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Record W4225997491 · doi:10.2196/36959

A Nurse-Led Multimedia Intervention to Increase Patient Participation in Recovery After Knee Arthroplasty: Hybrid Type II Implementation Study

2022· article· en· W4225997491 on OpenAlexvenueno aff
Jo McDonall, Bernice Redley, Patricia M. Livingston, Anastasia Hutchinson, Richard de Steiger, Mari Botti

Bibliographic record

VenueJMIR Human Factors · 2022
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityContext (archaeology)Intervention (counseling)NursingMedicineStakeholderAcute carePatient educationQuality (philosophy)Health careMedical educationPhysical therapyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Advances in digital technology and the use of multimedia platforms to deliver information provide clinicians with a unique opportunity to develop innovative ways to consistently provide high-quality, accessible, and evidence-based information to support patient participation. Introducing new technologies into everyday acute care clinical practice can be difficult. OBJECTIVE: The aim of this paper was to provide a description of an implementation strategy and the subsequent evaluation undertaken to examine the contextual factors important to the successful adoption of new technology by nurses in the context of acute postoperative care. METHODS: Implementation of the intervention and process evaluation was undertaken in 3 phases: phase 1, preimplementation stakeholder engagement and identification of barriers and enablers to implementation; phase 2, supported implementation of the intervention; and phase 3, evaluation of uptake, usability, and acceptability of the intervention in clinical practice. RESULTS: The outcomes of the implementation of the multimedia intervention in the context of acute postoperative care were positive. Of the 104 patients in the intervention group, 103 (99%) received the intervention. All 103 patients completed the 8-item intervention questionnaire and 93.3% (97/103) were interviewed on day 3 to evaluate usability, uptake, and acceptability. Of these 97 patients, almost all (n=94, 91%) found the program easy to use and most (n=64, 62%) could view the MyStay Total Knee Replacement program as often as they wanted. The findings also suggest that the time to implement the program was minimal (5-10 minutes). Collaboration with nurses and patients before and during implementation to identify potential barriers to successful implementation of the intervention was essential to develop timely strategies to overcome these barriers. To ensure end-user engagement, careful consideration was given to nurses' views on who was responsible for facilitating this intervention. CONCLUSIONS: The findings provide evidence that the structured implementation of the multimedia intervention was robust and successful in terms of patient participant recruitment and application; however, it was difficult to assess the level of engagement by nurse clinicians with the program. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12614000340639; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12614000340639.

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)0.006
metaresearch head score (Gemma)0.009
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: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.336
Teacher spread0.320 · 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
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

Citations5
Published2022
Admission routes1
Has abstractyes

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