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Record W2995584735 · doi:10.1124/pr.119.017772

The Psychopharmacology of Obsessive-Compulsive Disorder: A Preclinical Roadmap

2019· review· en· W2995584735 on OpenAlexaff
Henry Szechtman, Brian H. Harvey, Erik Z. Woody, Kurt L. Hoffman

Bibliographic record

VenuePharmacological Reviews · 2019
Typereview
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsMcMaster UniversityUniversity of Waterloo
FundersMedical Research CouncilServierSouth African Medical Research CouncilNational Research Foundation
KeywordsPsychopharmacologyNeurosciencePsychologyResearch Domain CriteriaDeep brain stimulationPsychotherapistBrain stimulationObsessive compulsivePsychiatryMedicineCognitionStimulation

Abstract

fetched live from OpenAlex

This review evaluates current knowledge about obsessive-compulsive disorder (OCD), with the goal of providing a roadmap for future directions in research on the psychopharmacology of the disorder. It first addresses issues in the description and diagnosis of OCD, including the structure, measurement, and appropriate description of the disorder and issues of differential diagnosis. Current pharmacotherapies for OCD are then reviewed, including monotherapy with serotonin reuptake inhibitors and augmentation with antipsychotic medication and with psychologic treatment. Neuromodulatory therapies for OCD are also described, including psychosurgery, deep brain stimulation, and noninvasive brain stimulation. Psychotherapies for OCD are then reviewed, focusing on behavior therapy, including exposure and response prevention and cognitive therapy, and the efficacy of these interventions is discussed, touching on issues such as the timing of sessions, the adjunctive role of pharmacotherapy, and the underlying mechanisms. Next, current research on the neurobiology of OCD is examined, including work probing the role of various neurotransmitters and other endogenous processes and etiology as clues to the neurobiological fault that may underlie OCD. A new perspective on preclinical research is advanced, using the Research Domain Criteria to propose an adaptationist viewpoint that regards OCD as the dysfunction of a normal motivational system. A systems-design approach introduces the security motivation system (SMS) theory of OCD as a framework for research. Finally, a new perspective on psychopharmacological research for OCD is advanced, exploring three approaches: boosting infrastructure facilities of the brain, facilitating psychotherapeutic relearning, and targeting specific pathways of the SMS network to fix deficient SMS shut-down processes. SIGNIFICANCE STATEMENT: A significant proportion of patients with obsessive-compulsive disorder (OCD) do not achieve remission with current treatments, indicating the need for innovations in psychopharmacology for the disorder. OCD may be conceptualized as the dysfunction of a normal, special motivation system that evolved to manage the prospect of potential danger. This perspective, together with a wide-ranging review of the literature, suggests novel directions for psychopharmacological research, including boosting support systems of the brain, facilitating relearning that occurs in psychotherapy, and targeting specific pathways in the brain that provide deficient stopping processes in OCD.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.136
GPT teacher head0.488
Teacher spread0.352 · 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 designNot applicable
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

Citations38
Published2019
Admission routes1
Has abstractyes

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