Validade e confiabilidade intraexaminador do aplicativo clinometer para avaliação da dorsiflexão do tornozelo: uma solução prática para usuários de Android
DOI:
https://doi.org/10.17267/2238-2704rpf.2026.e6545Palavras-chave:
Amplitude de Movimento Articular, Articulação do Tornozelo, Tecnologia Biomédica, Telefone Celular, Reprodutibilidade dos TestesResumo
RESUMO | INTRODUÇÃO: A avaliação precisa da amplitude de movimento (ADM) de dorsiflexão do tornozelo (DFT) é essencial na identificação e manejo de disfunções nos membros inferiores. Aplicativos (apps) inclinômetros para smartphones oferecem uma alternativa acessível às ferramentas tradicionais, mas ainda são pouco investigados em dispositivos Android. OBJETIVO: Avaliar a validade e a confiabilidade intraexaminador do aplicativo Clinometer em smartphones Android para mensuração da ADM de DFT durante o teste de avanço com descarga de peso (TADP). MATERIAIS E MÉTODOS: A ADM de DFT foi medida em 50 membros de 25 adultos saudáveis utilizando um goniômetro universal e o app Clinometer em um Samsung A55 durante o TADP. Foram realizadas duas sessões com intervalo de uma semana. A validade concorrente foi avaliada pelo coeficiente de correlação de Pearson; a confiabilidade intraexaminador por (ICC[3,3]), erro padrão de medida (EPM) e mudança mínima detectável (MDC95). A concordância foi analisada por meio do gráfico de Bland-Altman. RESULTADOS: O Clinometer apresentou validade concorrente muito alta com o goniômetro (r = 0,97), excelente confiabilidade intraexaminador (ICC = 0,93), EPM baixo (1,25º) e MDC95 adequado (3,47º). O gráfico de Bland-Altman indicou viés mínimo (-0,48º) e limites de concordância estreitos (-2,82o a +1,85º). CONCLUSÃO: O aplicativo Clinometer é uma ferramenta válida, confiável e acessível para mensuração da ADM de DFT durante o TADP em adultos saudáveis. Seu uso pode otimizar a avaliação musculoesquelética, especialmente quando aplicado por profissionais treinados sob protocolos padronizados, com potencial para aplicações clínicas e monitoramento remoto.
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Copyright (c) 2026 Katy Andrade Monteiro Zacaron, Maria Clara de Oliveira Araújo, Gislaynne Ferraz Keller, Ygor Alves Taborda, Ludimila Forechi
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
Esta obra está licenciada com uma Licença Creative Commons Atribuição 4.0 Internacional.
