Manifestations and Treatment of Alcohol Addictive Behavior under Coronavirus Disease 2019 (COVID-19)
Bibliographic record
Abstract
The topic of alcohol addiction has been on the world's radar. Since the global outbreak of COVID-19, people worldwide have been affected by COVID-19 to varying degrees, including economically, in health, and in education. In the context of COVID-19, the psychosocial strain has caused an escalation in alcohol addiction and issues such as suicide, violence, and severe alcohol dependence, leading to increased attention to alcohol addiction. This paper aims to examine the reasons for the increase in alcohol addiction (both new and relapsed) and the generalization of treatment options (pharmacological and non-pharmacological) for alcohol addiction in the context of COVID-19 through a biopsychosocial model. The mechanism of alcohol addiction involves different levels such as biological, psychological and social. This paper also discusses the advantages and disadvantages of popular online counseling in the context of the epidemic. For the individual, this paper may help enhance the future treatment of alcohol addiction to mitigate the harmful effects of alcohol addiction on the individual. This paper also provides a reference for research in related fields. More research into the treatment of alcohol addiction in the context of a large epidemic could help alleviate the suffering of patients in the future.
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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 | 0.000 | 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 | 0.001 | 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".