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Record W4390672332 · doi:10.9734/jammr/2023/v35i245345

Effect of Tobacco-Smoking on Cognitive Function among Young Adults in a Tertiary Care Hospital of North India-A Pilot Study

2023· article· en· W4390672332 on OpenAlexaboutno aff
Vishal Jindal, Bharat Udey, Jagriti Bhatia, Jawahar Singh, Gurvinder Singh

Bibliographic record

VenueJournal of Advances in Medicine and Medical Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsnot available
FundersAll-India Institute of Medical Sciences
KeywordsMontreal Cognitive AssessmentNeurocognitiveMedicineCognitionNicotinePopulationDepression (economics)PsychiatryMemory spanClinical psychologyCognitive impairmentEnvironmental health

Abstract

fetched live from OpenAlex

Introduction: Around 25% of the world's population uses tobacco, with smoking being the most common form. Smoking is linked to long-term health issues, respiratory, cardiovascular, malignancies, neuropsychological dysfunction, and increased risk of depression and cognitive decline. The study aimed to compare non-smokers and tobacco smokers to assess cognitive function impact, hypothesizing smokers have poorer cognitive function. Methodology: This cross-sectional study involved 50 young adults, 25 smokers and 25 non-smokers, in a psychiatry outpatient department at AIIMS Bathinda, Punjab, India. Participants were healthy individuals, without serious medical conditions, drug dependence, or significant brain trauma. The study was approved by the Institutional Ethics Committee. Cognitive functions were assessed using Montreal cognitive assessment (MoCA) (7.1 version) and Fagerstrom Test was used to assess severity of Nicotine dependence among smokers. A p value <0.05 was considered statistically significant. Results: Sample consisted of 25 male smokers and 25 non-smokers, with 64% aged 22-24 years. Both groups were comparable in in terms of age, education and socioeconomic status. There was no statistically significant difference in cognitive function (MoCA) across demographic profile of subjects. In comparison to tobacco smokers, non-users had a higher mean MoCA score (22.12 vs. 22.08). Abstraction and recall were significantly impaired (p values 0.048 and 0.007, respectively) in tobacco smokers. There was a significant association between cognitive function (MoCA) and nicotine dependency severity (Fagerstorm Test; p=0.026) among tobacco users. Conclusion: Tobacco smoking increases the risk of neurocognitive impairment, in young adults. The degree of smoking has an adverse effect on individuals' cognitive performance. Implications: Young adults frequently use tobacco, especially in the form of smoking. Smoking tobacco is thought to enhance performance and attention. However, the current study discovered that it was linked to diminished cognitive function in the areas of recall and attention. Additionally, smokers' cognition is considerably impaired due to the severity of their nicotine dependence. The study implies that in order to understand the relationship between tobacco smoking and cognitive functions, large-scale, prospective investigations are necessary. Additionally, including radiological evaluation of brain functions using functional MRI may provide clearer evidence of the areas of the brain affected by tobacco use.

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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.511
Teacher spread0.449 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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