Edited by: Peter James Kelly, University of Wollongong, Australia
Reviewed by: Suwa Goden Goar, University of Jos, Nigeria; Martin Zack, University of Toronto, Canada; Saeed Ahmed, Rutland Regional Medical Center, United States
This article was submitted to Addictive Disorders, a section of the journal Frontiers in Psychiatry
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
The prevalence of mental health conditions is higher in cigarette smokers than nonsmokers. However, those with diagnosed mental health disorders are understudied within general inpatient hospital settings. This study seeks to evaluate how having a mental health diagnosis influences response to a brief opt-out inpatient tobacco treatment intervention.
Data included 4,153 admitted patients who completed a tobacco treatment visit. Post-discharge self-reported abstinence was obtained via response to an automated call 1-month after discharge. Mental health co-morbidities were assessed by reviewing electronic medical records. Logistic regression was used to assess associations between having a mental health diagnosis and patients' smoking history, interest in quitting smoking, and post-discharge abstinence.
Overall 34.1% of patients were diagnosed with mental health disorders, most commonly depression or substance use disorders. Patients with a diagnosed mental health disorder were more likely to report a history of long-term heavy smoking and were less likely to express an interesting in remaining abstinent from smoking after hospitalization. An intent-to-treat analysis using logistic regression analysis found lower rates of self-reported smoking abstinence in those with a mental health disorder compared to those without (9 vs. 13.2%,
Patients with a history of mental health diagnoses, such as depression or substance use disorders, was associated with lower rates of smoking abstinence in patients after hospitalization. Hospital based opt-out smoking cessation programs have shown to be generally effective and efficient. However, certain subpopulations may require tailored intervention in order to improve treatment outcomes. Future research is needed to develop brief, effective tobacco treatment for hospital patients with comorbid mental health diagnoses.
According to the U.S. Department of Health and Human Services, 14 out of every 100 U.S. adults smokes cigarettes (
One initiative to address hospital-based smoking cessation rates at a population level is that of brief opportunistic opt-out interventions where treatment is provided as standard procedure for all patients who smoke rather than by patient request (
The present study aims to evaluate the effectiveness of a brief tobacco treatment intervention among a large, hospitalized sample treated by the Tobacco Treatment Program (TTP) at the Medical University of South Carolina. Results from these analyses will provide data regarding the adequacy of services delivered for this population and suggest future directions for improving outcomes among priority populations.
Inpatient tobacco treatment services at the hospital are provided via an opt-out system whereby counselors identify and provide services to all patients admitted to the hospital with a reported history of tobacco use. Interventions include a structured assessment interview, brief counseling, and pending smoking cessation pharmacotherapy (e.g., nicotine replacement therapy) orders for physicians to facilitate while inpatient and at discharge. Bedside counseling includes motivational interviewing and practical counseling strategies. Patients are then enrolled in an automated, interactive voice recognition telephone protocol, which calls them at 3, 14, and 30 days following discharge. Smoking status is assessed at these calls, and patients are offered a referral to outpatient counseling or the South Carolina Quitline. Visit notes are recorded in the electronic health record (Epic). This program has demonstrated clinical efficacy in improving treatment outcomes, reducing readmissions, and cutting costs (
All data were collected as part of routine treatment of general hospital patients within the TTP at Medical University of South Carolina (
Chart data were retrieved from patients who were admitted between July 2014 and December 2019. Patients who endorsed cigarette smoking, agreed to the bedside intervention, and accepted enrollment into the interactive voice recognition system were included in the present analysis. Of those identified, patient medical record numbers were used to obtain data on history of mental health conditions. Follow-up data were collected through review of patients' responses to the automated telephone system 30-days following discharge.
Patients' age, race, and biological sex were obtained from the electronic health record note (TTP encounter) during admission. History of mental health conditions on day of admission was obtained from the electronic health record (i.e., “problem list”) via an internal data request. Mental health diagnoses were then grouped into one of the following broad diagnostic categories: Depression, Anxiety, PTSD, chronic pain, childhood developmental disorder, serious mental illness, personality disorder, alcohol use disorder, or substance use disorder. Serious mental illness was defined as including the following diagnostic categories (1) schizophrenia, (2) bipolar disorder, (3) severe depression with psychotic features, (4) eating disorders.
TTP clinicians asked patients to report on how long they had been smoking, if they smoked daily, how many cigarettes were smoked per day, how soon they smoked after waking, if they use any other tobacco product, and if they live with another person who smokes. Patients were also asked how many times, if any, they tried to quit smoking during the past year. Importance to quit was measured by asking “How important is quitting smoking to you on a scale of 1–5, with 5 being the most important?” Confidence in quitting was measured by asking “How confident are you that you will be able to remain smoke free on a scale of 1–5, with 5 being the most confident?” Finally, patients were asked if they had requested and received a smoking cessation medication during hospitalization.
The automated telephone system contacted patients 30-days following discharge. Patients were coded “quit” if they endorsed not smoking for the 7-days prior to the phone call.
Logistic regressions, utilizing an intent-to-treat approach [ITT; (
Chart review identified 4,153 patients who endorsed current cigarette smoking upon admission and completed an interview with the TTP while inpatient. Patient demographics are presented in
Patient demographics and smoking characteristics.
| Age | 49.97 | 14.81 |
| Male | 2,223 | 53.5% |
| Female | 1,929 | 46.4% |
| White | 2,238 | 53.9% |
| Black/African American | 1,283 | 30.9% |
| Hispanic | 51 | 1.2% |
| American Indian/Alaska native | 17 | <1% |
| Asian | 14 | <1% |
| Mixed/ Other | 9 | <1% |
| Daily smoking | 3,320 | 79.9% |
| Cigarettes per day | 15.7 | 11.07 |
| Years smoking | 29.06 | 15.50 |
| <5 min | 1,900 | 45.8% |
| 6–30 min | 484 | 11.7% |
| 31–60 min | 223 | 5.4% |
| >61 min | 381 | 9.2% |
Patient mental health diagnoses can be seen in
Patient mental health diagnoses.
| All mental health | 1,417 | 34.1% |
| Depression | 460 | 11.1% |
| Anxiety | 335 | 8.1% |
| Chronic pain | 336 | 8.1% |
| PTSD | 58 | 1.4% |
| Alcohol use disorder | 447 | 10.8% |
| Substance use disorder | 353 | 8.5% |
| Serious mental illness | 173 | 4.2% |
| Personality disorder | 18 | <1% |
| Childhood developmental disorder | 16 | <1% |
Logistic regression analysis was utilized to investigate the effect of the presence of a mental health diagnosis on 7-day self-reported abstinence at 30-days post-discharge (ITT). Mental health diagnosis was found to significantly decrease the odds of abstinence at follow-up (B = 0.431, SE = 0.109, Wald = 15.69,
A second regression tested the effect of total number of mental health diagnoses on cigarettes per day at the time of intervention. Results of this analysis were also significant (B = 0.653, SE = 0.206,
Finally, a series of Pearson correlations were conducted in order to characterize variables associated with smoking cessation with mental health problems. Results of these correlations can be seen in
Mental health diagnosis and quit attempt variables.
| 1. Total mental health diagnoses | 4,153 | 0.53 | 0.90 | — | ||||
| 2. Number of quit attempts in the past year | 3,923 | 1.44 | 2.96 | −0.002 | — | |||
| 3. Importance to quit | 4,128 | 3.84 | 1.33 | −0.04 |
0.15 |
— | ||
| 4. Self-efficacy to quit | 4,128 | 3.56 | 1.29 | −0.06 |
0.13 |
0.75 |
— | |
| 5. Last quit duration | 3,608 | 93.71 | 172.53 | −0.009 | 0.22 |
0.17 |
0.21 |
— |
Importance to quit and self-efficacy to quit by mental health diagnosis category.
| Those without mental health diagnoses | 2,736 | 3.58 (1.31) | 3.85 (1.28) |
| Chronic pain | 336 | 3.44 (1.35) | 3.74 (1.38) |
| Anxiety | 335 | 3.36 (1.33) | 3.70 (1.37) |
| Alcohol use disorder | 447 | 3.36 (1.31) | 3.59 (1.42) |
| PTSD | 58 | 3.32 (1.35) | 3.62 (1.41) |
| Childhood dev. disorder | 16 | 3.32 (1.29) | 3.45 (1.41) |
| Depression | 460 | 3.30 (1.33) | 3.63 (1.40) |
| Substance use disorder | 353 | 3.20 (1.32) | 3.45 (1.40) |
| SMI | 173 | 3.06 (1.36) | 3.30 (1.50) |
| Personality disorder | 18 | 2.80 (1.29) | 3.17 (1.43) |
This study analyzes the effect of mental health diagnoses on outcomes of a brief, opt-out tobacco treatment intervention among a general hospitalized population. This study has several strengths: (1) the results reflect data on a relatively large number of patients treated within the opt-out program, (2) data reflect the effectiveness of an established and practical intervention, (3) data reflect an important population in need of additional research. Rates of mental health conditions, such as depression and substance use disorders, were consistent with general inpatient hospital mental health diagnosis prevalence (
There are several limitations of the present analysis that should be taken into consideration. No non-treatment control group was used for reference, which limits interpretations of tobacco cessation behavior in those with psychopathology with respect to baseline trends. Additionally, the large amount of missing data from follow-up may indicate responder bias.
While brief hospital-based opt-out interventions have been shown to be effective and capable of reaching a large proportion of hospital patients, it is important to identify subgroups for whom more tailored treatment would be beneficial. Those with mental health conditions represent a large subset of general hospital patients, report heavier daily smoking, and are less likely to report abstinence following standard intervention. Tobacco treatment programs should work to develop and test treatments which better identify, characterize, and serve these patients.
The original contributions presented in the study are included in the article/supplementary materials, further inquiries can be directed to the corresponding author.
The studies involving human participants were reviewed and approved by IRB-II - Medical University of South Carolina; ID - Pro00105610. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
BS contributed conceptualization, methodology, data analysis writing–original draft, and writing–review and editing. AR and KC contributed methodology and writing–review and editing. AP, MF, and SS contributed to writing–review and editing. BT: conceptualization, methodology, and writing-review and editing. All authors contributed to the article and approved the submitted version.
AR, BS, and BT report funding from the following NCI grants: R01 CA235697, R01 CA261232, R01 CA207229, and K07CA214839. AP is funded though NIH Institutional Postdoctoral Training Grant NIH-T32-HL144470.
BT and KC have both served as paid expert witnesses in litigation against cigarette manufacturers. BT also has received payment from Pfizer Inc., to serve on an Advisory Board exploring the role of e-cigarettes on smoking behavior. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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