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Does image congruence impact the effectiveness of a gain-framed physical activity
1Department of Psychology and Sport Sciences
University of Hertfordshire
Tel: (0) 1707 285971
Background: Gain-framed messages can improve processing and physical activity, however
inconsistency remains about the merits of using different accompanying images. This study
explored whether gain-framed messages alongside positive images (congruent) were more
effective than negative (incongruent) images at increasing Social Cognitive Theory (SCT)
constructs and moderate-to-vigorous physical activity (MVPA).
Method: Using a mixed design participants (N = 110) were randomly assigned to read a
gain-framed physical activity booklet containing either congruent or incongruent images.
Data were collected at two time points (baseline and one week later) using online
questionnaires assessing SCT constructs and interviews about MVPA over the previous seven
Results: A time by condition interaction showed that intentions (p = .039, η2 = .04) and self-
efficacy (p = .005, η2 = .07) increased in the congruent condition only. There was a time main
effect for self-regulation (p = .001, η2 = .09) and MVPA (p = .011, η2 = .06), but no difference
between conditions. Changes in self-regulation predicted changes in MVPA in both
conditions (congruent, p = .003; incongruent, p = .030).
Conclusions: Congruence between message content and images increased intentions and
self-efficacy, but not MVPA. Improving self-regulation may increase physical activity levels
regardless of message congruence.
Does image congruence impact the effectiveness of a gain-framed physical activity
In England the recommended amount of physical activity is 150 minutes of moderate-
intensity or 75 minutes of vigorous-intensity physical activity. Only 67% of men and 55% of
women are active at these levels (HSCIC, 2014) despite inactivity contributing to
cardiovascular disease, type 2 diabetes, and cancer (Baumann, 2004). One low-intensity
approach to increasing physical activity is persuasive health messaging, which can be framed
in terms of gains or losses. Low risk health-promotion behaviours such as physical activity
are more amenable to gain-framed messages (Rothman & Salovey, 1997). Gain-framed
messages are more likely to encourage physical activity behaviour but the evidence for
variables such as intentions is more mixed (Gallagher & Updegraff, 2012; Latimer, Brawley,
& Bassett, 2010).
Gain-framed messages can be more appealing, attracting significantly more attention,
lead to better message recall, produce more positive attitudes, and increase physical activity
levels (Berenbaum & Latimer-Cheung, 2014). Appropriate accompanying images can
increase health message comprehension and compliance (Delp & Jones, 1996), as well as
increase knowledge (Boer, Ter Huurne, & Taal, 2006). This emphasizes the need for image
content to be optimized in order to maximise behaviour change. Smith and Shaffer (2000)
presented participants with congruent images alongside a gain-framed health message. This
provided what they called ‘vividness congruency’ - described as the extent to which key
elements (text, imagery) were consistent with the overall tone and intention of the message.
This led participants in the ‘vivid congruent’ condition to pay more attention, enabling them
to process and recall the information more easily (Smith & Shaffer).
Gain-framed messages incorporating six or more arguments and a negative
background image can increase intentions (McCormick & McElroy, 2009). It was suggested
that the negative affect highlighted by the image draws attention to and increases the
persuasiveness of the health message. The image was however negative in tone and not
related to physical activity, and therefore were not measuring congruency between image and
message. The images were also not controlled for factors that have been shown to affect the
perceptions of perceivers such as body shape, clothing, or attractiveness (e.g. Howlett, Pine,
Orakçıoğlu, & Fletcher, 2013).
For the current study Social Cognitive Theory (SCT) was used as a theoretical
background. The core tenets of SCT related to physical activity are self-efficacy (one’s belief
that they can perform physical activity under challenging circumstance), outcome
expectations (beliefs about the utility of performing physical activity), goals (whether people
aim to perform physical activity) which includes the ability to self-regulate, and perceived
facilitators or impediments to performing physical activity (e.g. social support or lack of
exercise facilities) (Bandura, 2004; Young, Plotnikoff, Collins, Callister, & Morgan, 2014).
SCT variables strongly predict physical activity (Young, et al., 2014). Self-efficacy, self-
regulation, and goals all have an effect on physical activity, with less evidence for social
support and outcome expectancies (Young et al., 2014). Physical activity interventions have
also consistently shown that increasing participants’ ability to self-regulate through
techniques such as self-monitoring is effective (Michie, Abraham, Whittington, McAteer, &
The present study focuses solely on the use of gain-framed messages and seeks to
determine the influence of congruent and incongruent images alongside gain-framed health
messages upon MVPA and SCT constructs (self-efficacy, outcome expectancies, intentions,
and self-regulation). Intention is included because it has been posited as the equivalent of a
proximal goal (Bandura, 2004). This study further develops the work of McCormick and
McElroy (2009) in that the images used will be more closely linked to physical activity,
providing a true test of vividness congruency (Smith & Shaffer, 2000).
We predicted that participants in the congruent condition (booklet containing gain-
framed message and positive images) would have improved outcomes over and above the
incongruent condition (booklet containing gain-framed message and negative images) in SCT
constructs, and MVPA levels after reading the respective physical activity booklet. A further
prediction was that changes in SCT constructs would predict changes in physical activity,
particularly self-regulation due to its successful application in previous physical activity
This research was reviewed by the University of Hertfordshire Health and Human
Science Ethics Committee with Delegated Authority (ECDA) (protocol number:
Participants were randomly allocated using a computer random number generator to
either the congruent condition, containing 57 participants (13 males, 44 females; age, M =
24.07, SD = 9.23; BMI, M = 22.32, SD = 2.81) or the incongruent condition, containing 53
participants (10 males, 43 females; age, M = 22.81, SD = 8.46; BMI, M = 21.94, SD = 4.57).
This study used a mixed design with condition as the between-subjects factor
(congruent; gain-framed message and positive images, and incongruent; gain-framed message
and negative images) and time as the within-subjects factor (pre and post intervention, one
week apart). The outcome variables were SCT constructs (self-efficacy, outcome
expectancies, intentions, and self-regulation), and MVPA.
The intervention involved participants reading a four page booklet containing
information about physical activity.
Physical activity leaflet
Both booklets utilised the following behaviour change techniques: Instruction on how
to perform behaviour, information about health consequences, and credible source (Michie et
al., 2013). Booklets highlighted the current physical activity recommendations along with
examples of MVPA. A list of health benefits was also included to target expected outcomes
of being active. The text emphasised the benefits of physical activity and highlighted the ease
of fitting activities into daily routines, to increase self-efficacy. The gain-framed text was
identical in each booklet but the images differed.
On the first page, the text was presented alongside an image of a healthy young male
and female in physical activity attire. They displayed a positive facial expression (congruent)
and a neutral facial expression (incongruent). The models in the incongruent condition were
also manipulated to make them appear overweight, emphasizing the potential health
consequences of inactivity. On the second page the male was shown playing golf and the
female playing tennis (congruent) or sitting down (incongruent). The faces from the first page
were copied onto the third page and to emphasize that the booklet was from a credible source,
a University logo was included.
Physical Activity: The short form International Physical Activity Questionnaire
(IPAQ; Ainsworth et al., 2006) asked participants how many minutes and on how many days
they completed MVPA during the last week. A Metabolic Equivalent of Task (MET) score
was calculated taking into account frequency, duration, and intensity.
Intentions: A Theory of Planned Behaviour questionnaire (Francis et al., 2004) asked
participants to rate how strongly they agreed with three statements such as ‘I expect to take
part in regular physical activity over the next 7 days’ on a scale from 1, ‘strongly disagree’,
to 7, ‘strongly agree’ (reliability; pre a = .85; post a = .85).
Self-efficacy: The Physical Activity Appraisal Inventory (Haas & Northam, 2010)
asked how confident participants felt in performing regular physical activity in the presence
of difficulties. For example ‘when I am feeling tired.’ Answers were given for 13 items on an
11-point scale from 0, ‘cannot do at all’, to 100, ‘certain can do’ (reliability; pre a = .92; post
a = .94).
Outcome expectancies: An Expected Outcomes of Regular Physical Activity scale
(Steinhardt & Dishman, 1989) assessed how positively participants believe the outcomes of
regular physical activity to be. The 11 items were measured on a scale from 1, ‘strongly
disagree’, to 5, ‘strongly agree’ (reliability; pre a = .88; post a = . 88).
Self-regulation: The Self-Regulation and Action Planning scale (Sniehotta, Scholz, &
Schwarzer, 2005) required participants to indicate the extent they agreed with two statements.
For example, ‘during the past week I have constantly monitored myself whether I exercise
frequently enough.’ Answers were given on a scale from 1, ‘strongly disagree’, to 5,
‘strongly agree’ (reliability; pre r = .70; post r = .80).
Participants were presented with the information and consent screen. By clicking
‘continue’ participants gave their consent to participate. Participants completed the
questionnaires followed by demographic questions including their sex, age, height, and
weight. Participants then completed the IPAQ with the researcher, allowing for further
probing to address over-reporting (Rzewnicki, Auweel, & Bourdeaudhuij, 2003). The
participant was then given the corresponding physical activity booklet, and instructed to read
it at least once over the upcoming week. At the post-intervention meeting one week later
participants completed the same questionnaires and were then debriefed.
Between-group differences in baseline measures (including BMI and age) were
checked with independent sample t-tests. To adjust for the inclusion of multiple dependent
variables a mixed design MANOVA was used with time (pre and post) as the within-subjects
factor and condition (congruent and incongruent) as the between-subjects factor. Significant
main effects were then further explored with univariate ANOVAs where appropriate.
Multiple regression was then utilised to assess whether changes in SCT variables predicted
changes in MVPA.
Overall 55 of the 57 participants in the congruent condition and all 53 participants in
the incongruent condition reported reading the booklet. A set of independent samples t-tests
confirmed that there was no difference by condition at baseline on any outcome (all p > .05).
Insert table 1 about here
A mixed MANOVA was conducted, with one between subjects factor (condition -
congruent and incongruent) and one within subjects factor (time – pre and post) on SCT
constructs, and MVPA. There was a non-significant multivariate effect for condition, V = .09,
F(5, 103) = 2.10, p = .071, η2 = .09. A significant multivariate effect was found for time
point, V = .13, F(5, 103) = 3.13, p = .011, η2 = .13, as well as for the interaction between
condition and time point, V = .11, F(5, 103) = 2.46, p = .038, η2 = .11. To investigate these
effects further, univariate analyses were explored.
Insert table 2 about here
Mixed univariate analyses showed a time main effect for both self-regulation and
MVPA. The effect sizes indicated that 9.1% and 5.9% of variability in participant self-
regulation and MVPA respectively was accounted for by time point. There was a significant
univariate interaction between condition and time point for intentions and self-efficacy. The
effect sizes indicated that 3.9% of variability in intentions and 7.0% of variability in self-
efficacy was accounted for by the interaction. Post-hoc analyses showed that both intentions
and self-efficacy increased significantly in the congruent condition between pre and post,
t(55) = -2.76, p = .008, and t(55) = -3.17, p = .003, respectively, but not for the incongruent
condition, t(52) = .18, p = .860, and t(52) = .92, p = .362.
A multiple regression was undertaken to explore whether the changes in MVPA could
be predicted by changes in SCT constructs. For the congruent condition 19.3% of variability
in MVPA change and 10.0% for the incongruent condition could be explained by the changes
in SCT constructs. The regression model, was not significant for the incongruent condition,
R2 = .100, F(4,48) = 1.34, p = .269, but was significant for the congruent condition, R2 = .193,
F(4,51) = 3.05, p = .025. Changes in self-regulation were the only significant predictor of
change in MVPA for the congruent (p = .003) and incongruent (p = .030) condition.
Participants in the congruent condition showed a greater increase in intentions and
self-efficacy, whereas self-regulation and MVPA increased irrespective of condition.
Therefore the central part of the first hypothesis concerning physical activity was rejected.
Self-regulation (particularly in the congruent condition) predicted changes in MVPA,
supporting the secondary hypothesis. Vividness congruency between the key elements of the
congruent booklet (text and accompanying images) may have resulted in participants paying
more attention to (and having a greater understanding of) the health message (Smith &
Shaffer, 2000). This may have enabled them to better contemplate their ability to perform the
suggested exercises, thus increasing self-efficacy and intentions. Similar findings have shown
that congruency is effective in information provision for smoking cessation (Davis,
Nonnemaker, Farrelly, & Niederdeppe, 2011).
Outcome expectancies did not increase after the intervention despite the leaflet
outlining advantages of physical activity. However, high baseline scores indicated existing
favourable expected consequences. The increase in self-regulation across both conditions
may be explained by the fact that the health message encouraged participants to contemplate
the required frequency of physical activity, something they may not have previously
considered. The only increase across both conditions was seen in self-regulation suggesting
this construct may be of most importance in changing physical activity, a notion supported by
previous research (Michie et al., 2009).
A strength of the present study is the focus on gain-framed messages alongside
physical activity-related images and measuring baseline physical activity, something many
studies have not (Cheval, Sarrazin, Isoard-Gautheur, Radel, & Friese, 2015). Images of the
same individuals were used in each condition thus controlling for factors such as the models
perceived attractiveness. A limitation was the lack of a no-image control, which would have
helped uncover whether having images regardless of context is beneficial and/or whether the
increases seen were simply from a mere-measurement effect (Godin, Bélanger-Gravel,
Amireault, Vohl, & Pérusse, 2011). Also, teasing apart the potential effects of the static and
action images (congruent booklet) would also be beneficial in future research.
Ultimately the present study showed that congruence between message content and
images increased intentions and self-efficacy, but not MVPA. An increase in self-regulation
across both conditions mirrored the increase in physical activity, showing that self-regulation
may underpin physical activity change. Further research is needed to optimize health message
content and to analyse additional moderators, so that changes in SCT constructs can be more
successfully translated into changes in physical activity.
Ainsworth, B. E., Macera, C. A., Jones, D. A., Reis, J. P., Addy, C. L., Bowles, H. R., &
Kohl, H. W. (2006). Comparison of the 2001 BRFSS and the IPAQ physical activity
questionnaires. Medicine & Science in Sports & Exercise, 38(9), 1584-1592.
Bandura, A. (2004). Health promotion by social cognitive means. Health Education &
Behavior, 31(2), 143-164.
Bauman, A. E. (2004). Updating the evidence that physical activity is good for health: an
epidemiological review 2000–2003. Journal of Science and Medicine in Sport, 7(1),
Berenbaum, E., & Latimer-Cheung, A. E. (2014). Examining the link between framed
physical activity ads and behavior among women. Journal of Sport & Exercise
Psychology, 36(3), 271-280.
Boer, H., Ter Huurne, E., & Taal, E. (2006). Effects of pictures and textual arguments in sun
protection public service announcements. Cancer Detection and Prevention, 30(5),
Cheval, B., Sarrazin, P., Isoard-Gautheur, S., Radel, R., & Friese, M. (2015). Reflective and
impulsive processes explain (in)effectiveness of messages promoting physical
activity: A randomized controlled trial. Health Psychology, 34(1), 10-19.
Davis, K. C., Nonnemaker, J. M., Farrelly, M. C., & Niederdeppe, J. (2011). Exploring
differences in smokers' perceptions of the effectiveness of cessation media messages.
Tobacco Control, 20(1), 26-33.
Delp, C., & Jones, J. (1996). Communicating information to patients: the use of cartoon
illustrations to improve comprehension of instructions. Academic Emergency
Medicine, 3(3), 264-270.
Francis, J. J., Eccles, M. P., Johnston, M., Walker, A., Grimshaw, J., Foy, R., … Bonetti, D.
(2004). Constructing questionnaires based on the theory of planned behaviour: A
manual for health services researchers. Newcastle upon Tyne, UK: Centre for Health
Services Research, University of Newcastle upon Tyne.
Gallagher, K. M., & Updegraff, J. A. (2012). Health message framing effects on attitudes,
intentions, and behavior: A meta-analytic review. Annals of Behavioral Medicine,
Godin, G., Bélanger-Gravel, A., Amireault, S., Vohl, M., & Pérusse, L. (2011). The effect of
mere-measurement of cognitions on physical activity behavior: a randomized
controlled trial among overweight and obese individuals. International Journal of
Behavioral Nutrition and Physical Activity, 8(2), 1-6.
Haas, B. K., & Northam, S. (2010). Measuring self-efficacy: Development of the physical
activity assessment inventory. Southern Online Journal of Nursing Research, 10(4),
Health and Social Care Information Centre. Statistics on Obesity, Physical Activity and Diet:
Howlett, N., Pine, K. J., Orakçıoğlu, I., & Fletcher, B (2013). The influence of clothing on
first impressions: Rapid and positive responses to bespoke features in male attire.
Journal of Fashion, Marketing and Management, 17, 38-48. doi:
Latimer, A. E., Brawley, L. R., & Bassett, R. L. (2010). A systematic review of three
approaches for constructing physical activity messages: what messages work and
what improvements are needed? International Journal of Behavioral Nutrition and
Physical Activity, 7(1), 36-52.
McCormick, M., & McElroy, T. (2009). Healthy choices in context: How contextual cues can
influence the persuasiveness of framed health messages. Judgment and Decision
Making, 4(3), 248-255.
Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., … Wood,
C. E. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically
clustered techniques: building an international consensus for the reporting of behavior
change interventions. Annals of Behavioral Medicine, 46, 81-95.
Michie, S., Abraham, C., Whittington, C., McAteer, J., & Gupta, S. (2009). Effective
techniques in healthy eating and physical activity interventions: A meta-regression.
Health Psychology, 28(6), 690–701.
Rzewnicki, R., Auweele, Y. V., & Bourdeaudhuij, I. D. (2003). Addressing overreporting on
the International Physical Activity Questionnaire (IPAQ) telephone survey with a
population sample. Public Health Nutrition, 6(3), 299-305.
Rothman, A. J., & Salovey, P. (1997). Shaping perceptions to motivate healthy behavior: The
role of message framing. Psychological Bulletin, 121(1), 3-19.
Smith, S. M., & Shaffer, D. R. (2000). Vividness can undermine or enhance message
processing: The moderating role of vividness congruency. Personality & Social
Psychology Bulletin, 26(7), 769-779.
Sniehotta, F. F., Scholz, U., & Schwarzer, R. (2005). Bridging the intention–behaviour gap:
Planning, self-efficacy, and action control in the adoption and maintenance of
physical exercise. Psychology & Health, 20(2), 143-160.
Steinhardt, M. A., & Dishman, R. K. (1989). Reliability and validity of expected outcomes
and barriers for habitual physical activity. Journal of Occupational and
Environmental Medicine, 31(6), 536-546.
Young, M. D., Plotnikoff, R. C., Collins, C. E., Callister, R., & Morgan, P. J. (2014). Social
cognitive theory and physical activity: a systematic review and meta-analysis. Obesity
Reviews, 15(12), 983-995.