Changes in Psychiatric Inpatient Service Utilization During the First and Second Waves of the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has caused societal restrictions and public fear which may have impacted the pattern of seeking psychiatric care. There has generally been a decrease in the numbers seeking acute psychiatric care. It is important to investigate which groups seeking psychiatric treatment have decreased in number. The aim of our investigation was to identify which groups have a changed pattern in acute psychiatric service utilization during the first two waves of the COVID-19 pandemic. The study investigated changes in the rate and pattern of visits and hospital admissions for psychiatric disorders at a large Swedish hospital. A register-based study was conducted using administrative data on adult psychiatric emergency department visits (PEVs) and hospital admission rates. Data during the first two COVID-19 waves were compared to corresponding control periods in 2018–2019. Furthermore, a survey was performed among patients visiting the Psychiatric Emergency Department on their views of COVID-19 and acute psychiatric care. During the COVID-19 periods, PEVs were reduced overall by 16 and 15% during the first and second wave, respectively ( p < 0.001 in both cases), while the rate of admissions remained unaltered. PEVs were significantly reduced for most psychiatric diagnosis subgroups except for patients with schizophrenia and other related psychotic disorders as well as for those who required ongoing outpatient care. Most of the survey respondents disagreed that the pandemic affected their visit and about a quarter thought a video call with a doctor could have replaced their visit. In conclusion, there was a significant reduction in overall PEVs during both COVID-19 waves but this did not affect the numbers requiring admission for psychiatric inpatient care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".