A smarter way to conduct medical research.
One of the challenges of population based medical research exists in the process of data collection. This is particularly relevant in study methodologies involving surveys and questionnaires whereby subject response rate can be perilously low.1 Such deficiencies can compromise the quality of the study through introduction of bias and may limit the degree to which the data can be extrapolated and applied in daily practice. Furthermore, population data collection through traditional survey methods, especially those issued in mail is often limited by poor response rates and high attrition rates of surveys that were simply not returned.2
It is no surprise therefore, that a recent study by Dufau et al published in the journal PLos One utilised Smartphone technology as a new “scientific instrument” to collect data for cognitive assessment.3 The authors adapted the versatile touch screen responses and stimulus displays using Apple’s IPad and IPhone to analyse temporal patterns in understanding how fast the brain responds to psycholinguistic challenges such as lexical decision making. In their study, participants were required to download an application from an online source and install onto their IPad or IPhone. Participants completed one or more sessions of 40 to 150 words per session, during which response time and accuracy of word recognition was measured. The promising element of this study was the scope of data collection. The application was available in seven languages that used Roman alphabet. However, the authors commented that it was also possible to expand the data collection to incorporate other alphabetical scripts. Importantly, the study achieved to attract over 4000 participants in a period of four months, which a comparable study took over 3 years for a similar volume of data.
Despite the promise of using Smartphone technology in medical research, the limitations of Dufau’s paper alerted to areas for further improvement. Firstly, despite completing the tests on the Smartphone application, participants were then asked to send results via email. In order for such technology to be integrated into public health research, a greater emphasis on synchronising data entry and feedback is required. Another obvious limitation is the accessibility of Smartphone technology amongst the general population to participate in a study such as this. This does raise uncertainty of results from selection bias. The authors indirectly challenge this criticism by stating that comparable studies also possess a skewed demographic of mainly younger participants, and they have performed a regression analysis with basic age and gender variables.
Despite these limitations, Dufau et al have provided an insight into the evolution of medical research using Smartphone technology. They have demonstrated the capacity for such technology to facilitate an efficient system of population data collection on a global scale. It is clear that the touch-screen interface, portability and ability to register data in a timely manner using Smartphones opens the possibility of a new dynamic instrument for population health research.
References
1. Jansen HH, T. Nonresponse To Mail Surveys in a Lower-Class Urban Area – a Two-Stage Exploration of Access Failure and Refusal. Bulletin de Méthodologie Sociologique. 1999;62(5):5-27.
2. Brugulat-Guiteras P, Mompart-Penina A, Seculi-Sanchez E, Tresserras-Gaju R, de la Puente-Martorell ML. [Health surveys: lights and shadows]. Med Clin (Barc). Feb 2010;134 Suppl 1:21-26.
3. Dufau S, Dunabeitia JA, Moret-Tatay C, et al. Smart phone, smart science: how the use of smartphones can revolutionize research in cognitive science. PLoS One. 2011;6(9):e24974.
