Rates of Assessment of Social Media Use in Psychiatric Interviews Prior to and During COVID-19: Needs Assessment Survey
Bibliographic record
Abstract
Background Current research suggests that there is a nuanced relationship between mental well-being and social media. Social media offers opportunities for empowerment, information, and connection while also showing links with depression, high-risk behavior, and harassment. As this medium rapidly integrates into interpersonal interactions, incorporation of social media assessment into the psychiatric evaluation warrants attention. Furthermore, the COVID-19 pandemic and containment measures (ie, social distancing) led to increased dependence on social media, allowing an opportunity to assess the adaptation of psychiatric interviews in response to sociocultural changes. Objective The first aim of this study was to evaluate if general psychiatry residents and child and adolescent psychiatry fellows assessed social media use as part of the clinical interview. Second, the study examined whether changes were made to the social media assessment in response to known increase of social media use secondary to social distancing measures during the COVID-19 pandemic. Methods As part of a quality improvement project, the authors surveyed general psychiatry residents and child psychiatry fellows in a university-based training program (n=21) about their assessment of social media use in patient evaluations. Soon after the survey closed, “stay-at-home” orders related to the COVID-19 pandemic began. A subsequent survey was sent out with the same questions to evaluate if residents and fellows altered their interview practices in response to the dramatic sociocultural changes (n=20). Results Pre-COVID-19 pandemic survey results found that 10% (2/21) of respondents incorporated social media questions in patient evaluations. In a follow-up survey after the onset of the pandemic, 20% (4/20) of respondents included any assessment of social media use. Among the 15 participants who completed both surveys, there was a nonsignificant increase in the likelihood of asking about social media use (2/15, 13% vs 4/15, 27%, for pre- and during COVID-19, respectively; McNemar χ21=0.25, P=.617, Cohen d=0.33). Conclusions These small survey results raise important questions relevant to the training of residents and fellows in psychiatry. The findings suggest that the assessment of social media use is a neglected component of the psychiatric interview by trainees. The burgeoning use and diversity of social media engagement warrant scrutiny with respect to how this is addressed in interview training. Additionally, given minimal adaptation of the interview in the midst of a pandemic, these findings imply an opportunity for improving psychiatric training that incorporates adapting clinical interviews to sociocultural change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".