From the Editor

More and more, people use social media to debate current events, share personal experiences, and maybe enjoy a cat video or two. But if people are disclosing much, are they discussing suicidal thoughts? Could certain social media posts encourage people to get help?

In the first selection, Dr. Thomas Niederkrotenthaler (of the Medical University of Vienna) and his co-authors attempt to answer these questions with a new paper just published in the Australian & New Zealand Journal of Psychiatry. Drawing on more than 7.15 million tweets (from Twitter) and employing a machine learning approach, they divide content into several categories, then review volumes of calls to a suicide hotline and completed suicides. “This is the first large-scale study to suggest that daily volume of specific suicide-prevention-related social media content on Twitter corresponds to higher daily levels of help-seeking behaviour and lower daily number of suicide deaths.” We mull the paper and its implications.

Social media: more than cat videos?

In this week’s second selection, we consider a new Quick Takes podcast interview with Dr. David Castle (of the University of Toronto). Dr. Castle discusses crystal methamphetamine, a drug used more and more in Canada. Drawing on his Australian experience and noting the rise in use here, he comments: “it’s highly prevalent, highly available, highly pure and highly destructive.”

Finally, in the third selection, Dr. Jamison A. Harvey (of the Mayo Clinic) and her co-authors take a look at communication between patients and their physicians. Drawing on nearly 30,000 email messages, they consider the way patients address their physicians in a new JAMA Network Open research letter. “This is the first study to objectively identify patterns of addressing physicians through electronic messaging and may reveal potential bias. We found that women physicians… and primary care physicians were addressed by their first name more frequently.”

DG

Selection 1: “Association of 7 million+ tweets featuring suicide-related content with daily calls to the Suicide Prevention Lifeline and with suicides, United States, 2016–2018”

Thomas Niederkrotenthaler, Ulrich S. Tran, Hubert Baginski, et al.

Australian & New Zealand Journal of Psychiatry, 14 October 2022

Most studies in the field focus on news reports, but some have focused on entertainment media and social media including tweets. With regard to Twitter, a previous study specifically assessed social media contents in suicide-related tweets by high influencers (i.e. Twitter users with a large number of followers) geolocated to Toronto, Canada, over a 1-year period (July 2015–June 2016) and tested associations with suicides. Similar to findings from news media studies, tweets about a suicide by a celebrity and suicide death were associated with increases in suicides, whereas tweets on suicidal thoughts and messages of hope were associated with decreases in suicides.

All of the previous analyses assessing the associations of putatively harmful and protective media content have used human coding and/or keyword searches to classify media content. This approach means that either only a very limited number of media items can be characterized based on the human resources necessary for reliable coding or the specific meaning of keywords within the context of a post is not accounted for. Furthermore, previous approaches have typically only investigated associations with one relevant outcome, suicide. Knowledge about other relevant outcomes, particularly help-seeking, is very limited. Calling a crisis line, for example, is a rarely used indicator of help-seeking despite the fact that crisis lines such as the National Suicide Prevention Lifeline in the United States are often the most commonly referenced help service in media portrayals of suicide.

So begins a paper by Niederkrotenthaler et al.

Here’s what they did:

“We retrieved 7,150,610 suicide-related tweets geolocated to the United States and posted between 1 January 2016 and 31 December 2018. Using a specially devised machine-learning approach, we categorized posts into content about prevention, suicide awareness, personal suicidal ideation without coping, personal coping and recovery, suicide cases and other. We then applied seasonal autoregressive integrated moving average analyses to assess associations of tweet categories with daily calls to the US National Suicide Prevention Lifeline (Lifeline) and suicides on the same day.”

Here’s what they found:

  • They analyzed 7,150,610 suicide-related tweets that were geolocated to the United States.
  • Tweets by category. Awareness: 15.4%; prevention: 13.8%; suicide cases: 12.3%; suicidal ideation without coping: 2.4%; coping posts: 0.8%.
  • Tweets and calls. “Tweets about prevention were positively associated with Lifeline calls (B = 1.94…) and negatively associated with suicides (B = −0.11…).
  • Tweets and suicides. “Total number of tweets were negatively associated with calls (B = −0.01…) and positively associated with suicide, (B = 6.4 × 10−5…).”

A few thoughts:

1. This is an interesting study.

2. There is much to like here: including the use of social media and machine learning.

3. The main finding – prevention tweets were positively associated with calls for help – is interesting. The authors explain these social media posts as follows: “Tweets that focus on spreading information about a solution or an attempt to prevent suicide, including prevention at an individual (e.g. suggestion not to leave people alone in suicidal crisis situations) or public health level (e.g. safety nets on bridges). Vaguely hinting at a solution or a way of dealing with the problem is sufficient to qualify for prevention.”

4. Of course, the potential is really interesting. Ultimately, could social media posts result in real-time interventions? For instance, if a person tweets about suicide, could prevention tweets get automatically posted? (Tech companies are starting to walk down this path; try a google search for “suicide.”) Likewise, if someone spends significant time responding to tweets focused on suicide or just viewing such tweets, could they be encouraged to seek care? Over time, could machine learning allow for more customized responses (just as Amazon uses algorithms to suggest books of interest, except that we are trying to save lives)?

5. Let’s not forget: privacy concerns are real. As we gather data on people outside of the confines of provider offices, what safeguards could be put in place to ensure patient privacy?

6. Like all studies, there are limitations. The authors note several, including: “More than half of all tweets did not fit into our five categories of interest. It is possible that other groups of tweets that we considered irrelevant may have had an impact on help-seeking and/or suicide.” And is the link between tweaks and calls strong? I asked Dr. John Torous (of Harvard University) about this study. He writes: “This is interesting, but it is always hard to link correlation with causation. Many people I work with don’t use or access Twitter, so I think one has to wonder to about which segment of the population this helps the most? Still, I think this sets the stage for a very exciting prospective study that could really help us understand it.”

The full ANZJP paper can be found here:

https://journals.sagepub.com/doi/10.1177/00048674221126649

Selection 2: “Exploring crystal methamphetamine use with Dr. David Castle”

David Castle

Quick Takes, October 2022

A recent Canadian Journal of Psychiatry paper found amphetamine-related emergency department visits rose from just 1.5% to over 9.9% of all visits in just seven years; overwhelmingly, the amphetamine was crystal meth. In this episode of Quick Takes, I talk with Dr. David Castle about that drug. We discuss the impact on health care visits, the interventions available to physicians, and, yes, the Australian experience.

We highlight from the podcast.

The interview

Dr. David Castle, Director of the CAMH Centre for Complex Interventions.

Addictiveness

“Crystal meth is a very easy drug to get addicted to. The chances of re-using after you’ve used once are very high. One, it causes a very dramatic, profound increase in dopamine, which is the main reward chemical in the brain… Two, if you take it and you have an amazing experience (which people think that they do) and then you don’t take it, you can have a very nasty crash.”

Demographics

“Different groups who use include: highly educated, high-earning people who use it as a stimulant and on weekends. There’s obviously use in some communities. Men who have sex with men, for example, where it’s largely used for the enhancement of the sexual experience. And then there are people who are further down the socio-cultural strata, if I can put it delicately.”

Acute presentation

“Often people are so unwell and so agitated and so aggressive that they are brought in by police. It’s often a highly disruptive experience for everybody… including the patients themselves, their family and medical and other personnel.

“Some of the signs are grinding of the teeth and clenching of the jaw. The phenomena associated with psychosis are usually very uniform in the sense of grandiose beliefs, you can fly or the standard manic type symptoms.”

Medication options

“In terms of pharmacotherapy at St Vincent’s, we developed an algorithm where we would always offer oral medication first. We tended to use olanzapine wafers because they’re very easily dispersible and pretty safe. And also benzodiazepines. Just be aware they might have used benzos and or have quite a bit of tolerance for benzos, and there’s addictive potential. But in the short term, I think it’s quite reasonable and warranted.

“We then found if oral medication is not going to work, intramuscular haloperidol.”

The above answers have been edited for length.

The podcast can be found here, and it’s 28 minutes long:

https://www.porticonetwork.ca/web/podcasts/quick-takes/crystal-meth

Selection 3: “Patient Use of Physicians’ First (Given) Name in Direct Patient Electronic Messaging”

Jamison A. Harvey, Richard J. Butterfield, Shari A. Ochoa, et al.

JAMA Network Open, 5 October 2022

Physicians are typically formally addressed as ‘Doctor’ by patients, acknowledging the physician-patient relationship, signifying respect for physicians, and following established social norms. In a previous survey of 333 physicians, almost three-quarters of respondents reported being called by their first (given) name, with annoyance reported in 61%. A recent study revealed that having ‘DOCTOR’ identification badge labels were associated with female physicians and physicians underrepresented in medicine experiencing substantially fewer episodes of bias from misidentification. Here, we aim to determine factors that are associated with whether patients addressed physicians differently through electronic messaging.

Here’s what they did:

  • They conducted a retrospective review of patient to physician messaging through the Mayo Clinic’s electronic medical record from October 1, 2018, to September 30, 2021.
  • “Messages were evaluated using a natural language processing algorithm to identify the greeting and/or closing salutation used by patients and to classify these greetings based on formality. Available demographics of patients (age and gender) and physicians (age, gender, degree, training level, and specialty) were determined.”
  • Statistical analyses were done, including a “[m]ultilevel logistic regression analysis of first name greeting with patients nested within physicians was performed for available patient and physician demographic variables univariately and in a multivariable framework.”

Here’s what they found:

  • There were 90 830 messages from 34 829 patients. Of those, 32.5% from 14 958 patients included the physician’s name in the greeting or closing salutation.
  • Gender. “Women physicians had more than twice the odds as men to be called by their first name after adjusting for patient gender; physician age, degree, level, and specialty; and for messages sent on behalf of the patient (odds ratio [OR], 2.15…).”
  • Specialty. “Primary care physicians had approximately 50% greater odds to be called by their first name (OR, 1.48…). “
  • Age and training. “There was no difference based on patient or physician age or whether the physician was in training (resident or fellow).”

A few thoughts:

1. This is a really interesting study, drawing on data from tens of thousands of emails.

2. How to understand the results? The research letter runs with an editorial, “Jane (or Dr Doe?) Will Reply to Your Patient Portal Message Now.” (A great title, by the way.)

Drs. Lekshmi Santhosh and Leah Witt (of the University of California, San Francisco) write:

“Untitling (or uncredentialing) is a phenomenon in which an individual’s formal title is omitted in a professional context and is a subtle but important form of unconscious bias. It is a phenomenon not unique to health care, and is reported to be experienced by women from minoritized racial and ethnic groups with more frequency… Use of formal titles in medicine and many other professions is a linguistic signal of respect and professionalism.”

Dr. Lekshmi Santhosh

The editorial can be found here:

https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2797040

3. Like all studies, there are limitations. The authors note several including: “We were unable to control if physicians prefer to be addressed informally and for potential cultural, racial, or ethnic nuances in greeting structure.”

The research letter can be found here:

https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2797039

Reading of the Week. Every week I pick articles and papers from the world of Psychiatry.