Transtheoretical Model Constructs' Longitudinal ...

Transtheoretical Model Constructs’ Longitudinal Prediction of Sun Protection Over 24 Months Miryam Yusufov, Joseph S. Rossi, Colleen A. Redding, Hui-Qing Yin, Andrea L. Paiva, Wayne F. Velicer, Geoffrey W. Greene, et al. International Journal of Behavioral Medicine Official Journal of the International Society of Behavioral Medicine ISSN 1070-5503 Int.J. Behav. Med. DOI 10.1007/s12529-015-9498-7

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Author's personal copy Int.J. Behav. Med. DOI 10.1007/s12529-015-9498-7

Transtheoretical Model Constructs’ Longitudinal Prediction of Sun Protection Over 24 Months Miryam Yusufov 1 & Joseph S. Rossi 1 & Colleen A. Redding 1 & Hui-Qing Yin 1 & Andrea L. Paiva 1 & Wayne F. Velicer 1 & Geoffrey W. Greene 2 & Bryan Blissmer 3 & Mark L. Robbins 1 & James O. Prochaska 1

# International Society of Behavioral Medicine 2015

Abstract Purpose This research examined dynamic transtheoretical model (TTM) constructs for adopting sun protection practices. This secondary data analysis pooled four large populationbased TTM-tailored intervention studies and examined use of constructs across three groups, organized by longitudinal progress: maintainers, relapsers, and stable non-changers. Methods A total of 3463 adults, in the USA, who met criteria for unsafe sun exposure at baseline received a TTM-tailored computerized intervention at baseline, 6 months, and 12 months. The final analytic sample consisted of 1894 participants; the majority were female, White, married, and middle-aged. The three groups were assessed with reliable and valid scales assessing use of TTM constructs at baseline, 6 months, 12 months, and 24 months. Analyses included a MANOVA followed by a series of ANOVAs, with Tukey follow-up tests assessing differences in use of TTM constructs across the three groups at each timepoint. Results Findings demonstrated that relapsers and maintainers were similar in their use of most TTM processes of change at baseline, with the exception of Consciousness Raising, Stimulus Control, Reinforcement Management, and SelfLiberation.

* Miryam Yusufov [email protected] 1

Cancer Prevention Research Center, University of Rhode Island, 130 Flagg Road, Kingston, RI 02881, USA

2

Department of Nutrition and Food Sciences, University of Rhode Island, Kingston, RI 02881, USA

3

Department of Kinesiology, University of Rhode Island, Kingston, RI 02881, USA

Conclusions These findings suggest that although relapsers reverted to unsafe sun practices, their overall greater use of processes of change indicates that their change efforts remain better than that of stable non-changers. Keywords Stages of change . Sun exposure . Health . Transtheoretical model . Relapse . Behavior change theory . Intervention

Introduction Skin cancer is one of the most common forms of cancer and is associated with numerous consequences at both individual and population levels. Each year, over 3.5 million cases of non-melanoma skin cancer, including basal cell and squamous cell carcinoma, are diagnosed in over two million people in the USA. Moreover, the American Cancer Society [1] reported that one person dies of melanoma, the most serious and fatal form of skin cancer, every hour. In the USA, the annual cost of treating melanoma and non-melanoma skin cancers is estimated at $8.1 billion. Further, estimated annual productivity losses attributable to melanoma total $2.85 billion [2]. Despite the physical and financial consequences of skin cancer, only 58 % of adults report practicing at least one of the three sun-protective behaviors (sunscreen use, wearing sunprotective clothing, or seeking shade) [3]. Skin cancer is mainly caused by sun exposure and can be prevented by engaging in sun-protective behaviors. For example, Pfahlberg and colleagues [4] found that the risk for melanoma doubles with more than five sunburns. Further, Newton-Bishop and colleagues [5] reported that intense sun exposure is causal for melanoma in those who are at risk for sunburn. Moreover, the Centers for Disease Control (CDC) [3] reported that nearly 90 % of non-melanoma skin cancer cases could be prevented

Author's personal copy Int.J. Behav. Med.

by sun exposure reduction. Using sunscreen, wearing protective clothing, and seeking shade are the most validated methods of sun protection. For example, sunscreen use reduces the risk of squamous cell carcinoma by 40 % and melanoma by 50 % [6, 7]. Multiple studies have found that regular sunscreen application helps prevent melanoma incidence and prevalence [7–11]. In addition to its cancer prevention properties, daily sunscreen use has been shown to delay skin aging [12]. However, Linos and colleagues [13] found that the odds of multiple sunburns were significantly lower in individuals who sought shade or wore long sleeves, compared to those who used sunblock, suggesting that these methods may actually be more effective than sunscreen application. Nevertheless, the use of any sun-protective strategies, including sunscreen application, remains advantageous compared to unprotected sun exposure [6–13]. Despite the benefits of sun-protective behaviors, failure to use sun protection measures is pervasive. For example, a study of 15- to 29-year-olds in the USA found that 87.8 % of individuals spent more than 3 h outside in the summer per day, but only 17.3 % reported regular sunblock use. Furthermore, 41 % reported more than ten lifetime sunburns [14], increasing their risk of skin cancer, particularly melanoma. Strikingly, one study found that 27 % of individuals with a history of melanoma maintained inadequate sun protection, resulting in severe subsequent sunburns [15]. Such data suggests the need for strategies that target the social and psychological barriers to sun protection behavior changes [15–17]. In spite of the consequences of sun exposure and its strong association with skin cancer, research suggests that increased knowledge and awareness alone often do not translate to behavioral changes. This calls for efforts to move from education to engaging and inspiring behavior changes with specific, targeted strategies [15]. Sun exposure interventions have been shown to positively influence beliefs and attitudes toward sun protection, as well as increasing sun-protective behaviors [16–18]. Among interventions for sun-protective behaviors, those that provide tailored intervention or personalized normative feedback more effectively influence beliefs and attitudes toward sun exposure and tanning [19]. As a result, interventions should be tailored to the population targeted, involving consultation and education to facilitate change [19]. For example, a systematic review found positive effects of counseling interventions, particularly for decreasing midday sun exposure and increasing sunscreen use in young adolescents. Further, one randomized controlled study found that increased sun protection was observed in those who received an in-person physician consultation, rather than in those who received a written letter, at 3-year follow-up [20]. Previous studies have also found that interventions that include the appearancedamaging effects of UV exposure and the positive effects of sun protection play an essential role in health promotion [21].

Despite the efficacy of numerous sun exposure interventions, multiple studies have also failed to initiate or maintain sun protection behavior change. A systematic review of 23 studies revealed weak and inconclusive evidence for the efficacy of interventions in promoting sun-protective behaviors [22]. One randomized controlled trial revealed limited impact of using mobile phone interventions for increasing sun safety [23]. Such disappointing outcomes raise the question of what constructs contribute to and predict intervention response. Multiple static and dynamic variables have been shown to influence intervention response and maintenance of treatment gains. Static variables, such as demographic factors, have been found to be important factors affecting sun exposure habits and sun protection, further emphasizing the need to individualize and tailor sun protection advice [24]. For example, Chinese populations tend to engage in sun-protective measures more than their Caucasian counterparts, revealing a cultural difference in attitudes toward sun tanning. Moreover, 52 % of Chinese participants thought that sun tanning was harmful or unattractive [25]. Another study of 1676 Hispanic adults found that sun protection and exposure behaviors varied according to levels of acculturation to the USA, with those who were more acculturated engaging in more risky sun-related practices and demonstrating increased incidence of sunburns [26]. With regard to the influence of dynamic variables, a longitudinal study of 524 individuals found positive outcome expectancies, risk perception, and selfefficacy to be predictive of intent to engage in safer sun practices [27]. Cumulatively, these findings suggest that sun behavior differs as a result of varying attitudes and beliefs, which in turn, contributes to variability in intervention response. Such findings call for the need to assess readiness to change in the design and implementation of sun exposure behaviors. The transtheoretical model (TTM) has been used to successfully intervene on prevalent health risk behaviors, including smoking, high-fat diet, exercise, and sun exposure [28–35]. TTM is a model of intentional behavior change, organized around five stages of change: precontemplation (P), contemplation (C), preparation (PR), action (A), and maintenance (M). TTM research has found that forward stage progress can be predicted by three core constructs: decisional balance, self-efficacy (or confidence), and processes of change. Decisional balance reflects an individual’s rating the importance of pros and cons of change (i.e., advantages/ disadvantages of sun exposure) [36]. Self-efficacy describes the level of confidence that an individual has to change a behavior across a variety of challenging and tempting situations [37]. Processes of change encompass covert and overt techniques that individuals engage in to modify behaviors. They include five experiential processes (typically used in early stages of change) and five behavioral processes (typically used in later stages of change) that have been shown to facilitate stage progress (see Table 1) [38].

Author's personal copy Int.J. Behav. Med. Table 1 Definitions and examples of transtheoretical model (TTM) constructs

TTM constructs

Definition

Example related to sun protection

Decisional balance Pros

Pros of behavior change

The health risks from sun exposure are serious I look better when I have a tan Use sunscreen even if you do not like how it feels

Cons

Cons of behavior change

Confidence

Level of confidence that an individual has to change behavior across a variety of challenging and tempting situations

Experiential processes of change Consciousness Raising

Increasing knowledge and awareness about self and the problem behavior

Dramatic Relief

Experiencing feelings about one’s problem

Environmental Reevaluation

Evaluating how one’s problem affects their environment

Self-Reevaluation

Assessing how one feels and thinks about oneself, in the context of the problem behavior Increasing alternatives for problem behaviors

Social Liberation

Behavioral processes of change Counterconditioning

Using alternatives for problem behaviors

Helping relationships

Being open about one’s problems with others

Reinforcement management

Rewarding oneself for making changes to the problem behavior Choosing to act in a way that facilitates change

Self-liberation Stimulus control

Interventions with strong success rates of initiation and short-term behavior change have been developed [12, 21–23], but limited long-term follow-up data on adoption of safer sun practices are available [39]. This suggests the need for variables that distinguish individuals with varying intervention outcomes. The present study examines how the use of TTM constructs (Table 1) for safer sun practices differentiates over time between three groups (successful changers, relapsers, stable non-changers) organized by patterns of longitudinal progress, called dynatypes. Graphic analyses of longitudinal dynamic typologies (dynatypes) have provided a foundation for building computer-tailored interventions that have proven to be

Avoiding stimuli that elicit problem behaviors

I look for information about the risks of getting too much sun It bothers me when I see someone whose skin has been damaged by the sun Using sun screens more often might influence others to do the same I worry that too much sun will make my skin look bad I see more and more people using sunscreens to protect themselves from the sun I do something else instead of sunbathing when I need to relax I have a friend or family member who reminds me to use sunscreen I reward myself when I avoid the sun I make commitments to reduce my sun exposure I try not to spend time with people who encourage me to get a tan

remarkably effective in a series of population trials [40–44]. Previous analyses compared the use of TTM constructs of stable groups that remained in the same stage of change over 24 months, those who regressed one stage or more, those who recycled through the stages of change, and those who took action and maintained it [40]. These dynamic, longitudinal patterns of behavior change are referred to as dynatypes [40, 42–44]. The current analyses of successful changers, relapsers, and non-changers from a large sample of treated individuals were designed to provide guidance that could lead improve our current best practices for population trials. However, these are complex patterns that first need to be summarized to determine what they reveal about each of the three groups.


Sun and colleagues [41] compared three longitudinal dynatype patterns in a large sample of smokers, quitters, and relapsers. Quitters and relapsers applied change constructs significantly better than smokers, but no baseline differences between relapsers and quitters were observed. Successful quitters showed a decreasing pattern of experiential processes and an increasing pattern of behavioral processes over time. Stable smokers showed little change in process use over time. Relapsers tended to initially parallel quitters, but over time, their use of change constructs fell in between that of stable smokers and quitters. These findings suggest that although relapsers did revert back to smoking, their overall process use remained better compared to that of the stable non-changer group. Moreover, these patterns were similar in both treatment and control groups, suggesting common pathways to change. A second study using combined treatment groups for highfat diet compared successful changers, relapsers, and nonchangers on their use of TTM constructs over 24 months. Relapsers’ use of change variables initially paralleled successful changers but over time ended up between successful changers and non-changers. These results emphasize the importance of better understanding the stable non-changer group that interventions fail the most (Yusufov et al., submitted). Furthermore, the patterns identified in the smoking study were comparable to those identified in the high-fat diet study, suggesting similar patterns across distinct behaviors. This research identified dynatypes (i.e., individuals grouped by their patterns of change over time) [40–44]. These dynatypes were labeled as successful changers, stable non-changers, and relapsers. Successful changers were participants who moved to action or maintenance at any follow-up timepoint and remained in action/maintenance at 24 months. Relapsers were those who moved into action/maintenance at a follow-up timepoint but subsequently moved back into a preaction stage by final follow-up. Stable non-changers were those who remained in pre-action at all three follow-up timepoints. This study examined patterns of sun behavior change over 2 years. It was expected that the stable non-changer group would be the largest group, while relapsers would be the smallest group. Relapsers and successful changers were predicted to be similar at baseline on TTM variables and to be doing significantly better on these variables than stable nonchangers at baseline. At 24 months, successful changers were expected to perform better on all TTM variables, compared to stable non-changers, who were expected to display minimal change in their use of TTM variables.

Methods This study is a secondary data analysis drawn from three TTM-tailored randomized trials to examine use of 13 TTM

constructs for sun protection [28, 29, 33]. This study aggregated treatment group data with complete data at all timepoints from three randomized trials (studies 1–3) (N= 1894) that received the same TTM-tailored intervention feedback reports for safer sun behaviors at baseline, 6-month, and 12-month timepoints. Assessment of all TTM constructs was also at the same timepoints (baseline, 6 months, 12 months, and 24 months). All three trials intervened on multiple health behavior risks, including sun protection. Participants who were at risk for sun exposure at baseline and had complete follow-up data were included in the final sample. All study methods and procedures were approved by the Human Subjects Committee of the Institutional Review Board. Study 1 Study 1 included parents of adolescents from a school-based study in the USA who were at risk for high-fat diet, sun exposure, and/or cigarette smoking. The original sample of 2460 parents and their outcomes are described elsewhere [28]. From the original sample, 552 individuals were at risk for sun exposure at baseline and were retained through the 2 years of the study, thus meeting criteria to be included in this study. Study 2 Study 2 included primary care patients who were recruited from a large health insurance organization in the USA who were at risk for high fat diet, sun exposure, mammography screening, and/or cigarette smoking. These practices were involved in a study that examined the effects of an intervention to increase cancer prevention activities [45]. The original sample of 3701 participants and their outcomes are described elsewhere [29]. From the original sample, 1285 participants were at risk for sun exposure at baseline and were retained throughout the 2 years of the study, thus meeting criteria to be included in this study. Study 3 Study 3 included employees participating in a worksite study in the USA who were at risk for high-fat diet, sun exposure, sedentary lifestyle, and/or cigarette smoking [45]. From the original sample, 415 participants were at risk for sun exposure at baseline and were retained through the 2 years of the study, thus meeting all study inclusion criteria. Participants from the three studies were compared on demographic and key baseline characteristics prior to pooling the samples. As expected, some differences across study samples were found. For example, the mean age in the patient sample was significantly higher, compared to the other two samples. Second, the employee sample had significantly fewer female participants. Further, a smaller proportion of the patient sample rated their general health as Bvery good^ or Bexcellent^ (Cohen’s d=0.21). The parent sample had more participants in the PC stage and fewer in the C stage (Cohen’s


d=0.12), compared to the patient or employee samples at baseline. However, the proportion of participants in the preparation stage for sun protection was similar across all three study samples. Finally, participants in the employee sample reported slightly lower levels of sunprotective behaviors, compared to those in the parent and patient samples. Overall, the differences between samples were rather small (Cohen’s d R > M Confidence

Consciousness Raising

Dramatic Relief

50.33***

17.5***

4.83**

.063

Experiential Processes of Change Successful changers and relapsers used Consciousness Raising more than stable non-changers at baseline, 6 months, and 12 months. However, by 24 months, relapsers’ use declined but remained greater than the stable non-changers’ (Table 3, Fig. 3a). Table 3 and

Environmental Reevaluation

Self-Reevaluation

Social Liberation

18.09***

13.38***

18.68***

Counterconditioning 5.88**

Baseline 6 months 12 months 24 months

M,R > S M,R > S M,R > S M>R>S




M,R > S M,R > S M,R > S M,R > S


M,R > S R>M>S M,R > S M,R > S


M,R > S M,R > S M,R > S M,R > S


ns M,R > S M,R > S M>R>S


M,R > S M,R > S M,R > S M,R > S

.023

.006

Confidence Table 3 shows that successful changers and relapsers exhibited significantly higher confidence for adopting safer sun practices than stable non-changers at baseline, 6 months, and 12 months. However, by 24 months, relapsers’ confidence was less than successful changers’ but greater than stable non-changers’ (Fig. 2). With regard to differentiating the three dynatype groups, confidence demonstrated a medium effect size (η2 =.06). Successful changers and relapsers reported more confidence at baseline, 6 months, and 12 months than stable nonchangers. Interestingly, by 24 months, stable non-changers reported less confidence than relapsers, while relapsers reported less than successful changers. Further, relapsers’ confidence tended to plateau or decrease by 24 months, whereas successful changers sustained treatment gains.


.024

.018

.024

.008

Author's personal copy Int.J. Behav. Med. Table 3 (continued) Construct

F(2, 1498) Partial η

Helping Relationships

20.35***

Reinforcement Management

Self-liberation

2

10.47***

23.07***

Timepoint Pairwise comparisons

.026 Baseline 6 months 12 months 24 months

ns R>M>S M,R > S M,R > S



Baseline

M,R > S

.014

.03 6 months M,R > S 12 months M,R > S 24 months M > R > S

Stimulus Control

17.89***

.023 Baseline 6 months 12 months 24 months


ns not significant **p