Support via Online Social Networks to Promote safe Infant Care Practices Toward Reducing Racial Disparities in Infant Mortality (SUPERSONIC)

通过在线社交网络支持促进安全的婴儿护理实践,以减少婴儿死亡率的种族差异(超音速)

基本信息

  • 批准号:
    10559662
  • 负责人:
  • 金额:
    $ 69.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-07-10 至 2026-01-31
  • 项目状态:
    未结题

项目摘要

The focus of this renewal application is to build upon the findings from the Influence of Social Networks on Infant Care and Disparities in Postneonatal Infant Mortality (SONIC) study by conducting a 4-armed randomized controlled trial (RCT) using online social networks (OSNs) to promote safe infant care practices and reduce Black/White (B/W) disparities in adherence to these practices. In SONIC, we conducted social network analysis on 402 new and experienced mothers of young infants. We learned that there are 2 social network (i.e., family, friends, and peers) types: exclusive (kin-based) and expansive (not kin-based); that network social norms (group rules defining appropriate behaviors, values, and attitudes) are highly predictive of infant sleep practices (sleep position, bedsharing, soft bedding use); that mothers are more likely to change from safe to unsafe practices if their network members espouse unsafe practices; and that Black mothers are more likely to have exclusive networks, which are more likely to have unsafe practices as the norm. Safe sleep practices are associated with lower rates of sudden infant death syndrome (SIDS) and unintentional injury- related deaths (e.g. accidental suffocation) associated with the sleep environment. These sleep-related deaths (SRDs) remain the leading cause of postneonatal death in the US, with ~3600 deaths/year; Black infants die at more than double national rates. Thus, differences in social networks and norms contribute to the Black/White (B/W) disparity seen in safe sleep practices, which in turn contribute to the B/W disparity in postneonatal infant deaths; the influence of social networks and norms, if contrary to recommended infant care practices, is a major barrier to acceptance of these practices. OSNs have become a powerful tool for establishing social norms and influencing behavior, and data suggest that this is equally or more so for Blacks. Thus, our proposed SUPERSONIC (Support via Online Social Networks to promote Safe Infant Care practices Toward Reducing Racial Disparities in Infant Mortality) study is the natural next step after SONIC. We plan to test, through a 4-armed pragmatic RCT, an intervention strategy that uses OSNs (private Facebook groups) to change social norms among WIC recipient mothers, who have a disproportionate burden of SRDs and high proportion of Blacks. Mothers in each study arm will participate in an OSN and receive one of 4 messaging interventions: 1) safe sleep alone, 2) breastfeeding alone, 3) both safe sleep and breastfeeding, and 4) routine health messages (attention-matched control). Beginning prenatally, we will disseminate via OSNs videos and messages that address common myths and misconceptions to ultimately impact attitudes and social norms regarding infant sleep practices and breastfeeding. If utilization of OSNs is effective in changing network norms and maternal attitudes, and improving adherence, this approach is easily scalable. Moreover, it could be replicated and potentially readily applied to other health care messages, including vaccine acceptance and nutrition/obesity.
此续订申请的重点是建立在社交网络对 婴儿护理与新生儿后婴儿死亡率差异(SONIC)研究 使用在线社交网络(OSN)促进安全婴儿护理实践的随机对照试验(RCT) 并在遵守这些做法时减少黑白(B/W)差异。在Sonic中,我们进行了社交 402名有经验的新生婴儿母亲的网络分析我们了解到有两个社交网站 网络(即,家庭、朋友和同伴)类型:排他性(基于亲属)和扩张性(不基于亲属); 网络社会规范(定义适当行为、价值观和态度的团体规则)高度预测 婴儿睡眠习惯(睡姿、与人同床、使用柔软的床上用品);母亲更有可能改变 从安全的做法到不安全的做法,如果他们的网络成员拥护不安全的做法,而黑人母亲 更有可能拥有独家网络,这些网络更有可能将不安全的做法作为常态。安全睡眠 这种做法与较低的婴儿猝死综合症(SID)和意外伤害的发生率有关- 与睡眠环境有关的相关死亡(如意外窒息)。这些与睡眠有关的死亡 (SRDS)仍然是美国新生儿后死亡的主要原因,每年约有3600人死亡;黑人婴儿死于 是全国房价的两倍多。因此,社交网络和规范的差异导致了黑人/白人 (B/W)安全睡眠实践中出现的差异,这反过来又导致了新生儿后婴儿的B/W差异 死亡;社交网络和规范的影响,如果与推荐的婴儿护理做法相反,是一种 接受这些做法的主要障碍。OSN已经成为建立社交网络的强大工具 规范和影响行为,数据表明,这对黑人来说也是同样或更多的。因此,我们的 建议的超音速(通过在线社交网络支持,以促进安全的婴儿护理实践 减少婴儿死亡率中的种族差异)研究是继SONIC之后自然的下一步。我们计划测试, 通过四臂务实的RCT,一种使用OSN(私人Facebook组)的干预战略 改变WIC受孕母亲的社会规范,她们有不成比例的SRD负担和高 黑人的比例。每个研究分支中的母亲将参与OSN并收到4条消息中的一条 干预措施:1)单独安全睡眠,2)单独母乳喂养,3)安全睡眠和母乳喂养,4)常规 健康信息(注意力匹配对照)。从产前开始,我们将通过OSNS视频和 针对常见的神话和误解,最终影响态度和社会规范的信息 关于婴儿睡眠习惯和母乳喂养。OSN的使用是否有效地改变了网络规范 和母性态度,并提高依从性,这种方法很容易扩展。此外,它可能是 复制并可能容易地应用于其他保健信息,包括接受疫苗和 营养/肥胖。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

EVE R COLSON其他文献

EVE R COLSON的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('EVE R COLSON', 18)}}的其他基金

Get Social Media and Risk-Reduction Training (GET SMART)
获得社交媒体和降低风险培训(GET SMART)
  • 批准号:
    10737283
  • 财政年份:
    2023
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Confounders for Health Outcomes Linked to education
与教育相关的健康结果的社会混杂因素
  • 批准号:
    10208913
  • 财政年份:
    2018
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Confounders for Health Outcomes Linked to education
与教育相关的健康结果的社会混杂因素
  • 批准号:
    9769835
  • 财政年份:
    2018
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Confounders for Health Outcomes Linked to education
与教育相关的健康结果的社会混杂因素
  • 批准号:
    10455441
  • 财政年份:
    2018
  • 资助金额:
    $ 69.25万
  • 项目类别:
Support via Online Social Networks to Promote safe Infant Care Practices Toward Reducing Racial Disparities in Infant Mortality (SUPERSONIC)
通过在线社交网络提供支持,促进安全的婴儿护理实践,以减少婴儿死亡率的种族差异(超音速)
  • 批准号:
    10402335
  • 财政年份:
    2014
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Media And Risk-reduction Training for Infant Care Practices (SMART)
社交媒体和婴儿护理实践风险降低培训 (SMART)
  • 批准号:
    8331024
  • 财政年份:
    2012
  • 资助金额:
    $ 69.25万
  • 项目类别:
Improving Care Giver Adherence to Recommended Infant Care Practices
提高护理人员对推荐的婴儿护理实践的遵守程度
  • 批准号:
    10611420
  • 财政年份:
    2012
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Media And Risk-reduction Training for Infant Care Practices (SMART)
社交媒体和婴儿护理实践风险降低培训 (SMART)
  • 批准号:
    8921323
  • 财政年份:
    2012
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Media And Risk-reduction Training for Infant Care Practices (SMART)
社交媒体和婴儿护理实践风险降低培训 (SMART)
  • 批准号:
    8858658
  • 财政年份:
    2012
  • 资助金额:
    $ 69.25万
  • 项目类别:
Social Media And Risk-reduction Training for Infant Care Practices (SMART)
社交媒体和婴儿护理实践风险降低培训 (SMART)
  • 批准号:
    8680277
  • 财政年份:
    2012
  • 资助金额:
    $ 69.25万
  • 项目类别:

相似海外基金

Factors and effect of visual inattention on fall accidents
视觉注意力不集中对坠落事故的影响因素及影响
  • 批准号:
    23K19000
  • 财政年份:
    2023
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Research Activity Start-up
SBIR Phase I: Comprehensive, Human-Centered, Safety System Using Physiological and Behavioral Sensing to Predict and Prevent Workplace Accidents
SBIR 第一阶段:利用生理和行为感知来预测和预防工作场所事故的综合性、以人为本的安全系统
  • 批准号:
    2321538
  • 财政年份:
    2023
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Standard Grant
Preventing Accidents in School lunch for Food Allergies: Consideration of Strategies and Development of Support Applications.
预防学校午餐中的食物过敏事故:考虑策略和开发支持应用程序。
  • 批准号:
    23K01977
  • 财政年份:
    2023
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Political Geographies of Human Accidents and Trauma Care in Mumbai's Commuter Railways
孟买通勤铁路中人类事故和创伤护理的政治地理
  • 批准号:
    ES/X006239/1
  • 财政年份:
    2022
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Fellowship
Multiscale, Multi-fidelity and Multiphysics Bayesian Neural Network (BNN) Machine Learning (ML) Surrogate Models for Modelling Design Based Accidents
用于基于事故建模设计的多尺度、多保真度和多物理场贝叶斯神经网络 (BNN) 机器学习 (ML) 替代模型
  • 批准号:
    2764855
  • 财政年份:
    2022
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Studentship
OTIMO - Applying telematics to the learner driver market through innovations in AI and behavioural intervention, to improve driving and reduce accidents.
OTIMO - 通过人工智能和行为干预创新,将远程信息处理应用于学习驾驶员市场,以改善驾驶并减少事故。
  • 批准号:
    10035763
  • 财政年份:
    2022
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Collaborative R&D
Comprehensive safety strategy to achieve reducing accidents of central venous access port catheter rapture
综合安全策略,实现减少中心静脉通路导管断裂事故
  • 批准号:
    22K17330
  • 财政年份:
    2022
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Computational Scientific Study on Mechanism of Multiphase Thermal-Hydraulic Phenomena Related to IVR in Core Disruptive Accidents
堆芯破坏性事故中与IVR相关的多相热工水力现象机理的计算科学研究
  • 批准号:
    21K04944
  • 财政年份:
    2021
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Practical application of exposure dose evaluation method by DNA damage analysis for radiation exposure accidents
DNA损伤分析照射剂量评估方法在辐射事故中的实际应用
  • 批准号:
    21H01861
  • 财政年份:
    2021
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
An Australian Pilot Study of an Injury Prediction Algorithm for Early Rescue in Word Car Accidents
澳大利亚针对世界车祸早期救援的伤害预测算法的试点研究
  • 批准号:
    21H01578
  • 财政年份:
    2021
  • 资助金额:
    $ 69.25万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了