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Record W4401920276 · doi:10.1192/j.eurpsy.2024.571

The biology of mental pain: a systematic review to map the different expressions, definitions, hypotheses, experimental paradigms, investigation methods and candidate biomarkers of mental pain in human subjects

2024· review· en· W4401920276 on OpenAlexaff
E. K. Duranté, Alice Ornelas Ribeiro, L. Gaspard-Boulinc, Cédric Lemogne, Isabelle Boutron, Astrid Chevance

Bibliographic record

VenueEuropean Psychiatry · 2024
Typereview
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsPsychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Introduction Mental pain is a transdiagnostic symptom, predictive of suicide and reported as a critical outcome by patients. A previous systematic review of epidemiological and clinical research has shown a lack of consensual definition of mental pain in clinical research and high heterogeneity across the different measurement instruments of mental pain. Up today there is no systematic review synthetizing all published biological investigations on mental pain. Objectives This study aims to map the field of biological investigations of mental pain in human to identify what and how biomarkers are investigated with a meta-research approach, by providing a critical appraisal of the terms and definitions of mental pain, the studies’ hypotheses, the experimental paradigms used to induce or mimic mental pain and the measurement instruments used to measure mental pain. Methods We conducted a systematic review (compliant with PRISMA guidelines) of all primary research reporting to investigate candidate biomarkers of mental pain in human subjects as stated by the authors. We searched from inception to June 23rd, 2022, the 3 databases MEDLINE, Web of Science and EMBASE. We extracted the study characteristics (e.g., year of publication, population, etc.), the terms used for meaning mental pain, the definition of mental pain, the method to induce mental pain and its rational, the hypotheses and aims, the measurement instruments of mental pain, the candidate biomarkers, and their method of investigation. We performed descriptive statistics of the sample’s characteristics and the extracted data, a qualitative analysis of the definitions, hypothesis, aims and experimental paradigms, and a data visualization linking candidate biomarkers, experimental paradigms, and their investigation methods. Results The search retrieved 5685 papers of which we included 72 primary research publications constituting 78 distinct research studies. Only 37.5% of studies reported a definition of mental pain. 11.5% of studies did not show a measurement instrument of mental pain. The Cyberball (a social exclusion paradigm) was the most frequently used paradigm in experimental studies (62.7%). The cingulate cortex was the most frequently investigated biomarker category (15.3% of all candidate biomarkers), with fMRI as the most frequent investigation method (53.7% of all investigation methods). Conclusions The field of biological investigations on mental pain shows a marked heterogeneity of definitions, terms, hypotheses, experimental paradigms, and measurement instruments, with an over-representation of the construct of social pain and the Cyberball. These could compromise the comparison and combination of studies results in evidence synthesis and their translation into clinical practice. Disclosure of Interest None Declared

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)0.026
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.099
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.013
Bibliometrics0.0250.022
Science and technology studies0.0010.002
Scholarly communication0.0050.006
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.078
GPT teacher head0.374
Teacher spread0.296 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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