1. CURRENT STUDY OVERVIEW
Society for Personality and Social Psychology
January 21, 2017
Department of Psychology
L. Alison Phillips and Melissa Johnson
Interdependent Influence of Autonomous and Controlled Regulation on Exercise Behavior
BACKGROUND
RESULTS
Self-Determination Theory [1,2] states that Autonomous Regulation (being motivated to engage in a behavior for enjoyment or personally important reasons) promotes and Controlled Regulation (being motivated to engage in a behavior because of external pressures or due to guilt from non- performance) is detrimental to behavioral engagement.
This proposition has been tested using the Relative Autonomy Index (RAI), as a single predictor of behavioral engagement = a difference score, which increases risk of Type 1 and Type II error and does not allow evaluating combined effects of regulation types on behavioral engagement.
Sample 1
Sample 2
Sample 3
CURRENT STUDY OVERVIEW
Polynomial Regression
Autonomous and controlled regulation are used as separate predictors of physical activity, using exploratory polynomial regression analyses [3] in data from three samples.
Results from a “person-centered analysis”, cluster analysis, as in [4], were not interpretable and are not reported here.
Hypotheses
“Non-reciprocal effect”: greater physical activity will be associated with higher (vs lower) scores on both autonomous and controlled regulation.
“Reciprocal effect”: physical activity will increase as autonomous regulation increases and controlled regulation decreases.
Sample 1
N=467
Sample 2
N=106
Sample 3, Self-Report
N=129
Sample 3, Fitbit
N=75
Variable B
SE B β
Constant/Intercept
30.78
1.58
6.01
.16
3.09
.17
359.46
Autonomous Regulation (X)
13.17
1.73
.35†
.74
.21
.33†
1.05
.51†
360.61
.36**
Controlled Regulation (Y)
2.90
1.97
.07
-.20
.24
-.08
-.56
.25
-.19*
488.36
-.15
R2-Change
.15
.12
.23
F Change
40.53†
6.77**
18.48†
4.90**
30.96
2.43
6.16
.26
3.00
533.45
14.83
1.92
.40†
.80
.36†
1.09
.18
.53†
386.40
.41**
4.48
2.16
.11*
-.21
-.95
.33
-.32**
716.48 X2
1.78
1.67
.06
.27
.11
-.11
-.10
360.07 XY
4.11
2.50
.10
.29
-.07
-.04
118.46
470.86
.03 Y2
-4.33
1.89
-.13*
-.67
.30
-.21*
.45
.20
50.11
472.88
.02
.04
3.06*
2.41*
1.16
0.99
CONCLUSIONS
Slopes of the surfaces along the line of congruence (when X = Y) were significant and positive in Samples 1 and 3, supporting Hyp 1. Slopes of the surfaces along the line of incongruence (when X=-Y) were all significant and positive, supporting Hyp 2.
However, the hypotheses are mostly appropriate for linear final models and do not capture the curvilinear effects of controlled regulation on physical activity.
Testing the RAI as the single predictor of physical activity would have provided support only for Hyp 2 and would not have discovered the curvilinear effects of controlled motivation found in Samples 1 and 2.
Testing complex SDT hypotheses using unidimensional or separate treatment of regulation types provides false support for the proposition that controlled regulation is wholly detrimental to behavioral engagement.
Controlled regulation of physical activity may help maintain regular physical activity
Future research should verify these exploratory polynomial regression results.
METHOD
General Procedure
Autonomous and Controlled Regulations of Physical Activity were measured at baseline via self-report.
Physical activity was measured via self-report at baseline (Sample 1) and at one-month follow-up (Sample 3).
Physical activity was measured objectively (with Fitbits) for one month (Samples 2 & 3).
Measures
Autonomous Regulation = Average of Intrinsic and Identified Regulations from the BREQ-2 [5].
Controlled Regulation = Average of Introjected and External Regulations from the BREQ-2, per convention [4,6].
Self-Reported Physical Activity = IPAQ ([7]; Sample 1) and days of exercising for 20 or more minutes in past week (Sample 3).
REFERENCES
Note. *indicates regression coefficient is significantly different from 0 at p<0.07; **indicates p<0.01; †indicates p<0.001.
Ryan, R.M., & Deci, E.L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25,
Teixeira, P. J., Carraça, E. V., Markland, D., Silva, M. N., & Ryan, R. M. (2012). Exercise, physical activity, and self-determination theory: A systematic review. The International Journal of Behavioral Nutrition and Physical Activity, 9.
Phillips, L. A. (2013). Congruence research in behavioral medicine: Methodological review and demonstration of alternative methodology. Journal of Behavioral Medicine, 36(1),
Vansteenkiste, M., et al. (2009). Motivational profiles from a self-determination perspective: The quality of motivational matters. Journal of Educational Psychology, 101(3),
Markland, D., & Tobin, V. (2004). A modification to the behavioural regulation in exercise questionnaire to include an assessment of amotivation. Journal of Sport & Exercise Psychology, 26,
Deci, E. L., & Ryan, R. M. (2008). Facilitating optimal motivation and psychological well-being across life’s domains. Canadian Psychology, 49(1),
Ainsworth, B.E., et al. (2006). Comparison of the 2001 BRFSS and the IPAQ Physical Activity Questionnaires. Medicine and Science in Sports and Exercise, 38,
Description
% Female Identity
% Minority Race or Ethnicity Identity
Average Age (SD)
Sample 1
467 Students; urban, private university, concurrent assessment
71%
31%
19.40 (2.04)
Sample 2
106 students and staff, one month follow-up
75%
25%
25.40 (11.60)
Sample 3
129 patients with Type 2 Diabetes; one month follow-up
62%
59%
56.96 (12.04)
Acknowledgements
Funding for collection of Sample 3 came from an Adherence Starter Grant, from the PhRMA Foundation. Data was collected with assistance from Miriam Eisenberg, Jessica Abrams, Steffi Renninger, Margot Quinn, Katie Adams, and Benjamin Laman-Maharg