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Record W3136568357 · doi:10.1186/s13012-021-01091-6

The effectiveness of generic emails versus a remote knowledge broker to integrate mood management into a smoking cessation programme in team-based primary care: a cluster randomised trial

2021· article· en· W3136568357 on OpenAlex
Nadia Minian, Sheleza Ahad, Anna Ivanova, Scott Veldhuizen, Laurie Zawertailo, Arun Ravindran, Claire de Oliveira, Dolly Baliunas, Carol Mulder, Corneliu Bolbocean, Peter Selby

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueImplementation Science · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsQueen's UniversityCanada Research ChairsUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchUniversity of TorontoCentre for Addiction and Mental Health
KeywordsMedicineMoodSmoking cessationAbstinenceRandomized controlled trialPsychological interventionmHealthFamily medicineCluster randomised controlled trialPhysical therapyPsychiatrySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge brokering is a knowledge translation approach that has been gaining popularity in Canada although the effectiveness is unknown. This study evaluated the effectiveness of generalised, exclusively email-based prompts versus a personalised remote knowledge broker for delivering evidence-based mood management interventions within an existing smoking cessation programme in primary care settings. METHODS: The study design is a cluster randomised controlled trial of 123 Ontario Family Health Teams participating in the Smoking Treatment for Ontario Patients programme. They were randomly allocated 1:1 for healthcare providers to receive either: a remote knowledge broker offering tailored support via phone and email (group A), or a generalised monthly email focused on tobacco and depression treatment (group B), to encourage the implementation of an evidence-based mood management intervention to smokers presenting depressive symptoms. The primary outcome was participants' acceptance of a self-help mood management resource. The secondary outcome was smoking abstinence at 6-month follow-up, measured by self-report of smoking abstinence for at least 7 previous days. The tertiary outcome was the costs of delivering each intervention arm, which, together with the effectiveness outcomes, were used to undertake a cost minimisation analysis. RESULTS: Between February 2018 and January 2019, 7175 smokers were screened for depression and 2765 (39%) reported current/past depression. Among those who reported current/past depression, 29% (437/1486) and 27% (345/1277) of patients accepted the mood management resource in group A and group B, respectively. The adjusted generalised estimating equations showed that there was no significant difference between the two treatment groups in patients' odds of accepting the mood management resource or in the patients' odds of smoking abstinence at follow-up. The cost minimisation analysis showed that the email strategy was the least costly option. CONCLUSIONS: Most participants did not accept the resource regardless of remote knowledge broker strategy. In contexts with an existing KT infrastructure, decision-makers should consider an email strategy when making changes to a programme given its lower cost compared with other strategies. More research is required to improve remote knowledge broker strategies. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03130998 . Registered April 18, 2017, (Archived on WebCite at www.webcitation.org/6ylyS6RTe ).

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.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.409
Teacher spread0.355 · 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