Testing a Multi-Component Intervention to Improve Health Outcomes and Quality of Life Among Rural Older Adults Living With HIV
Phase: NA
Conditions: HIV
Sponsor: Medical College of Wisconsin

 
 
 
 
R56 NR019443 / NCT04549259 
Multi-Component Intervention to Improve Health Outcomes and Quality of Life Among Rural 
Older Adults Living With HIV 
ClinicalTrials.gov Study Protocol and Statistical Analysis Plan 
May 23, 2023 
 
 

METHODS 
Participants and Procedures 
Inclusion criteria for the study were (1) 50 years of age or older; (2) self-reported HIV-positive 
status; (3) residence in a rural zip code or county within 9 southern US states, including Alabama, 
Arkansas, Georgia, Kentucky, Mississippi, Missouri, Oklahoma, South Carolina, and Tennessee; (4) self-
reported willingness to participate in support groups and to provide a dried-blood spot sample; (5) access 
to a telephone at home; and (6) ability to provide informed consent. Participants met the rural residence 
eligibility criteria if they resided in a zip code classified as a "Small and Isolated Small Rural Town" area 
by Rural-Urban Commuting Area Codes (RUCAs),1 and/or in a county classified as rural based on 
RUCAs, and/or in a county with a score of .4 or higher on the index of relative rurality (IRR).2 
We recruited participants using several passive mechanisms. We engaged in partnerships with 15 
AIDS service organizations (ASOs) that serve rural clientele in the target southern US states. Partner 
agencies distributed recruitment materials by mail and/or displayed materials within their facilities. We 
also placed advertisements on social media sites, using targeted algorithms to deliver ads based on age 
and geographic location. Ads were also placed on two HIV-specific informational websites. Finally, we 
used a research registry of participants engaged in research previously to invite potential participants, 
based on demographic information, to be screened for eligibility for this study.  
Interested individuals completed screening either online—by directly clicking on an online ad, or 
by entering the website listed on recruitment materials—or by calling the study phone number, after 
which study staff would verbally complete the screener with participants. For eligible participants, 
informed consent was subsequently completed either online or over the phone. 
Following consent, patients completed a baseline survey either online or through a paper survey 
mailed to them (see Measures) and self-collected and returned a dried blood spot (DBS) kit to assess HIV 
viral load (see HIV Viral Load Testing). Following baseline survey and DBS completion, participants 
were randomized to one of 16 conditions (see Study Design and Randomization) and invited to participate 
in 0, 1, 2, 3, or 4 of the interventions (see Interventions). Following intervention delivery and at least 90 

days after baseline survey completion, participants were invited to complete a follow-up survey and DBS 
kit. 
This research was approved by the Medical College of Wisconsin Institutional Review Board 
(protocol #PRO00037672), and the trial was registered at ClinicalTrials.gov (protocol #NCT04549259). 
Measures 
Unless otherwise detailed, measures were completed at both baseline and follow-up. 
Demographics 
Participants reported their state of residence, age, gender identity, race and ethnicity, sexual 
orientation, education, annual income, work status, insurance type, and year of HIV diagnosis. 
Participants reported whether or not they currently had each of 16 comorbid health conditions (e.g., 
cancer, diabetes, heart disease, etc.). We coded the mode of data collection (online or on paper). 
Primary Outcomes 
 
Health-related quality of life. Quality of life (QOL) was assessed with 31 items from the 
WHOQOL-HIV BREF3 (e.g., “How would you rate your quality of life?”). Domains assessed include 
physical health; psychological health; level of independence; social relationships; environmental health; 
and personal beliefs. Additionally, two individual items focus on overall quality of life and general health. 
Items focus on the past 2 weeks, and all items are responded to using 5-point Likert scales. Domain scores 
were created as described by the WHO, with scores within each domain ranging from 4 to 20.4  We also 
created a composite quality of life score by equally weighting the 6 domains, overall quality of life item, 
and general health item. This composite score is in line with research supporting a single quality of life 
factor3; additionally, there was good reliability (α = .87-.90) for these 8 indicators. The composite score 
was rescaled such that overall scores ranged from 0 to 100, with higher scores indicating better health-
related QOL. We focus here on overall QOL and on the personal beliefs subscale (e.g., “To what extent 
do you feel your life to be meaningful?”). 
Depressive symptoms. Depressive symptoms during the past 2 weeks were assessed with the 9 
items from the Patient Health Questionnaie-9 (PHQ-9)5 (αs = .87-.90). Participants indicated how often 

they had experienced different depressive symptoms (e.g., “Feeling down, depressed, or hopeless”). 
Responses ranged from not at all (0) to nearly every day (3). Items were summed; higher scores indicated 
more depressive symptoms. 
ART adherence. Adherence to HIV antiretroviral medications in the past 30 days was assessed 
with the 3 items from the Wilson adherence scale6 (e.g. “In the last 30 days, on how many days did you 
miss at least one dose of any of your HIV medication(s)?”, αs = .71-.79). This scale was scored in line 
with Wilson et al.,6 with scores ranging from 0 to 100 and higher scores indicating better adherence. Due 
to significant skew in this outcome, we created a binary variable indicating perfect adherence to HIV 
medications (0 = imperfect adherence, 1 = perfect adherence). 
Mediating Mechanisms 
We also assessed several factors we viewed as potential mediating mechanisms. Theorized 
mechanisms for the social support and stigma reduction groups were social support, loneliness, and 
internalized stigma. Theorized mechanisms for strengths-based case management (SBCM) were 
accessing needed services and the personal beliefs subscale of the quality of life measure (discussed 
above). Finally, a theorized mechanism for the technology detailing intervention was eHealth literacy.   
Social support. Social support was assessed with 19 items from the MOS Social Support Scale7 
(αs = .98). Participants indicated how often different kinds of support were available to them (e.g., 
“Someone who understands your problems”) on a scale from none of the time (1) to all of the time (5). 
Items were averaged; higher scores indicated more support. 
Loneliness. Loneliness was assessed with 5 items from the Loneliness survey from the NIH 
Toolbox (αs = .95-.96).8 Participants indicated how often during the past month they had felt various 
ways (e.g., “I feel isolated from others.”) on a scale from never (1) to always (5). Items were averaged; 
higher scores indicated greater loneliness. 
Internalized stigma. Internalized stigma was assessed with 6 items from the internalized stigma 
subscale of the HIV Stigma Mechanisms scale (e.g., “I feel ashamed of having HIV,” αs = .95).9 

Responses were on a scale from strongly disagree (1) to strongly agree (5). Items were averaged; higher 
scores indicated more internalized stigma. 
Accessing needed services. Participants reported which of 12 HIV-related social and medical 
services they had needed during the previous 12 months (e.g., mental health counseling, help finding 
meals and food, transportation, etc.).10 For those services they reported needing, participants indicated 
whether or not they had been able to obtain that service. A composite variable was created indicating 
whether participants had obtained at least one needed service (0 = no, 1 = yes). 
eHealth literacy. eHealth literacy was assessed with 8 items from the eHealth Literacy Scale 
(e.g., “I know what health resources are available on the Internet,” αs = .92-.94).11 Responses were on a 
scale from strongly disagree (1) to strongly agree (5). Items were averaged; higher scores indicated 
greater literacy. 
Feasibility and Acceptability 
 
These items were included only in the follow-up assessment. 
 
Feasibility. To contribute additional information related to intervention feasibility, participants 
provided information on why they did not participate in or complete programs (when relevant) and 
reasons for missing sessions. In relation to the HemaSpot kits, participants provided open-ended 
information on issues they encountered before, during, or after collecting their blood sample. 
Intervention acceptability. Participants separately evaluated the acceptability of each individual 
program they were randomly assigned to by indicating how much they agreed or disagreed with 6 
statements (e.g., “The stigma reduction group sessions have helped me” and “I would recommend the 
strengths-based case management sessions to other people living with HIV”). Participants also provided 
open-ended responses regarding what they liked and disliked and suggestions for improvement. 
HIV Viral Load Testing 
At baseline and follow-up, participants were sent dried blood spot (DBS) kits by mail to complete 
self-collection of blood samples for HIV viral load testing. Each DBS kit contained a HemaSpot™ 
collection container, alcohol pads, lancets, gauze pads, bandages, a biohazard bag labeled with participant 

ID, a postage paid envelope for specimen return, and an instruction card, written at an 8th grade reading 
level, that described how to collect the specimen. Participants could also call the study coordinator for 
additional assistance. Following specimen collection, participants placed the filled HemaSpot™ container 
into the shipping envelope, which sent the specimen directly to the clinical laboratory for testing. 
Shipping was tracked by the study team and the laboratory also logged the arrival of each specimen. 
Study Design and Randomization 
This pilot was designed to test the feasibility and acceptability of both the interventions and of a 
multiphase optimization strategy (MOST) design. MOST involves testing the impact of multiple 
interventions or intervention components simultaneously using a factorial design.12 Therefore, using the 
REDCap randomization module, participants were randomly assigned to 1 of 16 conditions in a 2 (social 
support groups) x 2 (stigma reduction groups) x 2 (SBCM) x 2 (technology detailing) between-
participants factorial design. Based on condition, participants were invited to participate in 0, 1, 2, 3 or 4 
of the interventions. Information on the 16 conditions is provided in Table 1. To balance the number of 
participants in groups over time, randomization occurred in blocks of 32. Neither participants nor study 
staff were blinded to participant randomization. 
Interventions 
Prior work of our team and others identified factors that may affect health-related quality of life, 
engagement in medical care, medication adherence, and viral suppression. We chose interventions that 
aimed to increase social support, decrease HIV-related stigma, overcome participants’ structural barriers 
to care, and increase technology use to engage in healthcare for this study. We aimed to identify 
evidence-based interventions—that could potentially be delivered remotely— to target each domain. Prior 
to enrolling participants, we conducted interviews with staff members at our community partner agencies 
to discuss our proposed interventions and receive input on how best to adapt their implementation for our 
target population. Following this input, each intervention was fully manualized and staff members were 
trained on the interventions they delivered. 

Participants were randomly assigned to participate in zero to four of the interventions. All 
participants also received written information on healthy aging with HIV. Receipt of this information 
served as the control condition for those not assigned to any intervention group. 
Social support group-based intervention. Social support has been identified as a factor that could 
affect medication adherence among older people living with HIV (PLH).13 Researchers have 
demonstrated that many PLH lack needed social support, and low levels of perceived social support, 
isolation, and loneliness can impede medication adherence among older PLH.14  Social support 
availability and satisfaction can contribute to positive health outcomes as well as reduce internalized HIV-
related stigma.15 A review of social support group interventions for PLH found they have a high impact 
on morbidity and retention in care as well as a positive impact on mortality and quality of life. However, 
the availability of support groups are limited for PLH in rural areas, and access to such services is 
hampered by long distances and limited transportation options. In-person groups may exclude the most 
vulnerable adults and may not be practical for geographically isolated rural PLH.  
Based on this foundation, we adapted a supportive-expressive group therapy (SEGT) 
intervention16 for online delivery to rural older PLH. This telephone-administered intervention was 
previously shown to reduce depressive symptoms among older PLH. However, the efficacy of SEGT for 
improving viral suppression, medication adherence, and quality of life among rural older PLH has not 
been tested. 
The intervention was designed to generate social support among participants and provide them 
with skills and resources needed to identify and enhance other sources of social support in their lives. We 
adapted the intervention to allow video or telephone-only participation. The 8 weekly 90-minute sessions 
were held on an online platform, allowing video and telephone connectivity, and were facilitated by a 
licensed psychiatrist who assisted with adapting the intervention manual. Each of the 8 sessions had a 
specific focus: (1) introductions, overview, goal setting; (2) “Why did HIV happen to me?”; (3) values 
and life priorities; (4) uncertainty and lack of control; (5) doctor-patient relationship; (6) friend/family 

relationships; (7) self/body image; and (8) summary and closure. We ran 3 waves of this intervention with 
between 9 and 11 participants in each group. 
Stigma reduction group-based intervention. Prior work has demonstrated high levels of HIV-
related stigma in rural PLH and its association with poorer care engagement and viral suppression (R01 
3,14,15,16), Lucksted and colleagues published results from a 9-session group intervention, Ending Self 
Stigma, that successfully reduced internalized stigma related to mental illness and increased perceived 
social support.17 This intervention was based on the Social-Cognitive Model of Internalized Stigma. 
Additional cognitive restructuring interventions have also used affirmative and validating approaches 
shown success in reducing internalized stigmas and improving participants’ confidence and ability to 
cope with stigma and discrimination. (R01 29, 3). We adapted the Ending Self Stigma intervention to 
focus on reducing internalized stigma related to HIV. The six weekly 90-minute sessions were held online 
and were facilitated by a licensed psychiatrist who assisted with adopting the intervention manual for this 
study. Each session had a specific focus: (1) introducing stigma and eliciting participants’ experiences 
with stigma; (2) interrupting “automatic thoughts” that perpetuate stigma; (3) strengthening self-concept; 
(4) increasing belonging; (5) handling disrespect and discrimination; and (6) summary and next steps. We 
ran 3 waves of this intervention with between 7 and 11 participants in the groups.  
Strengths-based case management (SCBM). Practical and logistical challenges, and other 
individual-level barriers can pose obstacles to care engagement and medication adherence. SBCM 
interventions address participants’ proximal life stressors by assisting them to recognize their personal 
abilities and prior successes to establish self-efficacy for current and future problem solving. In practice, 
this may include empowering a participant to navigate issues related to employment, interpersonal 
relationships, medical insurance, general health, mental health, housing, or transportation. The strengths 
model of case management has been successful in linking recently diagnosed or out-of-care PLH to care 
and reducing HIV transmission risk among PLH.18-22  
Based on the previous success of SBCM, we adapted an SBCM intervention focused on STI 
acquisition23 to address barriers to HIV medical care and medication adherence. The adapted intervention 

used an individually-tailored approach to address barriers elicited from each participant and was delivered 
by a trained study staff member through one-on-one telephone or Zoom video sessions. 
The adapted intervention involved an initial session where rapport was developed between the 
staff member and participant, the participant’s background and life challenges were discussed, and the 
participant was assisted in eliciting and then ranking stressors or obstacles they perceived as barriers to 
HIV care or medication adherence. Then, the most prominent stressor was discussed and strategies for 
overcoming it were developed, along with a specific action plan. A longer session was held 
approximately one week later, where progress was reviewed, strengths in overcoming barriers or taking 
action were identified, and lessons to use for future challenges were elicited. Then, new short and 
intermediate term goals were identified to overcome additional identified barriers. Up to 3 additional brief 
follow up sessions were conducted over the next three to five weeks, as needed, to check on progress on 
the identified action steps and tweak individual goals. 
 
Personalized technology detailing. Medication adherence and care engagement can be affected 
by internet access and technology use among older rural PLH.24 Technology can be leveraged to improve 
access to HIV and mental health care for patients in rural areas who may face challenges traveling longer 
distances to treatment. However, telehealth, online prescription access, or electronic medical records may 
be more difficult to access for older adults with lower technology literacy.25  We developed this 
intervention based on the information-motivation-behavioral skills (IMB) model26 and provided each 
assigned participant with individual sessions wherein they were provided with information on utilizing 
the internet for health-related purposes; motivating them by discussing how they could utilize the internet 
for learning more about their health, accessing medical or pharmacy services, and finding social or 
practical support; and assisting them in building their skills in using technology. The intervention used a 
framework viewing technology use for healthcare purposes as a continuum, as follows: (1) technology 
literacy or awareness; (2) access to the internet at home (including device and service); (3) use of the 
internet in general; and the ultimate goals of (4) utilization of the internet for obtaining medical care, 
pharmacy services, health-related information, and social support.  

Up to 5 sessions were held with each participant assigned to this intervention. In the initial 
session, an assessment of current technology use was conducted. For those participants who were already 
at goal of technology utilization for healthcare information and services, no additional sessions were held. 
Up to a total of 5 sessions were held for those participants not already at goal technology utilization. The 
content of each session was individualized based on the participant's current status, and included 
education on the utility of technology in accessing health care or health information, understanding how 
to obtain internet access and an appropriate device (cellular-enabled tablets were made available to 
participants who could not otherwise afford equipment or internet access), accessing the participant’s 
electronic health record and their pharmacy online, conducting a virtual visit with a provider, and utilizing 
the internet to find social support and educational materials on health topics.  
Fidelity 
 
Fidelity was monitored using checklists that facilitators would complete at the end of each session 
of each intervention tracking whether all components of the session were implemented. Early sessions of 
each intervention were reviewed by the principal investigators to ensure fidelity and provide feedback. 
Debriefing Interviews 
We conducted debriefing phone interviews with 14 randomly selected participants to obtain 
additional acceptability data and identify potential areas for modification. Debriefing interviews lasted 
approximately 20 minutes and were conducted by study staff not involved in delivering the interventions.  
Data Analysis 
Statistical analyses were performed with SPSS and R.27,28 We analyzed data using an intent-to-
treat principle, with participants analyzed based on the interventions they were assigned to regardless of 
intervention participation. 
Descriptive statistics were used to summarize sample characteristics and intervention feasibility 
and acceptability. T-tests and Fisher’s exact tests were used to compare baseline characteristics of 
participants who did and did not complete the follow-up assessment as well as participants assigned vs. 
not assigned to each intervention. 

To test preliminary impact, we fit linear and generalized linear mixed models using the R package 
lme4. For continuous outcomes (QOL, depressive symptoms, social support, loneliness, internalized 
stigma, QOL personal beliefs, and eHealth literacy), we fit linear mixed models with the lmer function, 
and for categorical outcomes (medication adherence, DBS VL, and service utilization), we fit generalized 
mixed-effect logistic regression models with the glmer function and a logit link. Models included a 
random effect for participant and utilized all available data, including baseline data from participants 
missing follow-up data. Predictors (fixed effects) included time (baseline vs. follow-up), random 
assignment to each of the 4 interventions, and interactions between assignment to the 4 interventions and 
time. We adjusted for mode of survey completion, which differed for those with and without follow-up 
data as well as for those assigned vs. not assigned to the stigma reduction groups. Interaction terms were 
of primary interest, with significant interactions indicating differential changes in outcomes over time for 
those randomly assigned vs. not randomly assigned to different interventions. Due to the small sample 
size, we did not test interactions between different interventions. For continuous outcomes, we calculated 
Cohen’s d as a measure of effect size using the R function lme.dscore in the EMAtools package, which 
calculates Cohen’s d from the mixed model results. For categorical outcomes, we report odds ratios as a 
measure of effect size. 
Given that our factorial design resulted in many “control” participants who were assigned to 
alternative interventions, for this pilot we also report on changes over time in outcomes for participants 
randomly assigned to each intervention. These changes were once again tested with mixed models that 
contained only participants assigned to each intervention. Here, time was the predictor of interest, and we 
again controlled for mode of survey administration. 
All tests performed were 2-sided. Given that the study was a pilot, we used α = .25 as a 
significance level cutoff and focus primarily on patterns in the data and effect sizes. 
 
 

Table 1 
Random Assignments in the Full Factorial Multiphase Optimization Strategy (MOST) Design 
Condition # Social Support Stigma Reduction SBCM Tech Detailing HIV Info N Assigned 
1 
OFF 
OFF 
OFF 
OFF 
ON 
4 
2 
OFF 
OFF 
OFF 
ON 
ON 
4 
3 
OFF 
OFF 
ON 
OFF 
ON 
4 
4 
OFF 
OFF 
ON 
ON 
ON 
4 
5 
OFF 
ON 
OFF 
OFF 
ON 
4 
6 
OFF 
ON 
OFF 
ON 
ON 
4 
7 
OFF 
ON 
ON 
OFF 
ON 
3 
8 
OFF 
ON 
ON 
ON 
ON 
4 
9 
ON 
OFF 
OFF 
OFF 
ON 
4 
10 
ON 
OFF 
OFF 
ON 
ON 
4 
11 
ON 
OFF 
ON 
OFF 
ON 
4 
12 
ON 
OFF 
ON 
ON 
ON 
4 
13 
ON 
ON 
OFF 
OFF 
ON 
3 
14 
ON 
ON 
OFF 
ON 
ON 
3 
15 
ON 
ON 
ON 
OFF 
ON 
4 
16 
ON 
ON 
ON 
ON 
ON 
4 

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