Evidence map›Paper›PMID 40396338›Full record

ReviewSchizophrenia bulletin2025

From Idealist to Realist-Designing and Implementing Shared Decision-Making Interventions in the Choice of Antipsychotic Prescription in People Living With Psychosis (SHAPE): A Realist Review (Part 2-Designing SDM Interventions: Optimizing Design and Local Implementation).

Ita Fitzgerald, Jo Howe, Ian Maidment, Emma Wallace, Yaara Zisman-Ilani, Mikkel Højlund, Sarah O'Dwyer, Ciara Ní Dhubhlaing, Erin K Crowley, Laura J Sahm

Abstract readReview
In one paragraph

Review in Schizophrenia bulletin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Experiential and Medical Knowledge of Shared Decision-Making: Exploring Clinician and Service User Perspectives in NHS Community Mental Health Services.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ita FitzgeraldPharmacy Department, St Patrick's Mental Health Services, Dublin 8, D08K7YW, Ireland.ORCID 0000-0002-9570-8823
Jo HoweSchool of Pharmacy, College of Health and Life Sciences, Aston University, Aston St, Birmingham B4 7ET, United Kingdom.
Ian MaidmentSchool of Pharmacy, College of Health and Life Sciences, Aston University, Aston St, Birmingham B4 7ET, United Kingdom.ORCID 0000-0003-4152-9704
Emma WallaceDepartment of General Practice, School of Medicine, University College Cork, Cork T12 YN60, Ireland.
Yaara Zisman-IlaniDepartment of Social and Behavioral Sciences, College of Public Health, Temple University, Philadelphia, PA, United States.
Mikkel HøjlundDepartment of Psychiatry Aabenraa, Mental Health Services Region of Southern Denmark, Aabenraa, Denmark.
Sarah O'DwyerDepartment of Medicine, St Patrick's Mental Health Services, Dublin D08K7YW, Ireland.
Ciara Ní DhubhlaingPharmacy Department, St Patrick's Mental Health Services, Dublin 8, D08K7YW, Ireland.
Erin K CrowleyPharmaceutical Care Research Group, School of Pharmacy, University College Cork, Cork T12 YN60, Ireland.
Laura J SahmPharmacy Department, St Patrick's Mental Health Services, Dublin 8, D08K7YW, Ireland.

Funding

Health Research Board of Ireland Emerging Clinician Scientist Award HRB ECSA 2020 002
6 · The paper itself

Abstract

backgroundShared decision-making (SDM) implementation remains limited in psychosis management, particularly within antipsychotic prescribing. When and why prescribers engage in SDM within these contexts is largely unknown. Part 2 of this 2-part realist review aimed to understand what SDM intervention strategies and local implementation contexts are responsible for successful prescriber engagement and why. STUDY

designCINAHL Plus, Cochrane Library, Embase, PsycINFO, PubMed, Scopus, Sociological Abstracts, Web of Science, and Google Scholar were searched for evidence to develop realist program theories explaining relationships between meso- and micro-level contexts and impact on prescriber behaviors. STUDY

resultsFrom 106 included documents, 5 program theories were developed explaining mechanisms responsible for increasing prescriber engagement with desired behaviors, alongside facilitative features within service delivery contexts and workforce development. Key mechanisms included reducing prescriber fear of sole responsibility for harm, reducing the perceived burden of SDM, increasing prescriber confidence in their ability to productively negotiate treatment consultations and their confidence to safely increase patient autonomy within decision-making. These mechanisms should be the focus of those interested in designing SDM interventions to increase prescriber engagement and those responsible for translating results of effective interventions into real-world settings to ensure facilitative contexts are maintained.

conclusionIntervention strategies that should be prioritized for scale-up include attempting SDM within existing therapeutic relationships, adopting a multidisciplinary team (MDT) responsibility for SDM implementation, and workforce training in skillsets required of effective SDM application. Efforts to standardize psychosis care via MDTs and systematically reduce discontinuity and fragmentation of care are required at policy-level.

Indexed as

Antipsychotic AgentsDecision Making, SharedPsychotic DisordersHumansAntipsychotic Agentsantipsychoticsdecision aidrealist reviewshared decision making

Identifiers

PMID40396338
PMCPMC12236318

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.