Evaluating a continuing professional development course on cognitive functions for Music Therapists working in care homes

Mangiacotti, Anthony; Franco, Fabia; Hsu, Ming Hung; Biasutti, Michele

doi:10.1016/j.aip.2021.101800

Cited by 3 publications

(3 citation statements)

References 51 publications

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“…For the interpretation of the results, a threshold of 3.5/5 (70% of the rating scale score) was chosen as a measure of task appreciation (Mangiacotti et al, 2021). Experts’ ratings on each question were grouped by exercise (Table 1) and the results of the three beta-MCT overall-judgment Likert questions are reported in Table 2.…”

Section: Methodsmentioning

confidence: 99%

“…Most MT academic training programs are based on a psychotherapeutic approach with limited focus on neuropsychological insights and tools (Mangiacotti et al, 2021; Thaut, 2015). Music therapists traditionally use qualitative forms of assessment during patient evaluation, which constrains identification of cognitive impairment and suitability of the therapy (Lipe et al, 2007).…”

mentioning

confidence: 99%

“…76–77). Such assessment tools would also help music therapists acquire specific cognitive information about patients because they do not always have the opportunity to access patient’s medical data (Mangiacotti et al, 2021).…”

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confidence: 99%

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Development and validation of the Music Cognitive Test: A music-based cognitive screening test

Mangiacotti

Cipriani

Ward

et al. 2022

Psychology of Music

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Specific tools to measure the cognitive benefits of music therapy and music-rehabilitation training available to music therapists are few and empirically weak: they are mostly psychometrically unrefined or based on unclear tasks and scoring protocols; they do not take into consideration distinct cognitive functions or are based on exclusively observational protocols. To overcome these limitations, we developed a 15-min cognitive screening tool suitable for music therapists, Music Cognitive Test (MCT), which assesses cognitive abilities stimulated by music-making activities (e.g., attentional, verbal, and executive functions, short- and long-term memory) by including music-based items. MCT was validated with 335 participants (aged 18–100 years old) presenting a range of cognitive levels, from healthy cognition to severe impairment. MCT correlated strongly and positively with well-known tests: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Severe Mini-Mental State Examination (SMMSE). MCT also displayed excellent sensitivity in identifying impaired individuals according to both MMSE and MoCA diagnostic criteria (99.4% and 93.0%, respectively), and excellent specificity in identifying healthy participants based on MMSE (93.5%) and MoCA (97.8%) criteria. Overall, results highlight the reliability of this novel brief music-focused cognitive screening test, to enable music therapists to independently and consistently monitor the effectiveness of their intervention on cognitive functions.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Development and validation of the Music Cognitive Test: A music-based cognitive screening test

Mangiacotti

Cipriani

Ward

et al. 2022

Psychology of Music

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Fuzzy Neural Network Model for Intelligent Course Development in Music and Dance Education

Zhao,

Sun,

Tian

2024

Int J Comput Intell Syst

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Interactions are mandatory for online or offline music and dance education to improve understandability and learning efficacy. The course designed for such artistic education incorporates multi-point interactions and monotonous presentations. The validation of the key factor: interactivity is thus mandatory for enhancing efficiency. This article introduces an interactivity validation method (IVM) using combined fuzzy neural network (FNN) to aid artistic course development. The output of the existing course and its evaluation criteria are considered in enhancing its grade. The fuzzy performs interaction classification as mandatory and trivial based on the student’s performance. The neural network identifies the chances for maximum performance by increasing or decreasing the interaction rate. If a saturated performance is achieved at a high or low interactivity, then the further course design is performed based on the saturated interactivity factor. The failing factors are used for training the neural network for modifying the interactivity rate from the current course development suggestion. Such a process is keen on classifying and validating the impact of interactivity over artistic course design.

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Foundational frameworks supporting selection of music and outcome measures in studies of cognition among older adults with mild cognitive impairment (MCI): An integrative review

Tague

Lipe²

2023

Nordic Journal of Music Therapy

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Evaluating a continuing professional development course on cognitive functions for Music Therapists working in care homes

Cited by 3 publications

References 51 publications

Development and validation of the Music Cognitive Test: A music-based cognitive screening test

Development and validation of the Music Cognitive Test: A music-based cognitive screening test

Fuzzy Neural Network Model for Intelligent Course Development in Music and Dance Education

Foundational frameworks supporting selection of music and outcome measures in studies of cognition among older adults with mild cognitive impairment (MCI): An integrative review

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