Overweight and obese sedentary adults' physical activity beliefs and preferences.
Abstract: Despite the public health focus on physical activity, only 27.4% of U.S. adults meet the daily recommendations. This study explored sedentary overweight and obese adults' communication practices and preferences related to physical activity. Focus groups touched on behavior, constructs from Health Belief Model, Theory of Planned Behavior, and Social Cognitive Theory, information seeking and communication practices. Data were analyzed using framework analysis. Participants did not know the daily recommendations, lacked motivation, had low perceived behavioral control, and preferred tailored interpersonal communication. This study highlights physical activity preferences among an important population and offers suggestions for future research and practice.
Subject: Obesity (Research)
Cancer (Research)
Physical fitness
Oncology, Experimental
Behavior modification
Public health
Body weight
Authors: Suggs, L. Suzanne
McIntyre, Chris
Cowdery, Joan E.
Pub Date: 03/22/2010
Publication: Name: American Journal of Health Studies Publisher: American Journal of Health Studies Audience: Professional Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2010 American Journal of Health Studies ISSN: 1090-0500
Issue: Date: Spring, 2010 Source Volume: 25 Source Issue: 2
Topic: Event Code: 310 Science & research Canadian Subject Form: Behaviour modification
Product: Product Code: 8000220 Cancer & Cell R&D; 8000120 Public Health Care; 9005200 Health Programs-Total Govt; 9105200 Health Programs NAICS Code: 54171 Research and Development in the Physical, Engineering, and Life Sciences; 62 Health Care and Social Assistance; 923 Administration of Human Resource Programs; 92312 Administration of Public Health Programs SIC Code: 8731 Commercial physical research; 8733 Noncommercial research organizations
Accession Number: 308741497
Full Text: INTRODUCTION

Sedentary behavior and being overweight or obese is associated with increased risk of heart disease, diabetes, osteoporosis and certain cancers (World Cancer Research Fund, 2007). It is estimated that obesity and lack of physical activity account for almost 400,000 deaths in the United States each year (Rashad & Grossman, 2004). It is also estimated that global cancer rates could be reduced by at least one-third if individuals achieve a healthy weight, get regular physical activity and adopt a healthy diet (World Cancer Research Fund, 2009). Even small increases in physical activity levels among sedentary adults have generated health benefits, including reductions in systolic blood pressure, waist and hip size, and overall improved functional capacity (Ekkekakis, Hall, VanLanduyt & Petruzzello, 2000; Tully et al., 2007)

In 2006, the World Health Organization (WHO) identified obesity as a priority for public health efforts coupled with more attention to promoting physical activity (WHO, 2006). Despite the vast amount of health communication and promotion efforts related to physical activity in recent years, there are unmistakable signs that people have not been persuaded, or are unable, to alter their sedentary lifestyles as only 27.4% of U.S. adults get regular physical activity (CDC, 2007).

This quandary stems from a variety of environmental, personal and cognitive factors as well as individual health information management skills. Limitations in the communication research on physical activity and sedentary overweight adults, including ambiguity about the role of theory, model specification, and the operationalization of key variables, may also play a role in this problem. The large volume of health communication consisting of non-tailored, non theory-based and sometimes contradictory information certainly does not help alleviate the problem (Hesketh, Hesketh, Waters, Green, Salmon & Williams, 2005; Painter, Borba, Hynes, Mays & Glanz, 2008). Indeed, "merely disseminating information without reliance on cognitive, behavioral and attitudinal principles may lead to ineffective health messages, misdirected public health actions, and misleading outcomes" (Tinker, 1996, p. 198). Communication that does not account for environmental and cultural factors may also have a negative impact on a person's ability to succeed in behavior change efforts (Sallis, Johnson, Calfas, Caparosa & Nichols, 1997; Yancey et al., 2004).

Much quantitative research has been conducted about the determinants of obesity and physical inactivity. Findings suggest that socioeconomic status, cultural norms, TV time, physical environment, health status, and co-morbidities are correlated with sedentary and weight-related behaviors (Bauman, Sallis, Dzewaltowski & Owen, 2002; Humpel, Owen & Leslie, 2002; Kremers et al., 2006; Rennie, Johnson & Jebb, 2005; Sallies et al., 1997; Yancey et al., 2004). These studies provide useful data for policy planners, health promotion professionals, and communication scholars, yet they do not provide rich information from this population, where they are invited to describe preferences, challenges and opportunities in their own words. The current evidence shows limited effectiveness of health behavior change campaigns, suggesting that perhaps programs are not meeting the needs of this population (Abraham & Graham-Rowe, 2009; Anderson et al., 2009; Eakin, Lawler, Vandelanotte & Owen, 2007; Snyder et al. 2004). Therefore, this study adopts qualitative methodology that aims to understand: 1) factors that serve as barriers or facilitators to physical activity behavior and communication practices; and 2) preferences for physical activity communication of overweight and obese sedentary adults. The results can help health communication practitioners and researchers understand how to better reach this population with appropriate and effective physical activity communication, increasing potential exposure and receptivity to physical activity promoting communication (Rimer & Kreuter, 2006).

METHODS

This study followed a qualitative methodology to examine 1) barriers and/or facilitators to physical activity behavior and 2) communication practices and preferences for physical activity communication. The research was approved by the Ethics Committee at the host institution and was conducted in a large urban area in the northeastern region of the United States.

The study relied on a convenience sample of self-identified overweight and obese sedentary adults between 25 and 35 years of age. Three focus group sessions, lasting two hours each, were conducted between March 29 and April 1, 2007 in a centrally located facility. Participants were recruited through posted flyers in the downtown area and advertisements in several popular publications including Craigslist.com and the Metro newspaper. Prior to enrollment, interested individuals called the research team and responded to questions assessing eligibility (self described as overweight or obese, sedentary, and between 25-25 years of age). Eligible individuals were enrolled in a session and provided with directions to the facility. Information about how they learned about the project was also collected. E-mail and phone reminders, including the study purpose, incentive, start time, location and directions to the facility, were sent to each person three days before each session. Participants were asked to contact the research team if their plans for attending changed. Before the start of each session, participants were provided a written overview of the study and written consent was obtained. Sessions were recorded and transcripts were produced by a professional service.

Each session began with a self-administered survey gathering age, gender, height, weight, education level, average weekly physical activity level, perceived health status and susceptibility to disease. Group discussions focused on physical activity behaviors, knowledge, attitudes, barriers, intention, motivation, self-efficacy, and perceived behavioral control. In terms of health information and communication practices, we discussed current behaviors and strategies, attitudes and preferences about the type of communication and delivery channels (see Table 1 for the questions asked in each session).

ANALYSIS

Focus groups generate an extensive amount of textual data that must be systematically analyzed in order to minimize the effects of subjective bias in the process of analyzing and interpreting the data (Rabiee, 2004). Data for this study were analyzed using framework analysis. Framework analysis enables qualitative data to be analyzed through the use of a thematic classification scheme that reflects the underlying study objectives and can also incorporate additional or emergent themes from the discussions (Ritchie & Lewis, 2003). In other words, framework analysis enables qualitative data to be analyzed mainly through a deductive process using a thematic classification scheme (thematic framework) that reflects the underlying study objectives. It also allows for inductive process by incorporating additional or emergent themes from the discussions (Pope, Ziebland & Mays, 2000; Ritchie & Lewis, 2003; Waller, Waller, Marlow & Wardle, 2006). Following data management and analysis procedures described in the above papers, two investigators independently reviewed transcripts and identified themes. Using the purpose of the study as the initial themes, the transcripts were indexed and emergent themes identified. The themes were agreed upon after deliberation by both researchers. Next, the thematic framework was used to index the data. The investigators compared indexing and theme identification and differences were resolved through consensus.

RESULTS

Thirty-three people agreed to participate, but ultimately 13 individuals attended the sessions. Most learned of the study from the Metro newspaper (n = 20) followed by Craigslist.com (n = 11), What's Up Magazine (n = 1) and word of mouth (n = 1), which was similar for those who participated in the focus group sessions (Metro: n = 10, Craigslist: n = 3). The first session included four women, the second five women, and the third included four men, with an average age of 31 (sd = 3.62). The mean BMI was 38.8 (sd = 7.556), which was calculated from self reported height and weight in the pre-session survey. Sample characteristics and perceived susceptibility to disease are described in Table 2. Phone calls were made to those who did not attend their session (16 women and 3 men) and, despite having been sent reminder messages, the most common reason for the not attending a session was "I forgot"

Analysis of the transcripts from all of the sessions identified recurring themes clustered around physical activity behaviors and barriers, and communication practices and preferences. Within the theme "physical activity behaviors and barriers", two main clusters emerged: 1) perceptions and expectations and 2) contextual barriers. Within the theme "communication practices and preferences", two clusters emerged: 1) communication channel and 2) communication type. Excerpts from the sessions that best reflect the recurring themes and clusters are shown below.

PHYSICAL ACTIVITY BEHAVIORS AND BARRIERS

The physical activity recommendations for adults were defined as 30 minutes or more of moderate-intensity physical activity on most, preferably all, days of the week, which were the most current guidelines provided by the CDC and the American College of Sports Medicine at the time of this study (Pate et al., 1995). Participants were unfamiliar with the recommendations and underestimated them when asked to guess. No participant met the minimum guidelines for physical activity, but all got some activity as part of their activities of daily living, such as walking to public transportation, doing laundry, or looking after children.

"I probably get a little bit more because I do my laundry and go up and down the stairs. And I take my niece every other weekend and I am always running around with her"

"Oh, going to the mall, I like to walk around and shop, yeah"

"Well, I get out and I walk to the post office and then walk to the store"

Perceptions and expectations

The majority of participants recognized that they should be more physically active and believed that physical activity is associated with good health. They indicated that the strongest motivators for physical activity were to feel good, lose weight, and be able to do activities with family or friends. They wanted the effects of physical activity, longed to be happy with their size, and wanted more self-esteem (as a result of being smaller and setting a goal and sticking to it), but almost all participants (n = 12, 92%) stated that they lacked the motivation to initiate or sustain regular physical activity. There was a clear attitude that physical activity was hard, difficult work and they were unsure whether they were capable of incorporating that type of activity into their lives. Most expected noticeable differences in physical appearance soon after starting becoming active.

"I would expect to lose weight in the first week, and to feel better about myself "

"[it would be good because] I could feel comfortable with what I look like and how I feel when I go outside--and stuff like that"

"It is hard work. It takes time away from other things that you may enjoy more. Like eating and watching TV"

"That is my biggest problem, like I have time to do it, if I really want to, but I'm just too lazy"

"I guess motivation really is my problem and self esteem because that plays a major part in being physically active"

"It is very difficult, the things that I would have to do to prepare to go take a warm shower, loosen up my joints, rub with the Ben-Gay and you know... Ah, why the ordeal?"

"being as heavy as I am, I cant just say, Hey let's go out for a jog because I'd make it probably like 10 feet and then stop breathing"

Contextual barriers

Most of the participants did not have strong self-efficacy in being able to perform physical activities. Many said they lacked the information and ability to properly use exercise equipment or design a workout plan. They wanted other people to motivate them to be more active and to be more active with. They also reinforced the barrier of low self-esteem by revealing how uncomfortable they would feel to exercise next to a smaller, fitter person. Only one participant said that being active next to more fit people was not a barrier for them. Limited economic resources was mentioned consistently as a barrier to the ability to engage in physical activity, especially in terms of membership in fitness clubs or obtaining specific equipment such as bicycles or treadmills. Many participants, especially those with childcare or caregiver responsibilities, mentioned lack of time to incorporate additional activities. Environmental factors, like neighborhood safety, were mentioned as limitations on outdoor nighttime activities. The weather was described as a factor that influenced physical activity. In particular, winter was seen as a time when nothing could be done outside, while the summer was too hot and humid for physical activity.

"It is not that easy, I don't have the buddy system"

"I have a gym membership at Bally's and I actually go out there a couple of times over the winter but I kept looking for gym partners because I won't go by myself. I need somebody there for motivation, just a work out buddy"

"[it's]an embarrassment factor for me, me being a large person trying to work out in a gym"

"If I walk into a gym, I would walk right back out because I don't feel comfortable enough. You cant go work out in jeans or something... I don't wear shorts or anything"

"If I had like $300-400 lying around I would buy a bike, you know what I mean. I cant get that much money together all at once to invest in that. So, it is kind of economics for me"

"For me it's the time of the day because I live in xxxx and the crime... So like in my building, ...I see the young guys hooded up and my first thought is to grab my purse, should I take my rings off? The thing that troubles me is that in the summertime when I would like to go out in the evening, when it is nice and cool, is when they are out and hanging around"

"Because winter you cant really get around and then summer if it is like 98[degrees] and 100% humidity, the last thing that I want to do is go out and start running around and that's my activity wiping sweat"

"Winter time I am like a big bear, I don't like the cold, I don't go out. I don't do weather like that, man"

COMMUNICATION PRACTICES AND PREFERENCES

Connected to the issue of motivation was the near universal need for the involvement of other people in a social network of partnerships. They wanted motivation, friendly competitions, and social norms that promoted physical activity. They wanted health information and knowledge sharing, and assistance in practical needs, such as childcare. They wanted communication to take account of their preferences and personal situation. Overall, participants believed that there were insufficient communication resources devoted to physical activity available to them. Indeed, some suggested that there should be a high level political position in the U.S. government who would have responsibility to promote increased physical activity "much like the surgeon general does for smoking."

Channel

Nearly all of the participants valued interpersonal sources as the most trusted, useful, and motivational communication channel. They trusted their physicians most for information followed by their peers. Mass media sources, such as print, television, and the Web were valued. Some television programs, such as the Biggest Loser, were viewed as useful and motivational. Web-based sources, including Google, WebMD, Wikipedia, and Realage, were specifically mentioned as good sources of health information. They said the delivery channel should allow for the distribution of legitimate, credible sources that were relevant to their specific personal circumstances. They suggested using channels like audiotapes, iPods, and radio where they could select the types of music most motivational for them.

"I trust my doctor, I think she wouldn't steer me in the wrong direction"

"A lifestyle coach like [on the]"Biggest loser" to get me up and motivated"

"I would probably put a good upbeat tape of music together because I think that music can be a good motivator"

Communication Type

The participants were not active health information seekers and wanted communication that created an element of personal interaction. They valued personal stories about real people and thought it was counter productive to use extremely fit role models to promote physical activity. Participants felt that personal stories about weight loss from celebrities like Richard Simmons and Ricki Lake were "real" and trustworthy, unlike Oprah Winfrey who has the means to hire staff" to help her achieve weight loss goals. They mentioned the importance of having an information source that took account of their situation, such as a personal coach or exercise partner.

"Other people. Just people that they say they have lost 50 pounds. Stuff like that, real life people, not people on the TV or magazines who all the sudden lost 200 pounds and they are in a bathing suit"

"I like the personal stories"

"[If I was to motivate someone like me,] I would talk to them about what was going on with myself and say we can do it together, like a buddy system."

"A group of people [like me]. I know what I'm going through and being a mom, a single parent. I would probably put announcements out there for people that are in the same situation."

DISCUSSION

When discussing physical activity, participants focused on "exercise" and formal activities. Their attitudes were often negative and framed as being hard work and embarrassing. They lacked motivation to increase physical activity, yet wanted the benefits associated with it. In the context of recommended physical activity levels there was an overall low level of perceived behavioral control about their ability to meet the guidelines.

Participants demonstrated a preference for information that is personally relevant and in accordance with their preferred communication practices. This finding is consistent with recent literature examining the type of communication that is most effective in changing health behaviors (Noar, Benac & Harris, 2007; Rimer & Kreuter, 2006; Suggs, 2006). Tailored communication is individualized and thereby increases the relevance of the message. It has been associated with greater amounts of behavior change and health improvement compared to standardized and targeted communication (Kreuter & Skinner, 2000; Noar, Benac & Harris, 2007).

In terms of channels, participants preferred interpersonal communication sources. They wanted contact with other people, either as work out buddies or coaches who would motivate them, counsel them and recognize their unique circumstances. In particular, participants trusted their doctors. This result is consistent with research that has found interpersonal communication to be effective (Hasler, Fisher, MacIntyre & Mutrie, 2000; Tate et al., 2007). The preference for interpersonal doctor-patient communication channels also highlights the important role that healthcare providers have in physical activity promotion for overweight and obese sedentary adults. Despite doctors often being listed as the most trusted source for health information by health consumers, nearly half of physicians do not encourage overweight or obese patients to increase their physical activity (Hesse et al., 2005; Walker et al., 2007).

Participants revealed that some passive mass communication channels, such as music and TV programs, could be useful and motivating. However, while the mass media has a large reach and people tend to recall seeing physical activity messages, it is typically associated with little to no long-term behavior change (Marcus et al., 1998; Marshall, Owen & Bauman, 2004). Nonetheless, participants noted the appeal of TV programs, such as the Biggest Loser, that presented weight loss efforts of actual overweight and obese guests. While evidence is limited regarding the use of TV shows in changing physical activity behavior, health-related TV programs that focus on exercise and physical activity have been broadcast as early as 1951 when Jack Lalanne established a model for exercise-fitness TV programs. Thus a reality or edutainment approach could be worth investigating. Participants also spoke about the motivational nature of music. Importantly, some studies suggest that music can have beneficial effects on physical activity, including lower rates of perceived exertion during exercise, serving as a passive distracter, and higher participation rates in exercise classes (Matthews, Clair & Kosloski, 2001; Potteiger, Schroeder & Goff, 2000). Although it may be difficult to distribute tailored information that effectively synthesizes the unique information needs of most overweight and obese sedentary people through TV or music, these channels should not be discounted. They may be useful to the extent that they contribute to the establishment of norms, provide motivation for physical activity, foster increased awareness about the consequences of sedentary lifestyles and encourage interpersonal, active channel, communication (Rimal, Flora & Schooler, 1999).

Study Limitations

The small size of the groups is a limitation of this study, although it offered the flexibility to probe responses, encourage elaboration from the participants, and allowed the collection of detailed information. The objective of the study was to explore real life perspectives and practices among a group of overweight and obese sedentary adults sharing similar characteristics. Undoubtedly the views expressed by the participants reflect the unique characteristics of the geographic area and of those willing to discuss this topic in a focus group setting, which might not correspond entirely to other types of people or people in other regions. Despite these limitations, the findings provide meaningful insight for physical activity health communication practice and research.

IMPLICATIONS FOR PRACTICE AND RESEARCH

The study participants discussed their physical activity behaviors and elaborated on their attitudes, barriers, physical activity communication practices and preferences. The consistency of the participants' contributions in the sessions is noteworthy and points to patterns that can be further examined with representative samples and appropriate quantitative methods. Indeed, the study authors are using the results to inform the development and evaluation of two physical activity promoting communication campaigns that aim to promote the social norm of physical activity, increase social support, reduce barriers and increase motivation in adults.

The fact that a large number of enrolled participants did not show up for their scheduled focus group session is significant. Despite having sent each participant a reminder, the most common reason for not attending was that they forgot. More active recruitment methods must be used when recruiting overweight and obese sedentary adults. It could be that relying on this population to "come to you" is unrealistic without a meaningful incentive. Thus, future qualitative research should consider increasing the incentives offered and going to the population, by holding sessions in neighborhoods or by conducting interviews. To that end, in another physical activity promoting project, the authors of this study are conducting focus groups in schools with parents of young children.

Data from this study suggest that physical activity communication designed for overweight and obese sedentary adults should be delivered through a variety of channels, from a range of trusted sources, and be tailored to the needs of each individual. Thus, it may be useful to establish and evaluate interpersonal initiatives that expose people to important health issues, behaviors and their interconnections. Using the Theory of Planned Behavior as a framework, programs could focus on changing attitudes about physical activity being hard work by stressing the role of leisure time activity and activities of daily living. They could also aim to increase the perception that physical activity is normal and is expected within a person's social networks. Programs that promote a buddy system might be most effective at getting people to act and stay motivated. They could contribute to greater perceived behavioral control by teaching skills such as interpreting and evaluating health communication material, as well as learning information search strategies. Certainly the public should know that the government and health care professions support increased physical activity. Thus more promotion of the U.S. Surgeon General's focus on physical activity, as well as tobacco use, could be important for the credibility of physical activity promoting communication and behavior. Results from this study are informing two Theory of Planned Behavior guided tailored physical activity promotion campaigns aimed at sedentary working adults and sedentary parents of young children. Moreover, findings of this study will be tested with a larger sample using mixed methods followed by the development of intervention testing.

While this study is small, it is timely given the unambiguous benefits of physical activity, the persistent decline in physical activity levels, and rising overweight and obesity rates. Much more research is needed to help health communication researchers and practitioners develop and implement effective communication for a priority population and health behavior.

REFERENCES

Abraham, C., & Graham-Rowe, E. (2009). Are worksite interventions effective in increasing physical activity? A systematic review and meta-analysis. Health Psychology Review, 3(1), 108-144.

Anderson, L. M., Quinn, T. A., Glanz, K., Ramirez, G., Kahwati, L. C., Johnson, D. B., et al., (2009). The effectiveness of worksite nutrition and physical activity interventions for controlling employee overweight and obesity A systematic review. American Journal of Preventive Medicine, 37(4), 340-357.

Bauman, A. E., Sallis, J. F., Dzewaltowski, D. A., & Owen, N. (2002). Toward a better understanding of the influences on physical activity: The role of determinants, correlates, causal variables, mediators, moderators, and confounders. American Journal of Preventive Medicine, 23(2), S1, 5-14.

Campbell, M., James, A., Hudson, M., Carr, C., Jackson, E., Oakes, V., et al., (2004). Improving multiple behaviors for colorectal cancer prevention among African American church members. Health Psychology, 23(5), 492-502.

Centers for Disease Control and Prevention (2007). U.S. Obesity Trends 1985-2006. Retrieved December 10, 2008, from http://www.cdc.gov/nccdphp/dnpa/obesity/trend/maps/index.htm

Dutta-Bergman, M. J. (2004). Primary sources of health information: comparisons in the domain of health attitudes, health cognitions, and health behaviors. Health Communication, 16, 273-288.

Dutta-Bergman, M. J. (2005). Theory and practice in health communication campaigns: A critical interrogation. Health Communication, 18, 103-122.

Eakin, E. G., Lawler, S. P., Vandelanotte, C., & Owen, N. (2007). Telephone interventions for physical activity and dietary behavior change: A systematic review. American Journal of Preventive Medicine, 32(5), 419-434.

Ekkekakis, P., Hall, E. E., VanLanduyt, L. M., & Petruzzello, S. J. (2000). Walking in (affective) circles: Can short walks enhance affect? Journal of Behavioral Medicine, 23(3), 245-275.

Hasler, T. D., Fisher, B. M., MacIntyre, P. D., & Mutrie, N. (2000). Exercise consultation and physical activity in patients with type 1 diabetes. Practical Diabetes International, 17, 44-48.

Hesketh, K., Waters, E., Green, J., Salmon, L., & Williams, J. (2005). Healthy eating, activity and obesity prevention: A qualitative study of parent and child perceptions in Australia. Health Promotion International, 20(1), 19-26.

Hesse, B. W., Nelson, D. E., Kreps, G. L., Croyle, R. T., Arora, N. K., Rimer, B. K., et al., (2005). Trust and sources of health information: The impact of the Internet and its implications for health care providers: Findings from the first Health Information National Trends Survey. Archives of Internal Medicine, 165(22), 2618-2624.

Humpel, N., Owen, N., & Leslie, E. (2002). Environmental factors associated with adults' participation in physical activity: A review. American Journal of Preventive Medicine. 22(3), 188-199.

King, A., Castro, C., Wilcox, S., Eyler, A. A., & Sallis, J. F. (2000). Personal and environmental factors associated with physical inactivity among different racial-ethnic groups of U.S. middle-aged and older-aged women. Health Psychology, 19(4), 354-364.

Kremers, S. P., De Bruijn, G. J., Visscher, T. L., Van Mechelen, W., De Vries, N. K., & Brug, J. (2006). Environmental influences on energy balance-related behaviors: A dual process view. International Journal of Behavioral Nutrition and Physical Activity. 3(9), doi:10.1186/1479-5868-3-9

Kreuter M. W., & Skinner C. S. (2000). Tailoring: what's in a name? Health Education Research, 15(1), 1-4.

Leydon, G. M., Boulton, M., Moynihan, C., Jones, A., Mossman, J., Boudioni, M., et al., (2000). Cancer patients' information needs and information seeking behaviour: In depth interview study. British Medical Journal, 320, 909-913. doi:10.1136/bmj.320.7239.909

Marcus, B. H., Owen, N., Forsyth, L. H, Cavill, N. A., & Fridinger, F. (1998). Physical activity interventions using mass media, print media, and information technology. American Journal of Preventive Medicine, 15, 362-378.

Marshall, A. L., Owen, N., & Bauman, A. E. (2004). Mediated approaches for influencing physical activity: update of the evidence on mass media, print, telephone and website delivery of interventions. Journal of Science and Medicine in Sport, 7(Suppl. 1), 74-80.

Matthews, R. M., Clair, A. A., & Kosloski, K. (2001). Keeping the beat: Use of rhythmic music during exercise activities for the elderly with dementia. American Journal of Alzheimer's Disease and Other Dementias, 16, 377-380.

Noar, S. M., Benac, C. N., & Harris, M. S. (2007). Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological Bulletin, 133(4), 673-693.

Painter, J. E., Borba, C. P. C., Hynes, M., Mays, D., & Glanz, K. (2008). The use of theory in health behavior research from 2000 to 2005: A systematic review. The Society of Behavioral Medicine, 35, 358-362.

Pate, R. R., Pratt, M., Blair, S. N., Haskell, W. L., Macera, C. A., Bouchard, C., et al., (1995). Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. Journal of the American Medical Association, 273(5), 402-407.

Pope C., Ziebland, S., & Mays, N. (2000). Qualitative research in health care. Analysing qualitative data. British Medical Journal, 320(7227), 114-116. doi:10.1136/bmj.320.7227.114

Potteiger, J. A., Schroeder, J. M., & Goff, K. L. (2000). Influence of music on ratings of perceived exertion during 20 minutes of moderate intensity exercise. Perceptual and Motor Skills, 91(3 Pt 1), 848-854.

Rabiee, F. (2004). Focus-group interview and data analysis. Proceedings of the Nutrition Society, 63(4), 655-660.

Rashad, I., & Grossman, M. (2004). The economics of obesity. Public Interest, 156, 104-112.

Rennie, K., Johnson, L., & Jebb, S. (2005). Behavioural determinants of obesity. Best Practice & Research Clinical Endocrinology & Metabolism, 19(3), 343-358.

Rimal, R. A., Flora, J. A., & Schooler, C. (1999). Achieving improvements in overall health orientation. Effects of campaign exposure, information seeking, and health media use. Communication Research, 26(3), 322-348.

Rimer, B. K., & Kreuter, M. W. (2006). Advancing tailored health communication: A persuasion and message effects perspective. Journal of Communication, 56, S184-S201.

Ritchie, J., & Lewis, J. (2003). Qualitative Research Practice. A Guide for Social Science Student and Researchers. London: Sage.

Sallis, J. F., Johnson, M. F., Calfas, K. J., Caparosa, S., & Nichols, J. F. (1997). Assessing perceived physical environmental variables that may influence physical activity. Research Quarterly for Exercise & Sport, 68(4), 345-51.

Snyder, L. B., Hamilton, M. A., Mitchell, E. W., Kiwanuka-Tondo, J., Fleming-Milici, F., & Proctor, D. (2004). A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States, Journal of Health Communication, 9(S1), 71-96.

Suggs, L. S. (2006). A 10-year retrospective of research in new technologies for health communication. Journal of Health Communication, 11, 61-74. doi: 10.1080/10810730500461083

Tate, D. F., Jeffery, R. W., Sherwood, N. E., & Wing, R. R. (2007). Long-term weight losses associated with prescription of higher physical activity goals. Are higher levels of physical activity protective against weight regain? American Journal of Clinical Nutrition, 85(4), 954-959.

Tinker, T. L. (1996). Recommendations to improve health risk communication: lessons learned from the U.S. Public Health Service. Journal of Health Communication, 1(2), 197-217.

Tully, M. A., Cupples, M. E., Hart, N. D., McEnemy, J., McGlade, K. J., Chan, W. S., et al., (2007). Randomised controlled trial of home-based walking programmes at and below current recommended levels of exercise in sedentary adults. Journal of Epidemiology and Community Health, 61(9), 778-783.

van Sluijs, E. M., van Poppel, M. N., Twisk, J. W., Chin A Paw, M. J., Calfas, K. J., & van Mechelen, W. (2005). Effect of a tailored physical activity intervention delivered in general practice settings: Results of a randomized controlled trial. American Journal of Public Health, 95(10), 1825-1831.

Vandelanotte, C., De Bourdeaudhuij, I., Sallis, J., Spittaels, H., & Brug, J. (2005). Efficacy of Sequential or Simultaneous Interactive Computer-Tailored Interventions for Increasing Physical Activity and Decreasing Fat Intake. Annals of Behavioral Medicine, 29(2), 138-146.

Walker, O., Strong, M., Atchinson, R., Saunders, J., & Abbott, J. (2007). A qualitative study of primary care clinicians' views of treating childhood obesity. BMC Family Practice, 8(50). doi:10.1186/1471-2296-8-50

Waller, J., Marlow, L. A., & Wardle, J. (2006). Mothers' attitudes towards preventing cervical cancer through human papillomavirus vaccination: a qualitative study. Cancer Epidemiology Biomarkers and Prevention, 15(7), 1257-1261.

World Cancer Research Fund/American Institute for Cancer Research (2007). Policy and action for cancer prevention. Food, nutrition, physical activity, and the prevention of cancer: A global perspective. Washington DC: AICR.

World Cancer Research Fund/American Institute for Cancer Research (2009). Policy and action for cancer prevention. Food, nutrition, and physical activity: A global perspective. Washington DC: AICR.

Yancey, A. K., Wold, C. M., McCarthy, W. J., Weber, M. D., Lee, B. Simon, P. A., & Fielding, J. E. (2004). Physical inactivity and overweight among Los Angeles County adults. American Journal of Preventive Medicine, 27(2). 146-152.

L. Suzanne Suggs, PhD, CHES, Chris Mclntyre, PhD, Joan E. Cowdery, PhD

L. Suzanne Suggs, PhD, CHES, Assistant Professor, Faculty of Communication Sciences, University of Lugano, Via G. Buffi 13, CH 6900 Lugano, (p) +41.058.666.4484, (f) +41.058.666.4647, E-mail: suzanne. suggs@usi.ch. Chris Mclntyre, PhD, V.P., Health X Change, Canada and Lecturer, Faculty of Communication Sciences, University of Lugano, Via G. Buffi 13, CH 6900 Lugano. E-mail: chris@cmcintyre.info. Joan E. Cowdery, PhD, Associate Professor, Health Education, School of Health Promotion & Human Performance, Eastern Michigan University, 319A Porter, Ypsilanti, MI 48197, E-mail: jcowdery@emich.edu
Table 1. Focus Group Questions

Barriers or facilitators to physical activity behavior (PA) and
communication practices

  PA behavior:

    * How much PA do you typically get: (day/week)
    * What kinds of PA do you do?
    * Are there certain times of the year that you get more PA?
    * Are there certain times of the year that you think more about
      being more PA?

  Knowledge:

    * On the piece of paper in front of you, Please write down how
      much PA people are supposed to get each week?

  Barriers to PA:

    * What types of things make it difficult for you to get enough
      PA?
    * What is the #1 barrier to you being more PA?

  Attitudes:

    * What does PA mean to you?
    * In the past when you have engaged in PA, what did you like
      about it? what did you not like about it? why did you
      stop/reduce?
    * What kinds of PA do you like the most?
    * What do you expect to happen if you start being more PA?
      (immediately/long term)

  Intention & Motives

    * Do you want to be more PA?
    * Why do you want/not want to be more PA?

  Self-efficacy/behavioral control:

    * Do you believe that you can be more PA? (Why/Why not?)
    * If you start being more PA, do you think you can stick to it?

  Influencing others:

    * If you were trying to motivate someone like you to increase
      PA, what would you do?

Information seeking/communication behavior

  Behaviors & strategies:

    * Do you ever seek out information about PA? (If yes: What kind
      of info do you look for?)
    * Where do you go for information regarding health/PA?
    * What are some of the barriers/problems you have when needing
      to find trustworthy health information?

  Attitudes:

    * What do you like/dislike about these sources?
    * Do you trust theses sources? (Why/Why not? What makes that
      source trustworthy to you? Does the information you get seem
      relevant?)

  Preferences:

    * Where would you like PA/Health information to be available?
    * Have any of you ever used technologies such as pedometers,
      heart rate monitors, web based programs...(If yes: What did
      you like about them? What did you not like about them? Do you
      still use them? Why/why not).
    * Are there certain technologies or programs (for health or PA)
      that you wish you had access to?
      Want to change? Use more or less of?

Table 2. Sample characteristics

                   Session 1   Session 2   Session 3
                    (n = 4)     (n = 5)     (n = 4)

Age (mean)            30          31          30
Gender                 F           F           M
BMI mean *           40.38       38.26       36.53
BMI range *        36.6-49.8   27.4-55.7   32.8-40.4

Education level
completed

  No high school       1           -           -
  GED                  -           1           1
  High school          1           1           1
  Undergrad            -           3           2
  Trade school         1           -           -
  Missing              1           -           -

Perceived
susceptibility
for disease

  Very high            1           2           -
  High                 1           1           -
  Moderate             2           1           3
  Low                  -           1           -
  Very low             -           -           1

* calculated by self reported weight and height
(weight (lb)/[height (in)]2 x 703). CDC,
2009. http://www.cdc.gov/healthyweight/assessing/bmi/adult_BMI/
index.html#Interpreted
Gale Copyright: Copyright 2010 Gale, Cengage Learning. All rights reserved.