Benefits managers’ attitudes toward obesity treatment coverage

肥胖 心理干预 医学 人口 环境卫生 柱头(植物学) 公共卫生 老年学 家庭医学 精神科 护理部 内科学
作者
Caroline Ben Nathan,Jennifer Ben Nathan,Yiing Jenq Chou,Sukanya M. Joshi,Christine Gallagher,Ariana M. Chao
出处
期刊:Obesity Research & Clinical Practice [Elsevier BV]
标识
DOI:10.1016/j.orcp.2024.04.001
摘要

Despite the existence of effective treatments, obesity continues to present a severe public health crisis. Limited access to treatments works against efforts to reduce obesity prevalence. A major barrier to treatment access is a lack of insurance coverage. This study focused on an important population of stakeholders: benefits managers. The purpose of this study was to explore the relationships between attitudes about insurance coverage of obesity treatments and obesity stigma. Benefits managers have the ability to advocate for insurance coverage of medical interventions. We assessed whether attitudes toward covering obesity benefits for employees could be modified by receiving targeted information or were associated with particular factors. We recruited participants from Dun & Bradstreet's employer database using emails. Participants were randomized to one of three conditions that provided written information about: (1) prevalence of obesity (control), (2) prevalence + financial implications of obesity, and (3) prevalence + physiology of obesity. Questionnaires were self-administered online. The response rate was 4.8%, with 404 participants meeting eligibility criteria. While attitudes toward coverage of obesity interventions did not differ significantly based on condition (p > 0.05), gender, history of previous obesity treatment, and an individual's likelihood to attribute obesity to biological and environmental factors showed significant associations with supporting coverage of obesity treatment (p < 0.05). Findings suggest that understanding obesity as a condition caused by biological factors as opposed to personal responsibility and behavior is associated with greater support for coverage of all its treatments.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
苏苏发布了新的文献求助10
1秒前
1秒前
1秒前
所所应助L2采纳,获得10
2秒前
ze完成签到,获得积分10
2秒前
3秒前
英吉利25发布了新的文献求助10
3秒前
4秒前
4秒前
皮汤汤发布了新的文献求助10
4秒前
4秒前
Coarrb完成签到,获得积分10
5秒前
yeezy123发布了新的文献求助10
5秒前
zl发布了新的文献求助10
6秒前
科研通AI6.4应助长命百岁采纳,获得10
6秒前
初椿完成签到 ,获得积分10
7秒前
核桃应助烟波采纳,获得30
7秒前
7秒前
NMSL发布了新的文献求助10
7秒前
8秒前
Cole发布了新的文献求助10
8秒前
科研通AI6.4应助RickT采纳,获得10
9秒前
风中雅青发布了新的文献求助10
9秒前
上官若男应助学霸土豆采纳,获得10
9秒前
真实的蹇发布了新的文献求助10
9秒前
9秒前
芭乐完成签到,获得积分10
9秒前
9秒前
10秒前
科研通AI6.2应助热情醉冬采纳,获得10
10秒前
满意的文涛完成签到 ,获得积分10
10秒前
华仔应助LLF采纳,获得10
10秒前
10秒前
苏苏完成签到,获得积分10
10秒前
天涯过客完成签到,获得积分10
11秒前
11秒前
英俊的铭应助牙牙采纳,获得10
12秒前
热白发布了新的文献求助10
12秒前
RJ发布了新的文献求助10
12秒前
123完成签到,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
适配Micro-LED色转换的高兼容性量子点负性光刻胶制备与工艺研究 500
Direct and Iterative Linear System Solvers 500
Vander's Renal Physiology第10版 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7307569
求助须知:如何正确求助?哪些是违规求助? 8925211
关于积分的说明 18912393
捐赠科研通 6970243
什么是DOI,文献DOI怎么找? 3212617
关于科研通互助平台的介绍 2381192
邀请新用户注册赠送积分活动 2190222