Can fidgeting lead to enhanced attention and emotional regulation in adult ADHD?
Can fidgeting lead to enhanced attention and emotional regulation in adult ADHD?
批准号:
10600662
负责人:
JULIE B. SCHWEITZER
金额:
$11.73万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-02 至 2024-07-31
关键词:
AdultArousalAttentionAttention deficit hyperactivity disorderBehaviorBehavioralCharacteristicsChildChildhoodClinicalCodeCognitiveDataDevicesEmotionalEmploymentEngineeringFrequenciesFutureGesturesGoalsGrainHomeHyperactivityImpairmentIndividualInformal Social ControlInterventionLaboratoriesLeadLegMachine LearningMeasuresMotorMovementNational Institute of Mental HealthPerformancePhysiologicalPopulationRecommendationRegulationResearch PersonnelSensoryShort-Term MemoryStrategic PlanningSubstance Use DisorderSurfaceSystemTestingTimeTouch sensationTraffic accidentsTranslational ResearchWorkbasecognitive enhancementcognitive functioncognitive neurosciencecognitive performancecognitive reappraisalcollegecomputer data analysiscomputer sciencedesigneconomic impactemotion regulationemotional functioningimprovedmood regulationnoradrenergicpressure sensorprocessing speedprototyperandomized controlled studyresponsesensor
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
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