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. 2019 Jul;38(7):638-647.
doi: 10.1037/hea0000740. Epub 2019 Apr 25.

Identifying pathways to quitting smoking via telemedicine-delivered care

Edward P Liebmann  1 , Kristopher J Preacher  2 , Kimber P Richter  3 , A Paula Cupertino  4 , Delwyn Catley  5
Affiliations

Identifying pathways to quitting smoking via telemedicine-delivered care

Edward P Liebmann et al. Health Psychol. 2019 Jul.

Abstract

Objective: A randomized controlled trial of quitline-like phone counseling (QL) versus telemedicine integrated into primary care (ITM) compared the effectiveness of these modalities for smoking cessation. Study design and components were based on self-determination theory (SDT). The purpose of this study was to test our SDT-based model in which perceived health care provider autonomy support, working alliance, autonomous motivation, and perceived competence were hypothesized to mediate the effects of ITM on smoking cessation.

Method: Rural smokers (n = 560) were randomized to receive 4 sessions over a 3-month period of either QL or ITM. Follow-up assessments were conducted at Months 3, 6, and 12. The primary outcome was biochemically verified 7-day point prevalence at 12 -months. Structural equation modeling with latent change scores was used for the analysis.

Results: Participants in the ITM condition reported greater increases in perceived health care provider autonomy support (PAS) at end of treatment, which in turn was associated with enhanced perceived competence to quit smoking (PC). Increased PC was associated with a higher likelihood of cessation at 12-months. Mediation analysis demonstrated significant indirect effects, including a path from ITM to increases in PAS to increases in PC to cessation at 12-months (indirect effect = 0.0183, 95% confidence interval [.003, .0434]).

Conclusions: When integrated into primary care, ITM may influence smoking cessation by enhancing the extent to which smokers feel supported by their providers and thereby increase their perceived ability to quit. Findings suggest that locating tobacco treatment services in health care provider offices imparts a motivational benefit for cessation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Figures

Figure 1.
Figure 1.
Conceptual model of how the SDT Process Influences Cessation
Figure 2.
Figure 2.. Structural Model Diagram and Parameter Estimates.
Note: PAS = Healthcare provider autonomy support, PC = Perceived Competence to Quit Smoking, AM = Autonomous Motivation Subscale, WAI = Working Alliance Inventory, ITM = Integrated Telemedicine, QL = Quitline, * = Fixed parameters. Ovals represent latent variables and rectangles represent observed variables. Regression coefficients are unstandardized for latent variables. Coefficients for predictors of smoking cessation are odds ratios. The structural model was adjusted for age, gender, education, and nicotine dependence.
See this image and copyright information in PMC

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