"Delayed is preferable to never." - Danish proverb
Welcome back to the blog! This summer was busy for us at Ginkgo Leaf. During the past few months, we hired a new clinician. We gave continuing education talks to clinicians on topics like how to support patients with body image changes after life-altering medical events. We also provided a free talk for caregivers of loved ones with Dementia, and got a Certified Financial Planner (CFP) on board with our team. We are now able to offer pro bono financial counseling to our patients who are struggling with medical or academic debt. As such, blogging has been delayed - but we're okay with that. It has been a busy season, and a productive one.
Now we're back with more information about medical trauma, starting with news of a study completed through the University of Birmingham. The results were released on September 23, 2024. In this study, scientists were able to analyze millions of tweets to identify Covid-19 survivors living with Posttraumatic Stress Disorder (PTSD).
The study was novel in that it turned to social media to identify early warning signs for this disorder, and it demonstrated that doing so was effective. The researchers constructed a data set of 3.96 million posts from Twitter, now known as X, from users who reported that they were COVID-positive at some point between March 2020 and November 2021. They conceptualized being infected with COVID-19 as a triggering event. They then looked for signs of trauma responses, including re-experiencing, hyperarousal, and avoidance behavior, which are hallmark symptoms of PTSD.
This study is striking for other reasons as well. It demonstrated that the global community sees medical trauma as a legitimate focus of research and clinical attention. The international group of researchers was furthermore able to show the significant mental health impact of COVID-19, and they emphasized the need for early detection and intervention for PTSD related to Covid-19 infection. Mental health clinicians clearly need to be prepared to identify and address medical trauma in treatment.
The study also highlighted the fact that we are living in an era in which companies such as X collect data that can be used to assess our collective mental health and functioning, and that this data can be analyzed using machine learning models.
Researchers are certainly taking a look at artificial intelligence (AI) and machine learning models to extend our ability to identify and assess mental health symptoms. In a 2022 study, researchers used data from a large dataset that included interviews conducted by a virtual avatar named Ellie. Ellie was presented on a television screen. She was controlled by a human operator to conduct interviews with individuals regarding their PTSD symptoms. Researchers could later analyze text collected from these interviews to determine whether PTSD was present.
Ethics boards reviewed each of these studies before they were conducted. That said, we are living at an ethical tension point between the rights of individuals to protect their privacy, and the abilities of new technologies to identify and address public health concerns. There is still considerable controversy regarding how involved AI can and should be in healthcare. In previous blog posts, we discussed the effects of rationing in healthcare. Artificial intelligence could help to address the scarcity of healthcare resources that leads to rationing. It could also be useful in reducing errors (e.g. Amazon's use of AI in its pharmacy program). Patients and providers share concerns about healthcare delivery using avatars like Ellie, however.
What do you think - how involved does AI need to be in healthcare? How can we balance privacy concerns with scarcity concerns, and perhaps move forward to create a more healing healthcare environment for everyone? And, what is it like to hear that Covid-19 infection during the initial phases of the pandemic is linked to symptoms of trauma- and stressor-related disorders such as PTSD? Let us know.
Citations:
Anees Baqir, Mubashir Ali, Shaista Jaffar, Hafiz Husnain Raza Sherazi, Mark Lee, Ali Kashif Bashir, Maryam M. Al Dabel. Identifying COVID-19 survivors living with post-traumatic stress disorder through machine learning on Twitter. Scientific Reports, 2024; 14 (1) DOI: 10.1038/s41598-024-69687-8
Jeff Sawalha, Muhammad Yousefnezhad, Zehra Shah, Matthew R. G. Brown, Andrew J. Greenshaw, Russell Greiner. Detecting Presence of PTSD Using Sentiment Analysis From Text Data. Frontiers in Psychiatry, 2022; 12 DOI: 10.3389/fpsyt.2021.811392
Comments