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DOI10.1016/j.appet.2019.04.002
Reducing meat consumption: Identifying group-specific inhibitors using latent profile analysis
Lacroix, Karine1; Gifford, Robert2
发表日期2019
ISSN0195-6663
EISSN1095-8304
卷号138页码:233-241
英文摘要

Consumption of animal products is an important greenhouse gas emitting behavior. However, perceived hindrances to incorporating more plant-based diets present challenges for the successful design of behavior-change interventions. Latent profile analysis of survey responses revealed three distinct groups. Meat-reducers perceive the fewest inhibitors and are the most willing to incorporate more meat-free days in their diets. Moderate-hindrance meat eaters perceive many more inhibitors, and are hindered by a lack of social support, attachment to meat, not wanting to change their routine, and less awareness of the health benefits of eating less meat. They are willing to incorporate new healthy foods in their diet and are somewhat willing to avoid meat on some days. Strong-hindrance meat eaters report weak self-efficacy and the most inhibitors but are somewhat willing to incorporate healthier foods in their diets. Implications for tailored meat-reduction interventions are discussed. For example, when targeting meat-attached individuals, it might be beneficial to focus on replacing red meats with less carbon-intensive protein sources.


WOS研究方向Behavioral Sciences ; Nutrition & Dietetics
来源期刊APPETITE
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/100155
作者单位1.Univ Victoria, Sch Environm Studies, STN CSC, David Tiapin Bldg B243,POB 1700, Victoria, BC V8W 2Y2, Canada;
2.Univ Victoria, Dept Psychol, Victoria, BC, Canada
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Lacroix, Karine,Gifford, Robert. Reducing meat consumption: Identifying group-specific inhibitors using latent profile analysis[J],2019,138:233-241.
APA Lacroix, Karine,&Gifford, Robert.(2019).Reducing meat consumption: Identifying group-specific inhibitors using latent profile analysis.APPETITE,138,233-241.
MLA Lacroix, Karine,et al."Reducing meat consumption: Identifying group-specific inhibitors using latent profile analysis".APPETITE 138(2019):233-241.
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