Predictors of Community Support for Smoking Ban in the South - Research Proposal Example

Topic Predictors of Community Support for Smoking Ban in the South Outline: The two approaches I intend to utilize for this project are the historical and sociological approaches. Literary approach: An examination of the pertinent literature will prove to be very insightful in that it will serve to enhance the sociological approach. The literature will serve as guidance on the subject of community support for the smoking ban. I have chosen this approach because I feel that in order to gain a full understanding of the smoking ban one needs to look at the body of empirical research as well as other literature on the subject. Sociological approach: questionnaire 100 participants, location ________________ For this body of research, I plan to conduct telephone interviews of randomly selected participants. The questions are extensive as I plan to cover a vast amount of information as a means of gaining insight into predicting community support as any effective ban requires community support. Questionnaire Questions Please indicate which of the following 6 statements best describes your personal smoking behavior. 1. Never smoked cigarettes regularly. 2. Was a smoker for at least a 3-month period in my life, but have smoked 0 cigarettes in the past week. 3. Occasional smoker (1-5 cigarettes per week) for the last 3 months. 4. Light smoker (fewer than 10 cigarettes per day) for the last 3 months. 5. Moderate smoker (between 10 and 19 cigarettes per day) for the last 3 months. 6. Heavy smoker (20 or more cigarettes per day) for the last 3 months. Next, I would like you to please answer the following questions about how you have been affected by cigarette smoke. Never 0 Rarely 1 Sometimes 2 Often 3 Always 4 1. How often has being around cigarette smoke caused you to have a headache 0 1 2 3 4 2. How often has being around cigarette smoke caused you to have breathing problems 0 1 2 3 4 3. How often has being around cigarette smoke caused you to have eye irritation 0 1 2 3 4 4. How often have you felt bothered in general by being around cigarette smoke 0 1 2 3 4 Are you currently either employed or a student If not, what would be another group that you spend a significant amount of time with ____________________________________________________________________ Next, please answer the following 3 questions about your social activities. 5. On average, how many hours do you spend per week with your family members 6. On average, how many hours do you spend per week with your friends 7. On average, how many hours do you spend per week with your co-workers/peers (OR OTHER GROUP LISTED ABOVE) For the following questions, please describe the smoking behaviors of your family, friends, and co-workers. None 0 Less than half 1 About half 2 More than half 3 All 4 8. What portion of your immediate family members currently smoke (By immediate family I mean parents, siblings, spouse, children) 0 1 2 3 4 9. What portion of your friends currently smoke 0 1 2 3 4 10. What portion of your co-workers/peers currently smoke 0 1 2 3 4 Now, I am going to ask you about your feelings and opinions about different issues. For the following statements, please choose any response "1, 2, 3, 4, 5, or 6," understanding that a "1" means "strongly disagree" and a "6" means "strongly agree." Strongly Disagree 1 2 3 4 5 Strongly Agree 6 11. Smoking should be allowed in designated areas of restaurants. 1 2 3 4 5 6 12. Government should not regulate individual behaviors. 1 2 3 4 5 6 13. I would vote for a political candidate who favored public smoking bans. 1 2 3 4 5 6 14. A non-smoker should not have to be in contact with tobacco smoke. 1 2 3 4 5 6 15. If restaurants banned smoking, I would eat out less. 1 2 3 4 5 6 16. The government should create more policies to protect public health. 1 2 3 4 5 6 17. I would write a letter to my elected representative opposing smoking bans. 1 2 3 4 5 6 18. Incomes should be more equal, because people contribute equally to society. 1 2 3 4 5 6 19. Smoking should be banned in all indoor public places. 1 2 3 4 5 6 20. Smoking should be outlawed in bars. 1 2 3 4 5 6 21. The government should develop programs to improve quality of life for all of its citizens. 1 2 3 4 5 6 22. A person should have the right to smoke in outdoor public places. 1 2 3 4 5 6 23. If restaurants had complete smoking bans, I would eat out more. 1 2 3 4 5 6 24. Those who are well off in this country should be obligated to help those who are less fortunate. 1 2 3 4 5 6 25. I would vote to have current smoking restrictions reduced. 1 2 3 4 5 6 26. People should not expect to breathe smoke-free air. 1 2 3 4 5 6 27. We focus too much effort on having equal rights in this country. 1 2 3 4 5 6 28. Employers should be required to provide a smoke-free work environment for their employees. 1 2 3 4 5 6 29. I would enjoy eating out more if there was no smoking. 1 2 3 4 5 6 The Department of Health Statistics indicates that each year there are approximately 7,000 deaths which can be directly attributed to smoking. In fact, in St. James Hospital in Dublin, at least half of the in-patients have been admitted from smoking related illness. Additionally, the statistics indicate that there are approximately 870 deaths annually as a direct result of passive [second hand] smoke (Fine Geal, http://www.finegael.ie/news/index.cfm/type/details/nkey/22359/pkey/653). These alarming statistics have prompted a direct judicial response. This response has come in the form of a smoking ban and has prompted the need for investigation into the community response to such a ban. This research paper examines the level of community support and the factors utilized to predict this support. It utilized both a literary and sociological approach. The literary is utilized as a means of establishing the basic tenets of the sociological approach. The Literary Approach Predictors of Public Support for Smoking Bans Examination of the predictors of public support specifically related to smoke-free policies has been limited within the literature. In cases where these predictors were evaluated with regard to this issue, they were done so either informally or with limited-item measures (Brooks & Mucci, 2001; Dixon, Lowery, Levy, & Ferraro, 1991; Green & Gerken, 1989; Taylor, Ross, Goldsmith, Zanna, & Lock, 1998). Further investigation of predictors that have been used to predict other controversial political attitudes may lend valuable information to the smoke-free policies literature, and support a call from the literature to understand more comprehensively which factors are related to individual levels of support/lack of support for public smoking bans (Brooks & Mucci, 2001). By reviewing and adapting the predictors from previously existing attitude models, greater explanation in community attitudes about public smoking bans may be provided. The most common variable used to predict political attitudes and intentions has been self-interest. This variable was reviewed first. Through the expansion in the explanation of political attitudes, a model using self-interest, combined with social identification and value relevance, was developed by Boninger et al. (1995). An examination of the three predictors employed in the Boninger et al. (1995) model, and an evaluation of their individual and joint utility in predicting attitudes toward public smoking bans, was conducted. Self-interest Self-interest has been defined as "the degree to which a political issue impinges immediately and tangibly upon an individual's private life" (Young, Borgida, Sullivan, & Aldrich, 1987). The relationship between self-interest and support for public policies has been extensively debated within the literatures of psychology and political science. One set of studies has failed to find support for the relationship between self-interest and political attitudes (Barton, 1968; Lau, Brown, Sears, 1978; Shapiro & Mahajan, 1986). When examining attitudes in support of the Vietnam War, researchers were not able to substantiate a relationship between eligibility for the military draft (self-interest) and supportive attitudes for the Vietnam War (Barton, 1968; Lau, Brown, & Sears, 1978). In another of these studies, the researchers failed to find a relationship between women's employment status and their support for affirmative action for women (Shapiro & Mahajan, 1986). Specifically, in the arena of substance use, Sivacek and Crano (1982) did not find a significant relationship between the age of young people and their attitudes about a policy that would raise the legal drinking age. In contrast, a second group of studies did find support for the relationship between self-interest and attitudes. Crowe and Bailey (1995) found individuals with a high frequency of drinking behavior did in fact have less supportive attitudes toward more stringent drunk driving laws. Specifically in the area of self-interest predicting support for tobacco control legislation, there have been several studies supporting the relationship between self-interest (defined as personal smoking behavior) and attitudes of support for tobacco control legislation (Brooks & Mucci, 2001; Dixon et al, 1991; Green & Gerken, 1989; Taylor, Ross, Goldsmith, Zanna, & Lock, 1998). Since this has been a controversial predictor of attitudes, its measurement properties and capabilities for evaluating smoke-free policies were examined. Measuring Self-interest Personal smoking behavior. A dimension of self-interest that has been tested with regard to support for smoke-free policies is personal smoking behavior, which has been found to significantly predict attitudes toward smoke-free policies (Brooks & Mucci, 2001; Dixon et al., 1991; Green & Gerken, 1989; Taylor et al., 1998). Green and Gerken (1989) initially found that personal smoking behavior was related to support for smoke-free polices. They believed that this relationship was based on the fact that the participants were able to understand clearly how their self-interest (smoking behavior) would be impacted by policies that would reduce the locations where they could smoke (Green & Gerken, 1989). Specifically, heavy smokers tended to support reducing smoking restrictions (66%), while a majority of nonsmokers supported increasing smoking restrictions (60%). Green and Gerken (1989) were able to provide support for the relationship between self-interest and attitudes of policy support; however, the results provided were in terms of percentages of individuals who fell into particular categories. Collecting and analyzing bivariate or multivariate level data may have provided a greater understanding of this construct. In addition, individuals were asked to self-report into categories of personal smoking behavior. It did not appear that clear definitions were provided about how many daily cigarettes smoked indicated that an individual was a light, moderate, or heavy smoker. The study by Green and Gerken (1989) was replicated and extended by Dixon et al. (1991). They expanded the construct of self-interest to include the amount of income individuals received from tobacco, how much individuals were bothered by being around smoking, friends' smoking behavior, and parents' smoking behavior. Dixon et al. (1991) found significant correlations between each of the self-interest variables [amount of income individuals receive from tobacco (.14), how much individuals were bothered by smoking (.30), friends' smoking behavior (- .23), and parents' smoking behavior (.07)] and support for smoking restrictions in public. This study expanded the definition of self-interest and also measured it using a bivariate level of analysis. This study gave additional support to the theory that self-interest predicts political attitudes, specifically when applied to anti-smoking policies. Again, it did not appear that clear definitions of the number of cigarettes related to each category of personal smoking behavior were included. Degree bothered by smoke. Beyond simply personal smoking behavior, a second dimension of self-interest that has been measured in the literature is the ways in which an individual feels bothered by exposure to secondhand smoke (Dixon et al., 1991; Green & Gerken, 1989;). A large portion of those individuals who were very sensitive to cigarette smoke (71.3%) reported wanting an increase in smoking restrictions (Green & Gerken, 1989). When smoking behavior and sensitivity to smoke were combined, nonsmokers who were very sensitive to cigarette smoke (70%) wanted an increase in smoking restrictions (Green & Gerken, 1989). This supports that smoking behavior and sensitivity to smoke were both important dimensions of self-interest. Dixon et al. (1991), in their replication study of Green and Gerken (1989), also found significant positive correlations between the degree respondents were bothered by smoke and the support of the respondents for smoking restrictions, using the same scale employed by Green and Gerken (1989). While successful in finding support for the relationship between self-interest and support for smoke-free public policies, there were areas where the measurement of these constructs could have been improved upon. Specifically, definitions for participants on the number of cigarettes that are associated with the different levels of personal smoking behavior were not provided. Also, all four of the items measuring the degree to which someone was bothered by smoke were not combined into one scale whose psychometric properties could be assessed. Social Identification Beyond self-interest, another variable that has been used to evaluate support for political attitudes has been social identification. Social identification has included the need to understand an individual as a function of the groups that he/she identifies as being a part of (Brewer, 1991). This group categorization must be in a way that is logical to the particular individual (Tajfel, 1978). The individual's view of his/her social identity may be affected by context (Fu, Lee, & Chiu, 1999). Thus, it is important to provide a context for individuals to answer questions about their social identities. One context that can be used for individuals to evaluate group identifications within is political attitudes. When studying the types of groups that individuals identify with as a function of their social identities, there have been two sets of groups evaluated (Wong-Rieger & Taylor, 1981). The first set of groups has consisted of small, intimate, personalized groups. These groups have been categorized as primary groups. Examples of such groups have included friends and family members. The other set of groups have been those groups which are large, impersonal, and formal. These groups have been considered secondary groups. Culture and social class have been examples of secondary groups. When evaluating participants' ratings of how important particular groups were to their social identity, participants tended to rate family and friends as significantly higher than all other groups (Wong-Rieger & Taylor, 1981). These findings showed support for the importance of these primary groups to social identity, more important than secondary groups. Identification with primary groups can then be evaluated within the context of support for political attitudes. Measuring Social Identification The measurement of social identification specifically related to smoke-free policies has been limited, and has been described as self-interest rather than social identification. The smoke-free policies study which did include social identification-related items measured attitudes toward smoke-free policies based on their effect on a participant's family and friends (Dixon et al., 1991). Their results demonstrated a significant negative relationship between the smoking behavior of the individual's best friends and his/her support for smoke-free policies, meaning that the more an individual's best friends smoked, the less supportive of smoke-free policies the individual tended to be. Although Dixon et al. (1991) put these questions under the domain of self-interest, it seems that these questions would only be important depending on how much the participants identified themselves as being close to their relatives, friends, and parents. This is why it is important to look at these questions under the domain of social identification, when the strength of these group affiliations as a function of one's social identity can be assessed (Wong-Rieger & Taylor, 1981). Value Relevance An additional construct which has been used to predict supportive political attitudes is value relevance. Value relevance has referred to an individual's beliefs based on his/her personal and social values (Boninger, Krosnick, & Berent, 1995). According to Boninger et al. (1995), if an attitude being measured were related to the individual's personal and social values, then the attitude toward the issue would be strong. This has been supported by individuals in political psychology, who have suggested that understanding people's personal values, and how these values influence their views on candidates and policies, is crucial to understanding their roles in the political sphere (Kuklinski, 2002). The relationship between an individual's political values and his/her attitudes about public smoking bans is important to evaluate. Measuring Value Relevance Due its limited use as a construct to predict attitudes toward smoke-free policies, the history of measuring value relevance within this literature was examined. Dixon et al. (1991) measured value relevance by asking respondents about whether their political beliefs were more Democrat or Republican, and whether they were Independent, Moderate, Democratic, or Conservative in their political ideologies. However, no significant correlations between these measures of political ideology and attitudes in support for smoke-free policies were found. One reason for these weak relationships may be that these are not accurate measures of political ideology. A more sensitive measure of political ideology may produce a significant positive relationship with attitudes in support of smoke-free public policies. An example of a sensitive measure of political ideology was developed and utilized by Fried, Levi, Billings, and Browne (2001). The researchers used it to predict attitudes supporting affirmative action with African Americans. In order to develop a sensitive scale of ideology, they developed a scale that measured political ideology on a continuous scale ranging from individualism to egalitarianism. Significant positive correlations were found between egalitarianism and support for Affirmative Action. The researchers measured political ideology with reference to policies of inequity, poverty, and compassion. Other scales have also measured dimensions of individualism and egalitarianism (Feldman, 1988; Feldman 1999; Kluegel & Smith, 1986). Rather than only using simple political status measures, using a continuous measure of an individual's political ideologies may lead to a better understanding of the degree to which an individual supports an individualistic approach or egalitarian approach toward society. Through the development of a sensitive measure of political ideologies that is relevant specifically to public smoking bans, the utility of its predictive nature toward attitudes supporting smoke-free policies may be better understood. Intended Behaviors in Support of Smoke-Free Public Policies In order to expand the understanding of individuals' feelings about public smoking bans beyond attitudes, the utility of adding the variable of intended behaviors to the attitude model was explored. Studies in the literature that have measured support for smoke-free policies have done so only on the dimension of attitudes of support for such policies (Brooks & Mucci, 2001; Dixon et al., 1991; Green & Gerken, 1989). While attitudes of support are an important construct to assess (Boninger et al., 1995; Strobl & Latter, 1998), it is also important to understand individual behaviors (intended or actual) that also represent support for smoke-free public policies. Ratner and Miller (2001) provided insight as to why it is important to look not just at attitudes in support of public policy, but also at intentions/behaviors in support of public policy (e.g., signing a petition, attending a meeting). As Ratner and Miller (2001) explained, "not everyone who cares about a cause will feel equally comfortable taking action on its behalf (p. 6). Green and Cowden (1992) concluded that self-interest was a stronger predictor of actual behavior than of attitudes. They measured the impact of self-interest on political behavior. Specifically, they assessed parents whose children were bused to other schools for integration purposes (self-interest) and their participation in anti-busing organizations. Green and Gerken (1992) found that the parents whose children were being bused were significantly more likely to participate in anti-busing activities. Young, Borgida, Sullivan, and Aldrich (1987) also were able to find significant support for the relationship between self-interest and behaviors, specifically for voting behavior. In light of the need to include behaviors in the measurement of support for public policy (Green & Cowden, 1992; Ratner & Miller, 2001), it is also important to measure behaviors that support smoke-free public policies. Since the state where residents were interviewed does not currently have smoking bans in all public places, actual voting behaviors and other behaviors related to support/lack of support for these policies could not be measured. For this reason, intended behaviors in support of the policies were assessed. Since previous studies assessing the relationship between self-interest and behavior were measuring actual behaviors, it is not clear whether self-interest will predict intentions to act. The Sociological Approach Sampling Technique Participants were selected from a random number database developed by an independent sampling firm. Telephone numbers included in the database were pre-screened by the sampling firm in order to reduce the number of businesses and disconnected telephone numbers in the database. Random digit dialing was used as an alternative to only using listed telephone numbers. By only using listed telephone numbers, those households who did not list their telephone numbers would not be included, and would reduce the quality of the sample (Bezilla, 1992). One hundred residents of a Dublin completed telephone interviews based on a random-digit telephone number database. The sample was 67% female, and an average of 43 years old. Approximately half of participants had at least a 2-year college degree (50%) and were registered voters. Overall Results The outcome measure of interest in this study was the Attitudes and Intended Behaviors about Smoking Bans Scale. The overall mean score on this scale was 4.01 with a standard deviation of 1.16 (see Table 2). In this study, participants as a whole had pro-smoking ban attitudes and intentions; however, the strength of these attitudes was not that strong. On the 6-point Likert-scale that was used to measure this variable, a "4" was in the positive direction, but was the lowest of the positive values. A value of "6" was the highest possible positive value. The average personal smoking behavior of individuals in the sample was individuals who were former smokers (M = 1.1). The sample was comprised of 21.7% current smokers, 25.7% former smokers, and 52.6% never smokers. The percentage of current smokers in the sample (21.7%) corresponded closely with the current national average of 23.4% adult smokers (Centers for Disease Control, 2003b). Participants were rarely to sometimes bothered by being around smoke (M = 1.67). As a whole, about less than half of participants' family (M = .80), friends (M = 1.04), and co-workers/peers/other group (M = 1.18) were smokers. Individuals held political values that were in the middle in terms of being individual versus egalitarian, but leaned in the egalitarian direction (M = 3.55). The correlations between all of the variables can be found in Table 3. Table 1--Participant Demographic Information Gender Females 66% Males 34 % Age M = 43, SD= 15.54 Education Grade 8/Some high school 3% High School Diploma/GED 18% Some college 26% 2-year college degree 18% 4-year college degree 21% Graduate degree 11% Other 3% Number of Children (under 16) M = .71, SD= 1.263 Registered voter Yes 89 % No 11% Table 2--Variable Descriptive Statistics Scale Mean SD Self Interest Personal smoking behavior 1.10 1.59 Smoke bother scale 1.67 1.06 Group Smoking Behavior Family smoking behavior 0.80 0.98 Friends' smoking behavior 1.04 0.96 Co-workers/peers/other smoking behavior 1.18 0.97 Value relevance 3.55 1.22 Attitudes and intentions about smoking bans 4.01 1.16 Table 3-Correlation among variables Variable M 1. Personal smoking behavior 1.10 2. Smoke bother scale 1.67 3. Family smoking behavior .80 4. Friend smoking behavior 1.04 5. Co-workers/peers/other smoking behavior 1.18 6. Value relevance 3.55 7. Attitudes and intentions about smoking bans 4.01 Note. | r | < . 10 are not significant. . | r | > .20 are significant at the p are displayed on the diagonal. Variables 2 -4 are each 2-item scales, so 1-item scale. SD 1 2 3 4 5 6 7 1.59 1.05 -.45 (.74) .98 .24 -.09 (.33) .96 .47 -.37 .34 (.63) .97 .38 -.15 .20 .50 (.61) 1.22 -.16 .24 -.04 -.05 -.01 (.69) 1.16 -.55 .65 -.27 -.44 -.28 .36 (.89) .05 level. | r | > .20 are significant at the p < .01 level. Reliability values (a) tie correlation between the 2 items is reported instead of a. Variable 1 is a References Azjen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. Barton, A. H. (1968). The Columbia crisis: Campus, Vietnam, and the ghetto. Public Opinion Quarterly, 32(3), 333-351. Bartosch, W. J., & Pope, G. C. (2002). Economic effect of restaurant smoking restrictions on restaurant business in Massachusetts, 1992 to 1998. Tobacco Control, 11(2), 38-42. Bezilla, R. 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