Sturgill Ronda, Martinasek Mary, Schmidt Trine, Goyal Raj
Department of Health Sciences and Human Performance, The University of Tampa, Tampa, FL, United States.
Ajivar, Tarpon Springs, FL, United States.
JMIR Form Res. 2021 Jan 5;5(1):e25372. doi: 10.2196/25372.
Emotional intelligence (EI) and mindfulness can impact the level of anxiety and depression that an individual experiences. These symptoms have been exacerbated among college students during the COVID-19 pandemic. Ajivar is an app that utilizes artificial intelligence (AI) and machine learning to deliver personalized mindfulness and EI training.
The main objective of this research study was to determine the effectiveness of delivering an EI curriculum and mindfulness techniques using an AI conversation platform, Ajivar, to improve symptoms of anxiety and depression during this pandemic.
A total of 99 subjects, aged 18 to 29 years, were recruited from a second-semester group of freshmen students. All participants completed the online TestWell Wellness Inventory at the start and end of the 14-week semester. The comparison group members (49/99, 49%) were given routine mental wellness instruction. The intervention group members (50/99, 51%) were required to complete Ajivar activities in addition to routine mental wellness instruction during the semester, which coincided with the onset of the COVID-19 pandemic. This group also completed assessments to evaluate for anxiety, using the 7-item Generalized Anxiety Disorder (GAD-7) scale, and depression, using the 9-item Patient Health Questionnaire (PHQ-9).
Study participants reported a mean age of 19.9 (SD 1.94) years; 27% (27/99) of the group were male and 60% (59/99) identified as Caucasian. No significant demographic differences existed between the comparison and intervention groups. Subjects in the intervention group interacted with Ajivar for a mean time of 1424 (SD 1168) minutes. There was a significant decrease in anxiety, as measured by the GAD-7: the mean score was 11.47 (SD 1.85) at the start of the study compared to 6.27 (SD 1.44) at the end (P<.001). There was a significant reduction in the symptoms of depression measured by the PHQ-9: the mean score was 10.69 (SD 2.04) at the start of the study compared to 6.69 (SD 2.41) at the end (P=.001). Both the intervention and comparison groups independently had significant improvements in the TestWell Wellness Inventory from pretest to posttest. The subgroups in the social awareness and spirituality inventories showed significant improvement in the intervention group. In a subgroup of participants (11/49, 22%) where the GAD-7 was available during the onset of the COVID-19 pandemic, there was an increase in anxiety from the start of the study (mean score 11.63, SD 2.16) to mid-March (ie, onset of the pandemic) (mean score 13.03, SD 1.48; P=.23), followed by a significant decrease at the end of the study period (mean score 5.9, SD 1.44; P=.001).
It is possible to deliver EI and mindfulness training in a scalable way using the Ajivar app during the COVID-19 pandemic, resulting in improvements in anxiety, depression, and EI in the college student population.
情商（EI）和正念会影响个体所经历的焦虑和抑郁程度。在新冠疫情期间，大学生群体中的这些症状有所加剧。Ajivar是一款利用人工智能（AI）和机器学习来提供个性化正念和情商训练的应用程序。
本研究的主要目的是确定使用人工智能对话平台Ajivar提供情商课程和正念技巧，以改善疫情期间焦虑和抑郁症状的有效性。
从大学新生第二学期的学生中招募了99名年龄在18至29岁之间的受试者。所有参与者在为期14周的学期开始和结束时完成了在线TestWell健康量表测试。对照组成员（49/99，49%）接受常规心理健康指导。干预组成员（50/99，51%）除了在学期中接受常规心理健康指导外，还被要求完成Ajivar活动，该学期恰逢新冠疫情爆发。该组还使用7项广泛性焦虑障碍（GAD-7）量表进行焦虑评估，并使用9项患者健康问卷（PHQ-9）进行抑郁评估。
研究参与者的平均年龄为19.9（标准差1.94）岁；该组中27%（27/99）为男性，60%（59/99）为白种人。对照组和干预组之间在人口统计学上没有显著差异。干预组的受试者与Ajivar互动的平均时间为1424（标准差1168）分钟。用GAD-7测量的焦虑有显著下降：研究开始时的平均得分为11.47（标准差1.85），而结束时为6.27（标准差1.44）（P<0.001）。用PHQ-9测量的抑郁症状有显著减轻：研究开始时的平均得分为10.69（标准差2.04），而结束时为6.69（标准差2.41）（P = 0.001）。干预组和对照组从测试前到测试后在TestWell健康量表上都有显著改善。干预组在社会意识和精神性量表的子组中显示出显著改善。在一组在新冠疫情爆发时可获得GAD-7数据的参与者（11/49，22%）中，从研究开始（平均得分11.63，标准差2.16）到3月中旬（即疫情爆发时）焦虑有所增加（平均得分13.03，标准差1.48；P = 0.23），随后在研究期结束时显著下降（平均得分5.9，标准差1.44；P = 0.001）。
在新冠疫情期间，使用Ajivar应用程序以可扩展的方式提供情商和正念训练，有可能改善大学生群体的焦虑、抑郁和情商水平。
