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Record W3130555696 · doi:10.12688/hrbopenres.13228.1

Developing a complex intervention targeting antipsychotic prescribing to nursing home residents with dementia

2021· preprint· en· W3130555696 on OpenAlexafffund
Kieran Walsh, Stephen Byrne, Jenny McSharry, John Browne, Kate Irving, Eimir Hurley, Helen Rochford-Brennan, Carmel Geoghegan, Justin Presseau, Suzanne Timmons

Bibliographic record

VenueHRB Open Research · 2021
Typepreprint
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersAlzheimer SocietyHealth Research BoardAtlantic Philanthropies
KeywordsDementiaAntipsychoticNursing homesIntervention (counseling)NursingMedicinePsychiatryFamily medicineSchizophrenia (object-oriented programming)Internal medicine

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background</ns4:bold> : Antipsychotics are commonly prescribed to people living with dementia in nursing home settings, despite strong guideline recommendations against their use except in limited circumstances. We aimed to transparently describe the development process for a complex intervention targeting appropriate requesting and prescribing of antipsychotics to nursing home residents with dementia in Ireland, by nurses and general practitioners (GPs) respectively. </ns4:p> <ns4:p> <ns4:bold>Methods</ns4:bold> : We report the development process for the ‘Rationalising Antipsychotic Prescribing in Dementia’ (RAPID) complex intervention, in accordance with the ‘Guidance for reporting intervention development studies in health research’ (GUIDED) checklist. The UK Medical Research Council framework for developing and evaluating complex interventions guided our overall approach, incorporating evidence and theory into the intervention development process. To unpack the intervention development process in greater detail, we followed the Behaviour Change Wheel approach. Guided by our stakeholders, we conducted three sequential studies (systematic review and qualitative evidence synthesis, primary qualitative study and expert consensus study), to inform the intervention development. </ns4:p> <ns4:p> <ns4:bold>Results</ns4:bold> : The RAPID complex intervention was developed in collaboration with a broad range of stakeholders, including people living with dementia and family carers, between 2015 and 2017. The finalised RAPID complex intervention was comprised of the following three components; 1) Education and training sessions with nursing home staff; 2) Academic detailing with GPs; 3) Introduction of an assessment tool to the nursing home. </ns4:p> <ns4:p> <ns4:bold>Conclusions</ns4:bold> : This paper describes the steps used by the researchers to develop a complex intervention targeting antipsychotic prescribing to nursing home residents with dementia in Ireland, according to the GUIDED checklist. We found that the GUIDED checklist provided a useful way of reporting all elements in a cohesive manner and complemented the other tools and frameworks used. Transparency in the intervention development processes can help in the translation of evidence into practice. </ns4:p>

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0020.006
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.725
GPT teacher head0.611
Teacher spread0.114 · 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 designObservational
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

Citations14
Published2021
Admission routes2
Has abstractyes

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