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How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It

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How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It. / Rebar, Amanda L.; Rhodes, Ryan E.; Gardner, Benjamin.

In: International Journal of Behavioral Nutrition and Physical Activity, Vol. 16, No. 1, 71, 22.08.2019.

Research output: Contribution to journalArticle

Harvard

Rebar, AL, Rhodes, RE & Gardner, B 2019, 'How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It', International Journal of Behavioral Nutrition and Physical Activity, vol. 16, no. 1, 71. https://doi.org/10.1186/s12966-019-0829-y

APA

Rebar, A. L., Rhodes, R. E., & Gardner, B. (2019). How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It. International Journal of Behavioral Nutrition and Physical Activity, 16(1), [71]. https://doi.org/10.1186/s12966-019-0829-y

Vancouver

Rebar AL, Rhodes RE, Gardner B. How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It. International Journal of Behavioral Nutrition and Physical Activity. 2019 Aug 22;16(1). 71. https://doi.org/10.1186/s12966-019-0829-y

Author

Rebar, Amanda L. ; Rhodes, Ryan E. ; Gardner, Benjamin. / How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It. In: International Journal of Behavioral Nutrition and Physical Activity. 2019 ; Vol. 16, No. 1.

Bibtex Download

@article{a85963c47f8243f393007c4e02d59177,
title = "How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It",
abstract = "Background: Studies of the physical activity intention-behavior gap, and factors that may moderate the gap (e.g., habit, perceived behavioral control), can inform physical activity promotion efforts. Yet, these studies typically apply linear modeling procedures, and so conclusions rely on linearity and homoscedasticity assumptions, which may not hold.Methods: We modelled and plotted physical activity intention-behavior associations and the moderation effects of habit using simulated data based on (a) normal distributions with no shared variance, (b) correlated parameters with normal distribution, and (c) realistically correlated and non-normally distributed parameters. Results: In the uncorrelated and correlated normal distribution datasets, no violations were unmet, and the moderation effects applied across the entire data range. However, because in the realistic dataset, few people who engaged in physical activity behavior had low intention scores, the intention-behavior association was non-linear, resulting in inflated linear moderation estimations of habit. This finding was replicated when tested with intention-behavior moderation of perceived behavioral control. Conclusions: Comparisons of the three scenarios illustrated how an identical correlation coefficient may mask different types of intention-behavior association and moderation effects. These findings highlight the risk of misinterpreting tests of the intention-behavior gap and its moderators for physical activity due to unfounded statistical assumptions. The previously well-documented moderating effects of habit, whereby the impact of intention on behavior weakens as habit strength increases, may be based on statistical byproducts of unmet model assumptions.",
keywords = "Assumption testing, Exercise, Goals, Habit, Motivation, Simulation",
author = "Rebar, {Amanda L.} and Rhodes, {Ryan E.} and Benjamin Gardner",
year = "2019",
month = "8",
day = "22",
doi = "10.1186/s12966-019-0829-y",
language = "English",
volume = "16",
journal = "The international journal of behavioral nutrition and physical activity",
issn = "1479-5868",
publisher = "BioMed Central",
number = "1",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - How We Are Misinterpreting Physical Activity Intention – Behavior Relations and What to Do About It

AU - Rebar, Amanda L.

AU - Rhodes, Ryan E.

AU - Gardner, Benjamin

PY - 2019/8/22

Y1 - 2019/8/22

N2 - Background: Studies of the physical activity intention-behavior gap, and factors that may moderate the gap (e.g., habit, perceived behavioral control), can inform physical activity promotion efforts. Yet, these studies typically apply linear modeling procedures, and so conclusions rely on linearity and homoscedasticity assumptions, which may not hold.Methods: We modelled and plotted physical activity intention-behavior associations and the moderation effects of habit using simulated data based on (a) normal distributions with no shared variance, (b) correlated parameters with normal distribution, and (c) realistically correlated and non-normally distributed parameters. Results: In the uncorrelated and correlated normal distribution datasets, no violations were unmet, and the moderation effects applied across the entire data range. However, because in the realistic dataset, few people who engaged in physical activity behavior had low intention scores, the intention-behavior association was non-linear, resulting in inflated linear moderation estimations of habit. This finding was replicated when tested with intention-behavior moderation of perceived behavioral control. Conclusions: Comparisons of the three scenarios illustrated how an identical correlation coefficient may mask different types of intention-behavior association and moderation effects. These findings highlight the risk of misinterpreting tests of the intention-behavior gap and its moderators for physical activity due to unfounded statistical assumptions. The previously well-documented moderating effects of habit, whereby the impact of intention on behavior weakens as habit strength increases, may be based on statistical byproducts of unmet model assumptions.

AB - Background: Studies of the physical activity intention-behavior gap, and factors that may moderate the gap (e.g., habit, perceived behavioral control), can inform physical activity promotion efforts. Yet, these studies typically apply linear modeling procedures, and so conclusions rely on linearity and homoscedasticity assumptions, which may not hold.Methods: We modelled and plotted physical activity intention-behavior associations and the moderation effects of habit using simulated data based on (a) normal distributions with no shared variance, (b) correlated parameters with normal distribution, and (c) realistically correlated and non-normally distributed parameters. Results: In the uncorrelated and correlated normal distribution datasets, no violations were unmet, and the moderation effects applied across the entire data range. However, because in the realistic dataset, few people who engaged in physical activity behavior had low intention scores, the intention-behavior association was non-linear, resulting in inflated linear moderation estimations of habit. This finding was replicated when tested with intention-behavior moderation of perceived behavioral control. Conclusions: Comparisons of the three scenarios illustrated how an identical correlation coefficient may mask different types of intention-behavior association and moderation effects. These findings highlight the risk of misinterpreting tests of the intention-behavior gap and its moderators for physical activity due to unfounded statistical assumptions. The previously well-documented moderating effects of habit, whereby the impact of intention on behavior weakens as habit strength increases, may be based on statistical byproducts of unmet model assumptions.

KW - Assumption testing

KW - Exercise

KW - Goals

KW - Habit

KW - Motivation

KW - Simulation

UR - http://www.scopus.com/inward/record.url?scp=85071338481&partnerID=8YFLogxK

U2 - 10.1186/s12966-019-0829-y

DO - 10.1186/s12966-019-0829-y

M3 - Article

AN - SCOPUS:85071338481

VL - 16

JO - The international journal of behavioral nutrition and physical activity

JF - The international journal of behavioral nutrition and physical activity

SN - 1479-5868

IS - 1

M1 - 71

ER -

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