Abstract
SIGNIFICANCE:
Although it is a requirement that tobacco treatment is offered to cigarette smokers undergoing low-dose computed tomographic lung cancer screening (LCS), not all smokers engage in treatment. To understand the barriers to tobacco treatment in this setting, we evaluated predictors of attrition in a smoking cessation trial among individuals undergoing LCS.
METHODS:
Prior to LCS, 926 participants, 50–80 years old, completed the baseline (T0) phone assessment, including demographic, clinical, tobacco, and psychological characteristics. Following LCS and receipt of the results, participants completed the pre-randomization (T1) assessment.
RESULTS:
At the T1 assessment, 735 (79%) participants were retained and 191 (21%) dropped out. In multivariable analyses, attrition was higher among those who: smoked >1 pack per day (OR=1.44, CI 1.01, 2.06) or had undergone their first (vs. annual) LCS scan (OR=1.70, CI 1.20, 2.42). Attrition was lower among those with: more education (associates (OR=.67, CI=.46, .98) or bachelorʼs degree (OR=.56, CI .35, .91) vs. high school/GED), some (vs. none/a little) worry about lung cancer (OR=.60, CI .39, .92), or a screening result that was benign (OR=.57, CI .39, .82) or probably benign (OR=.38, CI .16, .90) vs. negative.
CONCLUSIONS:
This study illuminated several LCS-related factors that contributed to trial attrition. Increasing tobacco treatment in this setting will require targeted strategies for those who report little lung cancer worry, are undergoing their first LCS exam, and/or who have a negative LCS result. Addressing attrition and reducing barriers to tobacco treatment will increase the likelihood of cessation, thereby reducing the risk of developing lung cancer.
Keywords: smoking cessation, trial attrition, clinical trial, low-dose computed tomographic lung cancer screening
Introduction
Annual low-dose computed tomographic lung cancer screening (LCS) is recommended for individuals who are at high risk for lung cancer, more than half of whom currently smoke cigarettes.1–3 The recommendations were informed by the National Lung Screening Trial, which found that undergoing three annual rounds of LCS using low-dose CT vs. chest radiography resulted in a 20% relative reduction in lung cancer mortality.4,5 Both the U.S. Preventive Services Task Force (USPSTF) 2013 guidelines and the expanded 2021 guidelines recommend screening for individuals at high-risk for lung cancer, which is based on age and pack-years. However, maximum benefit from LCS will only be achieved if individuals who smoke receive tobacco treatment.6 Due to the importance of cessation in this context, the Centers for Medicare and Medicaid Services (CMS) mandates that cessation assistance is available to all individuals undergoing LCS who currently smoke.7
The NCIʼs Smoking Cessation at Lung Examination (SCALE) collaboration includes eight ongoing randomized smoking cessation trials, each assessing various intervention methods in this setting. The delivery of evidence-based tobacco treatment in conjunction with LCS may serve as a “teachable moment” in which individuals may be especially amenable to receiving support for quitting.8–10 One of the SCALE trials, the Lung Screening, Tobacco, and Health (LSTH) trial, is comparing intensive telephone counseling with nicotine replacement therapy vs. usual care.11 In an effort to leverage the teachable moment, the LSTH trial initiates tobacco treatment shortly following receipt of the LCS result. This period may be particularly important following an abnormal result, during which the motivation to quit smoking may be enhanced, especially when cessation assistance is provided.12
Attrition is a challenge in all tobacco treatment programs.13 Prior studies have identified sociodemographic (e.g., younger age, lower education) and tobacco-related (e.g., high nicotine dependence, low motivation to quit) characteristics that are associated with dropout.14–18 We are unaware of prior cessation interventions conducted in the LCS setting that have examined predictors of attrition. Given the low rate of engagement in tobacco treatment following LCS,19–22we conducted an exploratory analysis of demographic, tobacco, screening, and psychological predictors of attrition in an ongoing smoking cessation trial among individuals undergoing LCS.
Methods
Overview
The analytic sample (N=926) included individuals enrolled from May 2017-February 2020. The study setting and recruitment procedures were previously described in detail.11 All data were collected prior to randomization.
Participants
Baseline (T0) inclusion criteria were based on both the 2013 USPSTF4 and the National Comprehensive Cancer Network (NCCN) guidelines23 for LCS. Eligible individuals were asymptomatic and in either NCCN Group 1 (55–80 years old, 30+ pack-year smoking history) or NCCN Group 2 (50–80 years, 20+ pack-years, with one additional risk factor, including a personal history of cancer or lung disease, family history of lung cancer, radon exposure, or occupational exposure to carcinogens). Additional study criteria included: smoked within the past 7 days, registered for (but not yet completed) LCS screening, and English or Spanish-speaking. Prior LCS, prior or current cessation treatment, readiness to quit, psychiatric conditions, and access to a phone were not exclusion criteria.
Post-screening follow-up (T1) inclusion criteria included: 1) completion of the LCS exam and receipt of the exam results, and 2) smoked within the past 7 days.
Procedure
Baseline Enrollment Interview (T0).
After scheduling the LCS appointment, the site coordinator determined trial eligibility, obtained verbal consent, and conducted the 10-minute baseline (pre-LCS) telephone interview (Tables 1 and 2). Next, research staff obtained written consent and medical release forms by mail or email (Figure 1).
Table 1.
Baseline Demographic and Clinical Characteristics
| Total N = 926 n (%) | Retained at T1 N = 735 n (%) | Lost to Follow Up at T1 N = 191 n (%) | P-Value | |
|---|---|---|---|---|
| Age (M, SD) | M=63.4 (5.8) | M=63.7 (5.9) | M=62.0 (5.3) | (t) P=0.00 |
| 50 – 63 Years | 498 (53.8) | 376 (51.2) | 122 (63.9) | (χ) P=0.00 |
| 64 – 80 Years | 428 (46.2) | 359 (48.8) | 69 (36.1) | |
| Gender | (χ) P=0.10 | |||
| Female | 490 (52.9) | 356 (48.4) | 80 (41.9) | |
| Race | (χ) P=0.16 | |||
| White | 830 (90.7) | 659 (89.9) | 171 (94.0) | |
| Black | 57 (6.2) | 48 (6.5) | 9 (4.9) | |
| Other | 28 (3.1) | 26 (3.5) | 2 (1.1) | |
| Missing | 11 | 2 | 9 | |
| Ethnicity | (χ) P=0.00 | |||
| Hispanic/Latino/Spanish Origin | 81 (8.9) | 49 (6.7) | 32 (17.3) | |
| Missing | 12 | 6 | 6 | |
| Marital Status | (χ) P=0.68 | |||
| Married or Living as Married | 469 (50.8) | 375 (51.2) | 96 (50.5) | |
| Missing | 3 | 2 | 1 | |
| Education Level | (χ) P=0.00 | |||
| High School/GED or Less | 359 (39.0) | 264 (36.2) | 95 (50.0) | |
| Associate’s Degree/Vocational School | 355 (38.6) | 289 (39.6) | 66 (34.7) | |
| Bachelor’s Degree or More | 206 (22.4) | 177 (24.2) | 29 (15.3) | |
| Missing | 6 | 5 | 1 | |
| Lung Cancer Screening Result * | (χ) P=0.00 | |||
| Lung-RADS 1/1S | 291 (31.5) | 209 (28.5) | 82 (42.9) | |
| Lung-RADS 2/2S | 540 (58.4) | 447 (60.9) | 93 (48.7) | |
| Lung-RADS 3/3S | 52 (5.6) | 45 (6.1) | 7 (3.7) | |
| Lung-RADS 4/4A/4B/4X | 42 (4.5) | 33 (4.5) | 9 (4.7) | |
| Missing | 1 | 1 | 0 | |
| Annual vs. Baseline Screening | (χ) P=0.00 | |||
| Baseline | 403 (43.6) | 295 (40.2) | 108 (56.5) | |
| Annual | 522 (56.4) | 439 (59.8) | 83 (43.5) | |
| Missing | 1 | 1 | 0 | |
| Number of Tobacco-Related Comorbid Conditions ** | (χ) P=0.02 | |||
| 0 | 439 (62.8) | 373 (61.0) | 66 (75.0) | |
| 1 | 191 (27.3) | 178 (29.1) | 13 (14.8) | |
| 2+ | 69 (9.9) | 60 (9.8) | 9 (10.2) | |
| Missing | 227 | 124 | 103 | |
| Site *** | (χ) P=.00 | |||
| Site 1 (DC) | 29 (3.1) | 29 (3.9) | 0 (0) | |
| Site 2 (MA) | 399 (43.1) | 348 (47.3) | 51 (26.7) | |
| Site 3 (FL) | 119 (12.9) | 72 (9.8) | 47 (24.6) | |
| Site 4 (CT) | 44 (4.8) | 40 (5.4) | 4 (2.1) | |
| Site 5 (NJ) | 98 (10.6) | 71 (9.7) | 27 (14.1) | |
| Site 6 (IA, IL) | 192 (20.7) | 139 (18.9) | 53 (27.7) | |
| Site 7 (MD) | 36 (3.9) | 28 (3.8) | 8 (4.2) | |
| Site 8 (MD) | 9 (1.0) | 8 (1.1) | 1 (0.5) |
LR1 (negative), LR2 (benign appearance or behavior), LR3 (probably benign), LR4 (4A/4B/4X) (suspicious).23
Although the number of comorbid conditions was significant at the univariate level, this variable was not included in the multivariate models due to the substantial amount of missing data.
Small cell sizes.
Table 2.
Baseline Tobacco and Psychological Characteristics
| Total N = 926 n (%) | Retained at T1 N = 735 n (%) | Lost to Follow-Up at T1 N = 191 n (%) | P-Value (χ) | |
|---|---|---|---|---|
| Cigarettes per day (M, SD) | 18.48 (8.7) | 18.34 (8.9) | 19.01 (8.1) | (t) P=0.34 |
| < 20 | 384 (41.6) | 318 (43.4) | 66 (34.6) | (χ) P=0.03 |
| 20+ | 540 (58.4) | 415 (56.6) | 125 (65.4) | |
| Missing | 2 | 2 | 0 | |
| Pack Years (M, SD) | M=47.8 (16.6) | M=48.0 (17.1) | M=46.9 (14.8) | (t) P=0.46 |
| 20 – 39 | 257 (27.8) | 209 (28.5) | 48 (25.3) | (χ) P=0.06 |
| 40 – 49 | 374 (40.5) | 283 (38.6) | 91 (47.9) | |
| 50+ | 292 (31.6) | 241 (32.9) | 51 (26.8) | |
| Missing | 3 | 2 | 1 | |
| Time to First Cigarette | (χ) P=0.33 | |||
| Within 5 minutes | 255 (27.7) | 199 (27.2) | 56 (29.6) | |
| 6 to 30 minutes | 410 (44.5) | 331 (45.2) | 79 (41.8) | |
| 31 to 60 minutes | 157 (17.0) | 129 (17.6) | 28 (14.8) | |
| After 60 minutes | 99 (10.7) | 73 (10.0) | 26 (13.8) | |
| Refused/Missing | 5 | 3 | 2 | |
| Readiness to Quit (M, SD) | M=5.78 (1.7) | M=5.82 (1.7) | M=5.63 (1.8) | (χ) P=0.15 |
| Not Considering (1–5) | 510 (55.2) | 393 (53.6) | 117 (61.3) | (t) P=0.18 |
| Next 6 Months (6) | 127 (13.7) | 106 (14.5) | 21 (11.0) | |
| Next 30 Days (7–10) | 287 (31.1) | 234 (31.9) | 53 (27.7) | |
| Missing | 2 | 2 | 0 | |
|
Motivation to Quit (M, SD) (1=low, 10=high) |
M=6.50 (2.3) | M=6.50 (2.3) | M=6.48 (2.4) | (t) P=0.90 |
| 1 – 5 | 365 (39.9) | 288 (39.7) | 77 (40.7) | (χ) P=0.94 |
| 6 – 7 | 216 (23.6) | 171 (23.6) | 45 (23.8) | |
| 8 – 10 | 334 (36.5) | 267 (36.8) | 67 (35.4) | |
| Refused/Missing | 11 | 9 | 2 | |
|
Confidence in Quitting (1=low, 10=high) |
M=5.85 (2.4) | M=5.87 (2.4) | M=5.76 (2.5) | (t) P=0.60 |
| 1 – 4 | 226 (24.9) | 175 (24.2) | 51 (27.4) | (χ) P=0.67 |
| 5 – 7 | 427 (47.0) | 342 (47.4) | 85 (45.7) | |
| 8 – 10 | 255 (28.1) | 205 (28.4) | 50 (26.9) | |
| Refused/Missing | 18 | 13 | 5 | |
| Comparative Risk for Lung Cancer | (χ) P=0.37 | |||
| Lower Risk | 119 (13.5) | 100 (14.2) | 19 (10.9) | |
| About the same | 416 (47.3) | 336 (47.6) | 80 (46.0) | |
| Higher Risk | 345 (39.2) | 270 (38.2) | 75 (43.1) | |
| Refused | 46 | 29 | 17 | |
| Worry about Lung Cancer | (χ) P=0.09 | |||
| No/Little Worry | 238 (25.9) | 179 (24.6) | 59 (31.2) | |
| Somewhat | 352 (38.3) | 291 (39.9) | 61 (32.3) | |
| Extremely | 328 (35.7) | 259 (35.5) | 69 (36.5) | |
| Refused | 8 | 6 | 2 | |
| Pain or Discomfort | (χ) P=0.09 | |||
| None/Moderate | 830 (89.7) | 665 (90.6) | 165 (86.4) | |
| Extreme | 95 (10.3) | 69 (9.4) | 26 (13.6) | |
| Refused | 1 | 1 | 0 | |
| Anxiety or Depression | (χ) P=0.06 | |||
| None/Moderate | 808 (88.4) | 650 (89.4) | 158 (84.5) | |
| Extreme | 106 (11.6) | 77 (10.6) | 29 (15.5) | |
| Refused/Missing | 12 | 8 | 4 | |
| Health Index Scale | ||||
| (0=worst health, 100=best) | M=69.88 (18.8) | M=70.37 (18.3) | M=67.96 (20.6) | (t) P=0.12 |
| 0 – 64 | 296 (32.6) | 228 (31.5) | 68 (36.8) | (χ) P=0.45 |
| 65 – 79 | 248 (27.3) | 200 (27.7) | 48 (25.9) | |
| 80 – 100 | 364 (40.1) | 295 (40.8) | 69 (37.3) | |
| Refused/Missing | 18 | 12 | 5 |
Figure 1.
Flow Chart of Study Attrition from Approach to the T1 Assessment
Post-Screening Interview (T1).
Research staff called participants up to 10 times to complete the 20-minute T1 phone interview (median=25 days post-T0). At the conclusion of the interview, participants were randomly assigned to study arm. Participants did not receive compensation following either the T0 or T1 assessments, but were compensated for completing subsequent assessments.
Measures (Tables 1 and 2).
Demographic & Clinical Variables.
We collected self-report data on age, gender, race, ethnicity, marital status, and education. We abstracted EMR information on tobacco-related comorbid conditions, LCS history (baseline vs. annual scan) and Lung-RADS® (LR) screening results: LR1 (negative), LR2 (benign appearance or behavior), LR3 (probably benign), LR4 (4A/4B/4X) (suspicious).24
Smoking-Related Variables.
We assessed cigarettes per day (CPD), pack-years, nicotine dependence,25 and readiness, confidence, and motivation to quit smoking on a 10-point scale26,27 (Table 2).
Psychological Variables.
We measured perceived risk of lung cancer compared to other people who smoke,9 worry about lung cancer,9 pain/discomfort, anxiety/depression,28,29 and overall health (0 to 100).28
Data Analyses
We conducted chi-square tests and t-tests to compare those retained vs. lost to follow-up at T1 (Tables 1 and 2). Variables associated with the outcome (p≤.10) were included in the multivariable logistic regression model to assess the significant independent predictors of T1 attrition, displaying odds ratios and 95% confidence intervals (Table 3). We excluded ethnicity and site (due to small cell sizes) and pack-years (due to collinearity with CPD). We used SPSS v.26.0 to conduct the analyses.
Table 3.
Logistic Regression Model Predicting Attrition at the Post-Lung Screening Interview (N = 899)
| OR [95% CI] | |
|---|---|
| Age | |
| <63 (ref) | |
| 64+ | .75 [.53, 1.08] |
| Education | |
| HS/GED or less (ref) | |
| Assoc./Vocational | .67 [.46, .98 |
| Bachelors or more | .56 [.35, .91] |
| Gender | |
| Male (ref) | |
| Female | 1.24 [.87, 1.76] |
| Cigarettes per Day | |
| <20 (ref) | |
| 20+ | 1.44 [1.01, 2.06] |
| Lung-RADS | |
| Lung-RADS 1 (ref) | |
| Lung-RADS 2 | .57 [.39, .82] |
| Lung-RADS 3 | .38 [.16, .90] |
| Lung-RADS 4 | .75 [.33, 1.68] |
| Screening History | |
| Annual (ref) | |
| Baseline | 1.70 [1.20, 2.42] |
| Worry | |
| No to Little Worry (ref) | |
| Somewhat Worried | .60 [.39, .92] |
| Extremely Worried | .74 [.49, 1.14] |
| Pain | |
| No/Moderate Pain (ref) | |
| Extreme Pain | 1.28 [.76, 2.15] |
| Anxiety/Depression | |
| Low/Moderate Depression (ref) | |
| Extreme Depression | 1.21 [.74, 2.00] |
Notes:
Variables included in the analysis: age, education, gender, CPD, Lung-RADS, screening history, worry about lung cancer, pain, anxiety/depression. Ethnicity and screening site were excluded due to small cell sizes. Bolded odds ratios and 95% confidence intervals indicate significant findings.
Definition of LungRads: LR1 (negative), LR2 (benign appearance or behavior), LR3 (probably benign), LR4 (4A/4B/4X) (suspicious).23
Results
At the T1 assessment, 79% (N=735) completed the post-LCS interview and 21% (N=191) actively dropped out (N=144) or were never reached (N=47). In the univariate analyses, participants who dropped out were significantly: younger (<64 years), more likely to be Hispanic, less educated (high school/GED or less), less likely to have comorbid conditions, more likely to have a LR1 result, and more likely to smoke > 20 CPD (Tables 1 and 2).
The logistic regression analysis predicting attrition at T1 (Table 3) revealed that participants who dropped out were heavier smokers (20+ CPD: OR=1.44, CI 1.01, 2.06) and had undergone the baseline (vs. annual) scan (OR=1.70, CI 1.20, 2.42). Dropout was significantly lower among those who: had more education (associates (OR=.67, CI=.46, .98) or bachelor‟s degree (OR=.56, CI .35, .91) vs. high school/GED), were somewhat (vs. not at all/little) worried about lung cancer (OR=.60, CI .39, .92), or had a LR2 (OR=.57, CI .39, .82) or LR3 (OR=.38, CI .16, .90), screening result, compared to LR1. Age, gender, pain, and anxiety/depression were not significant predictors of attrition in the final model.
Discussion
Although CMS mandates that individuals who currently smoke cigarettes must be given information about tobacco treatment when undergoing LCS,7 engagement in tobacco treatment in the LCS setting is low.19,20 An understanding of the barriers to tobacco treatment is a necessary first step to increasing the quit rates among those undergoing LCS, which can lead to an increase in the public health impact of screening.6 Study results support prior findings that lower education15,30 and heavier smoking12,13,31 are associated with greater trial attrition. Importantly, novel findings indicated that trial attrition was associated with factors specific to the LCS setting. Attrition was worse among those with little lung cancer worry, those who were undergoing their initial (vs. annual) exam, or who received a negative (vs. benign or probably benign) LCS result.
In the context of smoking cessation, past research on the ʻteachable momentʼ suggests that tapping into risk perceptions and disease-specific worry can increase readiness to quit and cessation.9,32 Our findings suggest that having some lung cancer worry played a role in reducing attrition. Some prior studies have also suggested that an abnormal result may increase motivation to quit, although there have been conflicting findings.12,33 In the present study, individuals with a negative result may not have appreciated the importance of remaining enrolled in cessation treatment, compared to those with a potentially more concerning result. Limited research has examined associations between screening history and smoking cessation.34 Our findings showed that those new to undergoing LCS were more likely to drop out of the trial, compared to those who had previously been screened. It is possible that these individuals had less of a vested interest or may have been overwhelmed by the exam, compared to those who were already engaged in annual screening. Offering tailored communication about tobacco treatment at the multiple touchpoints during the course of LCS may increase awareness and willingness to participate in an intervention.
Study limitations include the missing data on comorbid conditions, the lack of sample diversity, the small sample of patients with LR3 and LR4 screening results, and the lack of data on reasons for dropout, which limited the ability to assess the role of these variables in attrition. Future studies are needed to assess additional screening-related predictors of attrition in more diverse samples and in clinically-based tobacco treatment programs in the LCS setting.
In summary, these findings confirmed prior findings and identified new predictors of trial attrition that are specific to the LCS setting. Identification of these factors can impact engagement in tobacco treatment by anticipating which participants may need additional attention. Further, these factors can inform intervention development, recruitment and retention strategies, and improve participant diversity. Patients undergoing LCS who express little to no lung cancer worry may need additional attention to address risk perceptions in order to prevent dropout. Additionally, those undergoing their baseline scan or those with a negative screening result may require additional communication to underscore the importance of cessation in an effort to engage them in tobacco treatment. Further research is needed to investigate tobacco treatment methods that impact willingness to engage in treatment, such as the type of treatment offered, communication of the importance of cessation for lung cancer risk reduction, the timing of when tobacco treatment is offered (pre- or post-LCS exam) and addressing the role of lung cancer worry. Alleviating these barriers to retention, while also capitalizing on the potential teachable moment provided by LCS, may aid in increasing tobacco treatment engagement and quit rates, thereby improving the overall impact of LCS.
Highlights.
Tobacco treatment is underutilized in the lung cancer screening setting
Lung screening patients (N=926) were enrolled in a phone-based cessation trial
Attrition was related to screening factors, including cancer worry and exam result
Targeted strategies are needed to reduce tobacco treatment attrition
Funding
This work was supported by the National Cancer Institute [R01CA207228].
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References
- 1.Landy R, Young CD, Skarzynski M, et al. Using Prediction-Models to Reduce Persistent Racial/Ethnic Disparities in Draft 2020 USPSTF Lung-Cancer Screening Guidelines. J Natl Cancer Inst. Published online January 5, 2021. doi: 10.1093/jnci/djaa211 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ma J, Ward EM, Smith R, Jemal A. Annual number of lung cancer deaths potentially avertable by screening in the United States. Cancer. 2013;119(7):1381–1385. doi: 10.1002/cncr.27813 [DOI] [PubMed] [Google Scholar]
- 3.Zahnd WE, Eberth JM. Lung Cancer Screening Utilization: A Behavioral Risk Factor Surveillance System Analysis. Am J Prev Med. 2019;57(2):250–255. doi: 10.1016/j.amepre.2019.03.015 [DOI] [PubMed] [Google Scholar]
- 4.Recommendation: Lung Cancer: Screening | United States Preventive Services Taskforce. Accessed April 15, 2021. https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/lung-cancer-screening
- 5.Aberle DR. Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. N Engl J Med. 2011;365(5):395–409. doi: 10.1056/NEJMoa1102873 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Villanti AC, Jiang Y, Abrams DB, Pyenson BS. A cost-utility analysis of lung cancer screening and the additional benefits of incorporating smoking cessation interventions. PloS One. 2013;8(8):e71379. doi: 10.1371/journal.pone.0071379 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Centers for Medicare and Medicaid Services, Billioux A, Verlander K, et al. Standardized Screening for Health-Related Social Needs in Clinical Settings: The Accountable Health Communities Screening Tool. NAM Perspect. 2017;7(5). doi: 10.31478/201705b [DOI] [Google Scholar]
- 8.Hahn EJ, Rayens MK, Hopenhayn C, Christian WJ. Perceived risk and interest in screening for lung cancer among current and former smokers. Res Nurs Health. 2006;29(4):359–370. doi: 10.1002/nur.20132 [DOI] [PubMed] [Google Scholar]
- 9.Taylor KL, Cox LS, Zincke N, Mehta L, McGuire C, Gelmann E. Lung cancer screening as a teachable moment for smoking cessation. Lung Cancer Amst Neth. 2007;56(1):125–134. doi: 10.1016/j.lungcan.2006.11.015 [DOI] [PubMed] [Google Scholar]
- 10.Tammemägi MC, Katki HA, Hocking WG, et al. Selection Criteria for Lung-Cancer Screening. N Engl J Med. 2013;368(8):728–736. doi: 10.1056/NEJMoa1211776 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Taylor KL, Deros DE, Fallon S, et al. Study protocol for a telephone-based smoking cessation randomized controlled trial in the lung cancer screening setting: the lung screening, tobacco, and health trial. Contemp Clin Trials. 2019;82:25–35. doi: 10.1016/j.cct.2019.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Slatore CG, Baumann C, Pappas M, Humphrey LL. Smoking behaviors among patients receiving computed tomography for lung cancer screening. Systematic review in support of the U.S. preventive services task force. Ann Am Thorac Soc. 2014;11(4):619–627. doi: 10.1513/AnnalsATS.201312-460OC [DOI] [PubMed] [Google Scholar]
- 13.Belita E, Sidani S. Attrition in Smoking Cessation Intervention Studies: A Systematic Review. Can J Nurs Res Rev Can Rech En Sci Infirm. 2015;47(4):21–40. doi: 10.1177/084456211504700402 [DOI] [PubMed] [Google Scholar]
- 14.Wiseman KP, Coa KI, Prutzman YM. Predictors of Retention in an Adult Text Messaging Smoking Cessation Intervention Program: Cohort Study. JMIR MHealth UHealth. 2019;7(8):e13712. doi: 10.2196/13712 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Courtney RJ, Clare P, Boland V, et al. Predictors of retention in a randomised trial of smoking cessation in low-socioeconomic status Australian smokers. Addict Behav. 2017;64:13–20. doi: 10.1016/j.addbeh.2016.07.019 [DOI] [PubMed] [Google Scholar]
- 16.Bahadir A, Iliaz S, Yurt S, Ortakoylu MG, Bakan ND, Yazar E. Factors affecting dropout in the smoking cessation outpatient clinic. Chron Respir Dis. 2016;13(2):155–161. doi: 10.1177/1479972316629953 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.MacPherson L, Stipelman BA, Duplinsky M, Brown RA, Lejuez CW. Distress tolerance and pre-smoking treatment attrition: examination of moderating relationships. Addict Behav. 2008;33(11):1385–1393. doi: 10.1016/j.addbeh.2008.07.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Metse AP, Hizam NAN, Wiggers J, Wye P, Bowman JA. Factors associated with retention in a smoking cessation trial for persons with a mental illness: a descriptive study. BMC Med Res Methodol. 2018;18(1):177. doi: 10.1186/s12874-018-0640-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Park ER, Gareen IF, Japuntich S, et al. Primary Care Provider-Delivered Smoking Cessation Interventions and Smoking Cessation Among Participants in the National Lung Screening Trial. JAMA Intern Med. 2015;175(9):1509–1516. doi: 10.1001/jamainternmed.2015.2391 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Steliga MA, Yang P. Integration of smoking cessation and lung cancer screening. Transl Lung Cancer Res. 2019;0(0). Accessed December 8, 2020. http://tlcr.amegroups.com/article/view/28363 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Li J, Chung S, Martinez M, Luft HS. Smoking Cessation Interventions After Lung Cancer Screening Guideline Change. Published online 2020. Accessed December 8, 2020. https://escholarship.org/uc/item/25p1g8tw [DOI] [PubMed]
- 22.Ostroff JS, Copeland A, Borderud SP, Li Y, Shelley DR, Henschke CI. Readiness of Lung Cancer Screening Sites to Deliver Smoking Cessation Treatment: Current Practices, Organizational Priority, and Perceived Barriers. Nicotine Tob Res Off J Soc Res Nicotine Tob. 2016;18(5):1067–1075. doi: 10.1093/ntr/ntv177 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Wood DE, Kazerooni EA, Baum SL, et al. Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Cancer Netw JNCCN. 2018;16(4):412–441. doi: 10.6004/jnccn.2018.0020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.American College of Radiology Committee on Lung-RADS®. Lung-RADS Assessment Categories version1.1. Available at https://www.acr.org/-/media/ACR/Files/RADS/Lung-RADS/LungRADSAssessmentCategoriesv1-1.pdf. Accessed on April 15, 2021.
- 25.Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom K-O. The Fagerström Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991;86(9):1119–1127. doi: 10.1111/j.1360-0443.1991.tb01879.x [DOI] [PubMed] [Google Scholar]
- 26.Apodaca TR, Abrantes AM, Strong DR, Ramsey SE, Brown RA. Readiness to change smoking behavior in adolescents with psychiatric disorders. Addict Behav. 2007;32(6):1119–1130. doi: 10.1016/j.addbeh.2006.07.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Biener L, Abrams DB. The Contemplation Ladder: validation of a measure of readiness to consider smoking cessation. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 1991;10(5):360–365. doi: 10.1037//0278-6133.10.5.360 [DOI] [PubMed] [Google Scholar]
- 28.EuroQol Group. EuroQol--a new facility for the measurement of health-related quality of life. Health Policy Amst Neth. 1990;16(3):199–208. doi: 10.1016/0168-8510(90)90421-9 [DOI] [PubMed] [Google Scholar]
- 29.Kessler RC, Andrews G, Colpe LJ, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959–976. doi: 10.1017/S0033291702006074 [DOI] [PubMed] [Google Scholar]
- 30.Gul RB, Ali PA. Clinical trials: the challenge of recruitment and retention of participants. J Clin Nurs. 2010;19(1–2):227–233. doi: 10.1111/j.1365-2702.2009.03041.x [DOI] [PubMed] [Google Scholar]
- 31.Pedersen JH, Tønnesen P, Ashraf H. Smoking cessation and lung cancer screening. Ann Transl Med. 2016;4(8). doi: 10.21037/atm.2016.03.54 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.McBride CM, Emmons KM, Lipkus IM. Understanding the potential of teachable moments: the case of smoking cessation. Health Educ Res. 2003;18(2):156–170. doi: 10.1093/her/18.2.156 [DOI] [PubMed] [Google Scholar]
- 33.Tammemägi MC, Berg CD, Riley TL, Cunningham CR, Taylor KL. Impact of lung cancer screening results on smoking cessation. J Natl Cancer Inst. 2014;106(6):dju084. doi: 10.1093/jnci/dju084 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Townsend CO, Clark MM, Jett JR, et al. Relation between smoking cessation and receiving results from three annual spiral chest computed tomography scans for lung carcinoma screening. Cancer. 2005;103(10):2154–2162. doi: 10.1002/cncr.21045 [DOI] [PubMed] [Google Scholar]