Mobile phone technology has a growing and pervasive influence on society, with >6 billion mobile phone subscribers worldwide. Round-the-clock connectedness increasingly represents the norm and smartphones are ubiquitous in many sectors of society. As costs for these technologies decrease, expansion into populations with more limited resources is increasing. With many persons now routinely carrying a portable computing and communication device, adaptation of these mobile technologies for monitoring or improving health has been touted as a revolution in health care [1, 2]. Mobile health, or mHealth, has been broadly defined as medical or public health practice supported by mobile devices. The purpose of this special issue is to provide a research and implementation update on the incorporation of mHealth approaches to improve health outcomes among persons living with HIV/AIDS (PLWHA) and substance use.
PLWHA who are drug and alcohol users face many health challenges including delayed HIV diagnosis, delayed linkage to care, difficulty with adherence to antiretroviral treatment (ART), poorer virologic control, and difficulties with long-term retention in care, compared to nonsubstance users [3, 4]. Substance use may often be associated with other barriers to optimal care (e.g., mental illness, financial and legal difficulties, and inadequate housing and transportation) [5]. Several strategies to improve HIV care among persons with substance abuse have been identified (e.g., multidisciplinary case management, peer navigation) but often require substantial resources. Novel, affordable, and evidence-based strategies that are feasible to implement are needed to identify substance-using persons at risk for poor outcomes, promote engagement in HIV care, enhance adherence, and improve treatment responses.
As with most chronic diseases that rely on adherence to prescribed medical regimens or lifestyle modifications, the underpinnings of optimal HIV care include enhanced capacity for self-management by patients. mHealth strategies hold great promise to transform the approach to HIV care. Real-time monitoring of PLWHA with mHealth devices can generate dynamic, individualized models of behavior and provide a foundation to inform health behavior change strategies. Technology can empower patients, with direct delivery of individualized motivation, education, and support. mHealth strategies will likely be significantly represented in evolving models of care delivery. Wireless technologies remove the barriers of time and distance between patients and providers; this is especially important for substance-using PLWHA and other populations that are hard to reach and difficult to keep engaged in care. Hopefully, mHealth approaches will facilitate HIV care providers to work more effectively and be able to collect higher quality data related to care delivery and health outcomes.
While mHealth holds great promise, this nascent field remains in early stages of development [6]. Current mHealth interventions to support HIV care have been largely centered in resource-limited countries. Strategies most widely employed have focused on supporting care providers in remote settings and providing text message support to HIV patients. A growing evidence base indicates that weekly text messages can improve ART adherence and viral suppression [7]. Text messaging appears to work best when the message is individually tailored, context-sensitive, and associated with follow-up intervention. In response to these accumulating data, UNAIDS has recommended that mHealth approaches be incorporated into national HIV care programs. As the next step, smartphone interventions will expand the ability to collect intensive, real-time data from patients, provide tailored education or counseling, and facilitate responsive, interactive communication.
To date, mHealth studies which focus on HIV-infected populations with substance abuse have been limited. In this special issue, eight manuscripts provide an assessment of the scope of mHealth strategies employed among marginalized, substance-using PLWHA. Consistent with the current state of the field, the studies largely represent early stage evaluations of applying novel technology in diverse populations.
Conducting research studies among vulnerable populations such as persons with HIV or substance abuse raises several ethical issues. Further, mHealth approaches that collect data from and/or deliver interventions to participants during their daily routine also pose unique ethical considerations. Dr. A. B. Labrique and colleagues apply a widely accepted ethical framework to describe a range of ethical issues salient to protection of participants in mHealth research on HIV/AIDS and substance abuse.
Several manuscripts in this special issue report on the acceptability, feasibility, and implementation of mHealth approaches. Dr. C. W. T. Miller and Dr. S. Himelhoch report high levels of ownership and interest in using mobile phones among patients at an urban HIV clinic to help support and improve adherence to ART. Dr. K. J. Horvath and colleagues report that while methamphetamine-using men who have sex with men (MSM) had poorer engagement in HIV care, their use of social media and mobile phone technologies was comparable to nonstimulant using MSM, thus raising the possibility of using mHealth in this population.
A major focus of mHealth interventions among substance-using PLWHA is to facilitate ART adherence. Among methamphetamine users studied by Dr. D. J. Moore and colleagues, daily texts were sent to assess drug use and ART adherence. In the preliminary analysis, the proportion of texts responded to and both qualitative and quantitative assessments of acceptability indicate favorable responses by participants. Among HIV-infected IDUs receiving ART in China, Dr. M. B. DeSilva and colleagues evaluated real-time, wireless adherence monitoring using the Wisepill system. Overall, their findings were promising with only minor technical issues and participant feedback highlighting the need for unobtrusive technologies.
Novel intervention strategies which can capture and respond to illicit drug use in realtime can provide a framework for improving engagement and adherence to HIV care. Dr. K. A. Phillips and colleagues report preliminary data from a study of video-based, risk reduction messaging delivered through a smartphone to opioid-dependent patients in drug treatment. Nested within a larger mHealth study in this population, the authors demonstrated the feasibility and acceptability of delivering educational video content as well as capturing feedback in drug users' natural environments. Dr. G. D. Kirk and colleagues report on implementation of ecological momentary analysis (EMA) methods using mobile devices among persons with a history of injecting drugs. During an intensive one-month study period, participants reported drug craving and use in realtime and displayed high levels of response to multiple daily EMA questionnaires regarding their mood, activity, and social and physical environment. Finally, Dr. A. Kurth and colleagues describe an mHealth intervention focused on PLWHA involved in the criminal justice system. In an ongoing randomized controlled trial, computer-delivered counseling is combined with text messaging to improve linkage, retention, and ART adherence during the critical transition following release from correctional settings.
The populations under study in this special issue are highly diverse. Several studies focus on marginalized IDU populations from urban settings in the US. Two studies evaluate mHealth approaches among MSM who abuse methamphetamine. Another study examines technology-enhanced ART adherence support among IDUs in China. Implementation into these disparate populations emphasizes the broad reach of mHealth to cross socioeconomic, racial, or geographic boundaries. Further, successful demonstration of mHealth strategies in these diverse groups bodes well for implementation into other HIV and substance-using populations.
To summarize the findings reported in this special issue, despite the field being in early stages of development, mHealth holds substantial promise for optimizing HIV care and improving adherence to treatment. These strategies appear feasible and acceptable even among challenging, marginalized populations confronted by HIV and substance use. The next steps in development of mHealth intervention strategies will be challenging [8]. Substantial work is needed to develop the theoretical frameworks underpinning mHealth interventions. Further efforts will be required to refine real-time data collection and analysis procedures, identify the best methods for delivering context-sensitive interventions, maintain patient confidentiality, and determine the most appropriate methods for defining effectiveness in mHealth. Challenges exist regarding data security, staying current with rapidly evolving technologies, and best practices for interaction with market-driven industry partners. Despite these challenges, we remain strongly enthusiastic that increasingly available and affordable mHealth tools will continue to evolve and provide successful strategies to improve HIV care outcomes among PLWHA and substance abuse.
Gregory D. Kirk
Seth S. Himelhoch
Ryan P. Westergaard
Curt G. Beckwith
[1]
G. Rutherford,et al.
Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection.
,
2012,
The Cochrane database of systematic reviews.
[2]
L. O'donnell,et al.
The Effectiveness of Video‐Based Interventions in Promoting Condom Acquisition Among STD Clinic Patients
,
1995,
Sexually transmitted diseases.
[3]
K. Kielmann,et al.
Tracking the rise of the “expert patient” in evolving paradigms of HIV care
,
2010,
AIDS care.
[4]
V. Soriano,et al.
Treatment of medical, psychiatric, and substance-use comorbidities in people infected with HIV who use drugs
,
2010,
The Lancet.
[5]
Steven J. Reynolds,et al.
Impact of a mHealth Intervention for Peer Health Workers on AIDS Care in Rural Uganda: A Mixed Methods Evaluation of a Cluster-Randomized Trial
,
2011,
AIDS and Behavior.
[6]
T. Quinn,et al.
Telecommunications and Health Care: An HIV/AIDS Warmline for Communication and Consultation in Rakai, Uganda
,
2008,
Journal of the International Association of Physicians in AIDS Care.
[7]
Norma R Anderson,et al.
Safe in the City
,
2008,
Home healthcare nurse.
[8]
Cristian Pop-Eleches,et al.
Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders
,
2011,
AIDS.
[9]
D. Hoover,et al.
A randomized controlled trial of soap opera videos streamed to smartphones to reduce risk of sexually transmitted human immunodeficiency virus (HIV) in young urban African American women.
,
2013,
Nursing outlook.
[10]
I. Grant,et al.
Methamphetamine dependence increases risk of neuropsychological impairment in HIV infected persons
,
2004,
Journal of the International Neuropsychological Society.
[11]
Gina B. Gaston,et al.
The Impact of African Americans’ Beliefs About HIV Medical Care on Treatment Adherence: A Systematic Review and Recommendations for Interventions
,
2012,
AIDS and Behavior.
[12]
Tigest Tamrat,et al.
Special Delivery: An Analysis of mHealth in Maternal and Newborn Health Programs and Their Outcomes Around the World
,
2012,
Maternal and Child Health Journal.
[13]
Ronald H Gray,et al.
Responding to the human resource crisis: peer health workers, mobile phones, and HIV care in Rakai, Uganda.
,
2008,
AIDS patient care and STDs.
[14]
J. Car,et al.
Mobile phone messaging for facilitating self-management of long-term illnesses.
,
2012,
The Cochrane database of systematic reviews.
[15]
R. Frankowski,et al.
Patients referred to an urban HIV clinic frequently fail to establish care: factors predicting failure
,
2005,
AIDS care.
[16]
J. Chmiel,et al.
Changes in Stimulant Drug Use Over Time in the MACS: Evidence for Resilience Against Stimulant Drug Use Among Men Who Have Sex with Men
,
2010,
AIDS and Behavior.
[17]
A T McLellan,et al.
An Improved Diagnostic Evaluation Instrument for Substance Abuse Patients: The Addiction Severity Index
,
1980,
The Journal of nervous and mental disease.
[18]
T. Flanigan,et al.
Participant Characteristics and HIV Risk Behaviors Among Individuals Entering Integrated Buprenorphine/Naloxone and HIV Care
,
2011,
Journal of acquired immune deficiency syndromes.
[19]
Rachel Jones.
Soap Opera Video Episodes Streamed to Smartphones in a Randomized Controlled Trial to Reduce HIV Sex Risk in Young Urban African American/Black Women
,
2013
.
[20]
R. Westergaard,et al.
Longitudinal changes in engagement in care and viral suppression for HIV-infected injection drug users
,
2013,
AIDS.
[21]
Rachel Jones,et al.
Streaming Weekly Soap Opera Video Episodes to Smartphones in a Randomized Controlled Trial to Reduce HIV Risk in Young Urban African American/Black Women
,
2012,
AIDS and Behavior.
[22]
J. Davila,et al.
Development and pilot testing of a standardized training program for a patient-mentoring intervention to increase adherence to outpatient HIV care.
,
2012,
AIDS patient care and STDs.
[23]
K. Broome,et al.
HIV risk reduction in outpatient drug abuse treatment: individual and geographic differences.
,
1999,
AIDS education and prevention : official publication of the International Society for AIDS Education.
[24]
Garrett Mehl,et al.
H_pe for mHealth: More "y" or "o" on the horizon?
,
2013,
Int. J. Medical Informatics.
[25]
Richard D Moore,et al.
Longitudinal assessment of the effects of drug and alcohol abuse on HIV-1 treatment outcomes in an urban clinic
,
2002,
AIDS.
[26]
D. Epstein,et al.
Daily temporal patterns of heroin and cocaine use and craving: relationship with business hours regardless of actual employment status.
,
2013,
Addictive behaviors.
[27]
Audie A Atienza,et al.
Mobile health technology evaluation: the mHealth evidence workshop.
,
2013,
American journal of preventive medicine.
[28]
K. Rivet Amico,et al.
A situated-Information Motivation Behavioral Skills Model of Care Initiation and Maintenance (sIMB-CIM): An IMB Model Based Approach to Understanding and Intervening in Engagement in Care for Chronic Medical Conditions
,
2011,
Journal of health psychology.
[29]
C. Rebholz,et al.
"Getting me back on track": the role of outreach interventions in engaging and retaining people living with HIV/AIDS in medical care.
,
2007,
AIDS patient care and STDs.
[30]
L. Traeger,et al.
Risk factors for missed HIV primary care visits among men who have sex with men
,
2012,
Journal of Behavioral Medicine.
[31]
A. Bandura.
Perceived self-efficacy in the exercise of control over AIDS infection
,
1990
.
[32]
W. Jack,et al.
Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial
,
2010,
The Lancet.
[33]
M. Chiasson,et al.
Substance use and high-risk sex among men who have sex with men: a national online study in the USA
,
2004,
AIDS care.
[34]
Y. Hser,et al.
Reliability of retrospective self-report by narcotics addicts.
,
1992
.
[35]
C. Grady,et al.
An ethical framework for biomedical research
,
2008
.
[36]
N. Heather,et al.
The reliability and validity of a scale to measure HIV risk-taking behaviour among intravenous drug users.
,
1991,
AIDS.
[37]
B. Lau,et al.
Changes in sexual and drug-related risk behavior following antiretroviral therapy initiation among HIV-infected injection drug users
,
2012,
AIDS.
[38]
Richard T Lester,et al.
M-health for health behaviour change in resource-limited settings: applications to HIV care and beyond.
,
2012,
Bulletin of the World Health Organization.
[39]
J. Stout,et al.
Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare.
,
2011,
Telemedicine journal and e-health : the official journal of the American Telemedicine Association.
[40]
J. Bradford,et al.
Living with HIV but without medical care: barriers to engagement.
,
2007,
AIDS patient care and STDs.
[41]
Francis Collins,et al.
How to fulfill the true promise of "mHealth": Mobile devices have the potential to become powerful medical tools.
,
2012,
Scientific American.
[42]
Julian C. Jamison,et al.
Mixed Method Evaluation of a Passive Mhealth Sexual Information Texting Service in Uganda
,
2013
.
[43]
A. Haines,et al.
The effectiveness of M-health technologies for improving health and health services: a systematic review protocol
,
2010,
BMC Research Notes.
[44]
A. Gaur,et al.
Delayed entry into and failure to remain in HIV care among HIV-infected adolescents.
,
2013,
AIDS research and human retroviruses.
[45]
R. Curtis,et al.
Self-reports of HIV risk behavior by injecting drug users: are they reliable?
,
1995,
Addiction.