This study analyzed data from ecological momentary assessment (EMA) and accelerometer to explore social cognitive constructs as mediators of affective response to physical activity and subsequent physical activity levels. It was presented at the 2017 Society of Behavioral Medicine Annual Meeting in San Diego, California.

1. Yue Liao, MPH, PhD
Jaejoon Song, MS
Michael Robertson, MPH
Karen Basen-Engquist, PhD, MPH

2. AffectiveFeelingStates&PhysicalActivity
 A growing number of
studies have shown
affective and physical
feeling states as
predictors of daily
physical activity (PA) in
free-living settings
 predicting PA ranging
from in the next few
hours to the next day
Liao et al., 2015

3. SocialCognitiveFactorsasPotential
Mediators
 Decision to engage in
PA is influenced partly
by self-efficacy and
outcome expectancy
 Have been shown to
predict same-day PA
 Affective & physical
feeling responses could
influence PA self-
efficacy and outcome
expectancy
Bandura, 1997; Williams et al., 2005
Basen-Engquist et al., 2013; Liao & Dunton, 2015

4. AimsofCurrentStudy
 To test whether affective and physical feeling
responses to PA predict PA levels the next day
 To explore self-efficacy and outcome expectancy as
mediators of the above relationships

5. DataSource
 99 endometrial cancer survivors from the Step
to Health Study, an intervention designed to
encourage home-based exercise
 Mean age = 57.0 (SD = 11.01)
 84.9% overweight/obese
 Home-based assessment occurred at 8 different
time points, for a total of 42 days
 Ecological momentary assessment (EMA) via PDAs
(HP iPAQ RX1950)
 Accelerometers (Actigraph GT1M)

6. Exercise
prescription
Lab Exercise
and assessment
Home-based
Assessment
(7 Days)
Weekly Telephone
Counseling for Exercise Adherence
Lab Exercise
and assessment
Semi-Weekly Telephone
Counseling for Exercise Adherence
Lab Exercise
and assessment
Monthly Telephone
Counseling for Exercise Adherence
Assessment and Intervention Schedule
Home-based
Assessment
(5 days)
Home-based
Assessment
(5 Days)
Home-based
Assessment
(5 Days)
Home-based
Assessment
(5 Days)
Home-based
Assessment
(5 Days)
Lab Exercise
and assessment
Home-based
Assessment
(5 Days)
Home-based
Assessment
(5 Days)
T0: Baseline
T1: 2 months
T2: 4 months
T3: 6 months
6

7. EMADesign&Measures
 Morning assessment
 Self-efficacy (1 item)
 How confident are you … exercise today for the recommended … time?
 Expected positive outcomes (6 items, Cronbach’s α = 0.93)
 I will sleep more soundly tonight if I exercise today
 Expected negative outcomes (3 items, Cronbach’s α = 0.62)
 Exercise today will be painful
 Pre/post exercise assessment
 Exercise-induced feeling inventory (12 items; Gauvin & Rejeski, 1993)
 Energetic, calm, tired, happy, relaxed
 Physiological somatic sensations (10 items; Pennebaker, 1982)
 Racing heart, tightness in chest, sore muscles, sweating, dizziness

8. DailyPhysicalActivityMinutes
 Three methods to
collect PA data
 Post exercise self-
reported duration
 Nighttime diary
 Accelerometer
 A composite daily PA
minutes was derived
from the above 3
measurements
Basen-Engquist et al., 2013

9. DataPreparation
 Affective and physical feeling responses to PA
were created by calculating change scores
 Post-exercise EFI – pre-exercise EFI
 Post-exercise SS – pre-exercise SS
 Each change score was matched with morning
self-efficacy and outcome expectancy, as well as
the daily PA minutes the next day
 A maximum of 34 possible matched days per
participant out of the 42 monitoring days

10. DataAvailability
 On average, women (n=97) reported exercised in
17 days out of the 42 monitoring days
 On average, each participant had 11 exercise
days that were matched with the next day
morning SE/OE and physical activity levels
 A total of 1,068 matched days across all
participants

11. DataAnalysis
 Multilevel linear regression model was used to test
change in affective/somatic feelings as predictor of
next day PA
 Multilevel mediation model (1-1-1) was used to
examine SE/OE as an mediator
 All models controlled for weight category, baseline activity,
exercise duration, and wave of assessment
Post-exercise
Change in
Affective/Somatic
Feelings
SE/OE
Next Day
Morning
Total PA Minutes
Next Day
a b
c’

12. Results
 Post-exercise changes in EFI and SS were not
associated with PA minutes the next day
Physical Activity Minutes
Next day
Beta Estimate (SE) p
Change in EFI
WP Effect 0.017 (0.140) 0.902
BP Effect -0.133 (0.154) 0.464
Change in Somatic
Sensation
WP Effect 0.015 (0.221) 0.948
BP Effect 0.014 (0.195) 0.943

13. Results
(EFI,NegativeOutcomeExpectancy,andPAatBPlevel)
Post-exercise
Change in EFI
Negative OE
Next Day Morning
Overall PA Level
Next Day
a = -0.036 (0.009)** b = -4.901 (1.910)*
c’ = -0.328 (0.181)
Indirect Effect = 0.176 (0.086)*
** p < .01, * p < .05

14. Results
(SomaticSensation,NegativeOutcomeExpectancy,and
PAatBPlevel)
Post-exercise
Change in SS
Negative OE
Next Day Morning
Overall PA Level
Next Day
a = 0.055 (0.015)** b = -4.657 (1.861)*
c’ = 0.298 (0.226)
Indirect Effect = -0.256 (0.125)*
** p < .01, * p < .05

15. Results
 Self-efficacy and positive outcome expectancy
did not have a significant indirect effect between
changes in EFI/SS and next day PA levels
 No significant indirect effects were found at the
within-person level

16. Conclusions
 No direct relationship between affective and
physical feeling response to PA and next day PA
 Affective and physical feeling responses to PA
might predict future PA engagement through their
effects on negative outcome expectancy
 These associations are due to the differences in the
average levels of post-exercise experiences that
vary between individuals

17. Limitations
 The EMA protocol did not enforce data entry
immediately after an exercise session
 Contextual information was not captured
 Walking was the main targeted exercise behavior
 Findings might be specific to this particular
population

18. FutureDirections
 Target the unpleasant
feelings that might arise
from PA engagement
 Identify people with higher
negative responses to PA
 Explore the within-person
variability in the
associations between
affect, social cognitive
factors, and PA through
capturing different
types/intensity of daily PA
across various situations

19. Acknowledgements
 NIH R01CA109919
 NIH P30CA016672
(PROSPR Shared
Resource)
 Center for Energy Balance
in Cancer Prevention and
Survivorship, Duncan
Family Institute, MD
Anderson Cancer Center
 Janice Davis Gordon
Memorial Postdoctoral
Fellowship, MD Anderson
Cancer Center