Audiology and Speech Pathology - Research Publications
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ItemNo Preview AvailableArtificial Intelligence Education for the Health Workforce: Expert Survey of Approaches and Needs(JMIR PUBLICATIONS, INC, 2022-04-04)BACKGROUND: The preparation of the current and future health workforce for the possibility of using artificial intelligence (AI) in health care is a growing concern as AI applications emerge in various care settings and specializations. At present, there is no obvious consensus among educators about what needs to be learned or how this learning may be supported or assessed. OBJECTIVE: Our study aims to explore health care education experts' ideas and plans for preparing the health workforce to work with AI and identify critical gaps in curriculum and educational resources across a national health care system. METHODS: A survey canvassed expert views on AI education for the health workforce in terms of educational strategies, subject matter priorities, meaningful learning activities, desired attitudes, and skills. A total of 39 senior people from different health workforce subgroups across Australia provided ratings and free-text responses in late 2020. RESULTS: The responses highlighted the importance of education on ethical implications, suitability of large data sets for use in AI clinical applications, principles of machine learning, and specific diagnosis and treatment applications of AI as well as alterations to cognitive load during clinical work and the interaction between humans and machines in clinical settings. Respondents also outlined barriers to implementation, such as lack of governance structures and processes, resource constraints, and cultural adjustment. CONCLUSIONS: Further work around the world of the kind reported in this survey can assist educators and education authorities who are responsible for preparing the health workforce to minimize the risks and realize the benefits of implementing AI in health care.
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ItemUse, and acceptability, of digital health technologies in musculoskeletal physical therapy: A survey of physical therapists and patients(WILEY, 2022-09)OBJECTIVES: Determine (a) frequency of digital health use to obtain/record clinical information (pre-COVID-19); (b) willingness to use digital technologies among physical therapists and patients with musculoskeletal conditions. METHODS: 102 physical therapists, and 103 patients were recruited in Australia. An electronic survey ascertained (a) demographic/clinical characteristics, (b) frequency of methods to obtain and record clinical information; (c) willingness to use digital technologies to support musculoskeletal care. RESULTS: Physical therapists mostly used non-digital methods to obtain subjective (e.g., face-to-face questioning, n = 98; 96.1%) and objective information (e.g., visual estimation, n = 95; 93.1%). The top three digital health technologies most frequently used by therapists: photo-based image capture (n = 19; 18.6%), accessing information logged/tracked by patients into a mobile app (n = 14; 13.7%), and electronic systems to capture subjective information that the patient fills in (n = 13; 12.7%). The top three technologies used by patients: activity trackers (n = 27; 26.2%), logging/tracking health information on mobile apps or websites (n = 12; 11.7%), and entering information on a computer (n = 12; 7.8%). Physical therapists were most willing to use technologies for: receiving diagnostic imaging results (n = 99; 97.1%), scheduling appointments (n = 92; 90.2%) and capturing diagnostic results (n = 92; 90.2%). Patients were most willing to use technologies for receiving notifications about health test results (n = 91; 88.4%), looking up health information (n = 83; 80.6%) and receiving personalised alerts/reminders (n = 80; 77.7%). CONCLUSIONS: Physical therapists and patients infrequently use digital health technologies to support musculoskeletal care, but expressed some willingness to consider using them for select functions.
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ItemNo Preview AvailableDigital Health Interventions in Physiotherapy: Development of Client and Health Care Provider Survey Instruments(JMIR PUBLICATIONS, INC, 2021-07)BACKGROUND: The advancement of digital health has widened the scope of technology use across multiple frontiers of health care services, including personalized therapeutics, mobile health, eHealth record management, and telehealth consultations. The World Health Organization (WHO) responded to this in 2018 by publishing an inaugural broad classification framework of digital health interventions (DHIs) used to address contemporary health system needs. OBJECTIVE: This study aims to describe the systematic development of dual survey instruments (clinician and patient) to support data collection, administered in a physiotherapy setting, about perceptions toward DHIs. This is achieved by adapting the WHO framework classification for DHIs for application in real-world research. METHODS: Using a qualitative item review approach, WHO DHI descriptors were adapted and refined systematically to be used in a survey form. This approach was designed to align with the processes of delivering and receiving care in clinical practice, using musculoskeletal physiotherapy as a practical case scenario. RESULTS: Complementary survey instruments (for health care providers and clients) were developed by adapting descriptor items. These instruments will be used in a larger study exploring the willingness of physiotherapists and patients to use digital technologies in the management of musculoskeletal conditions. CONCLUSIONS: This study builds on the WHO-standardized DHI framework. We developed dual novel survey instruments by adapting and refining the functions of DHIs. These may be deployed to explore the perceived usefulness and application of DHIs for different clinical care functions. Researchers may wish to use these survey instruments to examine digital health use systematically in a variety of clinical fields or technology scenarios in a way that is standardized and generalizable.
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ItemTalking to Toddlers: Drawing on Mothers' Perceptions of Using Wearable and Mobile Technology in the Home(IOS PRESS, 2017)BACKGROUND: Mother-child interactions often give rise to opportunities for early language learning in the context of everyday life. Persuasive technology has the potential to influence maternal language behaviours in the home and promote mothers' active engagement in the development of their children's communication skills. AIM: This paper explored maternal perceptions regarding the use of a language tracking wearable (Language Environment Analysis; LENA) device and a parent education smartphone application in an 8-week trial with their young children. METHODS: Mother/child dyads were enrolled in a feasibility trial designed to obtain objective auditory and linguistic data from each child's naturalistic settings (Control Condition), provide feedback to mothers about their child's home language environment (LENA Feedback Condition), and to explore effectiveness of an app designed to promote meaningful parent/child interactions during daily routines (LENA Feedback and App Condition). RESULTS AND DISCUSSION: The majority of mothers (80%) who participated in the trial reported a preference for using the mobile app and/or LENA technology again. Maternal responses during this pilot informed the design of an ongoing, prospective language intervention study for parents and their young children with significant hearing loss.
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ItemLong term communication outcomes for children receiving cochlear implants younger than 12 months: A multi-centre study(Wolters Kluwer, 2017)Objective: Examine the influence of age at implant on speech perception, language and speech production outcomes in a large unselected paediatric cohort. Study Design: This study pools available assessment data (collected prospectively and entered into respective databases from 1990 to 2014) from three Australian centres. Patients: Children (N=403) with congenital bilateral severe to profound hearing loss who received cochlear implants under 6 years of age (excluding those with acquired onset of profound hearing loss after 12 months, those with progressive hearing loss and those with mild/moderate/severe additional cognitive delay/disability). Main Outcome Measure(s): Speech Perception; open-set words (scored for words and phonemes correct) and sentence understanding at school entry and late primary school time points. Language; PLS and PPVT standard score equivalents at school entry, CELF standard scores. Speech Production; DEAP percentage accuracy of vowels, consonants, phonemes-total and clusters and percentage word-intelligibility at school entry. Results: Regression analysis indicated a significant effect for age-at-implant for all outcome measures. Cognitive skills also accounted for significant variance in all outcome measures except open-set phoneme scores. ANOVA with Tukey pairwise comparisons examined group differences for children implanted younger than 12 months (Group 1), between 13 and 18 months (Group 2), between 19 and 24 months (Group 3), between 25 and 42 months (Group 4), and between 43 to 72 months (Group 5). Open-set speech perception scores for Groups 1, 2 and 3 were significantly higher than Groups 4 and 5. Language standard scores for Group 1 were significantly higher than Groups 2, 3, 4 and 5. Speech production outcomes for Group 1 were significantly higher than scores obtained for Groups 2, 3, and 4 combined. Cross tabulation and Chi-square tests supported the hypothesis that a greater percentage of Group 1 children (than Groups 2, 3, 4, or 5) demonstrated language performance within the normative range by school entry. Conclusions: Results support provision of cochlear implants younger than 12 months of age for children with severe to profound hearing loss to optimise speech perception and subsequent language acquisition and speech production accuracy.
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ItemBarriers to early cochlear implantation(TAYLOR & FRANCIS LTD, 2016)OBJECTIVE: Identify variables associated with paediatric access to cochlear implants (CIs). DESIGN: Part 1. Trends over time for age at CI surgery (N = 802) and age at hearing aid (HA) fitting (n = 487) were examined with regard to periods before, during, and after newborn hearing screening (NHS). Part 2. Demographic factors were explored for 417 children implanted under 3 years of age. Part 3. Pre-implant steps for the first 20 children to receive CIs under 12 months were examined. RESULTS: Part 1. Age at HA fitting and CI surgery reduced over time, and were associated with NHS implementation. Part 2. For children implanted under 3 years, earlier age at HA fitting and higher family socio-economic status were associated with earlier CI. Progressive hearing loss was associated with later CIs. Children with a Connexin 26 diagnosis received CIs earlier than children with a premature / low birth weight history. Part 3. The longest pre-CI steps were Step 1: Birth to diagnosis/identification of hearing loss (mean 16.43 weeks), and Step 11: MRI scans to implant surgery (mean 15.05 weeks) for the first 20 infants with CIs under 12 months. CONCLUSION: NHS implementation was associated with reductions in age at device intervention in this cohort.