Development of an Evidence-Based Clinical Algorithm for Practice in Hypotonia Assessment: A Proposal

BACKGROUND: Assessing muscle tone in children is essential during the neurological assessment and is often essential in ensuring a more accurate diagnosis for appropriate management. While there have been advances in child neurology, there remains much contention around the subjectivity of the clinical assessment of hypotonia, which is often the first step in the diagnostic process. OBJECTIVE: In response to this challenge, the objective of the study is to develop and validate a prototype of a decision making process in the form of a clinical algorithm that will guide clinicians during this assessment process. METHODS: Design research within a pragmatic stance will be employed in this study. Multi-phase stages of assessment, prototyping and evaluation will occur. These will include processes that include a systematic review, processes of reflection and action as well as validation methods. Given the mixed methods nature of this study, use of NVIVO or ATLAS-ti will be used in the analysis of qualitative data and SPSS for quantitative data. RESULTS: Initial results from the systematic review revealed a paucity of scientific literature that documented the objective assessment of hypotonia in children. The review identified the need for more studies with greater methodological rigor in order to determine best practice with respect to the methods used in the assessment of low muscle tone in the paediatric population. CONCLUSIONS: It is envisaged that this proposal will contribute to a more accurate clinical diagnosis of children with low muscle tone in the absence of a gold standard. We anticipate that the use of this tool will ultimately assist clinicians towards moving to evidenced based practice whilst upholding best practice in the care of children with hypotonia.