References
- Anand, P., Springer, S., Copenhaver, M., & Altice, F. (2010). Neurocognitive impairment and HIV risk factors: A reciprocal relationship. AIDS and Behavior, 14(6), 1213–1226. doi: 10.1007/s10461-010-9684-1
- Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. G. (2001). The alcohol use disorders identification test: Guidelines for use in primary care. Zeneva, Switzerland: W. H. Organization. Retrieved from http://apps.who.int/iris/bitstream/10665/67205/1/WHO_MSD_MSB_01.6a.pdf
- Bates, M. E., Pawlak, A. P., Tonigan, J. S., & Buckman, J. F. (2006). Cognitive impairment influences drinking outcome by altering therapeutic mechanisms of change. Psychology of Addictive Behaviors, 20(3), 241–253. doi: 10.1037/0893-164X.20.3.241
- Copenhaver, M., Shrestha, R., Wickersham, J. A., Weikum, D., & Altice, F. L. (2016). An exploratory factor analysis of a brief self-report scale to detect neurocognitive impairment among participants enrolled in methadone maintenance therapy. Journal of Substance Abuse Treatment, 63, 61–65. doi: 10.1016/j.jsat.2016.01.002
- Finitsis, D. J., Pellowski, J. A., & Johnson, B. T. (2014). Text message intervention designs to promote adherence to antiretroviral therapy (ART): A meta-analysis of randomized controlled trials. PLoS ONE, 9(2), e88166. doi: 10.1371/journal.pone.0088166
- Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., … Haines, A. (2013). The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: A systematic review. PLoS Medicine, 10(1), e1001362. doi: 10.1371/journal.pmed.1001362
- Heron, K. E., & Smyth, J. M. (2010). Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behavior treatments. British Journal of Health Psychology, 15(Pt 1), 1–39. doi: 10.1348/135910709X466063
- Hosmer, D. W., Hosmer, T., Le Cessie, S., & Lemeshow, S. (1997). A comparison of goodness-of-fit tests for the logistic regression model. Statistics in medicine, 16(9), 965–980. doi: 10.1002/(SICI)1097-0258(19970515)16:9<965::AID-SIM509>3.0.CO;2-O
- Huedo-Medina, T. B., Shrestha, R., & Copenhaver, M. (2016). Modeling a theory-based approach to examine the influence of neurocognitive impairment on HIV risk reduction behaviors among drug users in treatment. AIDS and Behavior, (In press).
- Kim, J., Zhang, W., Nyonyitono, M., Lourenco, L., Nanfuka, M., Okoboi, S., … Moore, D. M. (2015). Feasibility and acceptability of mobile phone short message service as a support for patients receiving antiretroviral therapy in rural Uganda: A cross-sectional study. Journal of the International AIDS Society, 18(1), 20311. doi: 10.7448/IAS.18.1.20311
- Krishnan, A., Ferro, E. G., Weikum, D., Vagenas, P., Lama, J. R., Sanchez, J., & Altice, F. L. (2014). Communication technology use and mHealth acceptance among HIV-infected men who have sex with men in Peru: Implications for HIV prevention and treatment. AIDS Care, 1–10. doi: 10.1080/09540121.2014.963014
- Marshall, B. D. L., Friedman, S. R., Monteiro, J. F. G., Paczkowski, M., Tempalski, B., Pouget, E. R., … Galea, S. (2014). Prevention and treatment produced large decreases in HIV incidence in a model of people who inject drugs. Health Affairs, 33(3), 401–409. doi: 10.1377/hlthaff.2013.0824
- Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. doi: 10.1177/014662167700100306
- Shrestha, R., & Copenhaver, M. (2016). The influence of neurocognitive impairment on HIV risk behaviors and intervention outcomes among high-risk substance users: A systematic review. Frontiers in Public Health, 4), doi: 10.3389/fpubh.2016.00016
- Shrestha, R., Huedo-Medina, T., Altice, F., Krishnan, A., & Copenhaver, M. (2016). Examining the acceptability of mHealth technology in HIV prevention among high-risk drug users in treatment. AIDS and Behavior. doi: 10.1007/s10461-016-1637-x
- Shrestha, R., Huedo-Medina, T., & Copenhaver, M. (2015). Sex-related differences in self-reported neurocognitive impairment among high-risk cocaine users in methadone maintenance treatment program. Substance Abuse: Research and Treatment, 9, 17–24. doi: 10.4137/SART.S23332
- Shrestha, R., Karki, P., Altice, F., Huedo-Medina, T., Meyer, J. P., Madden, L., & Copenhaver, M. (2017). Correlates of willingness to use pre-exposure prophylaxis (PrEP) and the likelihood of practicing safer drug- and sex-related risk behaviors while on PrEP among high-risk drug users in treatment. Drug & Alcohol Dependence, 173, 107–116. doi: 10.1016/j.drugalcdep.2016.12.023
- Strathdee, S. A., Hallett, T. B., Bobrova, N., Rhodes, T., Booth, R., Abdool, R., & Hankins, C. A. (2010). HIV and risk environment for injecting drug users: The past, present, and future. The Lancet, 376(9737), 268–284. doi: 10.1016/S0140-6736(10)60743-X
- Torous, J., Friedman, R., & Keshavan, M. (2014). Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions. JMIR mHealth and uHealth, 2(1), e2. doi: 10.2196/mhealth.2994
- Ward, J., Darke, S., & Hall, W. (1990). The HIV risk-taking behaviour scale (HRBS) manual. National Drug and Alcohol Research Centre, University of New South Wales Sydney.
- WHO. (2011). mHealth: New horizons for health through mobile technologies: second global survey on eHealth. Geneva: Author. Retrieved from http://www.who.int/goe/publications/goe_mhealth_web.pdf