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Psychohygienic evaluation of depression level among Ukrainian youth forced to emigrate to Canada due to the war in Ukraine

2023· article· en· W4389339918 on OpenAlexaboutno aff
Olena Kozyr, Anna V. Blagaia

Bibliographic record

VenueUkrainian Scientific Medical Youth Journal · 2023
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)EmigrationContext (archaeology)UkrainianRefugeePopulationRehabilitationMedicinePsychologyPsychiatryPolitical scienceEnvironmental healthGeographyPhysical therapy

Abstract

fetched live from OpenAlex

the ongoing war in Ukraine since 2014 has led to the forced migration of thousands ofpeople, resulting in a range of social and psychological problems, including depression. In light of this,the purpose of the research was to investigate the level of depression among youth who were forced toemigrate abroad due to the war. The study was conducted in Canada in 2023 using the Patient HealthQuestionnaire-9 of young people aged 16 to 30 years old who emigrated from Ukraine due to the war escalation on the 24th of February 2022. The PHQ-9 is a questionnaire used to assess the level of de-pression symptoms in the last two weeks based on 9 questions which show the level of the depression disorder or indicate the risks of its development. The research aims to raise awareness of the psycholog-ical well-being issue among war-displaced people between Russia and Ukraine to determine the level of depression, which allows providing practical recommendations for managing depression in the contextof migration and developing psychological support and rehabilitation programs for this population.The study’s findings suggest that a moderate level of depression, with increased levels of the moderateoption, was observed among Ukrainian refugees aged 16 to 30 years old who migrated to Canada. Theresults also showed that the number of respondents who did not have signs of depression decreased dueto the war. The average value of the sample slightly increased from 9.4 in 2022 to 10.9 in the currentstudy. However, values of 9 and 10 are borderline for distinguishing «mild» and «moderate» levels ofdepression, so it can be assumed that this year was transitional between these conditions. The resultsof studying the most popular answers to some survey questions show that problems with falling asleep,poor sleep quality or too much concern more than half of the respondents almost every day. It can beargued that the stress associated with migration and war significantly affected the quality of sleep amongyoung people. One-third of respondents reported poor appetite or overeating, which can be resolvedwith simple recommendations and advice. These findings highlight the potential need for mental healthsupport for this population. The data obtained can be useful for government agencies in Canada andUkraine, social services, psychological counsellors, and all those working with military and civilianrefugees in the territories of North America and Europe.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.113
GPT teacher head0.376
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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