FW-HTF-P: Future of Work for Strength and Movement Training Professionals

FW-HTF-P：力量和运动训练专业人员的工作未来

• 批准号: 2129012
• 负责人: Conor Walsh
• 金额: $ 15万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2129012&HistoricalAwards=false
• 关键词: FW; HTF; Future; Work; Strength

This planning grant will focus on the future of work challenges for strength and movement training professionals(SMTPs) that include physical therapists, occupational therapists, and personal trainers. These workers make up a field that is essential to injury prevention and recovery, predominantly female, and 924,000 strong growing much faster than average (15-29% per year). Unfortunately, this field is currently underscored by job strain, administrative burden, and burn out. SMTPs are facing an increasing remote care trend (accelerated by the COVID pandemic), and outcome-based reimbursement has been evolving over the last decade. The future of work in this area will require versatile and affordable tools to collect objective and clear performance metrics. With advances in human strength, movement, and stability monitoring with wearable sensors, combined with machine learning there is an opportunity to drive client/patient accountability, give better insights into progress, and enrich increasing popular remote training sessions. This will give future workers in this area greater work flexibility, improve outcomes, and create more room for the human connection both trainer/therapist and client/patient draw satisfaction from. The project will leverage a recently developed technology that can track a person’s performance during strength training. It measures strength, range and speed of motion, rest time, number of reps and sets, force applied to the exercise equipment, and power. Algorithms use these data to provide detailed reports on a person’s performance with accessible visualization. This planning grant will help develop a research agenda thatincludes all the necessary convergent disciplines to transform the future of work in this area and provide the industry with a much-needed tool that promotes greater job satisfaction and reduced job strain through increased training successes. In addition, it will enable future workers in this area to be more accessible and enable more flexible access to rehabilitation, which will mean faster return to work after injury and more broadly improve wellness and reduce disease burden in the general population. This project will bring together several disciplines, including engineers, social scientists, strength and movement training scientists, and economists. The investigator team is structured to achieve multiple convergent goals. This planning grant will seek to establish a clear landscape of the work context through qualitative research including a series of worker and stakeholder interviews and review of relevant healthcare policies. It will also focus on the development of a minimum viable prototype to collect data from the appropriate body segment or strength training accessory, algorithms to appropriately interpret the sensor data, and an initial web application. Finally, it will enable the development and evaluation of a training module with SMTPs. Each of the three research thrusts – future work, future workers, and future technology – will be considered when evaluating the outcomes of the planning grant. Quantitative methods will be used where appropriate to judge things like technology performance and qualitative assessments such as interviews and standardized surveys will be used to assess the social and perception driven elements. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing design of intelligent work technologies that operate in harmony with human workers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该计划赠款将重点关注力量和运动培训专业人士（SMTP）的工作挑战的未来，包括物理治疗师，职业治疗师和私人教练。这些工人构成了一个对预防伤害和康复至关重要的领域，主要是女性，而924,000人的增长速度高于平均水平（每年15-29％）。不幸的是，该领域目前被工作压力，行政负担和耗尽所淹没。 SMTP面临着越来越多的远程护理趋势（由COVID大流行加速），在过去的十年中，基于结果的报销一直在不断发展。该领域的工作未来将需要多功能且负担得起的工具来收集客观和清晰的性能指标。随着人类力量，运动和稳定性监测的进步，可穿戴传感器，结合机器学习，有机会推动客户/患者问责制，更好地了解进步，并丰富了日益增长的流行远程培训课程。这将为这一领域的未来工人提供更大的工作灵活性，提高成果，并为人际关系培训师/治疗师和客户/患者提供更多的余地。该项目将利用最近开发的技术，该技术可以在力量训练期间跟踪一个人的性能。它可以衡量运动的强度，范围和速度，休息时间，次数和集合数量，施加到运动设备的力以及力量。算法使用这些数据以可访问的可视化提供有关人绩效的详细报告。该计划赠款将有助于制定研究议程，其中包括所有必要的收敛学科，以改变该领域的工作未来，并为行业提供急需的工具，从而通过增加培训成功来促进更高的工作满意度和减少工作压力。此外，这将使该领域的未来工人能够更容易获得，并使得更加灵活地获得康复，这意味着在受伤后更快地恢复工作，并更广泛地改善健康，并减少普通人群中伯恩的疾病。该项目将汇集几个学科，包括工程师，社会科学家，力量和运动培训科学家以及经济学。调查员团队的结构是实现多个收敛目标。该计划赠款将寻求通过定性研究（包括一系列工人和利益相关者访谈以及相关医疗保健政策的审查）来建立工作环境的清晰景观。它还将着重于开发最低可行的原型，以从适当的身体细分市场或力量训练配件，算法中收集数据，以适当解释传感器数据以及初始的Web应用程序。最后，这将使使用SMTP的培训模块的开发和评估。在评估规划赠款的结果时，将考虑三项研究推力 - 未来工作，未来的工人和未来技术。定量方法将在适当的地方使用，以判断技术绩效和定性评估，例如访谈和标准化调查，以评估社会和感知驱动因素。该项目的资助是由人类技术边界跨导向计划的未来资助，旨在通过推进与人类工人和谐相处的智能工作技术的设计，对工作环境中相互依存的人类技术伙伴关系的更深入的基本理解，这对NSF的法定任务和范围的构成了良好的支持，这些奖项对人为奖励的审查均具有良好的影响力。