Digital Engagement Strategy and Health Care Worker Mental Health: A Randomized Clinical Trial.

Importance: The health care workforce continues to experience high rates of depression and anxiety. Finding ways to effectively support the mental health and well-being of health care workers is challenging. Objective: To test the effectiveness of remote, pushed digital assessments and engagement to improve depression and anxiety among health care workers compared with usual care. Design, Setting, and Participants: This was a 9-month randomized clinical trial with a 6-month intervention period. Participants were health care workers with self-reported daily access to a smartphone and at least 4 clinical hours per week. Participants were randomized to usual care or the intervention between January 2022 and March 2023. Data analyses were conducted between May and July 2023. Interventions: All participants completed baseline, 6-month, and 9-month mental health, well-being, and burnout assessments. The control group had open access to a web-based mental health platform. Participants in the intervention group received monthly text messaging about mental health, mental health assessments, and linkages to care. Main Outcomes and Measures: The primary outcomes were mean change in depression and anxiety scores at 6 months from baseline. Secondary outcomes include mean change in well-being, burnout, and self-reported workplace productivity. Results: In this study, 1275 participants were randomized (642 [50.4%] to the intervention group and 633 [49.6%] to control group). Participants had a mean (SD) age of 38.6 (10.9) years, 1063 participants (83.4%) were female, 320 (25.1%) self-identified as Black, and 793 (62.2%) self-identified as White. Across the groups, the mean difference in depression score was significantly different at 6 months (-0.96 [95% CI, -1.52 to -0.40]) and at 9 months (-1.14 [95% CI, -1.69 to -0.58]). The mean difference in anxiety score from baseline to 6 months was statistically significantly larger for those in the intervention group vs usual care (-0.71 [95% CI, -1.25 to -0.17]) and held true at 9 months (-1.06 [95% CI, -1.59 to -0.52]). Conclusions and Relevance: In a trial of health care workers, a proactive digital engagement strategy, including pushed text messaging, mobile mental health assessments, and connection to care, improved depression and anxiety over a 6-month period compared with simply making the same resources available for individuals to find and use. Trial Registration: ClinicalTrials.gov Identifier: NCT05028075.

Characterizing Responses to COVID-19 Vaccine Promotion on TikTok.

PURPOSE: The Alabama Department of Public Health (ADPH) sponsored a TikTok contest to improve vaccination rates among young people. This analysis sought to advance understanding of COVID-19 vaccine perceptions among ADPH contestants and TikTok commenters. APPROACH: This exploratory content analysis characterized sentiment and imagery in the TikTok videos and comments. Videos were coded by two reviewers and engagement metrics were collected for each video. SETTING: Publicly available TikTok videos entered into ADPH's contest with the hashtags #getvaccinatedAL and #ADPH between July 16 - August 6, 2021. PARTICIPANTS: ADPH contestants (n = 44) and TikTok comments (n = 502). METHOD: A content analysis was conducted; videos were coded by two reviewers and engagement metrics was collected for each video (e.g., reason for vaccination, content, type of vaccination received). Video comments were analyzed using VADER, a lexicon and rule-based sentiment analysis tool). RESULTS: Of 44 videos tagged with #getvaccinatedAL and #ADPH, 37 were related to the contest. Of the 37 videos, most cited family/friends and civic duty as their reason to get the COVID-19 vaccine. Videos were shared an average of 9 times and viewed 977 times. 70% of videos had comments, ranging from 0-61 (mean 44). Words used most in positively coded comments included, "beautiful," "smiling face emoji with 3 hearts," "masks," and "good.;" whereas words used most in negatively coded comments included "baby," "me," "chips," and "cold." CONCLUSION: Understanding COVID-19 vaccine sentiment expressed on social media platforms like TikTok can be a powerful tool and resource for public health messaging.

Crowdsourced Community Support Resources Among Patients Discharged From the Emergency Department During the COVID-19 Pandemic: Pilot Feasibility Study.

BACKGROUND: The COVID-19 pandemic has placed strains on communities. During this public health crisis, health systems have created remote methods of monitoring symptom progression and delivering care virtually. OBJECTIVE: Using an SMS text message-based system, we sought to build and test a remote model to explore community needs, connect individuals to curated resources, and facilitate community health worker intervention when needed during the pandemic. The primary aims of this pilot study were to establish the feasibility (ie, engagement with the text line) and acceptability (ie, participant ratings of resources and service) of delivering automated well-being resources via smartphone technology. METHODS: Eligible patients (aged 18 years or older, having a cell phone with SMS text messaging capability, and recently visited the emergency department) were identified using the electronic health record. The patients were consented to enroll and begin receiving COVID-19-related information and links to community resources. We collected open-ended and close-ended resource and mood ratings. We calculated the frequencies and conducted a thematic review of the open-ended responses. RESULTS: In 7 weeks, 356 participants were enrolled; 13,917 messages were exchanged including 333 resource ratings (mean 4) and 673 well-being scores (mean 6.8). We received and coded 386 open-ended responses, most of which elaborated upon their self-reported mood score (29%). Overall, 77% (n=274) of our participants rated the platform as a service they would highly recommend to a family member or friend. CONCLUSIONS: This approach is designed to broaden the reach of health systems, tailor to community needs in real time, and connect at-risk individuals with robust community health support.

Characterizing COVID-19 Content Posted to TikTok: Public Sentiment and Response During the First Phase of the COVID-19 Pandemic.

PURPOSE: The purpose of this study was to characterize COVID-19 content posted by users and disseminated via TikTok, a social media platform that has become known largely as an entertainment platform for viral video-sharing. We sought to capture how TikTok videos posted during the initial months of the COVID pandemic changed over time as cases accelerated. METHODS: This study is an observational analysis of sequential TikTok videos with #coronavirus from January to March 2020. Videos were independently coded to assess content (e.g., health relatedness, humor, fear, empathy), misinformation, and public sentiment. To assess engagement, we also codified how often videos were shared relative to their content. RESULTS: We coded 750 videos and approximately one in four videos tagged with #coronavirus featured health-related content such as featuring objects such as face masks, hand sanitizer, and other cleaning products. Most videos evoked "humor/parody," whereas 15% and 6% evoked "fear" and "empathy", respectively. TikTok videos posted in March 2020 had the largest number of shares and comments compared with January and February 2020. The proportion of shares and comments for "misleading and incorrect information" featured in videos was lower in March than in January and February 2020. There was no statistical difference between the share and comment counts of videos coded as "incorrect/incomplete" and "correct" over the entire time period. CONCLUSIONS: Analyzing readily available social media platforms, such as TikTok provides real-time insights into public views, frequency and types of misinformation, and norms toward COVID-19. Analyzing TikTok videos has the potential to be used to inform public health messaging and public health mitigation strategies.