Implications of the COVID-19 pandemic for patients with schizophrenia spectrum disorders: narrative review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: COVID-19 was declared a pandemic in March 2020, by the World Health Organization. The pandemic has had unprecedented worldwide implications, in particular on marginalized populations. AIMS: The aim of this study is to review the impact of the pandemic on patients with schizophrenia spectrum disorders. METHOD: A number of databases were searched for this review, including PubMed, EMBASE, PsycINFO and Google Scholar. Search terms included psychosis and COVID-19, schizophrenia and COVID-19, and severe mental illness and COVID-19. We included all English language papers and preprints. The final search was done on 15 July 2020. RESULTS: Forty-seven relevant studies were identified and included in this review. Studies were summarised into five main subcategories: potential impact of the COVID-19 pandemic on physical health outcomes of patients with schizophrenia spectrum disorders, impact on mental health outcomes, review of case reports and case series to date, treatment recommendation guidelines and risk of increased prevalence of psychosis. CONCLUSIONS: Patients with schizophrenia spectrum disorders may be vulnerable to the effects of the COVID-19 pandemic. This patient population has a number of risk factors, including psychosocial adversities and illness related factors. Continuous monitoring and long-term studies of the impact of the pandemic on this patient population are required.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it