JOURNAL OF

Journal of Sport & Exercise Psychology, 2014, 36, 40-51 http://dx.doi.org/10.1123/jsep.2012-0278 © 2014 Human Kinetics, Inc.

SPORT EXERCISE PSYCHOLOGY

Official Journal of NASPSPA

www.JSEP-Journal.com ORIGINAL RESEARCH

Effects of Message Framing on Self-Report and Accelerometer-Assessed Physical Activity Across Age and Gender Groups Kin-Kit Li,1 Sheung-Tak Cheng,2 and Helene H. Fung3 1City

University of Hong Kong; 2Hong Kong Institute of Education; 3Chinese University of Hong Kong

This study compared message-framing effects on physical activity (PA) across age and gender groups. Participants included 111 younger and 100 older adults (68% were women), randomly assigned to read gain-framed or loss-framed PA messages in promotion pamphlets, and who wore accelerometers for the following 14 days. Using regression analyses controlling for demographic and health factors, we found significant age-by-genderby-framing interactions predicting self-report (B = –4.39, p = .01) and accelerometer-assessed PA (B = –2.44, p = .02) during the follow-up period. Gain-framed messages were more effective than loss-framed messages in promoting PA behaviors only among older men. We speculated that the age-related positivity effect, as well as the age and gender differences in issue involvement, explained the group differences in framing. In addition, more time availability and higher self-efficacy among older men might have contributed to the results. Keywords: message framing, persuasion, prospect theory, information processing, decision making, health communication The effectiveness of health promotion messages depends on how messages are framed (Rothman & Salovey, 1997). For health-affirming behaviors such as physical activity (PA), messages framed in terms of gains (i.e., benefits of participation) rather than losses (i.e., costs of nonparticipation) have been suggested to be more effective (Rothman, Bartels, Wlaschin, & Salovey, 2006; Rothman & Salovey, 1997). Although a weak advantage of gain-framed over loss-framed messages was found in meta-analyses (Gallagher & Updegraff, 2012), results of framing effects in previous PA studies have been mixed (e.g., Jones, Sinclair, Rhodes, & Courneya, 2004; van ’t Riet, Ruiter, Werrij, & de Vries, 2010). Characteristics of the message recipients may be potential moderators to explain the mixed findings (e.g., Covey, 2012; Rothman et al., 2006). Because age and gender are highly identifiable and accessible, age- and gender-specific messages can be selectively assigned to optimize intervention effectiveness. In addition, the extant findings did not include older adults, and outcome measures were often limited to attitudes, intentions, or self-report behaviors Kin-Kit Li is with the Department of Applied Social Studies, City University of Hong Kong, Kowloon Tong, Hong Kong. Sheung-Tak Cheng is with the Department of Psychological Studies and Center for Psychological Health and Aging, Hong Kong Institute of Education, Tai Po, Hong Kong. Helene H. Fung is with the Department of Psychology, Chinese University of Hong Kong, Shatin, Hong Kong.

40

(Gallagher & Updegraff, 2012). Further investigation of the validity and generalizability of the framing effects on PA is needed. Thus, this study examined the framing effect on PA across age and gender groups using both self-report and objective measures of PA.

Message Framing in Physical Activity Promotion Health messages can be framed on a gain or loss basis (Rothman & Salovey, 1997). Gain-framed messages describe the benefits of taking the health-relevant action, whereas loss-framed messages describe the costs of (or missing out on the benefits by) not taking the action. The message-framing effects on changes in health behavior depend on the functional characteristics of the behavior (Rothman et al., 2006). Detection behaviors (e.g., screening for breast cancer), which identify illnesses that are threatening and anxiety inducing, are construed as risky, whereas promotion and recuperative behaviors (e.g., participating in PA, using sunscreen), which maintain a healthy status, are construed as low-risk (Rothman & Salovey, 1997). Gain-framed messages are expected to be more effective in promoting low-risk behaviors including promotion and recuperative behaviors (i.e., positive framing effects), whereas loss-framed messages are more effective for risky behaviors including detection behaviors (i.e., negative framing effects; Rothman et al., 2006; Rothman & Salovey, 1997).

Effects of Message Framing on Physical Activity   41

A positive framing effect on PA has been supported by several studies. McCall and Ginis (2007) found that cardiac patients who read gain-framed messages tended to exercise more than those who read loss-framed messages over a 3-month follow-up. Although the difference was not significant in this small sample, the effect size was moderate (r = .31). In addition, Latimer et al. (2008) showed that people who received gain-framed messages on multiple occasions, rather than loss-framed messages, reported higher PA intention and self-efficacy after 2 weeks, and more PA participation after 9 weeks. In a community sample of adults, gain-framed messages were found to be more effective in increasing PA intention than loss-framed messages, and the effect on PA behaviors was marginally significant after 3 months (van ’t Riet, Ruiter, Werrij, & de Vries, 2010). Other studies, however, did not support the framing effect. For instance, Jones and colleagues (2004) found no difference in PA attitudes, intentions, or behaviors between students who read gainframed and loss-framed PA messages. The gain-frame advantage on PA promotion was not found in O’Keefe and Jensen’s (2007) meta-analysis, when effectiveness was evaluated by a combined measure of attitudes, intentions, and behaviors. A recent metaanalysis has revealed that gain-framed messages were more effective than loss-framed messages in increasing PA behaviors, but not attitudes and intentions (Gallagher & Updegraff, 2012). Because framing effects on behaviors were not fully mediated by attitudes and intentions, Gallagher and Updegraff suggested that actual behavioral measures were needed for meaningful assessment of message persuasiveness. Considering recall and desirability bias in self-report PA measures (Troiano et al., 2008), objective measures such as accelerometers are recommended. Thus, we hypothesized that gain-framed messages would be more effective than loss-framed messages in promoting self-report and accelerometerassessed PA. The mixed findings reviewed above may be partially driven by moderators such as age and gender. Some theoretical propositions of such moderations are elaborated below.

Age Differences in Framing Effects As physical capability declines with age (Vaupel, 2010), making health decisions becomes more frequent and salient among older adults. With the decline in cognitive processing, older adults become more likely to rely on the affective mode (i.e., more effortless, automatic, and associative strategies) than the deliberative mode (i.e., more conscious, analytical, and reason-based strategies) in making judgments and decisions (Peters, Hess, Västfjäll, & Auman, 2007). The deliberative mode is more flexible, and one of its functions is to provide effortful monitoring and control over the quality of processing and the impact of the affective system (Kahneman, 2003). In addition, the age-related motivational shift toward more emotionally meaningful goals also contributes to reliance on the affective mode of thinking. Specifically, older

adults tend to shift their attention to adaptively optimize their positive emotions according to the socioemotional selectivity theory (Carstensen, Fung, & Charles, 2003). Previous studies have shown that older adults attend more to and more accurately remember positive information than negative information (Carstensen & Mikels, 2005; Mather & Carstensen, 2005), which is often referred to as the positivity effect. Thus, older adults may be more sensitive to valence-framed messages and be more attentive to gain-framed and/or positively framed messages, in particular. The framing effects of health messages have often been tested among younger and middle-aged adults (see Gallagher & Updegraff, 2012; and O’Keefe & Jensen, 2007, for reviews). The extent to which framing effects on PA behaviors can be generalized to the older population has not yet been examined. Considering the age-related positivity effect, we hypothesized that the positive framing effects on PA should be stronger among older adults than among younger adults.

Gender Differences in Framing Effects Gender may also moderate framing effects. A few mechanisms (e.g., gender differences in information processing, risk perception, and issue involvement) have been proposed in the literature. However, their theoretical predictions are not entirely compatible. First, some studies suggested that women tend to process information more comprehensively than do men (Darley & Smith, 1995). Negatively framed messages tend to be more persuasive when information is processed comprehensively, because negative information is often unexpected in most situations and hence considered more diagnostic for forming judgment (Meyers-Levy & Maheswaran, 2004). Thus, loss-framed messages may be more effective among women (i.e., negative bias). However, other studies showed no gender differences in the dispositional tendency to engage in and enjoy effortful cognitive activities (see Cacioppo, Petty, Feinstein, & Jarvis, 1996, for a review). Second, individuals who perceived behaviors as more risky are more receptive to loss-framed messages and vice versa (Rothman et al., 2006). Women, in general, report greater levels of risk perception than men (see Gustafson, 1998, for a review) and may be more receptive to loss-framed messages (i.e., negative bias). For instance, Toll and colleagues (2008) found that women perceived greater negative consequences for quitting smoking than men did. In their study, gain-framed messages were more effective than loss-framed messages only among women with less perceived risks. However, their findings did not address the proposition that individual differences in risk perception may explain gender differences in framing. The first two mechanisms reviewed were unable to account for findings showing stronger positive framing effects among women than men in using sunscreen (Rothman, Salovey, Antone, & Keough, 1993; Experiment 2) and condoms (Kiene, Barta, Zelenski, & Cothran, 2005;

42  Li, Cheng, and Fung

Study 2), as well as delaying a smoking relapse (Toll et al., 2007). In this regard, the third mechanism may seem more viable. Women may be more involved with health issues (i.e., considering health issues as personally important) than men (Courtenay, 2000). For instance, Deeks, Lombard, Michelmore, and Teede (2009) have shown that women were more interested in receiving information about illness prevention than men. A high level of issue involvement facilitates more comprehensive information processing (Petty & Cacioppo, 1990) and thus may lead to a higher sensitivity to framing effects (Millar & Millar, 2000; Rothman et al., 2006; Rothman & Salovey, 1997). Contrary to the first mechanism, effects of health message framing are suggested to be amplified among women regardless of the direction of the framing effect. Rothman and Salovey (1997) indicated that most health message studies did not report gender differences in framing effects (e.g., Jones, Sinclair, & Courneya, 2003; Latimer et al., 2008), which might be owing to null results. Contrary to the evidence mentioned above, a few health message studies reported no gender differences in framing (e.g., Nan, 2012; van ’t Riet, Ruiter, Werrij, & de Vries, 2010). Despite the inconclusive theoretical predictions and empirical evidence, examining gender as well as age differences in PA framing effects is important in a practical sense. These demographic factors are easily identifiable and accessible for age- and gender-specific PA interventions. Therefore, this study explored whether PA framing effects would be different across gender groups using an objective behavioral measure.

Purposes of the Study Considering the potential practical implications, this study aimed to examine whether age and gender moderated PA message framing. Specifically, gain-framed messages were hypothesized to be more effective than loss-framed messages in increasing PA behaviors (Hypothesis 1). The positive framing effect was expected to be stronger for older adults than for younger adults (Hypothesis 2). No hypothesis was formulated for gender moderation. In addition, the combined effects of age and gender on framing (i.e., a three-way interaction) were also explored. This study was unique in using accelerometers to measure PA, which extended the testing of framing from immediate and self-report outcomes in experimental settings to the objective measure of PA in an unstructured environment.

Methods Participants Hong Kong Chinese adults aged 18–35 years and 60 years or older were included in the younger and older groups, respectively. Adults who were physically active, were unable to read the promotion pamphlets (i.e., they were visually impaired or illiterate), had mobility limitations, or had indications of dementia were not included.

Using an established PA recommendation (Haskell et al., 2007), we defined physical inactivity as fewer than 150 min of moderate-to-vigorous PA per week. This sedentary requirement ensured that the PA messages were more relevant to the participants. The Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975) was used to screen for any indication of cognitive deficits. Adults who scored 20 or more on MMSE were included to take into account the generally low education levels among older adults in Hong Kong (Chiu, Lee, Chung, & Kwong, 1994). Trost, McIver, and Pate (2005) suggested that a minimum of 3 to 5 days of wearing the accelerometer is required for reliable estimation of PA in field studies among adults. In this study, a minimum of 4 valid days (see the definition below) was used as the inclusion criterion for the analyses. Excluding those who provided fewer than 4 valid days of accelerometer data (n = 16) or whose monitors were not in calibration on return (n = 4), and those with incomplete survey data (n = 3), the sample in the analyses included 111 younger and 100 older adults. The mean ages were 22.31 (SD = 3.04) years and 71.66 (SD = 7.48) years for younger and older adults, respectively. Women were more highly represented (68%). Younger and older participants were recruited mainly in universities and community centers, respectively. Participation was voluntary, and informed consent was sought. A HK$50 gift coupon was given to the participants at the end of each part of the study.

Study Design and Procedures In the first part of the study, a screening tool that included the MMSE, the International Physical Activity Questionnaire (IPAQ), and a single-item on mobility limitations was administered by trained experimenters to determine the eligibility of those interested in participating. The levels of PA measured by the screening tool were used as the baseline (Time 1) levels of their PA in the subsequent analyses. After that, participants were randomly assigned to receive the gain- framed or the loss-framed PA promotion messages. Before receiving the promotion messages, participants were asked to respond to measures of their perceived health status and functional ability by completing the Instrumental Activities of Daily Living (Lawton & Brody, 1969) scale. After that, the PA messages were verbally and visually presented to the participants individually by the experimenters to ensure that participants paid ample attention to the materials. A manipulation check was then conducted, with questions on demographic information at the end. In the second part of the study, participants were invited to wear an accelerometer on one side of their waists to objectively monitor their PA for the following 14 days. Other than participating in water sports, taking a shower, and sleeping, they were asked to wear the accelerometer for the entire period. To enhance their adherence to the procedure, they received telephone prompts three

Effects of Message Framing on Physical Activity   43

times a week and were asked to complete an activity log every day during the period, as recommended by Trost et al. (2005). When they returned the accelerometer, they were asked again to report their PA using the IPAQ (Time 2). The study protocol was approved by Research Ethics Subcommittee at City University of Hong Kong.

Materials Two versions of PA promotion pamphlets were developed. Pamphlets were color-printed with messages printed in a large font size. The introductory section, which presented an overview of the PA recommendation and the prevalence of those meeting the recommendation, was the same across the two versions. In the second section, the benefits of PA participation were presented via either gain- or loss-framed messages. Messages were organized into three sections including physical, psychological, and social benefits, with 11, 8, and 4 statements, respectively. Physical benefits were printed on one page, and the other benefits were printed on the next page. Messages were rather short for better recognition and retention. Consistently with the gain- and loss-framed messages used in Jones et al.’s (2003) study, the content of the messages in the two versions was identical. Sample messages are shown in Table 1.

Instruments Manipulation Check.  Two manipulation-check ques-

tions were included. Participants decided whether the materials described the gains of PA participation and whether the materials described the lack of benefits of not participating in PA. Responses were on a 7-point scale (1 = strongly disagree; 7 = strongly agree).

Subjective Evaluation of the Messages.  Items used

in Fung and Carstensen’s (2003) study were used as the template for assessing subjective evaluation of each promotion pamphlet. Participants were asked to rate the following items on a 7-point scale (1 = strongly disagree; 7 = strongly agree): “I like the pamphlet,” “The pamphlet is memorable to me,” and “The pamphlet is persuasive.” Higher ratings indicated a more positive evaluation. In this study, the alpha coefficient was .81, indicating satisfactory internal consistency.

Self-Report Physical Activity.  The Chinese version

of the IPAQ (IPAQ-C; Macfarlane, Lee, Ho, Chan, & Chan, 2007) was administered in both parts of the study. Participants responded to questions related to the frequency and duration of vigorous PA, moderate PA, walking, and sitting over the past 7 days. The sum of the weekly minutes of moderate and vigorous PA was used in the analysis. Macfarlane et al. found that the scores of IPAQ-C were reliable across three administrations on Days 1, 8, and 11 (ICC = .79) and agreed reasonably well with PA log and accelerometer data.

Accelerometer-Assessed Physical Activity.  Participants were asked to wear a GT3X accelerometer, by Actigraph (http://www.actigraphcorp.com/), for 14 days following the first part of the study. The processing protocol was adapted from Troiano et al. (2008). The activity counts in the accelerometers were processed into the mean minutes of moderate-to-vigorous PA per day. For more evidence of validity and higher comparability with previous studies, only the uniaxial data were used. Data were recorded into 60-s epochs. An interval of at least 60 consecutive minutes of zero activity was defined as nonwear. Wear time was defined as 24 hr minus the daily nonwear time; 10 or more hours of wear time was defined

Table 1  Examples of Gain- and Loss-Framed Messages for Physical Activity Promotion Gained-Framed Messages If you participate in regular physical activity, you . . .

Loss-Framed Messages If you do NOT participate in regular physical activity, you . . .

Physical aspects (11 statements)   CAN improve immunity, reduce sickness, and enhance productivity   CAN increase joint mobility and flexibility, and prevent falls and injuries   CAN develop muscles, strengthen bones, and reduce risks of osteoporosis

  CANNOT improve immunity, reduce sickness, and enhance productivity   CANNOT increase joint mobility and flexibility, and prevent falls and injuries   CANNOT develop muscles, strengthen bones, and reduce risks of osteoporosis

Psychological aspects (8 statements)   CAN improve moods   CAN enhance mental alertness   CAN manage stress

  CANNOT improve moods   CANNOT enhance mental alertness   CANNOT manage stress

Social aspects (4 statements)   CAN establish new friendship   CAN improve social relationships   CAN gain social acceptance

  CANNOT establish new friendship   CANNOT improve social relationships   CANNOT gain social acceptance

44  Li, Cheng, and Fung

as a valid day. The cutoffs of activity counts for different intensity levels by Freedson, Melanson, and Sirard (1998) were adopted. The reliability and validity of the accelerometers have been shown in both controlled and natural settings (e.g., Le Masurier & Tudor-Locke, 2003). Covariates.  Several demographic and health factors

that might affect the interpretation of the results were measured and controlled for in the analyses. Demographic factors included marital status (0 = not married; 1 = married) and education level (0 = no formal education to 5 = bachelor degree or above). Health-related factors were body mass index (kg/m2), and number of chronic conditions such as asthma, arthritis, diabetes, and hypertension (0 to 20).

Analysis The skewed distributions of self-report and accelerometer-assessed PA were normalized by square-root transformation, so as to avoid biased results because of violations of statistical assumptions (Cohen, Cohen, West, & Aiken, 2003). As recommended by Kraemer and Blasey (2004), the binary independent variables that were multiplied to form interaction terms were coded as ±1/2. This centering procedure allows meaningful interpretations of the main effects and protects against most errors in statistical inferences when moderation is tested. Baseline Equivalence Analysis of Self-Report Physical Activity.  Because of randomization, people in the

gain- and loss-framed groups should be equal in terms of self-report PA. Although age and gender cannot be manipulated, their differences in baseline PA should be limited because only sedentary adults were recruited. To evaluate the adequacy of the randomization, the equivalence of self-report PA at Time 1 across age (1/2 = older; –1/2 = younger) and gender (1/2 = women; –1/2 = men) groups, and framing types (1/2 = gain; –1/2 = loss) was tested. In a regression model, self-report PA at Time 1 was regressed on age, gender, framing types, and their two-way and three-way interaction terms, controlling for the covariates.

Manipulation Check.  To examine the quality of the manipulation, the scores of the manipulation-check items were compared across age, gender, and framing types. A composite score was computed by subtracting the score of the loss-framed item from the score of the gain-framed item; hence a higher score indicated stronger agreement with reading gain-framed versus loss-framed messages. Based on the regression model described above, the composite scores were regressed on age, gender, framing, and their interactions with self-report PA at Time 1 as an additional covariate. The inclusion of self-report PA at Time 1 should have improved the precision of the results. These analyses also reflected the accuracy of reporting, indicating how different groups of individuals might receive, encode, retain, and retrieve the information differently.

Outcome Analyses.  The main outcomes of the study were self-report and accelerometer-assessed PA at Time 2, which served as the behavioral assessment. Supplementary to the main outcomes were subjective evaluation of the pamphlets, as an immediate cognitive assessment. Using the same models as the manipulationcheck analysis, the outcome measures were tested in separate regression models. Sensitivity Check.  Because age and gender groups

could not be manipulated, some characteristics (i.e., covariates) might be different across the groups. To examine to what extent the interactions among age, gender, and framing types might be explained by the differences in the covariates, the interactions between framing types and each of the covariates were tested in separate models. These analyses were conducted for all three outcome variables.

Results Sample characteristics across age and gender groups and framing types are presented in Table 2. On average, participants provided 12.31 days of valid accelerometer data (SD = 2.49). Over the study period, self-reported moderate-to-vigorous PA increased significantly from 3.72 (SD = 5.56) to 14.88 (SD = 32.06) minutes per day (t = 5.02, df = 210, p < .001). At Time 2, the self-report PA was lower than the accelerometer-assessed PA (M = 32.16, SD = 24.10; t = –6.17, df = 210, p < .001). More than 150 min per week of moderate-to-vigorous PA were undertaken by 24% and 66% of the participants, based on self-report and accelerometer-assessed PA, respectively.

Baseline Equivalence and Manipulation Check Age, gender, framing types, and their interactions did not predict self-report PA at baseline, controlling for demographic and health factors. Results supported the equivalence in self-report PA at baseline across groups. When predicting the manipulation-check composite score, framing type (B = 3.17, p < .001) and its interaction with age (B = –2.18, p = .001) were found to be significant. Other interactions were not significant. To decompose the age-by-framing interaction, marginal effects of framing types for younger and older adults were computed. The marginal effects for both younger (B = 4.28, p < .001) and older adults (B = 2.05, p < .001) were significant. Overall, 41% of the variance in the manipulation-check score was explained. Results of the manipulation check indicated that the gain- and loss-framed messages were in general received as intended. Younger adults, however, reported a greater distinction between gain- and lossframed messages than did older adults, and older adults tended to mistakenly report the loss-framed messages as gain-framed. A supplementary analysis showed that removing 16 cases of erroneous recalls (i.e., those who rated the message as having the other framing more

Effects of Message Framing on Physical Activity   45

Table 2  Sample Characteristics (N = 211) Younger Women SD Mean / %

Younger Men Mean / % SD

Older Women Mean / % SD

Older Men Mean / % SD

Gain-framed  Married

0.00%

—

0.00%

—

72.50%

—

85.71%

—

 Education

4.94

0.24

4.95

0.23

2.38

0.84

2.57

1.02

  Body mass index

20.54

2.29

21.15

2.48

23.85

4.29

22.81

3.06

  Chronic conditions

0.06

0.24

0.21

0.54

1.90

1.61

2.00

1.96

  Positive evaluation

4.61

1.07

5.09

1.05

6.08

0.84

6.48

0.79

  T1 self-report PA

3.13

5.22

3.92

4.79

4.55

6.54

5.28

7.29

  T2 self-report PA

7.33

14.79

5.80

7.77

13.83

19.84

51.03

60.09

  T2 accelerometer PA

36.70

12.52

49.63

18.35

16.96

16.39

41.55

44.54

  Sample size

34

19

40

14

Loss-framed  Married

2.63%

—

5.00%

—

43.75%

—

 Education

4.95

  Body mass index

20.48

  Chronic conditions

78.57%

—

0.32

5.00

2.59

21.14

0.00

2.25

2.33

24.11

0.72

2.71

1.54

3.35

24.19

3.83

0.24

0.59

0.25

0.55

2.22

1.54

1.71

1.44

  Positive evaluation

4.21

  T1 self-report PA

1.92

1.04

4.53

3.15

4.07

1.13

6.01

0.96

5.90

0.94

5.46

4.89

6.64

2.68

4.54

  T2 self-report PA

4.45

9.69

8.38

12.14

28.39

56.48

19.08

23.53

  T2 accelerometer PA

39.53

17.54

50.75

17.61

16.71

19.84

20.29

26.95

  Sample size

38

20

32

14

Note. PA = moderate-to-vigorous physical activity, in the unit of minutes per day.

than the intended framing) did not change the patterns of significant effects in the outcome analyses. Unstandardized and standardized regression estimates of the baseline equivalence analysis, manipulation check, and the outcome analyses are presented in Table 3.

Outcome Analyses When predicting subjective evaluation, age (B = 1.85, p < .001) and framing types (B = 0.40, p = .009) were significant. The messages were evaluated more positively among older adults and those who read gain-framed messages. No interaction effects were found to be significant. The model explained 42% of the variance of subjective evaluation. Gender (B = –1.02, p = .02) and age-by-gender-byframing interaction (B = –4.39, p = .01) were significant in predicting self-report PA. Other interaction effects were not significant. Marginal effects of framing across age and gender groups were computed to decompose the significant interaction effect. The framing effect was significant only among older men (B = 2.68, p = .01). When predicting accelerometer-assessed PA, the main effects of gender (B = –0.89, p = .001) and framing (B = 0.52, p = .0495), age-by-framing (B = 1.29, p =

.02), gender-by-framing (B = –1.34, p = .01), and ageby-gender-by-framing (B = -2.44, p = .02) interactions were significant. Marginal effects of framing were significant only among older men (B = 2.44, p < .001). The models explained 18% and 44% of the variances of the self-report and accelerometer-assessed PA, respectively. The predicted values of self-report and accelerometerassessed PA across groups are shown in Figure 1a and 1b. The framing effect was the strongest among older men who read gain-framed messages. Values of variance inflation factors indicated that multicollinearity was not a serious problem in these analyses. Because the standard deviations of the PA measures were relatively large in some groups, Mahalanobis distances (critical α = .05) and Cook’s distances (critical value = 1) were computed to detect possible multivariate outliers. No multivariate outliers were found.

Sensitivity Check In this study, older adults were more likely than were younger adults to be married, χ2(1) = 99.27, p < .001; be less educated, t(209) = 27.10, p < .001; have a higher BMI, t(209) = –7.20, p < .001; and have more chronic medical conditions, t(209) = –11.31, p < .001.

46 .19 –.03 .06 .02 –.05 .12 –.08

0.57 –0.09 0.20 0.09 –0.30 0.75 –1.00 4.64

R2 (%)

Note. PA = physical activity; T1 = Time 1; T2 = Time 2. *p < .05; **p < .01; ***p < .001.

.05 .28 .05 .04 —

0.16 0.29 0.02 0.04 —

Intercept Covariates  Married  Education   Body mass index   Chronic conditions   T1 self-report PA Main effects  Older  Women  Gain-framed 2-way interaction   Gain × older   Gain × women   Older × women 3-way interaction   Gain × older × women

T1 Self-Report PA B β –0.36

41.09***

–0.31

–2.18** –0.02 0.39

0.86 –0.34 3.17***

–0.41 –0.01 –0.09 –0.14 –0.15

–.01

–.20** .00 .04

.16 –.06 .58***

–.07 –.01 –.12 –.07 –.08

Manipulation Check B β 3.52*

41.54***

–0.37

–0.16 –0.35 0.30

1.85*** –0.26 0.40**

–0.04 0.09 –0.01 –0.03 –0.01

–.04

–.03 –.07 .06

.73*** –.10 .16**

–.01 .11 –.02 –.04 –.01

Message Evaluation B β 5.24***

18.09***

–4.39*

0.75 –1.62 –1.26

1.99 –1.02* 0.40

0.45 0.00 –0.01 –0.03 0.19

–.18*

.06 –.13 –.10

.32 –.15* .06

.07 .00 –.01 –.01 .09

T2 Self-Report PA B β 2.67

44.20***

–2.44*

1.28* –1.34* 0.09

–0.54 –0.89** 0.52*

0.24 0.67*** 0.06 –0.28** –0.11

–.13*

.14* –.15* .01

–.12 –.18** .11*

.05 .42*** .09 –.18** –.07

Accelerometer PA B β 2.03

Table 3  Unstandardized and Standardized Regression Estimates of Baseline Self-Report Physical Activity, Manipulation-Check Items, Evaluation of the Messages, and Time-2 Self-Report and Accelerometer-Monitored Physical Activity (N = 211)

Effects of Message Framing on Physical Activity   47

Figure 1 — Model-predicted group means of (a) self-report and (b) accelerometer-assessed physical activity. Error bars show standard errors.

No gender differences in the covariates were found. A set of analyses was conducted to examine how the results might change as a function of the covariates. Adding each of the interaction terms between a covariate and framing type into the models did not change the pattern of significant coefficients. Results demonstrated that the findings were not sensitive to the differences in demographic (except age and gender) or health-related factors.

Discussion This study examined the differences in framing effects on PA across age and gender groups. In addition to self-report and accelerometer-assessed PA, subjective evaluation of the messages was used as a cognitive indicator of the persuasive effects. Age-by-gender-byframing interaction effects were significant in predicting self-report and accelerometer-assessed PA, but not

positive evaluation. Findings generally supported both hypotheses 1 (i.e., positive framing effect) and 2 (i.e., age-by-framing effect). Gain-framed messages were found to be more effective than loss-framed messages in promoting PA, particularly among older adults. These relationships were further moderated by gender, in which the positive framing effect was mainly driven by older men. Demographic and health-related differences between younger and older adults did not influence the pattern of results. Although mechanisms of framing were not directly examined, potential theoretical implications are discussed.

Objective Measures of Physical Activity One unique contribution of this study was that subjective and objective measures of PA, rather than attitudes and intentions, were included. With accelerometer data as the standard, younger adults were more likely to under-report

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their PA than were their older counterparts. To enhance recall reliability, respondents of the self-report measures (including IPAQ-C) are often asked to exclude activity bouts of fewer than 10 min, whereas accelerometers are able to record more sporadic and activities of shorter bouts (Mackay, Oliver, & Schofield, 2011). Thus, the current results may reflect that older adults may perform more structured PA with longer bouts, whereas the PA of those younger adults may be more sporadic (e.g., brisk walk between public transport stations and classrooms or between various classrooms and canteens on campus). Despite the differences between the subjective and objective measures of PA, the patterns of the framing effects on these measures were consistent. Interestingly, the variances explained for subjective and objective measures of PA were quite different (18% and 45%, respectively). The lower variance explained for subjectively measured PA might be owing to the reporting errors, which support the use of accelerometers.

Framing Effects on Physical Activity Among Younger Adults No framing effect was found among younger adults. Results were consistent with previous studies showing no framing effects on exercise beliefs, intentions, or behaviors in the college population (Jones et al., 2003; Jones et al., 2004). Updegraff and Rothman (2013) suggested that message framing might influence health behaviors through both cognitive and emotional routes. Most research efforts intended to capture changes in attitudes and intentions have been focused on the cognitive route. The emotional route has not, however, received much attention. According to the socioemotional selectivity theory (Carstensen et al., 2003), the age-related positivity effect (Carstensen & Mikels, 2005; Mather & Carstensen, 2005), which may lead to a gain-framed advantage, may guide behaviors through the emotional route. Older adults are more likely to selectively attend to and process information to optimize their emotions than are their younger counterparts. Therefore, a positive bias might be found only among older adults. On the other hand, age differences in issue involvement might explain the results through the cognitive route. Rothman et al. (2006) suggested that framing effects may be obtained only when the information is being systematically processed. However, the extent to which younger adults systematically process information may depend on their levels of issue involvement in a particular domain. Younger adults are less interested, and thus less involved, in health-related information than are older adults (Deeks et al., 2009). Thus, neither cognitive nor emotional processes favored a gain-framed advantage in PA messages among younger adults. Unfortunately, the current study design was not able to directly test or tease out the unique contributions of these potential cognitive and emotional mechanisms.

Differences Between Older Men and Women Unlike other studies showing stronger framing effects on health behaviors among women than among men (Kiene et al., 2005; Rothman et al., 1993; Toll et al., 2007), the favorable effect of gain-framed over loss-framed messages was only apparent among older men in this study. Gender differences in the involvement of PA issues may be one feasible explanation. Women are more likely to perform health-promoting behaviors such as medical check-ups, seatbelt use, and fiber consumption and less likely to engage in health-risk behaviors such as smoking, drinking, and driving after drinking compared with men (Liang, Shediac-Rizkallah, Celentano, & Rohde, 1999). Interestingly, PA participation is an exception. Studies have shown that women are less likely to participate in PA than men (Liang et al., 1999; Troiano et al., 2008). Although some health behaviors such as using sunscreen and visiting the doctor may be considered to demonstrate weakness and vulnerability (Courtenay, 2000), PA participation may help display physical prowess and dominance and affirms the cultural beliefs that men are stronger and more muscular than women (Gorely, Holroyd, & Kirk, 2003). In addition, women often conform to the caregiving role and prioritize family obligations over their own needs, so spending personal time on PA may be considered selfish (Vrazel, Saunders, & Wilcox, 2008). Thus, we speculated that PA might be considered more personally important for men than for women. Together with the age effects, only older men were found to be sensitive to the positive framing effect in this study.

Subjective Evaluation of the Messages An age-related positivity effect was evident in the subjective evaluation of the messages. Gain-framed messages were more positively rated, as expected, and older adults reported more positive feelings toward the messages than did younger adults. Unlike PA behaviors, framing effects on subjective evaluation were not different across age and gender groups. Differences in measurement occasions might explain the differences in patterns of framing across the outcome measures. The favorable evaluation of the gain-framed messages might be translated to PA attitudes and intentions (van ’t Riet, Ruiter, Werrij, Candel, & de Vries, 2010) but not subsequently translatable to PA behaviors for adults of all age and gender groups. Subjective evaluation was reported immediately after the messages were read, whereas PA was measured and recalled over the two subsequent weeks. A certain level of self-efficacy may be necessary to translate cognitions into behaviors. For instance, limited time availability among younger adults might hinder the positive framing effects. Compared with most of the older adults who have retired, college students might have busier schedules. Thus, promoting PA may involve more than just promotional messages. For instance, scheduling self-efficacy was found to be predictive of PA

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(Rodgers, Hall, Blanchard, McAuley, & Munroe, 2002), which suggested that effective time management might be important. Besides, efficacy beliefs may also explain the gender differences among the older adults. Older men were found to be more efficacious in terms of PA participation compared with older women (Lee, 2005). Thus, older women might not increase their PA because they might be less confident about how action should be taken. In addition, the ceiling effect of the measure of subjective evaluation might have limited the ability of the study to find significant interactions. For instance, the mean score for older men who read gain-framed messages was 6.48 (SD = 0.79) on a 7-point scale, in which 57% gave a score of 7. In addition, cognitive measures may be less sensitive than behavioral measures in detecting framing effects in health behaviors (Gallagher & Updegraff, 2012).

Limitations There were several limitations in this study. First, because of the administrative constraints, baseline PA was measured using self-report items only. A more definitive conclusion would have been drawn if accelerometer-assessed PA had been used both before and after the manipulation. Second, the generalizability of the current findings was limited to younger adults and community-dwelling older adults who might be more socially engaged. Because they might be more likely to access information about PA benefits, the framing effects shown in this study were not strong. Although women were overrepresented, the effects that this might have on the main effects were taken into account when we tested the higher-order interactions. Third, younger and older adults did not represent two equivalent groups in terms of the demographic and health-related variables. Fortunately, these covariates did not change the patterns of results. People in these age groups were not matched on demographic and healthrelated variables, because doing so would have attenuated the external validity. Last but not least, the number of physical benefits outnumbered the social benefits in the promotion messages (see Table 1). This might render the framing effects less apparent in women, as women were more motivated by cultivating social relationships (Gabriel & Gardner, 1999).

Conclusion When designed and used effectively, messages promoting PA can trigger the thoughts of increasing and subsequent actions to increase PA of the message recipients. Messages are particularly important and powerful in a social marketing approach for health promotion. Other than media campaigns, physical education teachers, fitness instructors, physicians, parents, and other family members can also use these messages to increase PA behaviors via interpersonal communication. Because of the benefits of effective messages, an evidence-based approach in

designing these health messages is strongly recommended. Although framing effects on PA are generally small (Gallagher & Updegraff, 2012), the public health impact can be considerable given that most individuals can benefit from PA (Haskell et al., 2007) and inactivity is deemed a highly modifiable behavioral risk. This study was the first to discover an age- and gender-specific framing effect. As shown in the current study, older men may benefit particularly from gain-framed PA promotion messages. These dispositional factors should be considered in future designs of PA messages. More empirical evidence is needed, however, to assess the external validity of the findings. For instance, intervention studies, rather than laboratory-based testing, can be conducted to compare framing effects on PA across age and gender groups. From a theoretical perspective, multiple mechanisms may influence framing effects. Age-related positivity effect and individual differences in issue involvement, time availability, and self-efficacy were possible explanations of the results. Future studies should attempt to compare and contrast the explanations more directly. If evidence supports these mechanisms, message framing can be accompanied by intervention components to increase issue involvement, time management, and self-efficacy, so as to benefit sedentary individuals of all age and gender groups. In addition, the generalizability of framing effects in different populations should be further examined. Acknowledgment The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 147010).

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