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How COVID-19 is Affecting Apprentices

2020· article· en· W3091892462 on OpenAlexaboutno aff
Shamaila Hassnain, Naureen Omar

Bibliographic record

VenueBIOMEDICA · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsSnowball samplingAnxietyCoronavirus disease 2019 (COVID-19)PandemicOutbreakCross-sectional studyPsychologyDemographyPublic healthComputer-assisted web interviewingMedicineEnvironmental healthClinical psychologyPsychiatryDiseaseInfectious disease (medical specialty)NursingSociology

Abstract

fetched live from OpenAlex

<p><strong>Background and Objective:</strong> Coronavirus induced disease (COVID-19) is affecting people all around the world. The rising number of deaths due to COVID-19 is not only harassing people but also causing strong emotions in adults as well as in children due to anxiety, fear and stress. The objective of this study was to assess the fears, anxiety and stress due to COVID-19 pandemic and related issues among the apprentices at various levels in different parts of world. <strong>Methods: </strong>It was a cross sectional survey design to assess the students/trainee’s immediate psychological response during COVID-19 outbreak by using an anonymous online questionnaire. A snowball sampling technique was conducted focusing general public all around the world from 3rd April 2020 till 7th April 2020. A total of N=354 participants filled the form completely. The structured questionnaire collected information on demographic data and psychological aspect of this outbreak, including extreme fear and uncertainty. <strong>Results:</strong> A total of N = 354 participants completed the questionnaire; majority were from the age group of 21–30 years. Approximately 66.4% were females and 33.6% males. Participants from Asia were 83.6% while 9.9%, 3.4%, 2.8% and 1% from America/Canada, Europe, Africa and Australia respectively. Out of n = 354 participants 59.3% were relying on health professionals for authentic source of information regarding COVID-19 while 16.4%, 15% and 5.4% considered social media, television and World Health Organization (WHO) website respectively as their authentic guide. Out of the (n = 354) participants 80.5% were afraid about health status during COVID-19 most predominantly females (66.3%) (P = 0.000). A total of 65.8% participants felt agitated or irritated in this outbreak. <strong>Conclusion:</strong> COVID-19 lockdowns are affecting both physical and mental health of students and apprentices enrolled at different levels of education. Females are more affected and concerned to their loved ones and themselves. Working norms are being maintained and responsibilities are being fulfilled despite this grave situation.</p>

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.139
GPT teacher head0.435
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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