Dataset Information

Use of an mHealth Intervention to Improve Engagement in HIV Community-Based Care Among Persons Recently Released from a Correctional Facility in Washington, DC: A Pilot Study.

ABSTRACT: We examined the preliminary effectiveness of a computerized counseling session plus post-incarceration text messaging intervention (CARE?+?Corrections) to support ART adherence and linkage/engagement in community care among recently incarcerated persons with HIV in Washington, D.C. Recently incarcerated persons with HIV???18 years old were recruited from the D.C. jail or community outreach and randomized to CARE?+?Corrections or control arm. Participants completed assessments at baseline, 3-months and 6-months. Multivariable random effects modeling identified predictors of suppressed viral load (??200 copies/mL) and engagement in HIV care at 6 months. Participants (N?=?110) were aged 42 (IQR 30-49); 58% male, 24% female, 18% transgender, 85% Black, and lifetime incarceration was a median of 7 years (IQR 2-15). More controls had a regular healthcare provider at baseline. Although not statistically significant, intervention participants had increased odds of viral suppression versus controls at 6 months (AOR 2.04; 95% CI 0.62, 6.70). Those reporting high ART adherence at baseline had higher odds of viral suppression at follow-up (AOR 10.77; 95% CI 1.83, 63.31). HIV care engagement was similar between the two groups, although both groups reported increased engagement at 6 months versus baseline. We observed a positive but non-significant association of viral suppression in the CARE?+?Corrections group, and care engagement increased in both groups after 6 months. Further attention to increasing viral suppression among CJ-involved persons with HIV upon community reentry is warranted.

SUBMITTER: Kuo I

PROVIDER: S-EPMC6459706 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Use of an mHealth Intervention to Improve Engagement in HIV Community-Based Care Among Persons Recently Released from a Correctional Facility in Washington, DC: A Pilot Study.

Kuo Irene I Liu Tao T Patrick Rudy R Trezza Claudia C Bazerman Lauri L Uhrig Castonguay Breana J BJ Peterson James J Kurth Ann A Beckwith Curt G CG

AIDS and behavior 20190401 4

We examined the preliminary effectiveness of a computerized counseling session plus post-incarceration text messaging intervention (CARE + Corrections) to support ART adherence and linkage/engagement in community care among recently incarcerated persons with HIV in Washington, D.C. Recently incarcerated persons with HIV ≥ 18 years old were recruited from the D.C. jail or community outreach and randomized to CARE + Corrections or control arm. Participants completed assessments at baseline, 3-mont ...[more]

PMID: 30627850

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Project description:BACKGROUND:Previously incarcerated individuals have suboptimal linkage and engagement in community HIV care. Mobile health (mHealth) interventions have been shown to be effective in addressing these gaps. In Washington, District of Columbia (DC), we conducted a randomized trial of an SMS text messaging-based mHealth intervention (CARE+ Corrections) to increase linkage to community HIV care and antiretroviral treatment adherence among HIV-infected persons involved in the criminal justice system. OBJECTIVE:This study aimed to describe the SMS text messaging-based intervention, participant use of the intervention, and barriers and facilitators of implementation. METHODS:From August 2013 to April 2015, HIV-positive incarcerated individuals were recruited within the DC Department of Corrections, and persons released in the past 6 months were recruited within the community via street-based recruitment, community partnerships, and referrals. Participants were followed for 6 months and received weekly or daily SMS text messages. Formative research resulted in the development of the content of the messages in 4 categories: HIV Appointment Reminders, Medication Adherence, Prevention Reminders, and Barriers to Care following release from jail. Participants could customize the timing, frequency, and message content throughout the study period. RESULTS:Of the 112 participants enrolled, 57 (50.9%) were randomized to the intervention group and 55 (49.1%) to the control group; 2 control participants did not complete the baseline visit, and were dropped from the study, leaving a total of 110 participants who contributed to the analyses. Study retention was similar across both study arms. Median age was 42 years (IQR 30-50), 86% (49/57) were black or African American, 58% (33/57) were male, 25% (14/57) were female, and 18% (10/57) were transgender. Median length of last incarceration was 4 months (IQR 1.7-9.0), and median lifetime number of times incarcerated was 6.5 (IQR 3.5-14.0). Most participants (32/54, 59%) had a baseline viral load of <200 copies/mL. Nearly all participants (52/57, 91%) chose to use a cell phone provided by the study. The most preferred Appointment Reminder message was Hey how you feeling? Don't forget to give a call and make your appointment (19/57, 33%). The most preferred Medication Adherence message was Don't forget your skittles! (31/57, 54%), and 63% (36/57) of participants chose to receive daily (vs weekly) messages from this category at baseline. The most preferred Prevention Reminder message was Stay strong. Stay clean (18/57, 32%). The most preferred Barriers to Care message was Holla at your case manager, they're here to help (12/57, 22%). Minor message preference differences were observed among participants enrolled in the jail versus those from the community. CONCLUSIONS:Participants' ability to customize their SMS text message plan proved helpful. Further large-scale research on mHealth platforms is needed to assess its efficacy among HIV-infected persons with a history of incarceration. TRIAL REGISTRATION:ClinicalTrials.gov NCT01721226; https://clinicaltrials.gov/ct2/show/NCT01721226.

Project description:BACKGROUND:HIV cohort studies have been used to assess health outcomes and inform the care and treatment of people living with HIV disease. However, there may be similarities and differences between cohort participants and the general population from which they are drawn. OBJECTIVE:The objective of this analysis was to compare people living with HIV who have and have not been enrolled in the DC Cohort study and assess whether participants are a representative citywide sample of people living with HIV in the District of Columbia (DC). METHODS:Data from the DC Health (DCDOH) HIV surveillance system and the DC Cohort study were matched to identify people living with HIV who were DC residents and had consented for the study by the end of 2016. Analysis was performed to identify differences between DC Cohort and noncohort participants by demographics and comorbid conditions. HIV disease stage, receipt of care, and viral suppression were evaluated. Adjusted logistic regression assessed correlates of health outcomes between the two groups. RESULTS:There were 12,964 known people living with HIV in DC at the end of 2016, of which 40.1% were DC Cohort participants. Compared with nonparticipants, participants were less likely to be male (68.0% vs 74.9%, P<.001) but more likely to be black (82.3% vs 69.5%, P<.001) and have a heterosexual contact HIV transmission risk (30.3% vs 25.9%, P<.001). DC Cohort participants were also more likely to have ever been diagnosed with stage 3 HIV disease (59.6% vs 47.0%, P<.001), have a CD4 <200 cells/µL in 2017 (6.2% vs 4.6%, P<.001), be retained in any HIV care in 2017 (72.9% vs 59.4%, P<.001), and be virally suppressed in 2017. After adjusting for demographics, DC Cohort participants were significantly more likely to have received care in 2017 (adjusted odds ratio 1.8, 95% CI 1.70-2.00) and to have ever been virally suppressed (adjusted odds ratio 1.3, 95% CI 1.20-1.40). CONCLUSIONS:These data have important implications when assessing the representativeness of patients enrolled in clinic-based cohorts compared with the DC-area general HIV population. As participants continue to enroll in the DC Cohort study, ongoing assessment of representativeness will be required.

Project description:BackgroundEvaluating engagement with an intervention is a key component of understanding its efficacy. With an increasing interest in developing behavioral interventions in the mobile health (mHealth) space, appropriate methods for evaluating engagement in this context are necessary. Data collected to evaluate mHealth interventions are often collected much more frequently than those for clinic-based interventions. Additionally, missing data on engagement is closely linked to level of engagement resulting in the potential for informative missingness. Thus, models that can accommodate intensively collected data and can account for informative missingness are required for unbiased inference when analyzing engagement with an mHealth intervention.ObjectiveThe objectives of this paper are to discuss the utility of the joint modeling approach in the analysis of longitudinal engagement data in mHealth research and to illustrate the application of this approach using data from an mHealth intervention designed to support illness management among people with schizophrenia.MethodsEngagement data from an evaluation of an mHealth intervention designed to support illness management among people with schizophrenia is analyzed. A joint model is applied to the longitudinal engagement outcome and time-to-dropout to allow unbiased inference on the engagement outcome. Results are compared to a naïve model that does not account for the relationship between dropout and engagement.ResultsThe joint model shows a strong relationship between engagement and reduced risk of dropout. Using the mHealth app 1 day more per week was associated with a 23% decreased risk of dropout (P<.001). The decline in engagement over time was steeper when the joint model was used in comparison with the naïve model.ConclusionsNaïve longitudinal models that do not account for informative missingness in mHealth data may produce biased results. Joint models provide a way to model intensively collected engagement outcomes while simultaneously accounting for the relationship between engagement and missing data in mHealth intervention research.

Dataset Information

Use of an mHealth Intervention to Improve Engagement in HIV Community-Based Care Among Persons Recently Released from a Correctional Facility in Washington, DC: A Pilot Study.

Publications

Use of an mHealth Intervention to Improve Engagement in HIV Community-Based Care Among Persons Recently Released from a Correctional Facility in Washington, DC: A Pilot Study.

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