Can fidgeting lead to enhanced attention and emotional regulation in adult ADHD?

坐立不安可以增强成人多动症患者的注意力和情绪调节能力吗？

• 批准号: 10064501
• 负责人: JULIE B. SCHWEITZER
• 金额: $ 41.8万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10064501
• 关键词: Accidents; Adult; Affective; Arousal; Attention; Attention deficit hyperactivity disorder; Behavior; Behavioral; Biological Markers; Boredom; Brain region; Characteristics; Child; Childhood; Clinical; Code; Cognition; Cognitive; Cues; Data; Devices; Disease; Effectiveness; Emotional; Emotional Stress; Employment; Engineering; Exploratory/Developmental Grant; Frequencies; Future; Gestures; Goals; Grain; Home environment; Human; Hyperactive behavior; Impairment; Individual; Informal Social Control; Intervention; Laboratories; Lead; Leg; Machine Learning; Measures; Mental disorders; Methods; Microprocessor; Motor; Motor Activity; Movement; National Institute of Mental Health; Occupational; Outcome; Patient Self-Report; Pattern; Performance; Physiological; Physiology; Population; Prediction of Response to Therapy; Reaction Time; Readability; Recommendation; Recovery; Regulation; Reporting; Research; Research Domain Criteria; Research Personnel; Schools; Sensory; Short-Term Memory; Strategic Planning; Stress; Substance Use Disorder; Surface; System; Tactile; Task Performances; Taxes; Testing; Therapeutic Intervention; Time; Touch sensation; Toy; Traffic accidents; Translational Research; Update; Video Recording; Work; alertness; base; citizen science; cognitive enhancement; cognitive function; cognitive neuroscience; cognitive performance; cognitive reappraisal; college; computer data analysis; computer science; cost; design; digital; economic impact; emotion regulation; emotional functioning; heart rate variability; improved; large datasets; learning strategy; mood regulation; noradrenergic; novel; pressure sensor; processing speed; prototype; randomized controlled study; response; sensor; sensorimotor system; social relationships; success; theories; young adult

Fidgeting is a highly common behavior, with excessive fidgeting associated with attention-deficit/hyperactivity disorder (ADHD). Studies from our laboratory (1) and colleagues (2) suggest physical movement can enhance cognitive performance in children with ADHD. Hyper-sensorimotor behavior may be related to impaired regulation of arousal in the noradrenergic and dopaminergic systems (3). This project will assess if frequency and characteristics of sensorimotor behavior relates to cognitive and emotional response in adults with ADHD, in a fine-grained manner, unlike other studies. We will test if intrinsic fidgeting (Aim 1) and access to a specially designed fidget device (Aim 2) modulates behavioral and physiological response in cognitively and emotionally-demanding contexts. The hype of the commercially available Fidget Cube, its competitors and fidget spinners suggest it might, but there is no systematic evidence to inform consumers, a gap, we aim to fill. ADHD is a significant problem in adulthood, with estimates of 4.4% in the population (4). It is associated with higher rates of substance use disorders, traffic accidents and employment challenges and a national annual economic impact ranging from $143 to $266 billion (5). While overt hyperactivity is mostly associated with childhood, subtler, finer-grained frequent movements (e.g., leg movements, doodling, clicking objects, tapping) are highly common in adult ADHD. Little is known about the characteristics of fidgeting in adulthood or whether it can be harnessed to enhance self-regulation with the use of an external device. Our aims are as follows: Aim 1: Assess in a randomized controlled study if a) intrinsic fidgeting and b) use of a smart fidget device improves attention, working memory, processing speed and emotional regulation in adult ADHD; Aim 2: Identify specific touch characteristics associated with cognitive and emotional regulation in adult ADHD using behavioral coding and a prototype fidget ball (developed by Co-I Isbister) with embedded pressure sensors on the fidget surface transmitting real time data to a computer for data analysis; Exploratory Aim 3: Conduct a machine learning analysis of fidgeting behavior in relation to cognitive performance and emotional regulation to: 1) automate recognition of touch features present in fidgeting in adult ADHD; 2) correlate touch sequences with cognitive performance measures and; 3) recommend fidgeting strategies that should prove effective in a given situation. This project will build upon prior work by PI Schweitzer, with her expertise in ADHD, clinical translational research and cognitive neuroscience and Co-I Isbister, with expertise in computer science and engineering, who developed sensor-enabled, smart fidget devices with the goal of improving self-regulation of mood and attention (6-9); Co-I Shapiro (10) with machine learning expertise in analyzing fidgeting behavior. This project is highly responsive to NIMH Strategic Plan Objective 3 as it will inform researchers working to develop new interventions based on behavioral and physiological markers, tailored to the individual.

坐立不安是一种非常常见的行为，过度坐立不安与注意力缺陷/多动症有关 ADHD（ADHD）。我们实验室（1）和同事（2）的研究表明，身体运动可以增强 ADHD儿童的认知表现。超感觉运动行为可能与受损 调节去甲肾上腺素能和多巴胺能系统的觉醒（3）。该项目将评估是否频率 感觉运动行为的特征与ADHD成人的认知和情绪反应有关， 与其他研究不同的是，我们将测试是否内在的坐立不安（目标1）和访问一个特殊的 设计的坐立不安设备（目标2）调节认知和 情绪化的情境商业上可用的Fidget Cube的炒作，其竞争对手和 fidget spinners认为这可能，但没有系统的证据告诉消费者，我们的目标是填补这一空白。 ADHD是成年人的一个重要问题，估计占人口的4.4%（4）。与其相关联 药物使用障碍、交通事故和就业挑战的发生率较高， 经济影响从1430亿美元到2660亿美元不等（5）。虽然明显的多动症主要与 儿童期，更微妙，更细粒度的频繁运动（例如，腿部动作、涂鸦、点击物体、轻敲） 在成人多动症中很常见关于成年期坐立不安的特征， 可以利用外部设备来增强自我调节。我们的目标如下： 目的1：在一项随机对照研究中评估a）内在坐立不安和B）使用智能坐立不安器械 改善注意力、工作记忆、处理速度和成人ADHD的情绪调节;目的2： 识别与成人ADHD认知和情绪调节相关的特定触摸特征， 行为编码和一个原型的坐立不安球（由Co-I Isbister开发）与嵌入式压力传感器， 将真实的数据传输到计算机进行数据分析;探索目标3：进行一次 坐立不安行为与认知表现和情绪调节的机器学习分析 目的：1）自动识别成人ADHD患者坐立不安时的触摸特征; 2）关联触摸序列 与认知表现的措施，3）建议坐立不安的战略，应证明有效的， 鉴于情况。该项目将建立在PI Schweitzer之前的工作基础上，她在ADHD，临床 转化研究和认知神经科学以及Co-I Isbister，拥有计算机科学和 他开发了具有传感器功能的智能坐立不安设备，目的是改善自我调节， 情绪和注意力（6-9）; Co-I Shapiro（10）在分析坐立不安行为方面具有机器学习专业知识。 该项目高度响应NIMH战略计划目标3，因为它将告知研究人员， 根据行为和生理标记，为个人量身定制新的干预措施。