TOPLINE:
A study confirms the uptick in psychological distress experienced by healthcare workers (HCWs) early in the COVID-19 pandemic and shows that an artificial intelligence (AI) tool can help detect work-related anxiety and depression.
METHODOLOGY:
Researchers used an AI tool to analyze deidentified psychotherapy transcripts from telehealth visits during spring 2020 for 820 HCWs (median age, 31 years; 91% female) and 820 matched non-HCWs.
Structural topic models were used to determine treatment topics from each conversation.
Anxiety was measured using the General Anxiety Disorder-7 questionnaire and depression was measured using the Patient Health Questionnaire-9.
TAKEAWAY:
More than half of HCWs and non-HCWs (56% and 52%, respectively) were diagnosed with anxiety disorders.
Depressive disorders were more common in non-HCWs than in HCWs (27% vs 8%), and trauma and stress-related disorders were more common in HCWs than in non-HCWs (36% vs 17%).
The AI tool identified three concerns that were significantly associated with moderate to severe anxiety and depression in HCWs, including working on the hospital floor and intensive care unit (P < .001), mood disturbances (P = .03), and sleep disturbances (P = .02).
In contrast, no significant associations emerged between pandemic-related topics and anxiety/depression for non-HCWs.
IN PRACTICE:
"These results suggest that natural language processing may one day become an effective screening tool for detecting and tracking anxiety and depression symptoms," senior author Naomi Simon, MD, a professor in the Department of Psychiatry at NYU Langone Health in New York City, said in a
