Sociocultural & biobehavioral influences on pain expression and assessment

该协议措施疼痛相关的面部反应，在不同的人群，以衡量是否疼痛的非语言反应不同的生物和社会文化因素的功能。然后，我们将测量个体（包括健康志愿者和医疗服务提供者）是否注意疼痛的不同特征，或者在组内相对于组外个体对疼痛进行不同的评估，以及我们是否可以制定干预措施来减少注意力或疼痛评估中的任何偏见。 今年，我们继续为该方案的第一个子研究收集数据，并开始为子研究2和3准备刺激。第一个子研究包括大多数参与者的两次访视。在首次访视期间，我们通过资格检查表、尿液筛查、护理评估和标准临床访谈诊断来评估合格性。在第二次访问期间，我们使用视频记录和面部肌电图来测量面部对疼痛刺激的反应。我们会给病人三种伤害性刺激：电击、热痛和冷水。在2020财年，我们有19名新参与者完成了至少一次访视，16名参与者完成了所有任务（2020财年有3名受试者完成了所有任务）。这使我们有87名参与者完成了至少一次访问，64名参与者完成了两次访问。当我们有100名参与者完成两次访视时，数据收集将完成。 我们正在使用专门的软件来通过视频测量面部反应，并避免隐含的偏见，如果我们使用人类编码器，可能会影响结果。我们将测量在面部反应中是否观察到与疼痛中的性别差异相似的性别差异，以及我们是否将面部反应或性别差异的差异视为种族，民族或种族或性别的身份中心性的函数。 我们已经开始分析研究中的面部和自主数据，以建立我们的数据处理管道。 完成后，询问子研究1参与者是否希望将其图像包含在将向其他参与者显示的数据库中。选择加入该数据库的参与者的图像将被用作我们后续子研究2和3的刺激，这些子研究使用眼动追踪来测量个人（天真的参与者和医疗提供者）如何看待和判断他们认为与他们相似或不同的其他人的疼痛。通过这一点，我们希望能够深入了解疼痛中健康差异的行为介质。如果我们确定了导致感知疼痛差异的目标，我们将使用这些目标来制定干预措施，并观察个体是否可以在子研究3中提高准确性。我们已经开始从选择进入数据库的参与者中制作刺激剪辑，并正在设计子研究2和3。 显然，由于COVID 19大流行而需要停止健康志愿者研究，这是该协议数据收集进展的一个挫折。然而，我们成功地将重点转移到数据分析以及其他涉及在线数据收集的实验上。 幸运的是，我们已经获得批准恢复健康志愿者研究。我们正在修改该方案，以便在参与者亲自访问NIH之前通过安全的远程平台进行筛选和数据收集，这将减少面对面程序的持续时间，并为参与者和实验室工作人员提供保护。我们对实验室进行了改造，使参与者和实验人员位于不同的房间，并通过视频监控和对讲系统进行互动，从而使我们能够确保安全并完成子研究1，而不会因面具而模糊面部反应。 除了上面提到的数据收集和分析之外，我们还发表了一篇与这一研究领域相关的评论，其中我们认为面部反应的研究必须包括多样化的样本，特别是在人工智能正在面部数据库上进行训练的时候（Dildine & Atlas，2019）。我们还一直在准备对疼痛和歧视之间的关系进行系统性审查，并进行了几项IRB豁免的在线研究，这些研究测量了计算机生成的面部表情中的疼痛感知，这些表情也与这一领域的工作相关。

This protocol measures pain-related facial responses in a diverse population to measure whether nonverbal responses to pain vary as a function of biological and sociocultural factors. We will then measure whether individuals (both healthy volunteers and medical providers) pay attention to different features of pain or assess pain differently in in-group relative to out-group individuals, and whether we can develop interventions to reduce any biases in attention or pain assessment. This year, we continued data collection for our first sub-study on the protocol, and began to prepare stimuli for sub-studies 2 and 3. The first sub-study includes two visits for most participants. During the first visit, we assess eligibility via eligibility checklist, urine screen, nursing assessment, and a standard clinical interview diagnostic. During the second visit, we use video recording and facial electromyography to measure facial responses to painful stimuli. We administer three types of noxious stimuli: electric shock, thermal pain, and cold water. In FY20 we had 19 new participants complete at least one visit and 16 participants who completed all tasks (3 FY19 subjects completed in FY20). This places us at 87 total participants who have completed at least one visit and 64 participants who completed both visits. Data collection will be complete when we have 100 participants who have completed both visits. We are using specialized software to measure facial responses via video and to avoid implicit biases that could affect results if we used human coders. We will measure whether sex differences are observed in facial responses that are similar to sex differences in pain, as well as whether we see differences in facial responses or sex differences as a function of race, ethnicity, or identity centrality of race or sex. We have begun analyzing facial and autonomic data from the study to establish our data processing pipeline. Following completion, sub-study 1 participants are asked whether they want their images to be included in a database that will be shown to other participants. Images of participants who opt into this database will be used as stimuli for our subsequent sub-studies 2 and 3, which use eye tracking to measure how individuals (both naive participants and medical providers) view and judge pain in others that they perceive to be similar or different from them. Through this, we hope to gain insight on behavioral mediators of health disparities in pain. If we identify targets that contribute to differences in perceived pain, we will use these to develop interventions and see if individuals can improve accuracy in sub-study 3. We have begun making stimulus clips from participants who opted into the database and are in the process of designing sub-studies 2 and 3. Obviously the need to halt healthy volunteer research due to the COVID19 pandemic was a set-back for data collection progress on this protocol. However, we successfully shifted gears to focus on data analysis, as well as other experiments that involve online data collection. Fortunately we have received approval to resume healthy volunteer research. We are in the process of modifying this protocol to allow for screening and data collection through secure remote platforms prior to having participants visit NIH in person, which will reduce the duration of the face to face procedures and provide protection of both participants and laboratory staff. We have modified our experiment room so that participants and experimenters will be in different rooms and interact through a video monitoring and intercom system, thereby allowing us to ensure safety and complete sub-study 1 without obscuring facial responses due to masks. In addition to the data collection and analysis mentioned above, we published one commentary that is relevant to this line of research, in which we argued that studies of facial responses must include a diverse sample, particularly at this time when artificial intelligence is being trained on facial databases (Dildine & Atlas, 2019). We also have been preparing a systematic review on the relationship between pain and discrimination, and conducting several IRB-exempt online studies that measure perception of pain in computer generated facial expressions which are also relevant for this line of work.