mVIP (Use of mHealth Technology for Supporting Symptom Management in Underserved Persons Living With HIV) (mVIP)

• ClinicalTrials.gov Identifier: NCT02897141
• Recruitment Status: Completed
• First Posted: September 13, 2016
• Results First Posted: October 10, 2018
• Last Update Posted: March 26, 2019
• Sponsor: Columbia University
• Information provided by (Responsible Party): Rebecca Schnall, RN, MPH, PhD, Columbia University

Study Description

Brief Summary:

The goal of this study is to facilitate the dissemination and implementation of patient centered outcomes research using mHealth technology to improve self-management of adverse symptoms in persons living with HIV/AIDS (PLWH). Symptom management in PLWH is especially important because the US HIV epidemic continues to exact a huge toll, especially among Agency for Healthcare Research and Quality (AHRQ) priority populations including racial, ethnic, and sexual minorities and low-income persons. The incorporation of HIV symptom management strategies into patients' lives through the use of mHealth technologies has the potential to advance the effective dissemination and implementation of patient centered outcomes research findings.

Condition or disease	Intervention/treatment	Phase
HIV (Human Immunodeficiency Virus)	Device: Health Management App with symptom strategies; Device: Control App	Not Applicable

Detailed Description:

HIV has changed from an acute illness to a chronic disease. The success of HIV medications and treatments has significantly altered the course of the disease. While AIDS-related illnesses are no longer the primary threat, a new set of HIV-associated complications have emerged, resulting in a chronic disease that for many will span several decades of life. The ability to self-manage adverse symptoms of HIV illness has been shown to improve patient-centered outcomes. In response to this need, a team at University of California, San Francisco (UCSF) developed a paper-based symptom management manual with self-management strategies for 21 common HIV/AIDS adverse symptoms (PCOR evidence). The efficacy of the manual was demonstrated in a 775-person randomized controlled trial (RCT) over three months at 12 sites. However, subsequent use of these strategies has been very limited; mHealth offers an ideal platform for the implementation and dissemination of evidence-based strategies for HIV symptom management. Due to the high incidence of HIV among racial and ethnic minority populations, it is appropriate to develop mHealth tools tailored to the needs of these populations. mHealth technology has the potential to address many of the healthcare needs of persons living with HIV/AIDS (PLWH) including symptom management. In response to these current issues, this study seeks to inform the development and testing of a mHealth application that will incorporate findings from PCOR studies to improve the outcomes of PLWH. To improve outcomes for those most in need, study activities are focused on communities with the greatest burden of HIV in the US, including racial and ethnic minorities and those of low socioeconomic status.

Study Design

• Study Type: Interventional (Clinical Trial)
• Actual Enrollment: 80 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Masking: Double (Participant, Outcomes Assessor)
• Primary Purpose: Supportive Care
• Official Title: Use of mHealth Technology for Supporting Symptom Management in Underserved Persons Living With HIV
• Actual Study Start Date: December 12, 2016
• Actual Primary Completion Date: June 8, 2017
• Actual Study Completion Date: June 8, 2017

Arms and Interventions

Arm	Intervention/treatment
Experimental: mVIP group; This group will receive targeted symptom strategies via a Health Management App developed from the UCSF symptom management manual based on the symptoms that they report. This is the intervention app group.	Device: Health Management App with symptom strategies; The mVIP group will receive a Health Management App with symptom strategies. A mobile app which includes symptom strategies from the UCSF symptom management manual.
Placebo Comparator: Attention Control Group; This group will received an app without symptom strategies, pre-loaded on their smartphones. This is the control app group.	Device: Control App; The attention control group will receive an app which asked them about their symptoms but did not provide symptoms strategies

Outcome Measures

Primary Outcome Measures :

1. Change in Symptom Status From Baseline to Week 12 [ Time Frame: Baseline and 12 weeks ]
   Change in Symptom Status calculates the difference in symptom scores between the intervention and control groups at baseline versus follow-up after 12 weeks. Symptom scores were determined using the Revised Sign and Symptom Check-List for HIV (SSC-HIVrev), where participants who reported experiencing any one of the 13 symptoms in the past 7 days were asked how much it bothered them (a little bit, somewhat, quite a bit, or very much). Instances where the symptom did not bother the individual were coded as "0" whereas instances where the symptom bothered the individual any amount were recoded as "1". The overall difference between groups at baseline and after 12 weeks ("difference of differences") falls within a range of -1 to 1, where lower numbers indicate the symptom bothered the person less, while higher numbers indicate it bothered them more. With the Difference Between Groups, a more negative score (closer to -1) represents a better outcome.

Secondary Outcome Measures :

1. Change in Quality of Life -- RAND-36 [ Time Frame: Baseline and 12 weeks ]
   36-Item Short Form Survey (RAND-36) is a widely-used 36-item tool to measure health-related quality of life, where each item in the scale is scored as 0, 25, 50, 75, or 100. Scoring is a two-step process. First, precoded numeric values are recoded per the scoring key so that all items are scored so that a high score defines a more favorable health state. In addition, each item is scored on a 0 to 100 range so that the lowest and highest possible scores are 0 and 100, respectively. Scores represent the percentage of total possible score achieved. In step 2, items in the same scale are averaged together to create the 8 scale scores, where a lower score may indicate a better outcome for some of the scales, while it may indicate a better outcome for others.
2. Patient-Reported Outcomes Measurement Information System (PROMIS)-29 [ Time Frame: 12 weeks ]
   The PROMIS-29 includes seven health related quality of life domains on a 5-point scale from a score of 1 to 5 and the pain domain has two subdomains (interference and intensity) where pain intensity is assessed using a single 11-point numeric rating scale anchored between no pain (0) and worse imaginable pain (10). Raw scores are transformed using the T-score metric based on the item response theory calibrations in which scores have a mean of 50 and standard deviation of 10 for the general population in the US. T-scores can be estimated using the scoring tables listed in the PROMIS manuals. A higher PROMIS T-score implies more of the concept being measured; for instance, a higher PROMIS score on physical function indicates better functioning, whereas a higher score on depression indicates a greater severity of depression.
3. Engagement With Healthcare Provider [ Time Frame: Baseline and 12 weeks ]
   Engagement with Health Care Provide scale is a 13-item scale in which subjects rate their interactions with their health care providers on a four-point scale with 1=always true and 4=never true in which a lower score indicates a better outcome. The scores are then collated to an aggregate score where the minimum value = 13 and the maximum value = 52. A low score indicates greater provider engagement, where as higher scores indicate lower provider engagement (less favorable outcome). The difference in scores at baseline and follow-up at three months was calculated within both the intervention and control groups, and the difference was then taken between the resulting means of those scores.
4. Medication Adherence [ Time Frame: 12 weeks ]

   Medication adherence was calculated by two scales: the Center for Adherence Support Evaluation (CASE) Adherence Index and the Visual Analogue Scale (VAS). The CASE Adherence Index consists of the composite scores of three questions evaluating self-reported measures of adherence. The minimum score on this scale is 3 while the maximum score on this scale is 16, with higher scores indicating better outcome. Scores greater than 10 indicate "good adherence," while scores less than or equal to 10 indicate poor adherence.

   The VAS asks subjects to indicate a point on a line that shows their best guess about how much of each drug they have taken from a scale of 0% to 100% in which 0% means they have taken no drug, 50% means they have taken half their drugs, and 100% means they have taken every single dose. Consequently, a higher score (100%) indicates

5. Health-IT Usability Evaluation Scale (Health-ITUES) [ Time Frame: 12 weeks ]
   Health Information Technology Usability Evaluation Scale (Health-ITUES) was used to measure usability. Health-ITUES consists of 20 items rated on a 5-point Likert scale from strongly disagree (score of 1) to strongly agree (score of 5) measuring actual usage, intention to use, satisfaction, perceived usefulness, perceived ease of use, perceived performance speed, learnability, competency, flexibility/customizability, memorability, error prevention, information needs, and other outcomes. A higher score (5) indicates higher usability. Overall score was calculated as the mean score from the score for quality of life, perceived usefulness, perceived ease of use, and user control.

Eligibility Criteria

• Ages Eligible for Study: 18 Years and older (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Criteria

Inclusion Criteria:

1. Diagnosed with HIV/AIDS
2. Over the age of 18 years
3. Able to provide written informed consent
4. Able to communicate in English
5. Health literacy level of marginal or inadequate (as measured by the Newest Vital Sign (NVS): total score of 3 or lower)
6. Report at least 2 HIV related adverse symptoms in the past week
7. Owner of a smart phone/tablet.

Exclusion Criteria:

1. Inability to communicate in English
2. Documented diagnosis of dementia
3. Pregnancy
4. Unable to understand consent procedure
5. Self-reporting no adverse symptoms within the past week. (HIV-related symptoms include: anxiety, constipation, cough, depression, diarrhea, dizziness, fever, forgetfulness, fatigue, nausea, night sweats, neuropathy, shortness of breath, dermatitis, swelling of arms, hand, legs, feet, insomnia, weight loss, oral thrush, and vaginal itching, burning and discharge)

Contacts and Locations

Locations

United States, New York

Columbia University School for Nursing

New York, New York, United States, 10032

Sponsors and Collaborators

Columbia University

Investigators

• Principal Investigator: Rebecca Schnall, PhD, MPH, RN-BC, FAAN; Columbia University

  Study Documents (Full-Text)

Documents provided by Rebecca Schnall, RN, MPH, PhD, Columbia University:

Study Protocol and Statistical Analysis Plan  [PDF] June 17, 2018

More Information

• Responsible Party: Rebecca Schnall, RN, MPH, PhD, Assistant Professor of Nursing, Columbia University
• ClinicalTrials.gov Identifier: NCT02897141
• Other Study ID Numbers: AAAP1258; R21HS023963 ( U.S. AHRQ Grant/Contract )
• First Posted: September 13, 2016
• Results First Posted: October 10, 2018
• Last Update Posted: March 26, 2019
• Last Verified: March 2019

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

Keywords provided by Rebecca Schnall, RN, MPH, PhD, Columbia University:

HIV; Health Management App; HIV symptoms

Additional relevant MeSH terms:

Acquired Immunodeficiency Syndrome; HIV Infections; Immunologic Deficiency Syndromes; Immune System Diseases; Blood-Borne Infections; Communicable Diseases; Infections; Sexually Transmitted Diseases, Viral; Sexually Transmitted Diseases; Lentivirus Infections; Retroviridae Infections; RNA Virus Infections; Virus Diseases; Slow Virus Diseases