Psychological Crisis Intervention for COVID-19 Lockdown Stress in Patients With Type 1 Diabetes Mellitus: Survey Study and Qualitative Analysis
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has challenged the worldviews of most people. Social isolation after the COVID-19 lockdown has not only led to economic difficulties but also resulted in adverse psychological reactions. As in most countries, including Poland, this situation has been very challenging for patients with type 1 diabetes mellitus (T1DM). In Poland, a crisis intervention team for patients with T1DM was established. The goal of the team was to provide psychological support for these patients, if needed, and to present information concerning how these patients may obtain medical consultations and prescriptions. OBJECTIVE: We aimed to analyze the psychological parameters and main emotional reactions of patients with T1DM during the COVID-19 lockdown. METHODS: An email with information concerning the possibility of having a web-based consultation with psychologists and psychiatrists and an attached set of psychological tests was sent to all patients with T1DM who were under the care of an outpatient diabetes clinic. The consultations were performed by licensed clinical psychologists and psychologists. This study was approved by the Bioethics Committee of the Jagiellonian University in Krakow, Poland. RESULTS: The patients who decided to use psychological support had statistically higher levels of anxiety (state P=.043; trait P=.022), stress (P=.001) than those of patients from the group who did not seek support. CONCLUSIONS: The presented intervention team may be perceived as an example of important and successful cooperation and communication between specialists of different fields of medicine (diabetology, psychiatry, and psychology) in a crisis situation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".