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In 2010, 71.0% of 12th graders in the United States reported life-time alcohol use and 48.2% reported life-time illicit drug use [1]. Existing measures of substance use show high test–retest reliability [2], but adolescent populations present unique challenges to issues of validity. Studies of the effects of substance use on adolescent development often rely upon self-report drug use histories, but it is notoriously difficult to collect accurate use records from teens, especially over long recall periods. Specifically, the opportunistic pattern characteristic of adolescent substance use probably provides few associations to aid recall, and adolescents may under-report because of low perceived confidentiality or lack of recognition of drug definitions [3]. More general obstacles include substance-related memory deficits [4] and participant dropout. One opportunity to address these issues lies in mobile telephone technology. Text messaging is currently enhancing availability and delivery of substance use treatments [5], but also holds unmet potential for application to research methods. This letter discusses some considerations for future research with adolescent substance users.

International surveys report high mobile telephone usage among adolescents [6–8], and utilizing text messaging during prospective observation periods of baseline substance use could dramatically improve report accuracy while remaining cost- and time-effective for participants and researchers. Existing measures such as the time-line follow-back (TLFB) [9], which aids recall of substance use through a calendar format, offer insight for potential mobile telephone adaptations. Recent research has noted that daily assessments on wireless mobile devices capture similar rates of alcohol use as traditional paper-and-pencil daily diaries [10]. Another study suggested that young adults reported a greater number of drinking days, total drinks and binge episodes when interviewed using four 7-day TLFBs rather than one 30-day TLFB, and greater discrepancies between reports were observed earlier in the recall period [11]. Given these findings, daily or weekly text messaging regarding quantity and frequency of use throughout an observation period could provide more accurate concrete data or prompts for later interview administration.

Potential limitations to integrating text messaging into longitudinal data collection include possible low mobile telephone usage rates among high-risk populations and maintaining compliance with instructions. However, one sample of Australian adolescents and young adults appeared to find texting acceptable for research participation, with 73% of participants who were sent messages responding to a follow-up survey [12]. Mobile telephone usage was also found to be effective in following a typically hard-to-reach, high-risk population of homeless individuals [13]. A recent surge of studies examining the applications of text messaging for increasing compliance to medical appointments and treatments indicates general success in reaching patients through mobile telephones [14–16]. Given these trends, it is reasonable to expect that most participants, especially adolescents, would be amenable to brief updates via text messaging during longitudinal studies, and brief monthly messages would probably improve attrition rates. In summary, increasing the relevance of research to adolescents by adapting study participation to mobile telephone technology shows promise for improving data accuracy, and future research should consider incorporating text messaging into data collection.

References

  1. Top of page
  2. Declarations of interest
  3. References
  • 1
    Johnston L. D., O'Malley P. M., Bachman J. G., Schulenberg J. E. Marijuana Use Is Rising; Ecstasy Use Is Beginning to Rise; and Alcohol Use Is Declining among U.S. Teens [internet]. Ann Arbor, MI: University of Michigan News Service; 2010. Available at: http://www.monitoringthefuture.org/pressreleases/10drugpr_complete.pdf (accessed 18 October 2011; archived by Webcite at http://www.webcitation.org/64UkWWGjM).
  • 2
    Levy S., Sherritt L., Harris S. K., Gates E. C., Holder D. W., Kulig J. W. et al. Test–retest reliability of adolescents' self-report of substance use. Alcohol Clin Exp Res 2004; 28: 123641.
  • 3
    Harris K. M., Griffin B. A., McCaffrey D. F., Morra1 A. R. Inconsistencies in self-reported drug use by adolescents in substance abuse treatment: implications for outcomes and performance measurement. J Subst Abuse Treat 2008; 34: 34755.
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    Thoma R. J., Monnig M. A., Lysne P. A., Ruhl D. A., Pommy J. A., Bogenschutz M. et al. Adolescent substance abuse: the effects of alcohol and marijuana on neuropsychological performance. Alcohol Clin Exp Res 2011; 35: 3946.
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    Hafner K. Texting May Be Taking a Toll [internet]. New York Times, 26 May 2009. Available at: http://www.nytimes.com/2009/05/26/health/26teen.html (accessed 7 November 2011; archived by Webcite at http://www.webcitation.org/64U11ypKb).
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    van Heerden A. C., Norris S. A., Richter L. M. Using mobile phones for adolescent research in low and middle income countries: preliminary findings from the birth to twenty cohort, South Africa. J Adolesc Health 2010; 46: 3024.
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    Devís-Devís J., Peiró-Velert C., Beltrán-Carrillo V. J., Tomás J. M. Screen media time usage of 12–16 year-old Spanish school adolescents: effects of personal and socioeconomic factors, season and type of day. J Adolesc 2009; 32: 21331.
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    Sobell L. C., Sobell M. B. Timeline follow-back: a technique for assessing self-reported alcohol consumption. In: Litten R. Z., Allen J., editors. Measuring Alcohol Consumption: Psychosocial and Biological Methods. Totowa, NJ: Humana Press; 1992, p. 4172.
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    Hoeppner B. B., Stout R. L., Jackson K. M., Barnett N. P. How good is fine-grained Timeline Follow-back data? Comparing 30-day TLFB and repeated 7-day TLFB alcohol consumption reports on the person and daily level. Addict Behav 2010; 35: 113843.
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    Eyrich-Garg K. M. Mobile phone technology: a new paradigm for the prevention, treatment, and research of the non-sheltered ‘street’ homeless? J Urban Health 2010; 87: 36580.
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    Woolford S. J., Clark S. J., Strecher V. J., Resnicow K. Tailored mobile phone text messages as an adjunct to obesity treatment for adolescents. J Telemed Telecare 2010; 16: 45861.
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    Person A. K., Blain M. L. M., Jiang H., Rasmussen P. W., Stout J. E. Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare. Telemed J E Health 2011; 17: 18995.
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    Miloh T., Annunziato R., Arnon R., Warshaw J., Parkar S., Suchy F. J. et al. Improved adherence and outcomes for pediatric liver transplant recipients by using text messaging. Pediatrics 2009; 124: e84450.