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Record W4312254777 · doi:10.4103/0019-5545.341562

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2022· article· en· W4312254777 on OpenAlexaboutno aff
Alisha Nagar, Manchala Hrishikesh Giriprasad

Bibliographic record

VenueIndian Journal of Psychiatry · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyPsychologyFlexibility (engineering)Work (physics)Quarter (Canadian coin)Informed consentIndex (typography)Medical educationMedicineAlternative medicineManagementPsychiatryEngineeringComputer scienceWorld Wide WebHistory

Abstract

fetched live from OpenAlex

INTRODUCTION: WFH (work from home) is the today’s new normal. It has changed industry dynamics and given the ease and flexibility of being at office remotely, though it compromises on the traditional boundary between work-life balance. Since the beginning of the pandemic in 2020, the pluses and minuses have been debated extensively and now with gradual attempts of return to normalcy, an important question arises for companies and their employees whether WFH is the ‘semi-vacation’ like boon it seemed to be or it is like that dreaded Monday which doesn’t seem to end ever after work hours. AIMS: To study the perceived stress and anxiety in I.T. professionals who are working from home METHODOLOGY: The study was initiated after taking approval from institutional ethics committee, Osmania Medical college. Written informed consent was obtained from participants and data was collected using google forms from various I.T. professionals who are working from home. Perceived Stress Questionnaire (PSQ) and Hamilton Anxiety Rating Scale(HAM-A) were included in the google form. Data analysis was done using SPSS software. RESULTS: A quarter of the participants had PSQ Index greater than 0.5 suggesting higher perceived stress levels. As per HAM-A, about 60% participants had Mild Anxiety, less than 20% had moderate anxiety, 10% scoring in the range of moderate to severe anxiety and about 5% had severe anxiety.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.022
GPT teacher head0.237
Teacher spread0.215 · 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 designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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