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Characteristics of Patients Adhering to a Hospital's No-Smoking Policy
27, 846–853 (1998) PM980368
PREVENTIVE MEDICINE ARTICLE NO.
Characteristics of Patients Adhering to a Hospital’s No-Smoking Policy1 Karen M. Emmons, Ph.D.,*,2 Byron R. Cargill, Ph.D.,†,3 Jacki Hecht, R.N., M.S.N.,* Michael Goldstein, M.D., Richard Milman, M.D.,† and David B. Abrams, Ph.D.* *The Miriam Hospital/Brown University School of Medicine and †Rhode Island Hospital, Boston, Massachusetts 02115
INTRODUCTION
Objectives. The purpose of this paper is to examine the characteristics of smokers who adhere to a hospital smoking ban, compared to those who do not. Design. The data presented in this paper are baseline and discharge survey data collected among hospitalized smokers. Setting. This study was conducted in two teaching hospitals in a northeastern city. Patients/participants. The subjects were 358 smokers who participated in a larger smoking intervention trial. Main results. Seventy-six percent of the subjects reported adhering to the smoke-free policy during their hospital stay. In a multivariate model, demographic factors that predicted adherence included being older, having shorter length of stay, not reporting recreational drug use in the previous 12 months, and not having alcohol-related problems. Smoking history variables that predicted adherence included having had at least 24 h of abstinence in the 7 days prior to hospitalization; self-efficacy variables (e.g., confidence in ability to quit smoking in 1 month and less anticipated difficulty refraining from smoking during hospitalization) also predicted adherence. Conclusions. Understanding the factors that predict adherence to health care policies can provide useful information for health promotion interventions in a medical setting. The implications of these findings are discussed. q1998 American Health Foundation and Academic Press Key Words: hospitalized patients; smoking; adherence; hospital policy.
1 This research was supported in part by 1RO1HL48180 and 1RO1HL50017. This research was presented at the Annual Meeting of the Society of Behavioral Medicine, March 1995, San Diego CA. 2 To whom correspondence and reprint requests should be addressed at present address: Division of Community-Based Research, Dana-Farber Cancer Institute, 44 Binney Street, Boston MA 02115. Fax: (617) 632-4858. E-mail: karen [email protected]. 3 Present address: Cape Cod Hospital, Cape Cod, MA.
The nationwide smoking ban in accredited hospitals has increased the importance of hospitalization as an opportunity to reach a large number of smokers who may not have thought about seeking help, at a time when they may be the most receptive to the idea of cessation [1,2]. Hospital-based cessation interventions have been primarily targeted at individuals who are hospitalized for smoking-related illnesses [3–10], although some recent studies have focused on the hospital population as a whole [11–15]. Hospital smoking bans have the potential to change individuals’ attitudes and provide an opportunity for smokers to try out abstinence. This experience might produce cessation or motivate smokers towards cessation. However, it is likely that among those who do abstain during the hospital stay, there will be a high rate of relapse [16]. Behavior changes that are attributed to external factors (e.g., policies requiring abstinence) are at risk once those factors are no longer present (e.g., posthospitalization) [17,18]. Studies of attributional processes in behavior change suggest that individuals who view themselves as personally responsible for their behavior change will be more successful at long-term maintenance of those changes [18–20]. Several theoretical models, including social cognitive theory, health belief model, theory of reasoned action, and the transtheoretical model, also provide some insight into the variables that may influence behavior change during hospitalization. Key theoretical variables that cut across these theories include self-efficacy, perceived vulnerability, motivation to change, and facilitating factors (e.g., “cues to action”) [21–25]. For certain smokers, physiological factors, such as nicotine dependence and psychiatric or substance abuse comorbidities [26–29], may make mandated abstinence a most difficult challenge. Such patients may need and benefit from additional intervention and support from their health care providers. Few studies have examined the characteristics of smokers who are hospitalized and
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0091-7435/98 $25.00 Copyright q 1998 by American Health Foundation and Academic Press All rights of reproduction in any form reserved.
ADHERENCE TO HOSPITAL SMOKING POLICY
how individual differences might interact with public health changes, such as the JCAHO hospital smoking ban. A better understanding of the factors that might predict improved motivation or actual cessation during hospitalization could have important implications for treatment and policy. A better understanding of the predictors of adherence with smoking policies could help providers to better target available resources. Such information could also be helpful in elucidating stepped-care models that are becoming of increased interest for the treatment of smokers [36]. The purpose of this paper is to examine the characteristics of smokers who adhere to a hospital smoking ban, compared to those who do not. METHODS
Study Design The data presented in this paper are baseline and discharge survey data collected from smokers who were hospitalized in one of two community-based teaching hospitals. In order to evaluate characteristics that are associated with adherence to hospital smoking bans, this article compares selected attributes for patients who report either smoking or abstaining during hospitalization. Subjects The subject sample is composed of 358 smokers who were hospitalized at the Miriam Hospital, a 230-bed general medical/surgical facility, and on 6 units at Rhode Island Hospital, a 719-bed facility, and who completed both baseline and discharge surveys as part of this study. The selected units in the larger hospital were matched to the illness characteristics of the target units in the smaller hospital. Both hospitals are academic teaching hospitals and had total indoor smoking bans at the time the study was conducted. Measures The baseline survey contained questions about demographic characteristics, comorbidity factors, smoking history, perceived health vulnerability, self-efficacy, and motivational factors. Adherence was defined as selfreport of abstaining from cigarettes during the hospital stay, as assessed on the discharge survey. Demographics and individual characteristics. Demographic characteristics assessed included age, race/ ethnicity, gender, and educational level. The participating hospitals’ management information services departments provided patient data on admitting and discharge diagnoses, length of hospital stay, and use of
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nicotine replacement therapy prior to and during hospitalization. Exposure to cessation interventions delivered by the physician or house staff was assessed on the discharge survey. Comorbidity Factors Mental Health Inventory (MHI). The Mental Health Inventory (MHI), a five-item subscale of the SF-36 [30], was used as a diagnostic measure of psychological distress and depression. The MHI subscale has been demonstrated to possess good reliability and validity [30,31]. Substance use. History of problem drinking was assessed by the CAGE, a four-item alcoholism screening questionnaire which has been shown to demonstrate good external validity [32,33]. In one validation study with a medical population, it was found that endorsing one or more items was a better predictor of alcoholism at follow-up than biochemical screens or physician diagnoses [33]. Recreational drug use was assessed by asking subjects if they had used any recreational drugs (e.g., marijuana, cocaine, heroin) in the previous 12 months. Smoking history. Standard NCI measures for smoking history were utilized; constructs assessed included number of quit attempts in the previous year and lifetime, efforts to quit smoking prior to hospitalization, longest period of abstinence, years of regular smoking, and smoking rate. One item from the Fagerstrom Tolerance Questionnaire [34], time from awakening to the first cigarette, was used to assess nicotine dependence. Psychometric studies suggest that responses to this single item are related to levels of nicotine intake [35–37]. Perceived vulnerability. Perceived vulnerability to smoking-related illness was assessed by four items asking subjects to rate how much smoking affects various aspects of their health [38]. Degree of perceived vulnerability was rated on a five-point Likert-type scale (from “not at all” to “very much”). Self-efficacy. Self-efficacy was measured by two items assessing confidence in one’s ability to quit smoking in the next month and in the next 6 months. These items were rated on 10-point Likert-type scales (from “not confident” to “extremely confident”). Difficulty in refraining from smoking during hospitalization was rated on a 5-point Likert-type scale (from “not at all” to “very much”). Motivational variables. The Stages of Change Scale [22] was used to classify active smokers into three categories regarding readiness to quit smoking: (1) Precontemplation included subjects who reported that they were not seriously thinking about quitting smoking in
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the next 6 months; (2) Contemplation included individuals who reported that they were seriously thinking about quitting smoking in the next 6 months; and (3) Preparation included subjects who were intending to quit smoking in the next month and who had tried to quit in the past year. Intentions to quit smoking were assessed with a question regarding plans to quit smoking posthospitalization; overall desire to quit smoking was assessed using a five point Likert-type scale (from “not at all” to “very much”). Facilitating factors/cues to action. A key facilitating factor for smoking cessation in the health care environment is physician’s advice to quit smoking. Receipt of provider’s advice to quit smoking at any point, and in the 12 months prior to hospitalization, was assessed via patient self-report. Procedures All hospitalized smokers were identified through the admissions process and were approached and asked to participate within 24 h of hospitalization. A comprehensive search for potential subjects was done daily using lists of new admissions based on smoking status, nursing assessments, and medical chart reviews on the target units, and nurse referrals. The primary inclusion criteria were: (1) ability to complete a pulmonary function test (required by the larger study from which the sample was drawn); (2) no myocardial infarction or thoracic or abdominal surgery; (3) smoking a minimum of five cigarettes per day on average and have smoked at least one cigarette in the 7 days prior to admission; (4) being alert and oriented; and (5) being English-speaking. Efforts to maximize enrollment included emphasizing that subjects were not being asked to change their smoking as part of the study. This facilitated recruitment of smokers who did not want to quit smoking, as well as those who did. Data collection. Subject assessments were made at baseline and at discharge. The initial baseline survey was conducted as a structured interview at the bedside. The discharge survey was prompted by the patient’s primary nurse, but was self-administered by the patient within 8 h prior to discharge. Response rate to the discharge survey was 63%. Data analysis. The dependent measure, adherence to the hospital smoke-free policy, was collected on the discharge survey. ANOVAs and x2 analyses were utilized to determine the influence of patient characteristics on adherence to the no-smoking policy. Stepwise logistic regression analyses were used to determine the overall contribution of characteristics found to predict adherence in the univariate analyses.
RESULTS
Demographics/Sample Description The average age of the subjects was 46 years. The majority of participants were white (91%) and married (55%); 55% were female. Twenty-one percent of the subjects had less than a 12th grade education, while 35% had a high school degree or equivalent. The average hospital stay was 5.3 days. Average number of years smoking was 27.8, and 68% of the participants were nicotine dependent. Sixty-three percent of the patients indicated that they were thinking of quitting after discharge. Analysis of demographic characteristics based on whether respondents to the baseline also completed the discharge survey indicated that white participants were more likely to complete the discharge survey than members of other ethnic groups (x2(3) 5 10.57; P # 0.01). Other demographic characteristics and smoking history were not significantly related to discharge survey response rate. Limited demographic information was available regarding the characteristics of individuals who refused to be in the larger trial; there were no differences in participation status based on gender, but treatment refusers were approximately 5 years older than participants (P , 0.0001). Univariate Analyses Demographics. Seventy-six percent of the subjects reported adhering to the smoke-free policy during their hospital stay. Of those who did not adhere to the policy, the average number of cigarettes smoked per day during the hospital stay was 6.2 (median 5 4.0). Longer hospital stays were associated with less adherence to the smoking policy (F (1,351) 5 11.34, P # 0.001) (see Table 1). Older patients were more adherent than younger patients (F (1,354) 5 18.66, P # 0.001), and married patients were more adherent than those who were never married, widowed, divorced, or separated (x2(2) 5 8.02; P 5 0.02). There were no significant differences in adherence based on gender or level of education. Comorbidity factors. Patients who reported using recreational drugs within the previous year were less likely to adhere to the smoke-free policy (x2(1) 5 27.26; P # 0.001). In addition, patients with evidence of alcohol-related problems, as indicated by a positive CAGE score, were less likely to be compliant (x2(1) 5 5.40, P # 0.02). No relationship was found between adherence and psychological distress or depression. Patients with circulatory disease as the primary diagnosis during hospitalization were more likely to adhere to the smoking policy than other diagnostic categories, while patients with digestive disorders were least likely to adhere (x2(5) 5 12.48, P # 0.03).
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ADHERENCE TO HOSPITAL SMOKING POLICY
TABLE 1 Univariate Analysis of Factors Associated with Adherence to Hospital Smoke-Free Policies Adherent (n 5 271)
Nonadherent (n 5 87)
P value
Demographics/comordibity factors Age (M years) Marital status (% married) Length of stay (M days) No recreational drug use in past year Positive CAGE score
48.1 57.9% 4.9 90.0% 42.1%
41.1 43.7% 6.8 66.7% 56.3%
0.001 0.02 0.001 0.001 0.02
Smoking history Years smoking (M ) Ever try to quit smoking 24 h 1 abstinence in past 7 days
29.0 80.8% 77.5%
24.0 67.8% 44.8%
0.001 0.01 0.001
Perceived vulnerability Current illness is caused by smoking Continued smoking could hurt your health Health compared to average smoker
51.5% 4.16 3.24
39.1% 3.87 3.05
0.04 0.04 0.09
Confidence variables Anticipate difficulty in refraining from smoking while hospitalized (M ) Confidence in ability to quit in 1 month (M ) Confidence in ability to quit in 6 months (M )
25.5% 4.91 6.23
54.5% 3.26 5.06
0.001 0.001 0.03
Motivational variables Stage (% in precontemplation) Plan to quit smoking posthospitalization Desire to quit
22.6% 64.9% 4.05
36.8% 46.0% 3.28
0.01 0.001 0.001
Facilitating Factors Advised by MD to quit
79.9%
20.1%
0.01
Smoking history. Patients with longer smoking histories were more likely to be adherent, covarying the effect of age (P , 0.001). Patients who had ever made a quit attempt were also more likely to be adherent to the smoking ban (x2(1) 5 6.41, P # 0.01). Further, patients who reported not having smoked cigarettes for at least 1 day in the 7 days prior to completion of the baseline survey were more likely to adhere to the smoke-free policy (x2(1) 5 33.18; P # 0.001) (see Table 1). Although some patients completed the baseline survey after 24 h of hospitalization, a separate analysis performed on subjects whose baseline surveys were conducted within 1 day of admission confirmed that there was a significant relationship between adherence and prehospitalization abstinence (n 5 152; x2(1) 5 7.69; P # 0.01). Neither time to first cigarette (as a proxy for nicotine dependence) nor the average number of cigarettes smoked before hospitalization differed between adherent and nonadherent patients. Use of smoking cessation aids prior to, or during, hospitalization was also not related to smoking status during hospitalization.
likely to be adherent (F (1,351) 5 4.81, P # 0.04), as were patients who agreed that continuing to smoke would harm their health (F (1,353) 5 4.15, P # 0.04). In addition, there was a trend for adherent smokers to rate their health more highly than nonadherent smokers (P 5 0.09). Other measures of perceived vulnerability were not significantly related to adherence.
Perceived vulnerability. Patients who reported that their current illness was caused by smoking were more
Facilitating factors. Seventy-six percent of the participants reported that their physicians spoke with
Self-efficacy. Patients who indicated that refraining from smoking would be difficult during hospitalization were less likely to adhere to hospital policy (x2(2) 5 39.29, P # 0.001). Confidence ratings in one’s ability to quit smoking in both 1 month and 6 months were also related to adherence (F (1,353) 5 19.60, P # 0.001; F (1,353) 5 9.10, P , 0.03, respectively). Motivational variables. Patients in the later stages of smoking cessation at baseline were more adherent to hospital policy (x2(2) 5 9.06, P # 0.01). Intention to quit smoking after discharge was related to increased adherence (x2(2) 5 14.01, P # 0.001), as was a general indication of desire to quit smoking (F (1,355) 5 22.27, P # 0.001).
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them about their smoking prior to hospitalization. Being advised to quit smoking by a physician prior to hospitalization was significantly related to adherence (x2(1) 5 7.51, P # 0.01). Physicians’ offers of smoking cessation consultation or prescriptions for nicotine replacement were not significantly related to adherence. Multivariate Model All factors significantly related to adherence in the univariate analyses were entered in a multivariate logistic regression equation, utilizing a stepwise method. The results revealed that several variables were retained as significant predictors of adherence to the smoke-free policy (see Table 2). Demographic variables which predicted adherence included older age and shorter length of stay; comorbidity factors included not participating in recreational drug use, while not having a positive CAGE score was marginally significant; smoking history variables included any abstinence days in the week prior to hospitalization, and confidence variables included low level of anticipated difficulty refraining from smoking while hospitalized and confidence in one’s ability to quit smoking in the next 30 days. The model x2 was significant (x2(6) 5 61.5; P # 0.0001) and the Hosmer–Lemeshow goodness of fit x2 measure indicated that the predicted model was similar to the observed data (x2(8) 5 7.39, P 5 0.50). DISCUSSION
Increasing adherence to hospital smoke-free policies offers many advantages, such as demonstrating commitment toward educating the public about the impact of smoking on health, facilitating healing and patient recovery, and enhancing safety regarding fire hazards [39]. Having an understanding of patient characteristics that are related to adherence will provide clearer
direction for health care providers wanting to intervene with smokers during hospitalization and will help to identify patients who might be at higher risk for nonadherence [40]. Several of the characteristics hypothesized to be related to adherence were significantly different between adherent and nonadherent patients. Of particular note were significant predictors of adherence retained in the multivariate model, including age and length of stay, such that increasing age and shorter hospital stays were associated with greater adherence. Ratings of one’s ability to refrain from smoking during hospitalization and rating of confidence in one’s ability to quit were also significant predictors of adherence. Therefore, in order to maximize the number of people refraining from smoking during hospitalization, it may be most fruitful to target supportive interventions during hospitalization to younger patients, those with longer hospital stays, and those with lower confidence ratings regarding cessation. Because it might be expected that these individuals will be more resistant to intervention during hospitalization, intervention approaches for patients at risk for nonadherence should target a range of motivational levels for smoking cessation. Comorbid characteristics were also associated with smoking policy adherence. Patients reporting the use of recreational drugs tended to be less adherent to the smoking policy. This may be due to the need to relieve the discomfort of withdrawal symptoms associated with the abuse of, and dependence on, illicit drugs such as narcotics. In addition, if drugs and tobacco are used as primary means of coping with pain and stress, this population may perceive smoking as necessary to cope with the stress of a hospital stay. Individual characteristics or the severity of illnesses related to drug use may also have contributed to nonadherence. For example, there may be unique characteristics of those willing to
TABLE 2 Factors Retained in Regression Model Predicting Adherence with Hospital Smoke-Free Policies
Variable demographics Age (M years) Length of stay (M days) Recreational drug use CAGE score Smoking history 24 h 1 abstinence in past 7 days Self-efficacy variables Anticipate difficulty in refraining from smoking while hospitalized Kind of to somewhat Somewhat to very hard Confidence in ability to quit in 1 month
B
SE
OR
P value
CI
0.033 20.081 21.055 20.539
0.015 0.032 0.407 0.320
1.030 0.922 0.348 0.583
0.02 0.01 0.01 0.09
1.00, 0.87, 0.16, .031,
1.209
0.325
3.350
0.001
1.77, 6.34
21.410 21.448 0.127
0.456 0.463 0.059
0.243 0.235 1.140
0.002 0.002 0.03
0.10, 0.60 0.10, 0.58 1.01, 1.27
1.06 0.98 0.78 1.09
ADHERENCE TO HOSPITAL SMOKING POLICY
admit to a socially unacceptable behavior, which may distinguish patients who are more likely to behave in an autonomous, sometimes less compliant manner. Although the reasons for the relationship are only speculated here, special attention to the smoking behavior of patients reporting drug use and alcohol problems seems appropriate for health care specialists [41]. In particular, efforts to minimize withdrawal may increase the likelihood of adherence among substance abusers. Although the univariate analyses indicated that perceived vulnerability predicted adherence, this relationship was not maintained in the multivariate analyses. However, self-efficacy variables and recent abstinence were important predictors of adherence in both the univariate and the multivariate analyses. In contrast, trying to quit prior to hospitalization was not related to adherence. Acute medical illnesses may provide an opportunity for patients to “try out” cessation, without actively trying to quit, thus increasing both their confidence and their ability to abstain throughout the hospital stay. Physicians play an important role in helping patients start thinking about smoking cessation. It may be more important for health care providers to link the risks of smoking to the impact that smoking can have on the individual’s health, typical of the discussions physicians have with patients concerning coronary disease, a group among which abstinence rates have traditionally been quite high [4,42]. While discussing smoking cessation with a physician prior to hospitalization was not found to be related to increased adherence in the multivariate analyses, the time frame in which the advice was provided to patients could not be determined. Over 80% of the patients reported that their physician had talked with them about their smoking prior to hospitalization or during the hospital stay. These results suggest that physicians are doing a very good job in addressing smoking with their patients, particularly in the course of outpatient care. Stage of change was not found to predict adherence in the multivariate model. However, it is not clear if smokers in the later stages would be more or less responsive to smoking interventions delivered during hospitalization. Further, it is unclear whether the stages of change algorithm, which has not been well studied among hospitalized populations, adequately assesses motivation among a hospitalized sample for whom environmental restrictions may artifically force patients into a more advanced stage of readiness. The contribution of the stage model to hospital-based smoking interventions should be assessed in longitudinal trials. It should be noted that over 70% of the hospitalized smokers refrained from smoking during their hospital stay. This level of adherence is excellent, but perhaps not surprising given that both participating hospitals
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did not allow smoking at all inside the hospital buildings. For these adherent smokers, hospitalization offered an important opportunity to have a successful experience with abstinence. Intervention efforts should be targeted at discharge and posthospitalization in order to build these smokers’ motivation for and skills related to making a successful long-term quit attempt. It is also interesting that, despite this relatively high rate of adherence to the smoking ban, 30% of hospitalized smokers smoked during their hospital stay. Objective data about the situational or environmental factors (e.g., location of room, type of unit) that facilitated violation of the ban were not available. However, anecdotal reports from study staff suggested that these smokers often smoked in the bathrooms and that family members often supplied cigarettes during the hospital stay. Some patients did receive permission from their physicians to smoke outside of the hospital entrances. Limitations of the present study should be noted. First, the sample is based on only those participants in a larger study who completed both the baseline and the discharge surveys, and thus response bias cannot be ruled out. Second, the dependent variable, adherence to the hospital smoking policy, is based on self-report of smoking status during hospitalization. It is possible that some participants did not report their smoking during hospitalization accurately. Recent reports suggest that the false negative rate associated with selfreport of smoking status is quite low [43]. In addition, the study was presented as quite separate from the hospital smoking policy, and the outcome data was confidentially collected at discharge rather than during the hospital stay, which may have reduced the likelihood of a social desirability bias. This study extends the existing literature by elucidating the factors that predict adherence to smoking bans in the hospital setting. In particular, in light of the limited resources that are often available for smoking cessation interventions, a better understanding of the predictors of adherence with smoking policies may be helpful to providers in better targetting available resources, drawing on recent stepped care models proposed for delivery of smoking interventions [28,29]. Understanding the many factors that can affect a patient’s ability to refrain from smoking may help to identify patients who are most likely to remain smoke-free during hospitalization. Such patients may be responsive to brief messages to abstain, as well as to positive reinforcement for doing so. Patients who successfully refrain from smoking during the hospital stay may benefit from posthospitalization follow-up to build on their initial success. Approaching patients who are less likely to be adherent regarding smoking cessation while hospitalized may require different, or more labor-intensive approaches. For example, these patients may benefit from motivational and behavioral counseling, as well as
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from pharmacologic treatment to help them get through their hospital stay smoke free [10,44]. In addition, patients who were nonadherent with the smoking ban are more likely to have other barriers to smoking cessation (e.g., withdrawal from alcohol or other substances) which could be addressed as part of efforts to impact on their ability both to adhere to the smoking ban during hospitalization and to quit at some future time. Encouraging smokers to remain smoke free during a time of intensified awareness of health issues could prove to be a valuable means of promoting smoking cessation; identifying characteristics associated with adherence to hospital smoke-free policies should be helpful toward that end. ACKNOWLEDGMENTS The authors acknowledge the contributions of Nancy Farrell, Elena Morgans, and Carol Carlisle for data collection and Alicia Fontes for data analysis. REFERENCES 1. Abrams DB, Emmons KM, Niaura RS, Goldstein MG, Sherman CE. Tobacco dependence. In: Nathan PE, Langenbucher JW, McCrady BS, Frankenstein W, editors. Annual review of addictions and treatment & research, Vol. 7. New York: Pergamon, 1991:391–436. 2. Pederson L, Baskerville JC, Wanklin J. Multivariate statistical models for predicting smoking behavior following physician advice to quit. Prev Med 1982;11:536–49. 3. Orleans CT, Rotberg HL, Quade D, et al. A hospital quit-smoking consult service: clinical report and intervention guidelines. Prev Med 1990;19:198–212. 4. Ockene JK, Aney J, Goldberg RJ, Klar JM, Williams JW. Physician-delivered interventions for smoking cessation: Strategies for increasing effectiveness. Prev Med 1987;61:723–733. 5. British Thoracic Society. Comparison of four methods of smoking withdrawal in patients with smoking related diseases. Br Med J 1983;286:595–7. 6. Raw M. Persuading people to stop smoking. Behav Res Ther 1986;14:97–101. 7. Burt A, Illingworht D, Shaw TRD, Thornley P, White P, Turner R. Stopping smoking after myocardial infarction. Lancet 1974; I:304–6. 8. Baile WF, Bigelow GE, Gottlieb SH, et al. Rapid resumption of cigarette smoking following myocardial infarction: inverse relation to MI severity. Addictive Behav 1982;7:373–80. 9. Cutter G, Oberman MK, Kimmerling R, et al. The natural history of smoking cessation among patients undergoing coronary arteriography. J Cardiopulm Rehab 1985;5:332–40. 10. Scott R, Lamparski D. Variables related to long-term smoking status following cardiac events. Addictive Behav 1985;10: 257–64. 11. Hurt RD, Dale LC, McClain FL, et al. A comprehensive model for the treatment of nicotine dependence in a medical setting. Med Clin N Am 1992;76(2):495–514. 12. Stevens VJ, Glasgow RE, Hollis JF, Lichtenstein E, Vogt TM. A smoking cessation intervention for hospital patients. Med Care 1993;31:65–72. 13. Taylor CB, Miller NH, Herman S, et al. A nurse-managed smoking cessation program for hospitalized smokers. Am J Public Health 1996;86:1557–60.
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39. Orleans CT, Kristeller JL, Gritz ER. Helping hospitalized smokers quit: new directions for treatment and research. J Consult Clin Psychol 1993;61(5):778–89. 40. Emmons KM, Goldstein MG. Smokers who are hospitalized: a window of opportunity for cessation interventions. Prev Med 1992;21:262–9. 41. Abrams DB. Treatment issues: towards a stepped-care model. Tobacco Control 1993;2(Suppl):2–29. 42. Ockene JL, Kristeller RG, Ockene I, Merriam P, Barrett S. Smoking cessation and severity of disease: the coronary artery smoking intervention study. Health Psychol 1992;11(2):119–126. 43. Patrick DL, Cheadle A, Thompson DC, Diehr P, Koepsell T, Kinne S. The validity of self-reported smoking: a review and metaanalysis. Am J Public Health 1994;84:1086–93. 44. Hecht JP, Emmons KM, Brown RA, et al. Smoking interventions for patients with cancer: guidelines for nursing practice. Oncol Nursing Forum 1994;21(10):1657–66.
PREVENTIVE MEDICINE ARTICLE NO.
Characteristics of Patients Adhering to a Hospital’s No-Smoking Policy1 Karen M. Emmons, Ph.D.,*,2 Byron R. Cargill, Ph.D.,†,3 Jacki Hecht, R.N., M.S.N.,* Michael Goldstein, M.D., Richard Milman, M.D.,† and David B. Abrams, Ph.D.* *The Miriam Hospital/Brown University School of Medicine and †Rhode Island Hospital, Boston, Massachusetts 02115
INTRODUCTION
Objectives. The purpose of this paper is to examine the characteristics of smokers who adhere to a hospital smoking ban, compared to those who do not. Design. The data presented in this paper are baseline and discharge survey data collected among hospitalized smokers. Setting. This study was conducted in two teaching hospitals in a northeastern city. Patients/participants. The subjects were 358 smokers who participated in a larger smoking intervention trial. Main results. Seventy-six percent of the subjects reported adhering to the smoke-free policy during their hospital stay. In a multivariate model, demographic factors that predicted adherence included being older, having shorter length of stay, not reporting recreational drug use in the previous 12 months, and not having alcohol-related problems. Smoking history variables that predicted adherence included having had at least 24 h of abstinence in the 7 days prior to hospitalization; self-efficacy variables (e.g., confidence in ability to quit smoking in 1 month and less anticipated difficulty refraining from smoking during hospitalization) also predicted adherence. Conclusions. Understanding the factors that predict adherence to health care policies can provide useful information for health promotion interventions in a medical setting. The implications of these findings are discussed. q1998 American Health Foundation and Academic Press Key Words: hospitalized patients; smoking; adherence; hospital policy.
1 This research was supported in part by 1RO1HL48180 and 1RO1HL50017. This research was presented at the Annual Meeting of the Society of Behavioral Medicine, March 1995, San Diego CA. 2 To whom correspondence and reprint requests should be addressed at present address: Division of Community-Based Research, Dana-Farber Cancer Institute, 44 Binney Street, Boston MA 02115. Fax: (617) 632-4858. E-mail: karen [email protected]. 3 Present address: Cape Cod Hospital, Cape Cod, MA.
The nationwide smoking ban in accredited hospitals has increased the importance of hospitalization as an opportunity to reach a large number of smokers who may not have thought about seeking help, at a time when they may be the most receptive to the idea of cessation [1,2]. Hospital-based cessation interventions have been primarily targeted at individuals who are hospitalized for smoking-related illnesses [3–10], although some recent studies have focused on the hospital population as a whole [11–15]. Hospital smoking bans have the potential to change individuals’ attitudes and provide an opportunity for smokers to try out abstinence. This experience might produce cessation or motivate smokers towards cessation. However, it is likely that among those who do abstain during the hospital stay, there will be a high rate of relapse [16]. Behavior changes that are attributed to external factors (e.g., policies requiring abstinence) are at risk once those factors are no longer present (e.g., posthospitalization) [17,18]. Studies of attributional processes in behavior change suggest that individuals who view themselves as personally responsible for their behavior change will be more successful at long-term maintenance of those changes [18–20]. Several theoretical models, including social cognitive theory, health belief model, theory of reasoned action, and the transtheoretical model, also provide some insight into the variables that may influence behavior change during hospitalization. Key theoretical variables that cut across these theories include self-efficacy, perceived vulnerability, motivation to change, and facilitating factors (e.g., “cues to action”) [21–25]. For certain smokers, physiological factors, such as nicotine dependence and psychiatric or substance abuse comorbidities [26–29], may make mandated abstinence a most difficult challenge. Such patients may need and benefit from additional intervention and support from their health care providers. Few studies have examined the characteristics of smokers who are hospitalized and
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0091-7435/98 $25.00 Copyright q 1998 by American Health Foundation and Academic Press All rights of reproduction in any form reserved.
ADHERENCE TO HOSPITAL SMOKING POLICY
how individual differences might interact with public health changes, such as the JCAHO hospital smoking ban. A better understanding of the factors that might predict improved motivation or actual cessation during hospitalization could have important implications for treatment and policy. A better understanding of the predictors of adherence with smoking policies could help providers to better target available resources. Such information could also be helpful in elucidating stepped-care models that are becoming of increased interest for the treatment of smokers [36]. The purpose of this paper is to examine the characteristics of smokers who adhere to a hospital smoking ban, compared to those who do not. METHODS
Study Design The data presented in this paper are baseline and discharge survey data collected from smokers who were hospitalized in one of two community-based teaching hospitals. In order to evaluate characteristics that are associated with adherence to hospital smoking bans, this article compares selected attributes for patients who report either smoking or abstaining during hospitalization. Subjects The subject sample is composed of 358 smokers who were hospitalized at the Miriam Hospital, a 230-bed general medical/surgical facility, and on 6 units at Rhode Island Hospital, a 719-bed facility, and who completed both baseline and discharge surveys as part of this study. The selected units in the larger hospital were matched to the illness characteristics of the target units in the smaller hospital. Both hospitals are academic teaching hospitals and had total indoor smoking bans at the time the study was conducted. Measures The baseline survey contained questions about demographic characteristics, comorbidity factors, smoking history, perceived health vulnerability, self-efficacy, and motivational factors. Adherence was defined as selfreport of abstaining from cigarettes during the hospital stay, as assessed on the discharge survey. Demographics and individual characteristics. Demographic characteristics assessed included age, race/ ethnicity, gender, and educational level. The participating hospitals’ management information services departments provided patient data on admitting and discharge diagnoses, length of hospital stay, and use of
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nicotine replacement therapy prior to and during hospitalization. Exposure to cessation interventions delivered by the physician or house staff was assessed on the discharge survey. Comorbidity Factors Mental Health Inventory (MHI). The Mental Health Inventory (MHI), a five-item subscale of the SF-36 [30], was used as a diagnostic measure of psychological distress and depression. The MHI subscale has been demonstrated to possess good reliability and validity [30,31]. Substance use. History of problem drinking was assessed by the CAGE, a four-item alcoholism screening questionnaire which has been shown to demonstrate good external validity [32,33]. In one validation study with a medical population, it was found that endorsing one or more items was a better predictor of alcoholism at follow-up than biochemical screens or physician diagnoses [33]. Recreational drug use was assessed by asking subjects if they had used any recreational drugs (e.g., marijuana, cocaine, heroin) in the previous 12 months. Smoking history. Standard NCI measures for smoking history were utilized; constructs assessed included number of quit attempts in the previous year and lifetime, efforts to quit smoking prior to hospitalization, longest period of abstinence, years of regular smoking, and smoking rate. One item from the Fagerstrom Tolerance Questionnaire [34], time from awakening to the first cigarette, was used to assess nicotine dependence. Psychometric studies suggest that responses to this single item are related to levels of nicotine intake [35–37]. Perceived vulnerability. Perceived vulnerability to smoking-related illness was assessed by four items asking subjects to rate how much smoking affects various aspects of their health [38]. Degree of perceived vulnerability was rated on a five-point Likert-type scale (from “not at all” to “very much”). Self-efficacy. Self-efficacy was measured by two items assessing confidence in one’s ability to quit smoking in the next month and in the next 6 months. These items were rated on 10-point Likert-type scales (from “not confident” to “extremely confident”). Difficulty in refraining from smoking during hospitalization was rated on a 5-point Likert-type scale (from “not at all” to “very much”). Motivational variables. The Stages of Change Scale [22] was used to classify active smokers into three categories regarding readiness to quit smoking: (1) Precontemplation included subjects who reported that they were not seriously thinking about quitting smoking in
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the next 6 months; (2) Contemplation included individuals who reported that they were seriously thinking about quitting smoking in the next 6 months; and (3) Preparation included subjects who were intending to quit smoking in the next month and who had tried to quit in the past year. Intentions to quit smoking were assessed with a question regarding plans to quit smoking posthospitalization; overall desire to quit smoking was assessed using a five point Likert-type scale (from “not at all” to “very much”). Facilitating factors/cues to action. A key facilitating factor for smoking cessation in the health care environment is physician’s advice to quit smoking. Receipt of provider’s advice to quit smoking at any point, and in the 12 months prior to hospitalization, was assessed via patient self-report. Procedures All hospitalized smokers were identified through the admissions process and were approached and asked to participate within 24 h of hospitalization. A comprehensive search for potential subjects was done daily using lists of new admissions based on smoking status, nursing assessments, and medical chart reviews on the target units, and nurse referrals. The primary inclusion criteria were: (1) ability to complete a pulmonary function test (required by the larger study from which the sample was drawn); (2) no myocardial infarction or thoracic or abdominal surgery; (3) smoking a minimum of five cigarettes per day on average and have smoked at least one cigarette in the 7 days prior to admission; (4) being alert and oriented; and (5) being English-speaking. Efforts to maximize enrollment included emphasizing that subjects were not being asked to change their smoking as part of the study. This facilitated recruitment of smokers who did not want to quit smoking, as well as those who did. Data collection. Subject assessments were made at baseline and at discharge. The initial baseline survey was conducted as a structured interview at the bedside. The discharge survey was prompted by the patient’s primary nurse, but was self-administered by the patient within 8 h prior to discharge. Response rate to the discharge survey was 63%. Data analysis. The dependent measure, adherence to the hospital smoke-free policy, was collected on the discharge survey. ANOVAs and x2 analyses were utilized to determine the influence of patient characteristics on adherence to the no-smoking policy. Stepwise logistic regression analyses were used to determine the overall contribution of characteristics found to predict adherence in the univariate analyses.
RESULTS
Demographics/Sample Description The average age of the subjects was 46 years. The majority of participants were white (91%) and married (55%); 55% were female. Twenty-one percent of the subjects had less than a 12th grade education, while 35% had a high school degree or equivalent. The average hospital stay was 5.3 days. Average number of years smoking was 27.8, and 68% of the participants were nicotine dependent. Sixty-three percent of the patients indicated that they were thinking of quitting after discharge. Analysis of demographic characteristics based on whether respondents to the baseline also completed the discharge survey indicated that white participants were more likely to complete the discharge survey than members of other ethnic groups (x2(3) 5 10.57; P # 0.01). Other demographic characteristics and smoking history were not significantly related to discharge survey response rate. Limited demographic information was available regarding the characteristics of individuals who refused to be in the larger trial; there were no differences in participation status based on gender, but treatment refusers were approximately 5 years older than participants (P , 0.0001). Univariate Analyses Demographics. Seventy-six percent of the subjects reported adhering to the smoke-free policy during their hospital stay. Of those who did not adhere to the policy, the average number of cigarettes smoked per day during the hospital stay was 6.2 (median 5 4.0). Longer hospital stays were associated with less adherence to the smoking policy (F (1,351) 5 11.34, P # 0.001) (see Table 1). Older patients were more adherent than younger patients (F (1,354) 5 18.66, P # 0.001), and married patients were more adherent than those who were never married, widowed, divorced, or separated (x2(2) 5 8.02; P 5 0.02). There were no significant differences in adherence based on gender or level of education. Comorbidity factors. Patients who reported using recreational drugs within the previous year were less likely to adhere to the smoke-free policy (x2(1) 5 27.26; P # 0.001). In addition, patients with evidence of alcohol-related problems, as indicated by a positive CAGE score, were less likely to be compliant (x2(1) 5 5.40, P # 0.02). No relationship was found between adherence and psychological distress or depression. Patients with circulatory disease as the primary diagnosis during hospitalization were more likely to adhere to the smoking policy than other diagnostic categories, while patients with digestive disorders were least likely to adhere (x2(5) 5 12.48, P # 0.03).
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TABLE 1 Univariate Analysis of Factors Associated with Adherence to Hospital Smoke-Free Policies Adherent (n 5 271)
Nonadherent (n 5 87)
P value
Demographics/comordibity factors Age (M years) Marital status (% married) Length of stay (M days) No recreational drug use in past year Positive CAGE score
48.1 57.9% 4.9 90.0% 42.1%
41.1 43.7% 6.8 66.7% 56.3%
0.001 0.02 0.001 0.001 0.02
Smoking history Years smoking (M ) Ever try to quit smoking 24 h 1 abstinence in past 7 days
29.0 80.8% 77.5%
24.0 67.8% 44.8%
0.001 0.01 0.001
Perceived vulnerability Current illness is caused by smoking Continued smoking could hurt your health Health compared to average smoker
51.5% 4.16 3.24
39.1% 3.87 3.05
0.04 0.04 0.09
Confidence variables Anticipate difficulty in refraining from smoking while hospitalized (M ) Confidence in ability to quit in 1 month (M ) Confidence in ability to quit in 6 months (M )
25.5% 4.91 6.23
54.5% 3.26 5.06
0.001 0.001 0.03
Motivational variables Stage (% in precontemplation) Plan to quit smoking posthospitalization Desire to quit
22.6% 64.9% 4.05
36.8% 46.0% 3.28
0.01 0.001 0.001
Facilitating Factors Advised by MD to quit
79.9%
20.1%
0.01
Smoking history. Patients with longer smoking histories were more likely to be adherent, covarying the effect of age (P , 0.001). Patients who had ever made a quit attempt were also more likely to be adherent to the smoking ban (x2(1) 5 6.41, P # 0.01). Further, patients who reported not having smoked cigarettes for at least 1 day in the 7 days prior to completion of the baseline survey were more likely to adhere to the smoke-free policy (x2(1) 5 33.18; P # 0.001) (see Table 1). Although some patients completed the baseline survey after 24 h of hospitalization, a separate analysis performed on subjects whose baseline surveys were conducted within 1 day of admission confirmed that there was a significant relationship between adherence and prehospitalization abstinence (n 5 152; x2(1) 5 7.69; P # 0.01). Neither time to first cigarette (as a proxy for nicotine dependence) nor the average number of cigarettes smoked before hospitalization differed between adherent and nonadherent patients. Use of smoking cessation aids prior to, or during, hospitalization was also not related to smoking status during hospitalization.
likely to be adherent (F (1,351) 5 4.81, P # 0.04), as were patients who agreed that continuing to smoke would harm their health (F (1,353) 5 4.15, P # 0.04). In addition, there was a trend for adherent smokers to rate their health more highly than nonadherent smokers (P 5 0.09). Other measures of perceived vulnerability were not significantly related to adherence.
Perceived vulnerability. Patients who reported that their current illness was caused by smoking were more
Facilitating factors. Seventy-six percent of the participants reported that their physicians spoke with
Self-efficacy. Patients who indicated that refraining from smoking would be difficult during hospitalization were less likely to adhere to hospital policy (x2(2) 5 39.29, P # 0.001). Confidence ratings in one’s ability to quit smoking in both 1 month and 6 months were also related to adherence (F (1,353) 5 19.60, P # 0.001; F (1,353) 5 9.10, P , 0.03, respectively). Motivational variables. Patients in the later stages of smoking cessation at baseline were more adherent to hospital policy (x2(2) 5 9.06, P # 0.01). Intention to quit smoking after discharge was related to increased adherence (x2(2) 5 14.01, P # 0.001), as was a general indication of desire to quit smoking (F (1,355) 5 22.27, P # 0.001).
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them about their smoking prior to hospitalization. Being advised to quit smoking by a physician prior to hospitalization was significantly related to adherence (x2(1) 5 7.51, P # 0.01). Physicians’ offers of smoking cessation consultation or prescriptions for nicotine replacement were not significantly related to adherence. Multivariate Model All factors significantly related to adherence in the univariate analyses were entered in a multivariate logistic regression equation, utilizing a stepwise method. The results revealed that several variables were retained as significant predictors of adherence to the smoke-free policy (see Table 2). Demographic variables which predicted adherence included older age and shorter length of stay; comorbidity factors included not participating in recreational drug use, while not having a positive CAGE score was marginally significant; smoking history variables included any abstinence days in the week prior to hospitalization, and confidence variables included low level of anticipated difficulty refraining from smoking while hospitalized and confidence in one’s ability to quit smoking in the next 30 days. The model x2 was significant (x2(6) 5 61.5; P # 0.0001) and the Hosmer–Lemeshow goodness of fit x2 measure indicated that the predicted model was similar to the observed data (x2(8) 5 7.39, P 5 0.50). DISCUSSION
Increasing adherence to hospital smoke-free policies offers many advantages, such as demonstrating commitment toward educating the public about the impact of smoking on health, facilitating healing and patient recovery, and enhancing safety regarding fire hazards [39]. Having an understanding of patient characteristics that are related to adherence will provide clearer
direction for health care providers wanting to intervene with smokers during hospitalization and will help to identify patients who might be at higher risk for nonadherence [40]. Several of the characteristics hypothesized to be related to adherence were significantly different between adherent and nonadherent patients. Of particular note were significant predictors of adherence retained in the multivariate model, including age and length of stay, such that increasing age and shorter hospital stays were associated with greater adherence. Ratings of one’s ability to refrain from smoking during hospitalization and rating of confidence in one’s ability to quit were also significant predictors of adherence. Therefore, in order to maximize the number of people refraining from smoking during hospitalization, it may be most fruitful to target supportive interventions during hospitalization to younger patients, those with longer hospital stays, and those with lower confidence ratings regarding cessation. Because it might be expected that these individuals will be more resistant to intervention during hospitalization, intervention approaches for patients at risk for nonadherence should target a range of motivational levels for smoking cessation. Comorbid characteristics were also associated with smoking policy adherence. Patients reporting the use of recreational drugs tended to be less adherent to the smoking policy. This may be due to the need to relieve the discomfort of withdrawal symptoms associated with the abuse of, and dependence on, illicit drugs such as narcotics. In addition, if drugs and tobacco are used as primary means of coping with pain and stress, this population may perceive smoking as necessary to cope with the stress of a hospital stay. Individual characteristics or the severity of illnesses related to drug use may also have contributed to nonadherence. For example, there may be unique characteristics of those willing to
TABLE 2 Factors Retained in Regression Model Predicting Adherence with Hospital Smoke-Free Policies
Variable demographics Age (M years) Length of stay (M days) Recreational drug use CAGE score Smoking history 24 h 1 abstinence in past 7 days Self-efficacy variables Anticipate difficulty in refraining from smoking while hospitalized Kind of to somewhat Somewhat to very hard Confidence in ability to quit in 1 month
B
SE
OR
P value
CI
0.033 20.081 21.055 20.539
0.015 0.032 0.407 0.320
1.030 0.922 0.348 0.583
0.02 0.01 0.01 0.09
1.00, 0.87, 0.16, .031,
1.209
0.325
3.350
0.001
1.77, 6.34
21.410 21.448 0.127
0.456 0.463 0.059
0.243 0.235 1.140
0.002 0.002 0.03
0.10, 0.60 0.10, 0.58 1.01, 1.27
1.06 0.98 0.78 1.09
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admit to a socially unacceptable behavior, which may distinguish patients who are more likely to behave in an autonomous, sometimes less compliant manner. Although the reasons for the relationship are only speculated here, special attention to the smoking behavior of patients reporting drug use and alcohol problems seems appropriate for health care specialists [41]. In particular, efforts to minimize withdrawal may increase the likelihood of adherence among substance abusers. Although the univariate analyses indicated that perceived vulnerability predicted adherence, this relationship was not maintained in the multivariate analyses. However, self-efficacy variables and recent abstinence were important predictors of adherence in both the univariate and the multivariate analyses. In contrast, trying to quit prior to hospitalization was not related to adherence. Acute medical illnesses may provide an opportunity for patients to “try out” cessation, without actively trying to quit, thus increasing both their confidence and their ability to abstain throughout the hospital stay. Physicians play an important role in helping patients start thinking about smoking cessation. It may be more important for health care providers to link the risks of smoking to the impact that smoking can have on the individual’s health, typical of the discussions physicians have with patients concerning coronary disease, a group among which abstinence rates have traditionally been quite high [4,42]. While discussing smoking cessation with a physician prior to hospitalization was not found to be related to increased adherence in the multivariate analyses, the time frame in which the advice was provided to patients could not be determined. Over 80% of the patients reported that their physician had talked with them about their smoking prior to hospitalization or during the hospital stay. These results suggest that physicians are doing a very good job in addressing smoking with their patients, particularly in the course of outpatient care. Stage of change was not found to predict adherence in the multivariate model. However, it is not clear if smokers in the later stages would be more or less responsive to smoking interventions delivered during hospitalization. Further, it is unclear whether the stages of change algorithm, which has not been well studied among hospitalized populations, adequately assesses motivation among a hospitalized sample for whom environmental restrictions may artifically force patients into a more advanced stage of readiness. The contribution of the stage model to hospital-based smoking interventions should be assessed in longitudinal trials. It should be noted that over 70% of the hospitalized smokers refrained from smoking during their hospital stay. This level of adherence is excellent, but perhaps not surprising given that both participating hospitals
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did not allow smoking at all inside the hospital buildings. For these adherent smokers, hospitalization offered an important opportunity to have a successful experience with abstinence. Intervention efforts should be targeted at discharge and posthospitalization in order to build these smokers’ motivation for and skills related to making a successful long-term quit attempt. It is also interesting that, despite this relatively high rate of adherence to the smoking ban, 30% of hospitalized smokers smoked during their hospital stay. Objective data about the situational or environmental factors (e.g., location of room, type of unit) that facilitated violation of the ban were not available. However, anecdotal reports from study staff suggested that these smokers often smoked in the bathrooms and that family members often supplied cigarettes during the hospital stay. Some patients did receive permission from their physicians to smoke outside of the hospital entrances. Limitations of the present study should be noted. First, the sample is based on only those participants in a larger study who completed both the baseline and the discharge surveys, and thus response bias cannot be ruled out. Second, the dependent variable, adherence to the hospital smoking policy, is based on self-report of smoking status during hospitalization. It is possible that some participants did not report their smoking during hospitalization accurately. Recent reports suggest that the false negative rate associated with selfreport of smoking status is quite low [43]. In addition, the study was presented as quite separate from the hospital smoking policy, and the outcome data was confidentially collected at discharge rather than during the hospital stay, which may have reduced the likelihood of a social desirability bias. This study extends the existing literature by elucidating the factors that predict adherence to smoking bans in the hospital setting. In particular, in light of the limited resources that are often available for smoking cessation interventions, a better understanding of the predictors of adherence with smoking policies may be helpful to providers in better targetting available resources, drawing on recent stepped care models proposed for delivery of smoking interventions [28,29]. Understanding the many factors that can affect a patient’s ability to refrain from smoking may help to identify patients who are most likely to remain smoke-free during hospitalization. Such patients may be responsive to brief messages to abstain, as well as to positive reinforcement for doing so. Patients who successfully refrain from smoking during the hospital stay may benefit from posthospitalization follow-up to build on their initial success. Approaching patients who are less likely to be adherent regarding smoking cessation while hospitalized may require different, or more labor-intensive approaches. For example, these patients may benefit from motivational and behavioral counseling, as well as
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from pharmacologic treatment to help them get through their hospital stay smoke free [10,44]. In addition, patients who were nonadherent with the smoking ban are more likely to have other barriers to smoking cessation (e.g., withdrawal from alcohol or other substances) which could be addressed as part of efforts to impact on their ability both to adhere to the smoking ban during hospitalization and to quit at some future time. Encouraging smokers to remain smoke free during a time of intensified awareness of health issues could prove to be a valuable means of promoting smoking cessation; identifying characteristics associated with adherence to hospital smoke-free policies should be helpful toward that end. ACKNOWLEDGMENTS The authors acknowledge the contributions of Nancy Farrell, Elena Morgans, and Carol Carlisle for data collection and Alicia Fontes for data analysis. REFERENCES 1. Abrams DB, Emmons KM, Niaura RS, Goldstein MG, Sherman CE. Tobacco dependence. In: Nathan PE, Langenbucher JW, McCrady BS, Frankenstein W, editors. Annual review of addictions and treatment & research, Vol. 7. New York: Pergamon, 1991:391–436. 2. Pederson L, Baskerville JC, Wanklin J. Multivariate statistical models for predicting smoking behavior following physician advice to quit. Prev Med 1982;11:536–49. 3. Orleans CT, Rotberg HL, Quade D, et al. A hospital quit-smoking consult service: clinical report and intervention guidelines. Prev Med 1990;19:198–212. 4. Ockene JK, Aney J, Goldberg RJ, Klar JM, Williams JW. Physician-delivered interventions for smoking cessation: Strategies for increasing effectiveness. Prev Med 1987;61:723–733. 5. British Thoracic Society. Comparison of four methods of smoking withdrawal in patients with smoking related diseases. Br Med J 1983;286:595–7. 6. Raw M. Persuading people to stop smoking. Behav Res Ther 1986;14:97–101. 7. Burt A, Illingworht D, Shaw TRD, Thornley P, White P, Turner R. Stopping smoking after myocardial infarction. Lancet 1974; I:304–6. 8. Baile WF, Bigelow GE, Gottlieb SH, et al. Rapid resumption of cigarette smoking following myocardial infarction: inverse relation to MI severity. Addictive Behav 1982;7:373–80. 9. Cutter G, Oberman MK, Kimmerling R, et al. The natural history of smoking cessation among patients undergoing coronary arteriography. J Cardiopulm Rehab 1985;5:332–40. 10. Scott R, Lamparski D. Variables related to long-term smoking status following cardiac events. Addictive Behav 1985;10: 257–64. 11. Hurt RD, Dale LC, McClain FL, et al. A comprehensive model for the treatment of nicotine dependence in a medical setting. Med Clin N Am 1992;76(2):495–514. 12. Stevens VJ, Glasgow RE, Hollis JF, Lichtenstein E, Vogt TM. A smoking cessation intervention for hospital patients. Med Care 1993;31:65–72. 13. Taylor CB, Miller NH, Herman S, et al. A nurse-managed smoking cessation program for hospitalized smokers. Am J Public Health 1996;86:1557–60.
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