MétaCan
Menu
Back to cohort
Record W4409242339 · doi:10.3390/bs15040487

Content Moderator Mental Health and Associations with Coping Styles: Replication and Extension of Previous Studies

2025· article· en· W4409242339 on OpenAlexaboutno aff
Ruth Spence, Jeffrey DeMarco

Bibliographic record

VenueBehavioral Sciences · 2025
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsModerationMental healthPsychologyPsychological interventionCoping (psychology)DistressQuarter (Canadian coin)PopulationClinical psychologySample (material)Applied psychologySocial psychologyPsychiatryMedicineEnvironmental health

Abstract

fetched live from OpenAlex

There is an increasing evidence base that demonstrates the psychological toll of content moderation on the employees that perform this crucial task. Nevertheless, content moderators (CMs) can be based worldwide and have varying working conditions. Therefore, there is a need for studies to be replicated to ensure that the results are robust. The current study used a large sample of commercial CMs employed by an international company to replicate the results from two previous studies that relied on an anonymous online survey. The results pertaining to mental health, wellbeing, and the effectiveness of wellbeing services for this population were mostly replicated. Over a quarter of CMs demonstrated moderate to severe psychological distress, and a quarter were experiencing low wellbeing. Further, the results suggest the potential utility for interventions that increase problem-focussed problem solving, as well as a need for the efficacy of wellbeing services to be evaluated more broadly.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.367
GPT teacher head0.547
Teacher spread0.180 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBehavioral SciencesSame topicCommunication in Education and HealthcareFrench-language works237,207