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Record W2053870785 · doi:10.4236/aa.2014.43018

Cardiovascular Reactivity to Short Duration Videos in Adolescents: An Exploratory Study

2014· article· en· W2053870785 on OpenAlexaff
Julia Leclerc, Juliette Samson, Frederike Carrier-Toutant, Jacques Leclerc

Bibliographic record

VenueAdvances in Anthropology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDuration (music)Exploratory researchReactivity (psychology)PsychologyDemographyInternal medicineMedicineSociologyArtSocial science

Abstract

fetched live from OpenAlex

The objective of this study is to observe the cardiovascular changes associated to the visualization of three YouTube video sequences: humor-sad-violent in an adolescent population. Thirty-two adolescents (16 males and 16 females) were shown three YouTube one-minute sequences (humor-sad-violent). At key points during the sequences, the cardiac rate (HR) and blood pressure (BP) were recorded. A subjective perceptual evaluation of the videos was obtained. Statistical evaluation of the data was done with the Mann-Whitney test. Minor changes in HR and the diastolic blood pressure (DP) were recorded but did not prove to be statistically significant. Of statistical significance (p < 0.05), the males rated the violent sequence as more violent than the females did. There was a minor decrease of their HR and DP. An average 10 mmHg decrease in their systolic blood pressure nearly reached statistical significance (p = 0.067). In this exploratory study, exposure to a violent video sequence was associated with a decrease of the male adolescents' average systolic pressure. It is suggested that such a response may mean a relaxing effect due to this activity. Further investigation is required with a larger cohort and continuous monitoring to confirm these findings.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.371
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.329
Teacher spread0.316 · 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.

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
Published2014
Admission routes1
Has abstractyes

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