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Record W4285413870 · doi:10.21272/sec.6(2).50-56.2022

The Global Socioeconomic Impact of Mental Health

2022· article· en· W4285413870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSocioEconomic Challenges · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPopulationAnxietyPandemicSocioeconomic statusPsychiatryEuropean unionGlobal mental healthPsychologySubstance abuseRelevance (law)Mood disordersPublic healthMedicineEconomic growthEnvironmental healthPolitical scienceDiseaseCoronavirus disease 2019 (COVID-19)BusinessEconomics

Abstract

fetched live from OpenAlex

This paper outlines the arguments and counterarguments within the scientific communities on the issue of common genetic factors discovered in mental disorders. The main objective of the research is to analyse the relationship between genetics and mental health. The relevance of this study by FAAVM Canada, (North America), is to help recognize that major mental health disorders share certain genetic defects. These findings may also point to apply better multidisciplinary scientific research methodologies to diagnose and treat these conditions. However, genetic factors can increase the risks of mental health issues, or make us more vulnerable to developing them, by reducing the brain’s ability to deal with or compensate for traumas and other cognitive disruptions. This research empirically confirms and theoretically proves that the results can be useful for vaccine and pharmaceutical drug development. Across the European Union (EU) region, approximately 165 million people are affected annually by mental illnesses, for the most part, anxiety, mood, and substance abuse disorders. On average, over 50% of the general population in middle-income and high-income countries will experience at least one mental illness at some point in their lives. That being said, mental illnesses are by no means limited to a minority group of predisposed persons but are a major public health challenge. These scientific attributes are in fact mandatory diagnostic criteria that exert considerable socio-economic repercussions not only for those affected but also for their families, communities, social, and employment related environments. In the first year of the Coronavirus (COVID-19) global pandemic, global frequency of anxiety and depression increased by an immense 25%, according to a scientific summary released by the World Health Organization (WHO). Mental illnesses and substance abuse disorders account for over 10.4% of the global burden of mental health diseases, owing to demographic changes and prolonged life expectancy, and were the leading cause of years lived with disability among all disease groups.

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.

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 score0.596
Threshold uncertainty score0.994

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.043
GPT teacher head0.400
Teacher spread0.356 · 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