Background: Implementation fidelity refers to the degree to which an intervention or programme adheres to its original design. This paper examines implementation fidelity in the Sound Start Study, a clustered randomised controlled trial of computer-assisted support for children with speech sound disorders (SSD).
Method: Sixty-three children with SSD in 19 early childhood centres received computer-assisted support (Phoneme Factory Sound Sorter [PFSS] - Australian version). Educators facilitated the delivery of PFSS targeting phonological error patterns identified by a speech-language pathologist. Implementation data were gathered via (1) the computer software, which recorded when and how much intervention was completed over 9 weeks; (2) educators' records of practice sessions; and (3) scoring of fidelity (intervention procedure, competence and quality of delivery) from videos of intervention sessions.
Result: Less than one-third of children received the prescribed number of days of intervention, while approximately one-half participated in the prescribed number of intervention plays. Computer data differed from educators' data for total number of days and plays in which children participated; the degree of match was lower as data became more specific. Fidelity to intervention procedures, competency and quality of delivery was high.
Conclusion: Implementation fidelity may impact intervention outcomes and so needs to be measured in intervention research; however, the way in which it is measured may impact on data.
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http://dx.doi.org/10.1080/17549507.2017.1293160 | DOI Listing |
Geriatr Psychol Neuropsychiatr Vieil
December 2024
Epsylon EA 4556, Université Paul-Valéry Montpellier-3, Montpellier, France.
Despite the growing deployment of the Montessori method in nursing homes, there is no instrument to measure its implementation fidelity, limiting the interpretation of results. Our aims are to i) develop an evaluation grid for the Montessori method in nursing homes; ii) explore its sensitivity to practice heterogeneity among institutions pre-training; and iii) study its sensitivity to change after the training. Based on literature and expert opinions, we created an evaluation grid.
View Article and Find Full Text PDFBMJ Open
January 2025
University of Exeter Medical school, University of Exeter, Exeter, UK.
Objectives: To assess the feasibility of an intervention of midwifery support for antenatal pelvic floor muscle exercises (PFME) to prevent postnatal urinary incontinence (UI).
Design: Feasibility and pilot cluster randomised controlled trial. Clusters were community midwifery teams.
BMJ Open Qual
January 2025
IQ Health science department, Radboud university medical center, Nijmegen, The Netherlands
Background: Personalised outcomes forecasts (POFs) were introduced among physical and exercise therapists in the Netherlands to optimise supervised exercise therapy for patients with intermittent claudication. Yet, therapists' initial adoption and sustainable implementation of POFs can be influenced by various factors.
Objectives: The purpose of this study was to examine therapists' adoption of the POFs, their fidelity to the measurement protocol for supervised exercise therapy, and their perceived barriers and facilitators for using POFs in practice.
Cureus
January 2025
Otolaryngology-Head and Neck Surgery, College of Medicine, King Saud University, Riyadh, SAU.
The rapid evolution of generative artificial intelligence (AI) has introduced transformative technologies across various domains, with text-to-video (T2V) generation models emerging as transformative innovations in the field. This narrative review explores the potential of T2V AI generation models used in healthcare, focusing on their applications, challenges, and future directions. Advanced T2V platforms, such as Sora Turbo (OpenAI, Inc.
View Article and Find Full Text PDFFront Plant Sci
January 2025
College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, Henan, China.
The precise determination of tobacco leaf maturity is pivotal for safeguarding the taste and quality of tobacco products, augmenting the financial gains of tobacco growers, and propelling the industry's sustainable progression. This research addresses the inherent subjectivity and variability in conventional maturity evaluation techniques reliant on human expertise by introducing an innovative YOLOv10-based method for tobacco leaf maturity detection. This technique facilitates a rapid and non-invasive assessment of leaf maturity, significantly elevating the accuracy and efficiency of tobacco leaf quality evaluation.
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