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A Mobile, Personalized Intervention with Real-Time Adaptation to HAART Adherence

A Mobile, Personalized Intervention with Real-Time Adaptation to HAART Adherence
实时适应 HAART 依从性的移动、个性化干预
批准号:
8213202
负责人:
Edward W Boyer
金额:
$50.9万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2015-07-31

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项目成果

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中文摘要
翻译
描述(申请人提供):HIV是一种慢性疾病,需要坚持不懈的药物治疗。因此,支持治疗依从性的干预措施可能也需要永无止境。不幸的是,大多数改善HAART坚持性的干预措施在试验结束后几周内就失去了效果。因此,我们提出了iHAART(“i$”),这是一款智能手机应用程序(“app”),它提供个性化的干预措施,包括内容和“剂量”,可实时适应兴奋剂使用者的不同HAART依从性。i$最具创新性的特点是它的依从性干预措施。第一类干预涉及从实时依从性数据获得的动态图形图像,使参与者能够监测其自身抗逆转录病毒依从性对健康的影响。第二种类型的干预是组合短信。我们将对接受HAART治疗的兴奋剂使用者进行形成性定性访谈,以确定他/她个人认为能有效促进他/她坚持治疗的基于文本的信息。我们将在动机增强疗法(MET)中构建每个人的自我生成的短信,并根据参与者希望收到的信息内容的效力来组织它们,以提高当前的依从程度。然后,我们将把消息分解为“对话状态”(例如,问候、介入、结束等)。然后,i$软件将从每个对话状态中随机选择一个项目,并将它们组合成促进HAART依从性的新文本消息。这种方法允许自动创建数百万种不同的依从性干预措施。使用这两种类型的信息,i$将不断产生新的HAART依从性干预措施,以防止干预疲劳。然后,我们将在3个月的时间内评估接受HAART治疗的兴奋剂(如甲基苯丙胺、可卡因和MDMA)使用者i$的功能和可接受性。依从性的下降将促使更频繁地提供更有效的干预措施。提高依从性可以减少主要是支持性内容的发布频率。具体目标是:1)提供一种适应性的、个性化的移动技术,以提高艾滋病毒/艾滋病患者的HAART依从性;2)评估参与者对适应性、个性化、移动技术的体验,以了解技术利用的障碍和促进因素,特别关注可用性以及可能构成干预措施潜在有效性和患者-技术关系质量基础的行动机制。创新:它将根据坚持的程度改变其干预的效力,“剂量-反应”适应性以前从未实现过。意义:i$的独特目标是长期维持HAART治疗依从性,这是HIV治疗领域一个特别尖锐的问题。影响:i$将提供持续评估和个性化反馈,以便对许多常见、难治性和昂贵的疾病采取强有力的新干预措施。
英文摘要
DESCRIPTION (provided by applicant): HIV is a chronic disease that demands unremitting adherence to medication. Interventions that support therapeutic adherence may therefore need to be unending as well. Unfortunately, most interventions to improve HAART adherence lose effectiveness within weeks of trial conclusion. We therefore propose iHAART ("i$"), a smartphone application ("app") that delivers personalized interventions with content and "dose" that adapts in real time to variable HAART adherence in stimulant users. The most innovative features of i$ are its adherence interventions. The first type of intervention involves dynamic graphical images derived from real time adherence data that allow participants to monitor the health effects of their own antiretroviral adherence. The second genre of intervention is combinatorial text messages. We will conduct formative qualitative interviews with stimulant users receiving HAART to identify text-based messages s/he personally believes would be effective at promoting adherence for her/himself. We will frame each individual's self-generated text messages in Motivational Enhancement Therapy (MET) and organize them according to potency, the content of message the participant would like to receive to improve upon a current degree of adherence. Then we will dissect messages into "dialogue states" (eg, greeting, intervention, closing, etc). i$ software will then randomly select one item from each dialogue state and combine them into new text messages that promote HAART adherence. This method allows the automated creation of millions of different adherence interventions. Using these two types of messages, i$ will continually produce fresh HAART adherence interventions to prevent intervention fatigue. We will then assess over a 3 month period the functionality and acceptability of i$ among stimulant (e.g., methamphetamine, cocaine, and MDMA) users receiving HAART. Declining adherence will trigger the more frequent delivery of interventions with greater potency. Improving adherence leads to the less frequent delivery of content that is primarily supportive. The specific aims are: 1) To provide an adaptive, personalized, mobile technology to improve HAART adherence in patients with HIV/AIDS; and 2) To evaluate participant experience with an adaptive, personalized, mobile technology to understand the barriers and facilitators of technology utilization with a specific focus on usability as well as mechanisms of action that might underlie the potential effectiveness of the interventions and quality of the patient-technology relationship. Innovation: i$ will vary the potency of its intervention according to the degree of adherence, a "dose-response" adaptability has never before been achieved. Significance: i$ uniquely targets long-term maintenance of HAART adherence, a particularly acute problem in the HIV treatment field. Impact: i$ will provide ongoing assessment and individualized feedback to enable powerful new interventions for many common, intractable, and expensive diseases. PUBLIC HEALTH RELEVANCE: HIV is a chronic disease that demands constant obedience to medication; unfortunately most interventions to improve HAART adherence lose effectiveness within months of trial conclusion. ie uniquely targets long-term maintenance of HAART adherence, a particularly problem in HIV stimulant users by offering mobile interventions that change, in real time. ie will provide ongoing assessment and individualized feedback to enable powerful new interventions for many common, challenging, and expensive diseases.
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Mentoring in Advanced mHealth Technologies and Machine Learning for HIV/Drug Abuse Research
  • 批准号:
    10529984
  • 项目类别:
  • 资助金额:
    $19.13万
  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
Mentoring in Advanced mHealth Technologies and Machine Learning for HIV/Drug Abuse Research
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    10668451
  • 项目类别:
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    $19.13万
  • 财政年份:
    2021
  • 负责人:
    Edward W Boyer
  • 依托单位:
Mentoring in Advanced mHealth Technologies and Machine Learning for HIV/Drug Abuse Research
  • 批准号:
    10469618
  • 项目类别:
  • 资助金额:
    $19.13万
  • 财政年份:
    2021
  • 负责人:
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  • 项目类别:
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  • 负责人:
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  • 依托单位:
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