Predictors of client retention in a state-based tobacco quitline

Abstract

IntroductionQuitlines are standard care for smoking cessation; however, retaining clients in services is a problem. Little is known about factors that may predict dropout.AimsTo examine predictors of retention while in-program and at follow-up for clients enrolling in a state quitline.MethodsThis was a retrospective analysis of quitline enrolled clients from 2011 to 2017 (N = 49,347). Client retention in-program was categorized as (a) low adherence to treatment (receiving zero coaching calls), moderate (1–2 calls), and high adherence (3+ calls). Dropout at follow-up included participants who were not reached for the 7-month follow-up.ResultsMore than half the sample dropped out during treatment; 61% were not reached for follow-up. Women (odds ratio (OR) = 1.21; 95% confidence interval (CI) = [1.16, 127]) and those with high levels of nicotine dependence (OR = 1.03; 95% CI = [1.02, 1.04]) were more likely to have moderate adherence to treatment (1–2 coaching calls). Dropout at follow-up was more likely among clients who used nicotine replacement therapy (OR = 1.14; 95% CI = [1.09, 1.19]) and less likely among those who had high treatment adherence (OR = 0.41; 95% CI = [0.39, 0.42]).ConclusionGiven the relapsing nature of tobacco use and the harms related to tobacco use, quitlines can improve their impact by offering tailored services to enhance client engagement and retention in-treatment and at follow-up.

Prospective estimation of the age of initiation of cigarettes among young adults (18–24 years old): Findings from the Population Assessment of Tobacco and Health (PATH) waves 1–4 (2013–2017)

“…In addition, population-based strategies, such as FDA’s required cigarette health warnings that include text, color graphics, and descriptions of some of the less-known but serious health risks from cigarette use [ 69 , 70 ], will be paramount to reduce cigarette initiation overall. Other effective strategies that can be implemented at the population level include mass media campaigns [ 66 , 71 ], comprehensive smoke-free policies [ 72 ], state-funded cessation programs [ 73 , 74 ], reducing the nicotine content in cigarettes [ 75 ], menthol bans [ 76 ], and increasing the tax on cigarettes [ 77 ]. Additional research is needed to better inform the development of culturally-relevant tobacco prevention interventions for young adults, and to evaluate the reach and coverage of those interventions.…”

Examining service participation and outcomes from a population-level telephone-coaching service supporting changes to healthy eating, physical activity and weight: A comparison of participants with and without a mental health condition

“…Of those no longer active in the program, participants with a mental health condition were less likely to have completed a coaching program than those without (31% vs 36%). Little research has similarly compared retention rates for health behaviour coaching programs between participants with and without a mental health condition, although some Quitline research suggests rates to be similar ( Nair et al, 2020 ). In the current study, there was no difference between participants with and without a mental health condition in terms of the proportions giving a service-related versus participant-related reason for electing to withdraw.…”

“…Cochrane review evidence indicates that individuals engaging with Quitlines are up to 10% more likely to have quit than those using self-help material alone ( Matkin et al, 2019 ). International evidence suggests that 20–40% of Quitline users have a mental health condition ( Kerkvliet et al, 2015 , Hebert et al, 2011 , Nair et al, 2020 , Lien et al, 2016 , Railton, 2015 ), and gain benefit from the Quitline, although sustained cessation may be more difficult for this group ( Railton, 2015 ). Contributing factors may include higher nicotine dependence ( Bowden et al, 2011 , Rüther et al, 2014 ), as well as social determinants impacting behaviour change including lack of social support, poorer physical health and lower self-efficacy ( Rüther et al, 2014 , Hughes, 2006 ).…”

Engaging Patients in Smoking Cessation Treatment within the Lung Cancer Screening Setting: Lessons Learned from an NCI SCALE Trial

“…Although the literature describing predictors of intervention engagement in SCALE trials is limited to date, there has been substantial research in the area of engagement and adherence to cessation programs and quitlines in other settings [6,[18][19][20][21]. The current literature on this topic suggests that women [6]; older adults [18,19]; and individuals with higher income [20], higher education [20], and health insurance [20] have greater treatment engagement. Further, higher nicotine dependence [6,18] and higher motivation to quit [20] are associated with higher treatment engagement and adherence, although there have been exceptions to these findings [22].…”

“…Based on the classic reach x effectiveness = impact paradigm [2], regardless of the effectiveness achieved, low reach will limit the impact that treatment will have on the number who quit, and ultimately, on mortality reduction [3]. In the current paper, we have assessed the factors related to reach and engagement among individuals offered cessation services in the lung screening context with the goal of maximizing the public health benefit of pairing smoking cessation treatment with lung screening [4][5][6].…”