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Record W4393276433 · doi:10.3389/falgy.2024.1352840

Can scent-detection dogs detect the stress associated with trauma cue exposure in people with trauma histories? A proof-of-concept study

2024· article· en· W4393276433 on OpenAlexaff
Laura Kiiroja, Sherry H. Stewart, Simon Gadbois

Bibliographic record

VenueFrontiers in Allergy · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyAudiologyShameClinical psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Introduction: Post-traumatic stress disorder (PTSD) is an impairing mental health condition with high prevalence among military and general populations alike. PTSD service dogs are a complementary and alternative intervention needing scientific validation. We investigated whether dogs can detect putative stress-related volatile organic compounds (VOCs) in the breath of people with trauma histories (54% with PTSD) exposed to personalized trauma cues. Methods: Breath samples were collected from 26 humans over 40 experimental sessions during a calm (control breath sample) and stressed state induced by trauma cue exposure (target breath sample). Two scent detection canines were presented with the samples in a two alternative forced choice (2AFC) discrimination and yes/no detection task. The 2AFC task assessed the dogs' ability to discriminate between the two states within the breath samples of one individual. The detection task determined their ability to generalize the target odour across different individuals and different stressful events of one individual. Signal Detection Theory was applied to assess dogs' sensitivity, specificity, precision, and response bias. Results: The dogs performed at ∼90% accuracy across all sample sets in the discrimination experiment, and at 74% and 81% accuracy, respectively, in the detection experiment. Further analysis of dog olfactory performance in relation to human donor self-reported emotional responses to trauma cue exposure suggested the dogs may have been detecting distinct endocrine stress markers. One dog's performance correlated with the human donors' self-reported fear responses and the other dog's performance correlated with the human donors' self-reported shame responses. Based on these correlations between dog performance and donor self-report measures, we speculate that the VOCs each dog was detecting likely originated from the sympathetico-adreno-medullary axis (SAM; adrenaline, noradrenaline) in the case of the first dog and the hypothalamo-pituitary-adrenal axis (HPA; glucocorticoids) in the case of the second dog. Conclusion: Our proof-of-concept study is the first to demonstrate that some dogs can detect putative VOCs emitted by people with trauma histories when experiencing distress theoretically associated with the intrusion and arousal/reactivity symptoms of PTSD. Results have potential to improve the effectiveness and training protocol of PTSD service dogs with a focus on enhancing their alert function.

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)0.004
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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