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CAPTURING PERSON-SPECIFIC SELF-REPORTED SUBJECTIVE EXPERIENCES AS BEHAVIORAL PREDICTORS

机译:捕捉特定于人的自我报告的主观体验作为行为预测因子

摘要

Methodologies combine emotion and data sciences. Advanced tools capture, measure, store, and analyze self-report of subjective experiences using digital applications and platforms. Patient-specific data is obtained regarding emotional or affective determinants and social determinants for generating a calculated composite score of the patient's probability of adherence or achievement relative to target outcomes, e.g. adherence to treatment plans, wellness activities, etc. for a subject individual. Internal/subjective factors are judged by self-report measures designed to validly judge tested factors based on a patient adjusting continuously-variable graphical interfaces to capture and measure subjective experiences. Emotional characteristics may include perception and intensity in each category of sicknes versus wellness, stress, depression, anxiety, pain, and feelings about most recent health provider/staff interaction (with determined intensity for choices of Delighted, Satisfied, Meh, Disappointed, Frustrated). Emotional characteristics may be considered among health, and social characteristics in measuring potential obstacles to adherence.
机译:方法组合情绪和数据科学。使用数字应用和平台捕获,测量,存储和分析主观体验的自我报告。关于情绪或情感决定因素和社会决定因素的患者特异性数据,用于产生患者相对于目标结果的计算综合或成就概率的计算综合评分。遵守主题个人的治疗计划,健康活动等。通过自我报告措施来判断内部/主观因素,旨在验证基于患者的患者进行判断,以调整连续变量的图形界面来捕获和测量主观体验。情绪特征可能包括每类患病的感知和强度与健康,压力,抑郁,焦虑,痛苦和对大多数最近的健康提供者/员工互动的感受(具有决定的强烈的选择,对高兴,满意,Meh,失望,沮丧的选择。在衡量潜在障碍的健康和社会特征中,可以考虑情绪特征。

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