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Record W4417170494 · doi:10.2196/76013

The Effect of Semaglutide With Lifestyle Intervention on the Physical Health of Patients Treated With Antipsychotic Drugs in a Secure Mental Health Setting: Protocol for an Uncontrolled Pretest-Posttest Pilot Mixed Methods Study

2025· article· en· W4417170494 on OpenAlexvenueno aff
Kristina Brenisin, Florence‐Emilie Kinnafick, James A. King, Louise Millard, Donna Arya, Elizabeth Hodgson, Michelle Huggins, Andrew Simmons-Roberts, Martin O'Dowd, Nick Rayment, Pankaj Shah, Kieran C. Breen

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSemaglutideMental healthPhysical healthIntervention (counseling)AntipsychoticObesityHealth coachingProtocol (science)SeclusionMental illness

Abstract

fetched live from OpenAlex

Background: Antipsychotic-induced weight gain is a common side effect of antipsychotic drug treatment, particularly with second-generation medications such as clozapine and olanzapine. Weight gain in patients undergoing antipsychotic therapies is a significant concern, often compounded by factors related to their condition that can be particularly challenging in a secure care setting. While there is significant evidence to support the benefits of semaglutide, one of the available glucagon-like peptide-1 receptor agonists, in promoting weight loss for those who have a general weight-related health issue and meet the referral criteria for specialist services, it is unclear whether it will be as successful in people who have specifically gained weight due to medication-associated side effects and who reside in a secure care setting. Objective: This study aims to assess the impact of semaglutide in combination with a lifestyle behavior change intervention on the physical health measures of patients in a secure setting who have atypical antipsychotic-induced weight gain and identify enhancements to the intervention, specifically geared toward improving adherence and acceptability from both staff and patient perspectives. Methods: This 2-year uncontrolled pretest-posttest pilot study aims to recruit 20 inpatient participants. Adult patients of any diabetic status with a minimum BMI of 35.0 kg/m2 (or a BMI of 32.5 kg/m2 for people from South Asian, Chinese, other Asian, Middle Eastern, Black African, or African-Caribbean descent) who are receiving inpatient treatment and are treated with either olanzapine or clozapine will be eligible for inclusion in the study. Patients will receive semaglutide (Wegovy) at a maintenance dose of 2.4 mg once a week for 2 years. All participants will also receive a lifestyle behavior change intervention. Results: The findings will reveal whether the format of the interventional approach is both sustainable and effective for adult patients diagnosed with severe mental illness and living with obesity who are currently residing in a secure mental health setting. Implementation changes that could improve the acceptability of and adherence to the intervention will be explored. Conclusions: This research should be beneficial for patients with severe mental illness who are living with obesity and are residing in a secure setting as the findings may ultimately reduce the mortality risk in this patient group.

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)0.015
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.010
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0250.004

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 head0.077
GPT teacher head0.558
Teacher spread0.480 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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
Published2025
Admission routes1
Has abstractyes

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