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Record W2900119563 · doi:10.1186/s12885-018-4962-9

Comparison of implementation strategies to influence adherence to the clinical pathway for screening, assessment and management of anxiety and depression in adult cancer patients (ADAPT CP): study protocol of a cluster randomised controlled trial

2018· article· en· W2900119563 on OpenAlexaff
Phyllis Butow, Joanne Shaw, Heather L. Shepherd, Melanie A. Price, Lindy Masya, Brian Kelly, Nicole Rankin, Afaf Girgis, Thomas F. Hack, Philip Beale, Rosalie Viney, Haryana M. Dhillon, Joseph Coll, Patrick J. Kelly, Melanie Lovell, Peter Grimison, Tim Shaw, Tim Luckett, Jessica Cuddy, Fiona A. White

Bibliographic record

VenueBMC Cancer · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsCancerCare ManitobaUniversity of Manitoba
FundersSydney Medical SchoolCancer Council NSWUniversity of Technology SydneyUniversity of New South WalesIngham Institute for Applied Medical ResearchCancer Institute NSW
KeywordsMedicinePsychological interventionAnxietyProtocol (science)Randomized controlled trialCluster randomised controlled trialNursingPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Health service change is difficult to achieve. One strategy to facilitate such change is the clinical pathway, a guide for clinicians containing a defined set of evidence-based interventions for a specific condition. However, optimal strategies for implementing clinical pathways are not well understood. Building on a strong evidence-base, the Psycho-Oncology Co-operative Research Group (PoCoG) in Australia developed an evidence and consensus-based clinical pathway for screening, assessing and managing cancer-related anxiety and depression (ADAPT CP) and web-based resources to support it - staff training, patient education, cognitive-behavioural therapy and a management system (ADAPT Portal). The ADAPT Portal manages patient screening and prompts staff to follow the recommendations of the ADAPT CP. This study compares the clinical and cost effectiveness of two implementation strategies (varying in resource intensiveness), designed to encourage adherence to the ADAPT CP over a 12-month period. METHODS: This cluster randomised controlled trial will recruit 12 cancer service sites, stratified by size (large versus small), and randomised at site level to a standard (Core) versus supported (Enhanced) implementation strategy. After a 3-month period of site engagement, staff training and site tailoring of the ADAPT CP and Portal, each site will "Go-live", implementing the ADAPT CP for 12 months. During the implementation phase, all eligible patients will be introduced to the ADAPT CP as routine care. Patient participants will be registered on the ADAPT Portal to complete screening for anxiety and depression. Staff will be responsible for responding to prompts to follow the ADAPT CP. The primary outcome will be adherence to the ADAPT CP. Secondary outcomes include staff attitudes to and experiences of following the ADAPT CP, using the ADAPT Portal and being exposed to ADAPT implementation strategies, collected using quantitative and qualitative methods. Data will be collected at T0 (baseline, after site engagement), T1 (6 months post Go-live) and T2 (12 months post Go-live). DISCUSSION: This will be the first cluster randomised trial to establish optimal levels of implementation effort and associated costs to achieve successful uptake of a clinical pathway within cancer care. TRIAL REGISTRATION: The study was registered prospectively with the ANZCTR on 22/3/2017. Trial ID ACTRN12617000411347.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.084
GPT teacher head0.497
Teacher spread0.413 · 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 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

Citations58
Published2018
Admission routes1
Has abstractyes

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