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A systematic review of hyperscanning in clinical encounters

2025· review· en· W4411079423 on OpenAlexafffund
Lena Adel, Kyle T. Greenway, Guillaume Dumas, Michael Lifshitz

Bibliographic record

VenueNeuroscience & Biobehavioral Reviews · 2025
Typereview
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsUniversité de MontréalMila - Quebec Artificial Intelligence InstituteCentre Hospitalier Universitaire Sainte-JustineJewish General HospitalMontreal General Hospital
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaFonds de recherche du QuébecStudienstiftung des Deutschen VolkesUsona InstituteFondation de l'Hôpital général juifCanadian Institute for Advanced Research
KeywordsPsychologyNeuroscienceCognitive psychologyDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Therapeutic alliance is defined as the collaborative relationship between patient and therapist. Strong therapeutic alliances have been associated with positive clinical outcomes, but much remains unknown about alliance and its physiological basis. Interpersonal neural synchrony (INS) - the synchronization of neural signals between interacting individuals - is emerging as a novel lens for studying interactions with relatively objective and time-sensitive neuroimaging techniques. We searched four databases to identify studies of INS in clinical encounters. Our search yielded 161 articles, 46 met criteria for full-text review and 11 were included. The included articles reported INS across a total of 160 dyads, all published since 2018. Despite diverse methodologies, INS was observed in all studies and was often related to therapeutic outcomes. However, results were mixed regarding associations between INS and therapeutic alliance. These results highlight that, while promising, additional research is needed to elucidate the relationship between INS, therapeutic alliance and clinical outcomes. Future studies should aim to standardize methodologies, explore temporal dynamics (e.g., through longitudinal assessments), and include larger sample sizes.

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)0.003
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.234
GPT teacher head0.481
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 teacher head, not a consensus.

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

Citations9
Published2025
Admission routes2
Has abstractyes

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