全部 标题 作者
关键词 摘要


The Exposure Assessment in Current Time Study: Implementation, Feasibility, and Acceptability of Real-Time Data Collection in a Community Cohort of Illicit Drug Users

DOI: 10.1155/2013/594671

Full-Text   Cite this paper   Add to My Lib

Abstract:

Objective. We describe the study design and evaluate the implementation, feasibility, and acceptability of an ecological momentary assessment (EMA) study of illicit drug users. Design. Four sequential field trials targeting observation of 30 individuals followed for a four week period. Participants. Participants were recruited from an ongoing community-cohort of current or former injection drug users. Of 113 individuals enrolled, 109 completed study procedures during four trials conducted from November 2008 to May 2013. Methods. Hand-held electronic diaries used in the initial trials were transitioned to a smartphone platform for the final trial with identical data collection. Random-prompts delivered five times daily assessed participant location, activity, mood, and social context. Event-contingent data collection involved participant self-reports of illicit drug use and craving. Main Outcome Measures. Feasibility measures included participant retention, days of followup, random-prompt response rates, and device loss rate. Acceptability was evaluated from an end-of-trial questionnaire. Sociodemographic, behavioral, clinical, and trial characteristics were evaluated as correlates of weekly random-prompt response rates ≥80% using logistic regression with generalized estimating equations. Results. Study participants were a median of 48.5 years old, 90% African American, 52% male, and 59% HIV-infected with limited income and educational attainment. During a median followup of 28 days, 78% of 11,181 random-prompts delivered were answered (mean of 2.8 responses daily), while 2,798 participant-initiated events were reported (30% drug use events; 70% craving events). Self-reported acceptability to study procedures was uniformly favorable. Device loss was rare (only 1 lost device every 190 person-days of observation). Higher educational attainment was consistently associated with a higher response rate to random-prompts, while an association of HIV infection with lower response rates was not observed after accounting for differences in trial recruitment procedures. Conclusion. Near real-time EMA data collection in the field is feasible and acceptable among community-dwelling illicit drug users. These data provide the basis for future studies of EMA-informed interventions to prevent drug relapse and improve HIV treatment outcomes in this population. 1. Introduction Optimal HIV care requires prompt identification of HIV infection, linkage to HIV care, prolonged engagement in HIV care with regular attendance at appointments, and high levels of adherence to

References

[1]  E. M. Gardner, M. P. McLees, J. F. Steiner, C. Del Rio, and W. J. Burman, “The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection,” Clinical Infectious Diseases, vol. 52, no. 6, pp. 793–800, 2011.
[2]  R. P. Westergaard, T. Hess, J. Astemborski, S. H. Mehta, and G. D. Kirk, “Longitudinal changes in engagement in care and viral suppression for HIV-infected injection drug users,” AIDS, 2013.
[3]  D. B. Hanna, K. Buchacz, K. A. Gebo et al., “Trends and disparities in antiretroviral therapy initiation and virologic suppression among newly treatment-eligible HIV-infected individuals in North America, 2001–2009,” Clinical Infectious Diseases, vol. 56, no. 8, pp. 1174–1182, 2013.
[4]  S. Shiffman, A. A. Stone, and M. R. Hufford, “Ecological momentary assessment,” Annual Review of Clinical Psychology, vol. 4, pp. 1–32, 2008.
[5]  D. H. Epstein, J. Willner-Reid, M. Vahabzadeh, M. Mezghanni, J. Lin, and K. Preston, “Real-time electronic diary reports of cue exposure and mood in the hours before cocaine and heroin craving and use,” Archives of General Psychiatry, vol. 66, no. 1, pp. 88–94, 2009.
[6]  “Telecom: tools connecting the world and communicating about HIV,” UNAIDS, 2009, http://www.unaids.org/en/resources/presscentre/featurestories/2009/october/20091005telecom/.
[7]  R. T. Lester, P. Ritvo, E. J. Mills et al., “Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial,” The Lancet, vol. 376, no. 9755, pp. 1838–1845, 2010.
[8]  C. Pop-Eleches, H. Thirumurthy, J. P. Habyarimana et al., “Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders,” AIDS, vol. 25, no. 6, pp. 825–834, 2011.
[9]  N. R. Reynolds, M. A. Testa, M. Su et al., “Telephone support to improve antiretroviral medication adherence: a multisite, randomized controlled trial,” Journal of Acquired Immune Deficiency Syndromes, vol. 47, no. 1, pp. 62–68, 2008.
[10]  J. M. Simoni, D. Huh, P. A. Frick et al., “Peer support and pager messaging to promote antiretroviral modifying therapy in seattle: a randomized controlled trial,” Journal of Acquired Immune Deficiency Syndromes, vol. 52, no. 4, pp. 465–473, 2009.
[11]  S. A. Safren, E. S. Hendriksen, N. Desousa, S. L. Boswell, and K. H. Mayer, “Use of an on-line pager system to increase adherence to antiretroviral medications,” AIDS Care, vol. 15, no. 6, pp. 787–793, 2003.
[12]  S. R. Downer, J. G. Meara, A. C. da Costa, and K. Sethuraman, “SMS text messaging improves outpatient attendance,” Australian Health Review, vol. 30, no. 3, pp. 389–396, 2006.
[13]  N. J. Perron, M. D. Dao, M. P. Kossovsky et al., “Reduction of missed appointments at an urban primary care clinic: a randomised controlled study,” BMC Family Practice, vol. 11, article 79, 2010.
[14]  T. Horvath, H. Azman, G. E. Kennedy, and G. W. Rutherford, “Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection,” Cochrane Database of Systematic Reviews, vol. 3, Article ID CD009756, 2012.
[15]  K. E. Muessig, E. C. Pike, S. Legrand, and L. B. Hightow-Weidman, “Mobile phone applications for the care and prevention of HIV and other sexually transmitted diseases: a review,” Journal of Medical Internet Research, vol. 15, no. 1, articla e1, 2013.
[16]  D. H. Epstein and K. L. Preston, “Daily life hour by hour, with and without cocaine: an ecological momentary assessment study,” Psychopharmacology, vol. 211, no. 2, pp. 223–232, 2010.
[17]  D. H. Epstein, G. F. Marrone, S. J. Heishman, J. Schmittner, and K. L. Preston, “Tobacco, cocaine, and heroin: craving and use during daily life,” Addictive Behaviors, vol. 35, no. 4, pp. 318–324, 2010.
[18]  K. L. Preston and D. H. Epstein, “Stress in the daily lives of cocaine and heroin users: relationship to mood, craving, relapse triggers, and cocaine use,” Psychopharmacology, vol. 218, no. 1, pp. 29–37, 2011.
[19]  D. Vlahov, J. C. Anthony, A. Munoz et al., “The ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users: description of methods and characteristics of participants,” NIDA Research Monograph Series, vol. 109, pp. 75–100, 1991.
[20]  C. W. Schmidt, “Monitoring environmental exposures: now it's personal,” Environmental Health Perspectives, vol. 114, no. 9, pp. A528–A535, 2006.
[21]  R. C. Bollinger, J. McKenzie-White, and A. Gupta, “Building a global health education network for clinical care and research. The benefits and challenges of distance learning tools. Lessons learned from the Hopkins center for clinical global health education,” Infectious Disease Clinics of North America, vol. 25, no. 2, pp. 385–398, 2011.
[22]  H. Tumwebaze, E. Tumwesigye, J. M. Baeten, et al., “Household-based HIV counseling and testing as a platform for referral to HIV care and medical male circumcision in Uganda: a pilot evaluation,” PLoS ONE, vol. 7, no. 12, Article ID e51620, 2012.
[23]  K. L. Preston, M. Vahabzadeh, J. Schmittner, J. Lin, D. A. Gorelick, and D. H. Epstein, “Cocaine craving and use during daily life,” Psychopharmacology, vol. 207, no. 2, pp. 291–301, 2009.
[24]  M. J. Freedman, K. M. Lester, C. McNamara, J. B. Milby, and J. E. Schumacher, “Cell phones for ecological momentary assessment with cocaine-addicted homeless patients in treatment,” Journal of Substance Abuse Treatment, vol. 30, no. 2, pp. 105–111, 2006.
[25]  A. Okifuji, D. H. Bradshaw, G. W. Donaldson, and D. C. Turk, “Sequential analyses of daily symptoms in women with fibromyalgia syndrome,” Journal of Pain, vol. 12, no. 1, pp. 84–93, 2011.
[26]  R. A. Carels, O. M. Douglass, H. M. Cacciapaglia, and W. H. O'Brien, “An ecological momentary assessment of relapse crises in dieting,” Journal of Consulting and Clinical Psychology, vol. 72, no. 2, pp. 341–348, 2004.
[27]  D. W. Baker, “The meaning and the measure of health literacy,” Journal of General Internal Medicine, vol. 21, no. 8, pp. 878–883, 2006.
[28]  R. L. Sudore, K. M. Mehta, E. M. Simonsick et al., “Limited literacy in older people and disparities in health and healthcare access,” Journal of the American Geriatrics Society, vol. 54, no. 5, pp. 770–776, 2006.
[29]  T. W. Bickmore and M. K. Paasche-Orlow, “The role of information technology in health literacy research,” Journal of Health Communication, vol. 17, Supplement 3, pp. 23–29, 2012.
[30]  C. Norman, “eHealth literacy 2.0: problems and opportunities with an evolving concept,” Journal of Medical Internet Research, vol. 13, no. 4, article e125, 2011.
[31]  K. Preston, “Ecologic momentary assessment methods to quantify exposure to psychosocial stress and illegal drugs,” in mHealth Summit 2011, NIH National Institute on Drug Abuse, 2011.
[32]  S. Kumar, W. J. Nilsen, A. Abernethy et al., “Mobile health technology evaluation: the mHealth evidence workshop,” The American Journal of Preventive Medicine, vol. 45, no. 2, pp. 228–236, 2013.

Full-Text

comments powered by Disqus