Monitoring sedentary patterns in office employees: validity of an m-health tool (Walk@Work-App) for occupational health.

OBJECTIVE: This study validated the Walk@Work-Application (W@W-App) for measuring occupational sitting and stepping. METHODS: The W@W-App was installed on the smartphones of office-based employees (n=17; 10 women; 26±3 years). A prescribed 1-hour laboratory protocol plus two continuous hours of occupational free-living activities were performed. Intra-class correlation coefficients (ICC) compared mean differences of sitting time and step count measurements between the W@W-App and criterion measures (ActivPAL3TM and SW200Yamax Digi-Walker). RESULTS: During the protocol, agreement between self-paced walking (ICC=0.85) and active working tasks step counts (ICC=0.80) was good. The smallest median difference was for sitting time (1.5seconds). During free-living conditions, sitting time (ICC=0.99) and stepping (ICC=0.92) showed excellent agreement, with a difference of 0.5minutes and 18 steps respectively. CONCLUSIONS: The W@W-App provided valid measures for monitoring occupational sedentary patterns in real life conditions; a key issue for increasing awareness and changing occupational sedentariness.

Measuring and influencing physical activity with smartphone technology: a systematic review.

BACKGROUND: Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. OBJECTIVE: This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. DATA SOURCES: Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. STUDY SELECTION: The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. STUDY APPRAISAL AND SYNTHESIS METHODS: Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. RESULTS: A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100% (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre-post and one comparative) reported physical activity increases (12-42 participants, 800-1,104 steps/day, 2 weeks-6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. LIMITATIONS: Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. CONCLUSIONS: Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

Monitoring sedentary patterns in office employees: validity of an m-health tool (Walk@Work-App) for occupational health / Monitorización de patrones sedentarios en oficinistas: validación de una aplicación móvil (Walk@Work-App) en salud laboral

Objective: This study validated the Walk@Work-Application (W@W-App) for measuring occupational sitting and stepping. Methods: The W@W-App was installed on the smartphones of office-based employees (n=17; 10 women; 26±3 years). A prescribed 1-hour laboratory protocol plus two continuous hours of occupational free-living activities were performed. Intra-class correlation coefficients (ICC) compared mean differences of sitting time and step count measurements between the W@W-App and criterion measures (ActivPAL3TM and SW200Yamax Digi-Walker). Results: During the protocol, agreement between self-paced walking (ICC=0.85) and active working tasks step counts (ICC=0.80) was good. The smallest median difference was for sitting time (1.5seconds). During free-living conditions, sitting time (ICC=0.99) and stepping (ICC=0.92) showed excellent agreement, with a difference of 0.5minutes and 18 steps respectively. Conclusions: The W@W-App provided valid measures for monitoring occupational sedentary patterns in real life conditions; a key issue for increasing awareness and changing occupational sedentariness

Objetivo: Validar la aplicación móvil Walk@Work (W@W-App) para monitorizar los patrones de actividad y sedentarios en el trabajo. Método: W@W-App se instaló en teléfonos móviles de oficinistas (n=17; 10 mujeres; 26±3 años). El tiempo sentado y el número de pasos se midieron mediante un test de laboratorio y bajo condiciones habituales. Las diferencias entre W@W-App y las medidas de referencia (ActivPAL3TM y SW200Yamax Digi-Walker) se compararon mediante coeficientes de correlación intraclase (CCI). Resultados: En el test de laboratorio, los valores de correlación fueron buenos en los pasos realizados a baja intensidad (CCI=0.85-0.80). La menor diferencia de mediana fue para el tiempo sentado (1,5 segundos). En condiciones habituales, el tiempo sentado (CCI=0.99) y los pasos (CCI=0.92) mostraron valores de correlación excelentes, con una diferencia de 0,5 minutos y 18 pasos. Conclusiones: W@W-App proporciona medidas válidas para la monitorización de patrones sedentarios en el trabajo; aspecto clave para modificar el sedentarismo en las oficinas