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Findings, limitations and new directions in tACS studies in schizophrenia research: A scoping review

2022· review· en· W4225080932 on OpenAlexaff
Adriana Farcas, Felicia Iftene

Bibliographic record

VenueJournal of Psychiatric Research · 2022
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsTranscranial alternating current stimulationSchizophrenia (object-oriented programming)Psychological interventionMEDLINEPsychologyBrain stimulationMedicinePsychiatryPsychotherapistClinical psychologyTranscranial magnetic stimulationNeuroscience

Abstract

fetched live from OpenAlex

BACKGROUND: Schizophrenia (SZ) is a severe neurodevelopmental spectrum disorder with significant consequences for the individual who is diagnosed and their family, resulting in notable system-level costs associated with the current methods of treatment. With a complex etiology, this syndrome continues to evade our thorough understanding and invites cautious analysis into how the newest research findings may translate into meaningful interventions. Recent explorations of non-invasive interventions in psychiatry suggest that transcranial alternating current stimulation (tACS) is a safe and potentially promising add-on to the current SZ treatment. METHODS: We performed a systematic literature search for tACS studies on SZ in three databases - Embase, Pubmed and Medline. The search yielded 29 titles and abstracts, of which 8 met the criteria for inclusion: experimental use of tACS on patients with SZ. RESULTS: We found 8 publications where findings from tACS were applied on participants with SZ. The most common frequencies used were theta (4.5 Hertz [Hz] and 6 Hz), alpha (10 Hz) and gamma (40 Hz). The main findings resulting from tACS delivery were: (1) decrease in auditory hallucinations; (2) decrease in negative symptoms; (3) cognitive improvement; and, (4) no change. CONCLUSIONS: This scoping review provides a highlight of current protocols used in tACS studies on SZ, their main findings and limitations, and points towards a direction for new approaches. The wide variety of objectives, protocols and assessments used by researchers demonstrates the diversified nature of research currently used in this field, suggesting the need for a more thorough exploration as results continue to emerge.

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)0.011
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0070.013
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.812
GPT teacher head0.602
Teacher spread0.210 · 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 designOther design
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

Citations10
Published2022
Admission routes1
Has abstractyes

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