Development and validation of an appearance motivation attitudes scale for sun protection

Transcription

1 Psychology and Health December, 2005, 20(6): Development and validation of an appearance motivation attitudes scale for sun protection JAY E. MADDOCK 1, COLLEEN A. REDDING 2, JOSEPH S. ROSSI 2, & MARTIN A. WEINSTOCK 3 1 Department of Public Health Sciences, University of Hawaii at Manoa, 1960 East-West Rd., Honolulu, HI 96822, USA, 2 Cancer Prevention Research Center, University of Rhode Island, 2 Chafee Rd., Kingston, RI 02881, USA, and 3 Dermatoepidemiology Unit, V A Medical Center and Department of Dermatology, Rhode Island Hospital and Brown University, 830 Chalkstone Ave., Providence, RI 02908, USA (Received 23 March 2004; in final form 2 May 2005) Abstract A reliable two-factor instrument measuring appearance motivation attitudes for sun protection was developed using a longitudinal sample of beachgoers. At baseline, data on sun protection and appearance motivation attitudes were collected on 2324 individuals. Principal components analyses (PCA) indicated a two-factor solution measuring attitudes toward tan attractiveness and skin protection with only 2 items loading on the skin protection factor. At 12-months, the instrument was revised and shortened but including 3 new skin protection items. Split-half analyses were conducted to further refine and develop the instrument. PCA on half of the sample revealed a twofactor solution, which was confirmed using structural equation modeling on the remaining half. This resulted in a two correlated-factor, 10-item measure. Each factor was summed to create two scales. Both scales were internally consistent and demonstrated good external validity, correlating with sun protection specific Transtheoretical model variables. The tan attractiveness attitudes scale significantly improved prediction of sun protection outcomes over 24 months, over and above TTM variables. Keywords: Sun protection, measurement development, skin cancer, behavior change, Transtheoretical model Introduction Skin cancer incidence now roughly equals that of all other cancers combined (approximately 1.3 million cases per year) and continues to increase (Geller et al., 2002; Miller & Weinstock, 1994; Wingo, Reis, Rosenberg, Miller, & Edwards, 1998). The primary cause Correspondence: Jay E. Maddock, Department of Public Health Sciences, University of Hawaii 1960 East-West Road, Honolulu, HI 96822, USA. Tel.: Fax: jmaddock@hawaii.edu ISSN print/issn online ß 2005 Taylor & Francis DOI: /

2 776 J. E. Maddock et al. of skin cancer is chronic unprotected exposure to the sun s ultraviolet light, as well as intense, intermittent exposures such as those at the beach (Council on Scientific Affairs, 1989; DiGiovanna, 1991; Weinstock, Clark, & Calabresi, 1993). Most skin cancers are therefore largely preventable with appropriate environmental and behavioral changes to minimize exposure. However, 47% percent of the U.S. population reports not being very likely to protect themselves when outside in the sun for more than 1 h (Hall, May, Lew, Koh, & Nadel, 1997). One plausible reason for this is the relationship between suntans and perceived attractiveness. Body image has been shown to be a strong motivating factor in many studies in relationship to weight, muscle mass and eating disorders (McCabe & Ricciardelli, 2003; Stice, Shaw, & Nemeroff, 1998). Several studies have also shown that individuals view suntans as increasing attractiveness and the appearance of health (Broadstock, Borland, & Gason, 1992; Miller, Aston, McHoskey, & Gimbel, 1990; Vail-Smith & Felts, 1993). Recently, several studies using different strategies have found appearance-focused interventions to significantly reduce intentions to tan (Hillhouse & Turrisi, 2002; Jones & Leary, 1994; Mahler, Kulik, Gibbons, Gerrard, & Harrell, 2003; Pagoto, McChargue, & Fuqua, 2003). Jones and Leary (1994) compared the effectiveness of health-based versus appearance-based messages to promote sun protection and found that messages targeted on the negative appearance effects of sun exposure had a stronger influence than healthbased messages on intentions to practice sun protective behaviors. These studies suggest at least two competing appearance related motivations for and against using sun protection measures: the immediate positive effects of a tan on attractiveness, and the long-term detrimental effects of sun exposure on the skin. Therefore, measuring competing tanning and skin protection appearance motivation attitudes may provide important understanding of sun protective behaviors and suggestions for future intervention studies. Interventions based on the Transtheoretical model of health behavior change have shown modest to medium sized effects in increasing sun protection (Pagoto et al., 2003; Prochaska et al., 2004; Prochaska et al., 2005; Weinstock, Rossi, Redding, & Maddock, 2002). This model suggests that individuals attempting to change a problem behavior progress through a series of five stages of change: precontemplation (not thinking about change), contemplation (seriously considering change), preparation (deciding and planning to change), action (initiation of overt behavior change), and maintenance (sustained behavior change over time). Progression from one stage to the next involves: (1) use of distinct subsets of processes (strategies and techniques) of change; (2) assessment of the importance of the pros and cons of change (decisional balance); and (3) ability to resist situational temptations to engage in the problem behavior and increasing situational self-efficacy to engage in more healthful behaviors (Prochaska, Redding, & Evers, 2002; Rossi, Blais, Redding, & Weinstock, 1995). Since this model was originally developed and refined for smoking cessation, other behavior-specific constructs have been found to make important additions to its predictive value when it has been adapted to other behaviors. Recent studies have demonstrated the predictive validity of attitudes towards a behavior and the TTM for nutrition and physical activity (Armitage & Arden, 2002; Armitage, Povey, & Arden, 2003; Jordan, Nigg, Norman, Rossi, & Benisovich, 2001). For sun exposure, appearance motivation attitudes could be an important behaviorally specific construct, which may add to the predictive value for this and other models of health behavior change. The goals of this study were to develop appearance motivation attitudes scales for sun protection which measured effects of sun exposure on appearance and attitudes towards skin protection; to evaluate cross-sectional and longitudinal evidence for the scales

3 Appearance motives 777 reliability and validity; and to assess whether these scales could add to the prediction of sun protection behaviors over and above Transtheoretical model variables. Method Phase 1 Participants. Study participants (N ¼ 2324) were recruited from seven of the largest coastal salt-water beaches in southern Rhode Island and ranged in age from 16 to 65 (M ¼ 33, SD ¼ 12). The sample was primarily female (60%), white (94%), single (51%) or married (40%), with at least a high school education (88%), and with a median income of $45,000 65,000 per year. Further details on the baseline characteristics of this sample have been reported elsewhere (Weinstock, Rossi, Redding, Maddock, & Cottrill, 2000). Procedure. Study participants were approached on the beach by trained interviewers and recruited to participate in a two-year study of the efficacy of stage-tailored interventions to increase protective sun behaviors. Additional details on study procedures and outcomes are reported elsewhere (Weinstock et al., 2000, 2002). After describing the study and receiving signed informed consent to participate, the interviewer administered the baseline survey. Interviews lasted min. Follow-up assessments were conducted by mail or telephone interview for all study participants at 2 and 12 months after baseline, and a final assessment was conducted at 24 months. Initial follow-up attempts were conducted by mail. After about two weeks, mail non-respondents were contacted by telephone. We have used mixed-mode data collection procedures for most of our previous population-based intervention studies without discernable respondent bias (Prochaska, Velicer, Fava, Rossi, & Tsoh, 2001; Prochaska et al., 2004). All study participants were eligible for a lottery prize of $1000 for completing each assessment. Study retention rates were 83% of baseline at 2 months (N ¼ 1930), 70% of baseline at 12 months (N ¼ 1629); and 62% of baseline at 24 months (N ¼ 1449). The average retention rate was 85% of those contacted at the previous time point. The University of Rhode Island s Institutional Review Board approved all the procedures. Measures Initial appearance inventory. Items for the Appearance Inventory were developed over the course of three years of pilot studies on Rhode Island beaches in preparation for a large skin cancer intervention study (Rossi, Blais, & Weinstock, 1994). Interviews conducted with sunbathers along with literature searches and expert review provided the basis for the development of an initial pool of items. A set of 17 items was refined based on face validity and clarity to measure appearance motivation attitudes towards sun tanning and sun protection. Participants were asked to rate their agreement with each item using a 5-point Likert scale with 1 ¼ Strongly disagree and 5 ¼ Strongly agree. Examples of specific items included, I look better with a tan and Taking good care of my skin is important to me. Sun protection behavior scale (SPBS). Sun protection was measured using the 9-item sun protection behavior scale (SPBS) (Weinstock et al., 2000). Each item was a self-report of behavior on a 5-point Likert scale of frequency (never, rarely, sometimes, often, and always) when in the sun for more than about 15 min. The SPBS included components of sun avoidance, sunscreen use, and hat use, and has been shown to be reliable and

4 778 J. E. Maddock et al. valid (Rossi et al., 1995), as well as sensitive to intervention effects (Prochaska et al., 2004, in press; Weinstock et al., 2002). Transtheoretical model constructs. Two algorithms were specifically used to measure stage of change for general sun protection and for sunscreen use. Each algorithm consisted of a short series of questions designed to assess intentions and behaviors for reducing sun exposure. The purpose of the staging algorithm is to classify respondents into one of the five stages of change: precontemplation, contemplation, preparation, action, or maintenance. The general sun protection algorithm classified subjects by stage based on a combination of their intentions and behaviors to protect themselves from the sun consistently by: (1) avoiding sun exposure (2) covering up with clothing/hats, and (3) using SPF 15 sunscreens. The sunscreen algorithm classified subjects by stage based on their behaviors and intentions to protect themselves from sun exposure by consistently using SPF 15 sunscreens. The development of the staging algorithms is described in more detail elsewhere (Rossi et al., 1995; Weinstock et al., 2000). Both algorithms have been validated against self-reported use of sun protection behaviors as well as against all major constructs of the Transtheoretical model, including decisional balance (the pros and cons of changing a behavior), self-efficacy (confidence in the ability to change), and the processes of change. The decisional balance instrument consisted of 4 items measuring the pros of sun protection ( ¼ 0.78) and the cons of sun protection ( ¼ 0.74). The instrument asked respondents to rate how important each item was in deciding whether or not to protect themselves from too much sun exposure on a 5-point Likert scale from not important (¼ 1) to extremely important (¼ 5). The self-efficacy instrument consisted of 7 items measuring confidence to use sun protection ( ¼ 0.84). The respondents were asked to rate how confident they were in protecting themselves from the sun in a variety of situations on a 5-point Likert scale from not at all confident (¼ 1) to extremely confident (¼ 5). Ten processes of change were assessed using 3 items each. Respondents were asked how often they used the processes of change on a 5-point Likert scale ranging from never (¼ 1) to always (¼ 5). Processes of change included counter conditioning, consciousness raising, dramatic relief, environmental reevaluation, helping relationships, reinforcement management, self reevaluation, social reevaluation, stimulus control, and self liberation. Coefficient alphas ranged from 0.71 to 0.81 for the 10 processes of change scales. Other measures. Demographic variables included age, sex, income, marital status, educational level, and race/ethnicity. Brief health histories focusing on skin cancer risk factors were also obtained including sun sensitivity (Weinstock, 1992), sun exposure and sunburn history, presence of large moles, use of tanning/sun lamps (Karagas et al., 2002), and personal/familial history of skin cancer. Exploratory analyses. An exploratory principal components analysis (PCA) was conducted on the correlation matrix of Appearance Inventory items generated from the sample using pairwise deletion. The number of components to retain was determined by comparing the results of three procedures that have been shown to be valid predictors of the dimensionality of an item set (Zwick & Velicer, 1986). The scree procedure, an improved procedure for parallel analysis, and the minimum average partial (MAP) method were used (Cattell, 1966; Horn, 1965; Lautenschlager, 1989; Velicer, 1976). Both orthogonal (varimax) and oblique (direct quartimin) rotations were examined.

5 Appearance motives 779 Phase II Participants. Participants who completed the baseline assessment described above in Phase I and completed a follow-up assessment 12 months later were included in Phase II. Of the original sample of 2324, 70.1% (N ¼ 1629) met these criteria. Chi-square and t-tests were used to assess differences in individuals who remained in the study at 12 months and those who were lost to follow-up. No significant differences were seen in sun sensitivity, baseline attraction subscale, family history of melanoma, lifetime severe sunburns, weekday and weekend time spent outside, or presence of large moles (p > 0.05). Those who remained in the study were more likely to be female (63.0% vs. 54.5%, p < 0.05), to have used a tanning bed (57.4% vs. 50.5%, p < 0.05), were slightly older (M ¼ 33.5 vs. 30.9, p < 0.05) and scored slightly lower on the 2 items of the sun protection factor assessed at baseline (M ¼ 8.18 vs. 8.36, p < 0.05). Measures Appearance motivation attitudes scale (AMAS). A revised set of 18 items hypothesized to measure appearance motivation attitudes for sun protection was administered. This scale contained 15 of the original items in the appearance inventory (described above) and 3 new items designed to measure attitudes towards skin protection. Two items from the original scale that loaded on factor 1 were deleted at this phase due to concerns with scale length. Participants were asked to rank their agreement with each item using a 5-point Likert scale with 1 ¼ Strongly disagree and 5 ¼ Strongly agree. Other measures. The Transtheoretical model measures and SPBS described above were assessed on all surveys. Only demographics that could vary over time (i.e. marital status) were assessed at the follow-up time points. Data analysis Scale development. The instrument was developed using the split-half cross-validation procedure in which the sample was randomly divided in half. The first half of the sample was selected for exploratory analysis using the procedures described for Phase I. Confirmatory factor analyses including cross-validation and model testing of the factor structure delineated in the exploratory phase was then conducted on the second half of the sample using structural equation modeling. Cronbach s (1951) coefficient alpha was computed to assess the internal consistency of the scales. To avoid confirmation bias, and as a further test of the adequacy of the structural factor model derived from the exploratory analyses in the first phase, several alternative measurement models representing different conceptualizations of the factor structure were evaluated to see which one best described the data. These conceptualizations include a one-factor model, a two uncorrelated factor model, and a two correlated factor model. Measurement models were assessed with maximum likelihood confirmatory factor analysis using LISREL 7 (Joreskog & Sorbom, 1989). Evaluation of model adequacy requires an assessment of the model s overall fit to the data. Four indices of fit were computed and compared to determine goodness-of-fit, as recommended by Marsh, Balla, and McDonald (1988): the maximum likelihood 2 statistic, the Root Mean Square Residual (RMSR), the Tucker Lewis non-normed fit index (TLI), and the comparative fit index (CFI) (Bentler, 1990; Joreskog & Sorbom, 1989; Tucker & Lewis, 1973). Concurrent validity. Once the confirmatory factor analyses were completed, items from each factor were summed to create scales. Concurrent validity of the scales was assessed

6 780 J. E. Maddock et al. in several ways. First, we compared the scales to the sun protection behavior scale, sun sensitivity, age and constructs from the Transtheoretical model (pros and cons of sun protection, self-efficacy, and the processes of change) using bivariate correlations. Next, we examined the scales by stage of change and gender using two-way analyses of covariance (ANCOVAs), controlling for the effects of age. For the stage of change analysis, we also tested both scales for departure from the linear trend using polynomial contrast analysis and adjusting for unequal sample sizes as recommended by Sutton (2000). Finally, we assessed behavioral ambivalence across the stages of change using the Griffen index (Thompson, Zanna, & Griffin, 1995). This index examines the intensity and similarity of positive and negative attitudes as follows: Ambivalence ¼ðProtection score þ Attractiveness scoreþ=2 ðprotection AttractionÞ: Predictive validity. We examined the predictive validity of the appearance scales on stage of change and sun protection behaviors 12 months later. First, we conducted t-tests on 12-month appearance scores comparing individuals in pre-action stages of change at baseline who had either progressed to action at 12 months or had not progressed to action at 12 months. Next, we conducted the same analysis with individuals in Action or Maintenance at 12 months who either relapsed or maintained their post-action status at 24-months. Finally, we examined Precontemplators at 12 months who either progressed to any other stage or remained in Precontemplation at 24 months. Predictive validity was also assessed using two multiple regressions to predict Sun Protection Behavior Scale (SPBS) scores. In the first regression, pros, cons, self-efficacy, behavioral and cognitive processes, and the two appearance scales were used to predict SPBS cross-sectionally at the 12-month time-point. The next multiple regression was conducted to predict the SPBS at 24 months from the baseline variables. In this regression, SPBS, pros, cons, self-efficacy, behavioral and cognitive processes, and AMAS scale were entered. Results Phase I A principal components analysis was conducted on the entire baseline sample (N ¼ 2324). All stopping criteria indicated a two-factor solution. In the varimax rotated two-factor solution, 14 items loaded >0.40 on one factor and 3 items loaded >0.40 on a second factor. The first factor measured the perceived attractiveness of having a tan and the second factor measured attitudes towards protecting one s skin. The items on the second factor had low loadings on the first factor, indicating the factors were not redundant. At this point, measurement development analyses were stopped and more items were written for the 12-month assessment to further develop the second scale. Phase II Half of the 12-month sample (n ¼ 774) was randomly selected for principal components analysis. The MAP rule and parallel analysis indicated a three-factor solution, while the scree plot indicated a two-factor solution. Both the two- and three-factor solutions were examined. The two-factor solution was easily interpretable with one factor measuring attitudes towards skin protection (Protection) and the other factor measuring

7 Appearance motives 781 the perceived attractiveness of a tan (Attractiveness). The three-factor solution included the same two factors with most of the same items and a third factor that contained 5 items that also loaded on the attractiveness factor and only two unique items. Since this factor was not robust, the two-factor solution was retained. Seventeen of the items loaded on one of the factors (>0.40) and none of the items loaded on both factors. This two-component pattern accounted for 56.6% of the variance. These 17 items were retained for further analysis. Structural equation modeling (SEM) was then conducted using the LISREL 7 structural modeling computer program to improve upon the PCA solution and further reduce scale length. Since SEM is based on a specified model, a two correlated factors model solution based on the PCA results was imposed on the remaining matrix of item correlations. This initial model provided poor fit to the data across all measures of model adequacy, 2 (119) ¼ 2628, RMSR ¼ 0.139, TLI ¼ 0.68, CFI ¼ All items loaded (> 0.40) on their target factors. Decisions to delete items were made by examining modification indices and normalized residuals, which revealed complex items and poorly functioning items. After items were deleted on empirical bases, evaluating breadth of construct for the two factor subscales eliminated additional items. These procedures resulted in a 10-item model, with 5 items on each factor, 2 (34) ¼ 179, RMSR ¼ 0.053, TLI ¼ 0.93, CFI ¼ Cronbach s (1951) coefficient alpha was 0.83 for the Protection factor and 0.86 for the Attraction factor. Final scale items are displayed in Appendix A. Confirmatory analyses The second half of the sample (n ¼ 794) was then used for confirmatory analysis. Cronbach s coefficient alpha for the Protection factor was 0.83 and for the Attractiveness factor was SEM was used to confirm the two-factor structure of the measure. The correlated two-factor model provided an excellent fit to the data across all measures of model adequacy, 2 (34) ¼ 168, RMSR ¼ 0.053, CFI ¼ 0.96, TLI ¼ This model fits significantly better than either an uncorrelated two-factor model, 2 (35) ¼ 196, RMSR ¼ 0.099, CFI ¼ 0.95, TLI ¼ 0.93, or a one-factor model, 2 (35) ¼ 1596, RMSR ¼ 0.203, CFI ¼ 0.55, TLI ¼ The correlated model was retained as the best representation of the data and is displayed in Figure 1. External validity Due to the low correlation between the factors (r ¼ 0.21) we treated them as independent scales for the external validation analyses. The tan attractiveness and skin protection scales were created by summing the items and were examined for external validity by examining their relationships with several other variables. These variables included age and gender, the sun protection behavior scale, sun sensitivity, the pros and cons of sun protection, processes of change, self-efficacy to protect oneself from the sun and stages of change for sun protection. Using the entire 12-month time point sample (N ¼ 1568), Pearson r correlations were calculated for age, pros, cons, self-efficacy, and processes and SPBS score and analysis of variance techniques were used to examine differences based on both gender and stage of change. Nearly all correlations were significant ( p < 0.001) and revealed small to moderate sized relationships among the variables (see Table I). A two-way multivariate analysis of covariance was conducted to assess differences in the scales by gender and stage of change, controlling for age. Significant main effects using Wilks criterion were found for both sex, F(2, 1573) ¼ 17.3, p < 0.001, multivariate

8 782 J. E. Maddock et al. Many people look much healthier with a tan. I like to take good care of my skin. Many people look younger with a tan Taking care of my health is very important. Most people look more sexy with a tan Tan attractiveness Skin protection My skin is worth protecting I look better with a tan Taking good care of my skin is important to me. Men look more masculine with a tan. Staying healthy is more important to me than being attractive. Figure 1. Correlated model of appearance motivation attitudes scale. Table I. Correlations between the appearance motivation attitudes subscales and external validity variables. a External validity variables Tan attractiveness subscale Skin protection subscale Age 0.076* 0.130* Sun protection behavior scale 0.366* 0.406* Avoid subscale 0.334* 0.272* Sunscreen subscale 0.280* 0.399* Hat subscale 0.099* 0.092* Sun sensitivity 0.081* 0.101* Pros 0.252* 0.511* Cons 0.589* 0.162* Self-efficacy 0.351* 0.413* Counterconditioning 0.311* 0.341* Consciousness raising 0.241* 0.506* Dramatic relief 0.190* 0.476* Environmental reevaluation 0.252* 0.461* Helping relationships * Reinforcement management 0.166* 0.217* Stimulus control 0.300* 0.384* Self liberation 0.282* 0.504* Social liberation 0.142* 0.440* Self reevaluation 0.259* 0.546* Note: *p < 0.001, N ranges from 1576 to a Data is from the 12-month timepoint. 2 ¼ 0.022, and stage, F(8, 3148) ¼ 37.0, p < 0.001, multivariate 2 ¼ Age was a significant covariate ( p < 0.001), but the interaction between stage and sex was not significant ( p > 0.05). Separate ANCOVAs were then conducted on the two appearance scales using stage of change and sex as independent variables. The stage and sex main effects were significant for both scales ( p < 0.001). The means and standard deviations

9 Appearance motives 783 Table II. Appearance motivation attitudes scales by stage of change and gender. Appearance scales Tan attractiveness Skin protection Ambivalence F(4, 1608) ¼ 37.4, F(4, 1599) ¼ 65.8, F(4,1584) ¼ 54.3, p < 0.001, 2 ¼ 0.09 p < 0.001, 2 ¼ 0.14 p < 0.001, 2 ¼ 0.12 Stage of change a N Mean SD Mean SD Mean SD Precontemplation Contemplation Preparation Action Maintenance F(1, 1608) ¼ 17.6, F(1, 1599) ¼ 56.7, p < 0.001, 2 ¼ 0.01 p < 0.001, 2 ¼ 0.03 Gender N Mean SD Mean SD Females Males a Data is from the 12-month timepoint. of the scales by sex and stage of change, along with the ANCOVA F, p-values, and effect sizes are displayed in Table II. Finally, we tested both scales for departure from the linear trend. The linear trend was significant for both scales and the measure of ambivalence. Neither the quadratic or cubic term was significant for the tan attractiveness or attitude ambivalence scale. For the sun protection subscale, the quadratic term approach significance, p ¼ Predictive validity Predictive validity was assessed by dividing participants into several groups. T-tests revealed that scores on the Attractiveness and Protection scales at 12 months were significantly different among individuals who were pre-action at 12 months and stayed in pre-action at 24 months versus those that progressed to action. Significant differences were only seen on the Protection scale for those post-action at 12 months who either relapsed or stayed in action and maintenance at 24 months. Finally, Precontemplators at 12 months who advanced in stage by 24 months also showed higher scores on both scales than those who did not advance. These results are displayed in Table III. Predictive validity was also assessed using two multiple regressions to predict Sun Protection Behavior Scale (SPBS) scores. In the first regression, pros, cons, self-efficacy, behavioral and cognitive processes, and the two appearance scales were used to predict SPBS cross-sectionally at the 12-month time-point. The overall regression was significant, F(7, 1570) ¼ 408.6, p < 0.001, R 2 ¼ 0.65, and the tan attractiveness subscale was a significant predictor ( ¼ 0.05, p < 0.05), while the sun protection subscale was not ( ¼ 0.01, p ¼ 0.61). The next multiple regression was conducted to predict the SPBS at 24 months from the baseline variables. In this regression, SPBS, pros, cons, self-efficacy, behavioral and cognitive processes, and the tan attractiveness scale were entered. The overall regression was significant, F(7, 1401) ¼ 243.7, p < 0.001, R 2 ¼ 0.55, and the tan attractiveness subscale was a significant predictor ( ¼ 0.05, p < 0.05). Results of the regressions are presented in Table IV.

10 784 J. E. Maddock et al. Table III. Predictive validity of the appearance motivation attitudes scales with stage of change. N Mean (SD) at 12 months t value Tan attractiveness subscale Pre-action (12 months) Pre-action (24 months) (4.2) t(764) ¼ 4.2, p < Post-action (24 months) (4.5) d ¼ 0.33 Post-action (12 months) Pre-action (24 months) (4.7) t(614) ¼ 0.8, ns Post-action (24 months) (5.0) d ¼ 0.09 Precontemplation (12 months) Precontemplation (24 months) (4.1) t(550) ¼ 3.2, p < Advanced in stage (24 months) (4.4) d ¼ 0.32 Skin protection subscale Pre-action (12 months) Pre-action (24 months) (3.1) t(761) ¼ 4.6, p < Post-action (24 months) (2.7) d ¼ 0.35 Post-action (12 months) Pre-action (24 months) (2.9) t(611) ¼ 3.7, p < Post-action (24 months) (2.1) d ¼ 0.28 Precontemplation (12 months) Precontemplation (24 months) (3.2) t(547) ¼ 4.2, p < Advanced in stage (24 months) (2.9) d ¼ 0.38 d ¼ Cohen s d measure of effect size. Table IV. Multiple regressions predicting sun protection behavior scale (SPBS) using Transtheoretical model variables and appearance scales. Variable Standardized Regression 1: Cross-sectional analysis predicting SPBS at 12-month time-point a Pros of sun protection 0.105** Cons of sun protection 0.093** Self efficacy 0.450** Behavioral processes 0.241** Cognitive processes Tan attractiveness subscale 0.045* Skin protection subscale Regression 2: Longitudinal analysis predicting SPBS at 24-month time-point from baseline variables b SPBS (baseline) 0.481** Pros of sun protection 0.081** Cons of sun protection Self-efficacy 0.163* Behavioral processes Cognitive processes Tan attractiveness subscale 0.052* a F(7, 1570) ¼ 408.6, p < 0.001, R 2 ¼ b F(7, 1401) ¼ 243.7, p < 0.001, R 2 ¼ * ¼ p < 0.05, ** ¼ p < 0.01 Discussion This study has resulted in the development of a short, psychometrically sound instrument to measure appearance motivation attitudes for sun protection, consisting of two scales measuring attitudes towards tan attractiveness and skin protection. These new scales are

11 Appearance motives 785 reliable, have good internal consistencies, and a stable factor structure that is evident in both the exploratory and confirmatory analyses. The external validity of both scales was good, with strong concurrent validity with the TTM including stages of change, pros and cons of sun protection, self-efficacy for sun protection, processes of change for sun protection, and the sun protection behavior scale. The skin protection subscale showed the strongest relationships (r > 0.50) to the pros of sun protection, consciousness raising (seeking information on skin protection), self liberation (making a commitment to skin protection), and self reevaluation (viewing oneself as the kind of person who protects their skin from the sun). The tan attractiveness subscale was most highly related to the cons of sun protection (r ¼ 0.59). Because of their low correlation, combining the two scales is not recommended. The series of ANCOVA s revealed that stages of change accounted for substantially more variance in these scales than did sex. Tests for discontinuity patterns were not significant and indicated that the linear trend best fit the data. In general, attitudes towards tan attractiveness decreased across the stages while attitudes towards skin protection increased. This indicates that changes in appearance attitudes are salient across all the stages of change. However, for the skin protection subscale the largest mean change occurred between precontemplation and all the other stages. This finding is similar to other studies that have found a linear relationship between stages of change and attitudes (i.e. Jordan et al., 2001). The linear decrease in attitude ambivalence differs from the discontinuity pattern seen between attitude ambivalence and stage of change for fruit and vegetable and fat consumption where ambivalence is the lowest in precontemplation and maintenance (Armitage et al., 2003). The predictive validity of the scales was supported by the fact that it added to the prospective prediction of sun protective behaviors 24 months later, over and above TTM variables and baseline sun protection behavior. The predictive validity of the scale also received good support from its prospective prediction of not only those who progressed to action, but also those who were at-risk of relapsing over the subsequent year. Predictive validity analyses supported the tan attractiveness subscale more consistently and strongly than the skin protection subscale. This indicates that attitudes towards the attractiveness of tanning may be an important area to target interventions towards. This is an area that could be addressed through a campaign targeting social norms of attractiveness. Appearance-based intervention studies have focused largely on women and some have assumed women would be more concerned with appearances than men (Abroms, Jorgensen, Southwell, Geller, & Emmons, 2003; Berwick, Fine, & Bolognia, 1992; Hall et al., 1997; Weinstock et al., 2000). In contrast, our data show that men showed stronger levels of agreement with the tan attractiveness subscale than women, although this sex difference accounted for only 1% of the variance in tan attractiveness attitudes. Consistent with expectations, men also scored lower on the skin protection subscale than women, accounting for 3% of the variance in skin protection attitudes. Taken together, sex differences on these two scales demonstrate greater barriers to sun protection among men (Abroms et al., 2003; Hillhouse & Turrisi, 2002; Jones & Leary, 1994; Mahler et al., 2003). This finding is consistent with the repeatedly observed sex differences in sun protection and skin cancer rates (Abroms et al., 2003; Berwick et al., 1992; Hall et al., 1997; Weinstock et al., 2000). It will be interesting to observe whether and how these findings change over time as the fashion and skin care industry increasingly targets men. This was a beach-going community-based sample that included representative portions from each age group (Weinstock et al., 2000). Since the scale was administered

12 786 J. E. Maddock et al. in its entirety at the 12-month follow-up, attrition likely reduced the representativeness of the sample, although overall attrition was low for a study of this size and scope. Nevertheless, administering and evaluating this scale in other samples and settings will broaden our understanding of its generalizability. The use of retrospective self-report in the follow-up surveys also introduces some additional bias. While observational measures can reduce respondent bias, studies that assess usual sun protection habits are typically limited to self-report especially in large public health studies. To date, appearance-based interventions have been conducted on small samples of mostly college age students (Hillhouse & Turrisi, 2002; Jones & Leary, 1994; Mahler et al., 2003). This scale, which measured attitudes towards tanning and skin protection in a large community-based sample, could be important for reducing the population burden of skin cancer. Tailored sun protection interventions could use this appearance scale to provide feedback to facilitate change or help prevent relapse (Redding et al., 1999; Skinner, Campbell, Rimer, Curry, & Prochaska, 1999). Since the tan attractiveness scale shows stronger predictive validity, interventions targeted to changing this perception could be the key in influencing population sun protection and exposure rates. Reliable and valid measures of appearance motivation attitudes, such as these, can be very useful in enhancing the specificity of tailored interventions as well as social marketing and individual interventions and have the potential to impact on the growing problem of skin cancer in the United States. Further work needs to be done to test these scales and various potential intervention messages based on them in intervention settings. Acknowledgements This research was supported by Grant #AR Portions of this article were presented at the annual meeting of the Society of Behavioral Medicine in San Diego, CA, March, Authors also wish to gratefully acknowledge the administrative and data collection assistance of Margaret Boyle, Sally Cottrill, and the contribution of all project participants. References Abroms, L., Jorgensen, C. M., Southwell, B. G., Geller, A. C., & Emmons, K. M. (2003). Gender differences in young adults beliefs about sunscreen use. Health Education & Behavior, 30, Armitage, C. J., & Arden, M. A. (2002). Exploring discontinuity patterns in the Transtheoretical model: An application of the theory of planned behavior. British Journal of Health Psychology, 7, Armitage, C. J., Povey, R., & Arden, M. A. (2003). Evidence for discontinuity patterns across the stages of change: A role for attitudinal ambivalence. Psychology and Health, 18, Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, Berwick, M., Fine, J. A., & Bolognia, J. L. (1992). Sun exposure and sunscreen use following a community skin cancer screening. Preventive Medicine, 21, Broadstock, M., Borland, R., & Gason, R. (1992). Effects of suntan on judgments of healthiness and attractiveness by adolescents. Journal of Applied Social Psychology, 22, Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, Council on Scientific Affairs (1989). Harmful effects of ultraviolet radiation. JAMA, 262, Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, DiGiovanna, J. J. (1991). Prevention of skin cancer due to sun exposure. In V. J. Devita, S. Hellman & S. Rosenberg (Eds), Cancer prevention (pp. 1 9). Philadelphia, PA: Lippincott. Geller, A. C., Miller, D. R., Annas, G. D., Demierre, M. F., Gilchrest, B. A., & Koh, H. K. (2002). Melanoma incidence and mortality among US Whites: JAMA, 288, Hall, H. I., May, D. S., Lew, R. A., Koh, H. K., & Nadel, M. (1997). Sun protection behaviors of the US white population. Preventive Medicine, 26,

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14 788 J. E. Maddock et al. Weinstock, M. A., Clark, J. W., & Calabresi, P. (1993). Melanoma. In P. Calabresi & P. S. Schein (Eds.), Medical oncology: Basic principles and clinical management of cancer (2nd Edn, pp ). New York: McGraw-Hill, Inc. Weinstock, M. A., Rossi, J. S., Redding, C. A., & Maddock, J. E. (2002). Randomized controlled community trial of the efficacy of a multicomponent stage-matched intervention to increase sun protection among beachgoers. Preventive Medicine, 35, Weinstock, M. A., Rossi, J. S., Redding, C. A., Maddock, J. E., & Cottrill, S. D. (2000). Sun protection behaviors and stages of change for the primary prevention of skin cancers among beachgoers in southeastern New England. Annals of Behavioral Medicine, 22, Wingo, P. A., Ries, L. A. G., Rosenberg, H. M., Miller, D. S., & Edwards, B. K. (1998). Cancer incidence and mortality, : A report card for the U.S. Cancer, 82, Zwick, W. R., & Velicer, W. F. (1986). A comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, Appendix A: Final appearance motivation attitudes for sun protection scale This questionnaire measures how much you agree or disagree with the following statements. Please circle the number from 1 to 5 that best reflects your feelings. Strongly Agree Somewhat Agree 5 Neither Agree Nor Disagree 4 Somewhat Disagree 3 Strongly Disagree Most people look healthier with a tan I like to take good care of my skin Many people look younger with a tan Taking care of my health is very important Most people look more sexy with a tan My skin is worth protecting I look better with a tan Taking care of my skin is important to me Men look more masculine with a tan Staying healthy is more important than being attractive To create the subscale scores, take the sum of the items on each subscale listed below. Tan Attractiveness (Items #1,3,5,7, & 9) Skin Protection (Items #2,4,6,8, & 10)

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