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An examination of the relationships ...
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Voci, Sabrina C.
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An examination of the relationships between causal attributions for smoking and smokers' treatment seeking and quit intentions: A structural equation modeling approach.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
An examination of the relationships between causal attributions for smoking and smokers' treatment seeking and quit intentions: A structural equation modeling approach./
作者:
Voci, Sabrina C.
面頁冊數:
233 p.
附註:
Source: Dissertation Abstracts International, Volume: 75-05(E), Section: B.
Contained By:
Dissertation Abstracts International75-05B(E).
標題:
Psychology, Social. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR98801
ISBN:
9780494988015
An examination of the relationships between causal attributions for smoking and smokers' treatment seeking and quit intentions: A structural equation modeling approach.
Voci, Sabrina C.
An examination of the relationships between causal attributions for smoking and smokers' treatment seeking and quit intentions: A structural equation modeling approach.
- 233 p.
Source: Dissertation Abstracts International, Volume: 75-05(E), Section: B.
Thesis (Ph.D.)--University of Windsor (Canada), 2014.
With increasing knowledge of the role that genetics play in the development and treatment of nicotine dependence, it is expected that in the future smoking cessation treatment will be able to be tailored to a smoker's genetic profile. Despite anticipated benefits such as improved quit rates, concerns have been raised about the impact of genetic testing results on perceived control over smoking, motivation to quit, and treatment seeking behaviour. One potential mediator of such outcomes are causal attributions, the causal explanations people form for behaviours and events, which evidence suggests can be altered by genetic testing feedback. The purpose of the current study was to perform a comprehensive assessment of causal attributions for current smoking and to examine the associations between these attributions and variables expected to predict future smoking cessation behaviour. Two structural equation models were tested that represented a series of hypotheses regarding how causal attributions influence intentions to quit smoking and intentions to seek smoking cessation treatment, via beliefs about perceived control over smoking and perceived effectiveness of treatment. Causal attributions were represented by causal types (biological, psychological, social, and stress) in one model and by causal dimensions (locus of causality, stability, internal control, and external control) in a second model; both models were otherwise identical.
ISBN: 9780494988015Subjects--Topical Terms:
529430
Psychology, Social.
An examination of the relationships between causal attributions for smoking and smokers' treatment seeking and quit intentions: A structural equation modeling approach.
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With increasing knowledge of the role that genetics play in the development and treatment of nicotine dependence, it is expected that in the future smoking cessation treatment will be able to be tailored to a smoker's genetic profile. Despite anticipated benefits such as improved quit rates, concerns have been raised about the impact of genetic testing results on perceived control over smoking, motivation to quit, and treatment seeking behaviour. One potential mediator of such outcomes are causal attributions, the causal explanations people form for behaviours and events, which evidence suggests can be altered by genetic testing feedback. The purpose of the current study was to perform a comprehensive assessment of causal attributions for current smoking and to examine the associations between these attributions and variables expected to predict future smoking cessation behaviour. Two structural equation models were tested that represented a series of hypotheses regarding how causal attributions influence intentions to quit smoking and intentions to seek smoking cessation treatment, via beliefs about perceived control over smoking and perceived effectiveness of treatment. Causal attributions were represented by causal types (biological, psychological, social, and stress) in one model and by causal dimensions (locus of causality, stability, internal control, and external control) in a second model; both models were otherwise identical.
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Participants were 418 current daily smokers in Ontario, Canada, that had previously participated in the Ontario Health Study. Overall, participants most frequently attributed their smoking to habit, addiction, and/or stress, while attributions to genetics were among the least frequent. Additionally, knowledge that genetics play a role in determining level of addiction to nicotine was not pervasive. Study findings supported the hypothesized model in which causal dimensions directly predicted level of perceived control over smoking (personal or via treatment), which in turn predicted perceived effectiveness of pharmacological and psychosocial smoking cessation treatments, intentions to quit smoking, and intentions to seek cessation treatment. Results failed to find similar associations with causal types. Current findings can be applied to future research on the effects of providing genetic testing feedback to smokers in clinical settings, and may have wider applicability to other health threats.
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