MétaCan
Menu
Back to cohort
Record W4413991402 · doi:10.3390/ijerph22091383

A Qualitative Exploration of Policy, Institutional, and Social Misconceptions Faced by Individuals with Multiple Chemical Sensitivity

2025· article· en· W4413991402 on OpenAlexaffabout
Susan Yousufzai, Elaine Psaradellis, Rohini Peris, Caroline Barakat

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsUniversité du QuébecOntario Tech University
Fundersnot available
KeywordsSensitivity (control systems)Qualitative researchPsychologyMultiple chemical sensitivitySociologySocial scienceEngineeringPsychiatry

Abstract

fetched live from OpenAlex

Multiple Chemical Sensitivity (MCS) is characterized by recurring symptoms in response to low-level chemical exposures that are typically well-tolerated by the general population. Despite the debilitating health impact of MCS, public indifference and prevailing skepticism often result in stigma, misinformation, and systemic barriers that obstruct individuals' access to essential environments. This qualitative study examined the lived experiences of individuals with MCS, focusing on how their condition is misunderstood and the factors that contribute to misconceptions about MCS. Seven focus group transcripts were analysed using thematic analysis in NVivo. Participants (aged 50-60) were drawn from various regions in Canada. One main category emerged from the analysis, centred on misconceptions influenced by policy and community factors. This category was divided into four themes, each with subcategories: (1) Psychological misattribution of MCS, (2) Healthcare and Institutional Gaps, (3) Policy Barriers, Compliance, and Resistance, and (4) Commercial Influences and Misleading Practises. These themes suggest a need for improvements in policies and transparency related to chemicals used in household and personal-care products, institutional compliance with fragrance-free guidelines, and increased awareness of MCS to reduce stigma and misconceptions. Addressing these issues can lead to adequate accommodations and support systems, which significantly improve quality of life.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.244

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.082
GPT teacher head0.413
Teacher spread0.331 · 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 designBench or experimental
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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicChemical Safety and Risk ManagementFrench-language works237,207