Online Tailored Interventions & Relational Agents for Exercise and Sun Protection

在线定制干预措施

• 批准号: 7669088
• 负责人: Wayne F Velicer
• 金额: $ 55.65万
• 依托单位: UNIVERSITY OF RHODE ISLAND
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7669088
• 关键词: Adoption; Behavior; Cancer Prevention Intervention; Characteristics; Collaborations; Computers; Control Groups; Effectiveness; Effectiveness of Interventions; Environment; Exercise; Expert Systems; General Population; Goals; Individual; Internet; Intervention; Knowledge; Life Style; Malignant Neoplasms; Modeling; Multimedia; Population; Recruitment Activity; Research; Research Personnel; Research Project Grants; Rhode Island; Risk; Risk Behaviors; Risk Factors; Sampling; Series; Site; Subgroup; Sun Exposure; System; Testing; Theoretical model; Universities; Work; base; behavior change; cancer prevention; cost; design; innovation; novel strategies; population based; sedentary; sun protection

DESCRIPTION (provided by applicant): The overarching goal of this research project is to revise and enhance a multimedia computer-based multiple risk factor intervention for cancer prevention, using the internet to reach a general population. Two innovative, individualized, easily disseminated, low-cost, and interactive interventions, both for multiple behaviors (sun protection and exercise adoption), will be developed and evaluated in comparison to a control condition. The first intervention involves adapting our effective multimedia expert system interventions to the internet environment. The second intervention builds on the first with the additional inclusion of a Relational Agent, a recently developed computer-based approach to establishing a personal relationship typically missing on internet sites. Both systems will employ the same theoretical model of behavior change, the Transtheoretical Model, as the deep knowledge, and all systems will employ empirically based decision rules. The design is a 3 Group (Control, Internet, Internet plus Relational Agent) x 3 Occasions (0, 12, 24 Months) with intervention occurring during the first 12 months. A representative national sample of 1639 individuals at risk for both behaviors will be recruited. The primary aims are: (1) To develop and assess the effectiveness of a tailored internet intervention on a national sample; (2) To develop and assess the effectiveness of the internet intervention enhanced by a relational agent; and (3) To determine if the intervention with the relational agent can outperform the regular tailored internet intervention. The secondary aims are: (1) To determine if the two interventions are differentially effective with each behavior and with different subgroups, and (2) To determine if the relational agent intervention is utilized more often for increasing exercise than for sun protection. This study targets two major risk factors for cancer; is designed to treat the behaviors on a population basis, using proactive recruitment strategies; intervenes on multiple behaviors simultaneously, thereby producing greater impacts for cancer prevention; utilizes one of the most promising approaches to low cost population based interventions for health-related behavior change, namely the internet; and develops and tests a promising new approach to increasing the utilization and effectiveness of internet-based interventions, relational agents.

描述(申请人提供)：这项研究项目的总体目标是修改和加强基于计算机的多媒体多风险因素癌症预防干预，利用互联网接触到普通人群。将开发两种创新的、个性化的、易于传播的、低成本的和互动的干预措施，两者都针对多种行为(防晒和锻炼采用)，并与对照条件进行比较和评估。第一个干预措施涉及使我们的有效多媒体专家系统干预措施适应互联网环境。第二种干预建立在第一种干预的基础上，增加了关系代理，这是最近开发的一种建立个人关系的基于计算机的方法，通常在互联网网站上找不到。这两个系统将使用相同的行为改变的理论模型，即跨理论模型，作为深入的知识，所有系统将使用基于经验的决策规则。设计为3组(控制、互联网、互联网+关系代理)×3次(0、12、24个月)，干预发生在前12个月。将招募1639名有这两种行为风险的具有代表性的全国样本。主要目标是：(1)在全国样本上开发和评估定制互联网干预的有效性；(2)开发和评估由关系代理增强的互联网干预的有效性；以及(3)确定与关系代理的干预是否能够超过常规的定制互联网干预。第二个目标是：(1)确定这两种干预措施是否对每种行为和不同的亚组有不同的效果，以及(2)确定关系代理干预是否更多地用于增加锻炼而不是用于防晒。这项研究针对癌症的两个主要风险因素；旨在以人群为基础治疗行为，使用积极的招募策略；同时干预多种行为，从而对癌症预防产生更大影响；利用最有希望的低成本基于人群的干预措施之一，即互联网；并开发和测试一种有前景的新方法，以提高基于互联网的干预措施的利用率和有效性，即关系代理。