Sarah Evers-Casey1, Robert Schnoll2, Brian P Jenssen3, Frank T Leone1. 1. Comprehensive Smoking Treatment Program. 2. Center for Interdisciplinary Research on Nicotine Addiction, Perelman School of Medicine, University of Pennsylvania. 3. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania.
Abstract
OBJECTIVE: Given the number of annual interactions between people who smoke and health care providers, even low-efficacy interventions would be expected to have a large cumulative effect on smoking prevalence. Efforts to improve uptake of tobacco dependence treatment guidelines have had limited success. It remains unclear whether complex social motivations influence treatment decision-making among providers, despite widespread understanding of the condition's impact on morbidity. METHOD: Clinicians from across the United States participated in a computer-based survey of potential explicit tobacco treatment biases, relative to care of hypertension. Items corresponded to framework domains of Weiner's causal attribution theory of social motivation (Weiner, 1993). Single-word, open-response items were used to gain insight into the frequency of spontaneous perceptions regarding treatment of each condition. Implicit association testing (IAT) measured strength of association between images of smoking and evaluation of guilt versus innocence. RESULTS: Significant differences in agreement scores were identified within the causal attribution, emotional response, and help investment domains. Single-word answers confirmed a significant difference in emotional response to tobacco treatment (28.1% vs. 10.5%, p = .02), and suggested the difference was driven by the frequent perception of frustration (75% vs. 0%, p = .07). IAT revealed incompatibility between images of smoking and words conveying "innocence" compared with "guilt" (latency 1,846 ms vs. 1,113 ms, p < .001). CONCLUSIONS: Complex social motivations may be operational in the context of tobacco dependence treatment, limiting provider willingness to follow treatment guidelines. If confirmed, this represents a critical obstacle to sophisticated guideline implementation, and should be addressed in future implementation strategies. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
OBJECTIVE: Given the number of annual interactions between people who smoke and health care providers, even low-efficacy interventions would be expected to have a large cumulative effect on smoking prevalence. Efforts to improve uptake of tobacco dependence treatment guidelines have had limited success. It remains unclear whether complex social motivations influence treatment decision-making among providers, despite widespread understanding of the condition's impact on morbidity. METHOD: Clinicians from across the United States participated in a computer-based survey of potential explicit tobacco treatment biases, relative to care of hypertension. Items corresponded to framework domains of Weiner's causal attribution theory of social motivation (Weiner, 1993). Single-word, open-response items were used to gain insight into the frequency of spontaneous perceptions regarding treatment of each condition. Implicit association testing (IAT) measured strength of association between images of smoking and evaluation of guilt versus innocence. RESULTS: Significant differences in agreement scores were identified within the causal attribution, emotional response, and help investment domains. Single-word answers confirmed a significant difference in emotional response to tobacco treatment (28.1% vs. 10.5%, p = .02), and suggested the difference was driven by the frequent perception of frustration (75% vs. 0%, p = .07). IAT revealed incompatibility between images of smoking and words conveying "innocence" compared with "guilt" (latency 1,846 ms vs. 1,113 ms, p < .001). CONCLUSIONS: Complex social motivations may be operational in the context of tobacco dependence treatment, limiting provider willingness to follow treatment guidelines. If confirmed, this represents a critical obstacle to sophisticated guideline implementation, and should be addressed in future implementation strategies. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Authors: Nastasja Robstad; Frank Siebler; Ulrika Söderhamn; Thomas Westergren; Liv Fegran Journal: Res Nurs Health Date: 2018-10-10 Impact factor: 2.228
Authors: Bethany Bass; Elizabeth Lake; Chelsea Elvy; Sarah Fodemesi; Mara Iacoe; Emilie Mazik; Dina Brooks; Annemarie Lee Journal: Physiother Can Date: 2018 Impact factor: 1.037
Authors: David P Miller; John G Spangler; Mara Z Vitolins; Stephen W Davis; Edward H Ip; Gail S Marion; Sonia J Crandall Journal: Acad Med Date: 2013-07 Impact factor: 6.893
Authors: Frank T Leone; Yuqing Zhang; Sarah Evers-Casey; A Eden Evins; Michelle N Eakin; Joelle Fathi; Kathleen Fennig; Patricia Folan; Panagis Galiatsatos; Hyma Gogineni; Stephen Kantrow; Hasmeena Kathuria; Thomas Lamphere; Enid Neptune; Manuel C Pacheco; Smita Pakhale; David Prezant; David P L Sachs; Benjamin Toll; Dona Upson; Dan Xiao; Luciane Cruz-Lopes; Izabela Fulone; Rachael L Murray; Kelly K O'Brien; Sureka Pavalagantharajah; Stephanie Ross; Yuan Zhang; Meng Zhu; Harold J Farber Journal: Am J Respir Crit Care Med Date: 2020-07-15 Impact factor: 21.405
Authors: Brian P Jenssen; Robert Schnoll; Rinad Beidas; Justin Bekelman; Anna-Marika Bauer; Callie Scott; Sarah Evers-Casey; Jody Nicoloso; Peter Gabriel; David A Asch; Alison Buttenheim; Jessica Chen; Julissa Melo; Lawrence N Shulman; Alicia B W Clifton; Adina Lieberman; Tasnim Salam; Kelly Zentgraf; Katharine A Rendle; Krisda Chaiyachati; Rachel Shelton; E Paul Wileyto; Sue Ware; Frank Leone Journal: Implement Sci Date: 2021-07-15 Impact factor: 7.327