Implementation factors influencing the sustained provision of tele-audiology services: insights from a combined methodology of scoping review and qualitative semistructured interviews.

OBJECTIVES: The objectives of the current study were to (a) identify long-term tele-audiology services reported to be implemented beyond the research phase and determine whether they are sustained, (b) map the implementation process to Standards for Reporting Implementation Studies guidelines and (c) map the factors that influenced its sustainability to the Implementation Outcomes Framework (IOF) to understand the gaps from an implementation research perspective. STUDY DESIGN, SETTING AND PARTICIPANTS: This cross-sectional study included a scoping review of articles describing long-term tele-audiology services from around the world to determine the factors influencing the implementation. Six electronic databases (PubMed, Cochrane Library, Web of Science, Scopus, Google Scholar and ProQuest) were searched for literature published between 2010 and 2023. This was followed by semistructured interviews (SSIs), which were guided by the IOF. Six project implementers were interviewed to obtain an in-depth understanding of factors that influenced sustainability of these tele-audiology services. Thematic analysis of the interview transcripts was carried out using a hybrid inductive-deductive approach. RESULTS: Data were extracted from 32 tele-audiology studies included in the review, which were then mapped to 21 projects. The findings of the scoping review reveal that tele-audiology services were predominantly provided using synchronous telepractice methods. The 'professional-facilitator-patient' model was most commonly used. None of the studies reported the use of implementation research and/or outcome frameworks. Factors that influenced sustainability of tele-audiology services were identified from the combined results of the scoping review and the SSIs. These factors could be mapped to implementation outcomes of acceptability, adoption, feasibility, implementation cost and sustainability. CONCLUSION: Implementation research and/or outcome framework should be used to guide the implementation processes, its evaluation and measurement of outcomes systematically in tele-audiology service delivery. When such frameworks are used, gaps in information regarding the context influencing implementation, reporting of fidelity and adaptability measures can be addressed.

Understanding the implementation of telepractice in speech and language services using a mixed-methods approach.

Background: Telepractice emerged as a solution to overcome the challenges of access issues in the delivery of healthcare. Telepractice in speech language pathology (SLP) has existed for nearly a decade yet there is a significant knowledge gap with respect to the factors influencing the implementation of telepractice as a routine or long-term, sustained effort. This mixed-methods study aimed to identify implementation factors that influence the provision of telepractice in SLP services. Method: A mixed-methods study consisting of a scoping review and semi-structured interviews (SSI) was carried out. Articles that described telepractice in SLP were included based on an operational definition of implementation and a set of inclusion criteria. Results: Data was extracted from 11 studies that were mapped to nine projects in telepractice in SLP. The broad focus areas identified included diagnostics and evaluation, therapeutics and comprehensive assessment, management and follow-up care services. Synchronous/ real-time telepractice methods were always used for the provision of diagnostic testing or when providing therapy services using video conferencing. The ' professional-facilitator-patient' model was used most commonly followed by the ' professional-patient' model.  Barriers for long-term sustainability included inadequate initial capital investment, lack of reimbursement and payment options, low internet speed and bandwidth, resistance and hesitancy to use telepractice from the patient's end, lack of organizational policies and uniform regulations. Sustainable source of funding, having a dedicated team of professionals and technicians with clear roles and responsibilities, and inclusion of systematic planning facilitated implementation.  Conclusion: In general, telepractice in SLP was not explicitly guided by implementation science or framework. The use of implementation frameworks ensures systematic planning and feasibility assessment to inform the scale-up of implementation. Therefore, it would be worthwhile for program implementers to consider these aspects when exploring telepractice services.

On characterizing population commonalities and subject variations in brain networks.

Brain networks based on resting state connectivity as well as inter-regional anatomical pathways obtained using diffusion imaging have provided insight into pathology and development. Such work has underscored the need for methods that can extract sub-networks that can accurately capture the connectivity patterns of the underlying population while simultaneously describing the variation of sub-networks at the subject level. We have designed a multi-layer graph clustering method that extracts clusters of nodes, called 'network hubs', which display higher levels of connectivity within the cluster than to the rest of the brain. The method determines an atlas of network hubs that describes the population, as well as weights that characterize subject-wise variation in terms of within- and between-hub connectivity. This lowers the dimensionality of brain networks, thereby providing a representation amenable to statistical analyses. The applicability of the proposed technique is demonstrated by extracting an atlas of network hubs for a population of typically developing controls (TDCs) as well as children with autism spectrum disorder (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity. These hubs are then used to compare ASD and TDCs. Our method is generalizable to any population whose connectivity (structural or functional) can be captured via non-negative network graphs.

Towards a Quantified Network Portrait of a Population.

Computational network analysis has enabled researchers to investigate patterns of interactions between anatomical regions of the brain. Identification of subnetworks of the human connectome can reveal how the network manages an interplay of the seemingly competing principles of functional segregation and integration. Despite the study of subnetworks of the human structural connectome by various groups, the level of expression of these subnetworks in each subject remains for the most part largely unexplored. Thus, there is a need for methods that can extract common subnetworks that together render a network portrait of a sample and facilitate analysis of the same, such as group comparisons based on the expression of the subnetworks in each subject. In this paper, we propose a framework for quantifying the subject-specific expression of subnetworks. Our framework consists of two parts, namely subnetwork detection and reconstructive projection onto subnetworks. The first part identifies subnetworks of the connectome using multi-view spectral clustering. The second part quantifies subject specific manifestations of these subnetworks by nonnegative matrix decomposition. Positivity constraint is imposed to treat each subnetwork as a structure depicting the connectivity between specific anatomical regions. We have assessed the applicability of the framework by delineating a network portrait of a clinical sample consisting of children affected by autism spectrum disorder (ASD), and a matched group of typically developing controls (TDCs). Subsequent statistical analysis on the intra- and inter-subnetwork connections, revealed decreased connectivity in ASD group between regions of social cognition, executive functions, and emotion processing.

Functionally driven brain networks using multi-layer graph clustering.

Connectivity analysis of resting state brain has provided a novel means of investigating brain networks in the study of neurodevelpmental disorders. The study of functional networks, often represented by high dimensional graphs, predicates on the ability of methods in succinctly extracting meaningful representative connectivity information at the subject and population level. This need motivates the development of techniques that can extract underlying network modules that characterize the connectivity in a population, while capturing variations of these modules at the individual level. In this paper, we propose a multi-layer raph clustering technique that fuses the information from a collection of connectivity networks of a population to extract the underlying common network modules that serve as network hubs for the population. These hubs form a functional network atlas. In addition, our technique provides subject-specific factors designed to characterize and quantify the degree of intra- and inter- connectivity between hubs, thereby providing a representation that is amenable to group level statistical analyses. We demonstrate the utility of the technique by creating a population network atlas of connectivity by examining MEG based functional connectivity in typically developing children, and using this to describe the individualized variation in those diagnosed with autism spectrum disorder.