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Record W3162782552 · doi:10.3389/fphar.2021.659644

Protocol for Outcome Evaluation of Ayahuasca-Assisted Addiction Treatment: The Case of Takiwasi Center

2021· article· en· W3162782552 on OpenAlexaff
Brian Rush, Olivia Marcus, Sara Mallén García, Anja Loizaga-Velder, Gabriel Loewinger, Ariane Spitalier, Fernando Mendive

Bibliographic record

VenueFrontiers in Pharmacology · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsAyahuascaContext (archaeology)AddictionProtocol (science)Focus groupAddiction treatmentMedicineIntervention (counseling)RehabilitationPsychologyData collectionOutcome (game theory)PsychotherapistPsychiatryAlternative medicinePhysical therapyGeographySociology

Abstract

fetched live from OpenAlex

The present study describes the protocol for the Ayahuasca Treatment Outcome Project (ATOP) with a special focus on the evaluation of addiction treatment services provided through Takiwasi Center, the first ATOP study site. The goal of the project is to assess treatment outcomes and understand the therapeutic mechanisms of an Ayahuasca-assisted, integrative treatment model for addiction rehabilitation in the Peruvian Amazon. The proposed intervention protocol highlights the significance of treatment setting in the design, delivery, and efficacy of an addiction rehabilitation program that involves the potent psychedelic tea known as Ayahuasca. After describing the context of the study, we put forth details about our mixed-methods approach to data collection and analysis, with which we seek to gain an understanding of why, how, and for whom this specific ayahuasca-assisted treatment program is effective across a range of outcomes. The ATOP protocol employs qualitative research methods as a means to determine which aspects of the setting are meaningful to clients and practitioners, and how this may correlate with outcome measures. This paper delineates the core principles, methods, and measures of the overall ATOP umbrella, then discusses the role of ATOP in the context of the literature on long-term residential programs. To conclude, we discuss the strengths and limitations of the protocol and the intended future of the project.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.162
GPT teacher head0.493
Teacher spread0.331 · 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 designNot applicable
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

Citations26
Published2021
Admission routes1
Has abstractyes

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