05, η 2 =.02) Main effects tests indicated significantly higher (p.05, η 2 =.02; Fall > Winter < Spring = Fall). d = 0.60 d = 0.59d = 0.56 d = 0.33

23  Children’s school travel and daily physical activity are subject to seasonal change  Regardless of whether it is delivered in fall or spring, a 6-week school-based intervention can beneficially influence the morning school commute and daily physical activity of upper elementary school children  A 6-week school-based intervention has limited short, medium or long-term effects on behavioral determinants of active travel  (from the TPB Model and Habit theory) 23

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25  Pilot, pilot, pilot  Incentives – maybe the best $2 you ever spent  Find a “champion”  Person-power 25

26 26 From McMinn et al. 2012, Research Quarterly for Exercise and Sport Actual route Recorded route

27  More strategic use of incentives  Comprehensive process evaluation  Add qualitative elements  Target parents more explicitly  90% identified that the parent/s was/were the primary decision-maker in commuting mode  Introduce at a later age  Focus on “breaking unhealthy habits” (car/bus) as much as forming new habits (walk) 27

28 28 HABIT Frequency Automaticity Identity

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30 30 david.rowe@strath.ac.uk David McMinn, PhD Shemane Murtagh, PhD Dr. Norah Nelson http://www.se-cat.co.uk/ Part-funded by the Scottish Government and Sustrans


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