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Biological age calculators to motivate lifestyle change: Environmental scan of online tools and evaluation of behaviour change techniques

OBJECTIVE: “Biological age” calculators are widely used as a way of communicating health risk. This study evaluated the behaviour change techniques (BCTs) within such tools, underlying algorithm differences and suitability for people with varying health literacy. METHODS: Two authors entered terms i...

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Detalles Bibliográficos
Autores principales: Bonner, Carissa, Batcup, Carys, Fajardo, Michael, Trevena, Lyndal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10091808/
https://www.ncbi.nlm.nih.gov/pubmed/36198168
http://dx.doi.org/10.1002/hpja.671
Descripción
Sumario:OBJECTIVE: “Biological age” calculators are widely used as a way of communicating health risk. This study evaluated the behaviour change techniques (BCTs) within such tools, underlying algorithm differences and suitability for people with varying health literacy. METHODS: Two authors entered terms into Google (eg, biological/heart age) and recorded the first 50 results. A standard patient profile was entered into eligible biological age calculators. Evaluation was based on Michie et al's BCT taxonomy and a readability calculator. RESULTS: From 4000 search results, 20 calculators were identified: 11 for cardiovascular age, 7 for general biological age and 2 for fitness age. The calculators gave variable results for the same 65‐year‐old profile: biological age ranged from younger to older (57‐87 years), while heart age was always older (69‐85+ years). Only 11/20 (55%) provided a reference explaining the underlying algorithm. The average reading level was Grade 10 (range 8.7‐12.4; SD 1.44). The most common BCTs were salience of consequences, information about health consequences and credible source. CONCLUSIONS: Biological age tools have highly variable results, BCTs and readability. PRACTICE IMPLICATIONS: Developers are advised to use validated models, explain the result at the average Grade 8 reading level, and incorporate a clear call to action using evidence‐based behaviour change techniques.