Development of an Electronic Data Collection System to Support a Large-Scale HIV Behavioral Intervention Trial: Protocol for an Electronic Data Collection System

Comulada, W. Scott; Tang, Wenze; Swendeman, Dallas; Cooper, Amy S.; Wacksman, Jeremy

doi:10.2196/10777

Cited by 15 publications

(13 citation statements)

References 23 publications

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“…Secure data platforms are advised for data collection [1,10,11,19,24]. Investigators in several studies were careful to remove as much identifying participant information as possible, using telephone numbers or participant IDs in the datasets [11,25], recommending that participants immediately delete messages after answering them, and encouraging participants to password protect their phones [16,17,24].…”

Section: The Datamentioning

confidence: 99%

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Best practices for collecting repeated measures data using text messages

Shimoni

Nippita

Castaño

2020

BMC Med Res Methodol

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Background: Researchers and clinicians use text messages to collect data with the advantage of real time capture when compared with standard data collection methods. This article reviews project setup and management for successfully collecting patient-reported data through text messages. Methods: We review our experience enrolling over 2600 participants in six clinical trials that used text messages to relay information or collect data. We also reviewed the literature on text messages used for repeated data collection. We classify recommendations according to common themes: the text message, the data submitted and the phone used. Results: We present lessons learned and discuss how to create text message content, select a data collection platform with practical features, manage the data thoughtfully and consistently, and work with patients, participants and their phones to protect privacy. Researchers and clinicians should design text messages to include short, simple prompts and answer choices. They should decide whether and when to send reminders if participants do not respond and set parameters regarding when and how often to contact patients for missing data. Data collection platforms send, receive, and store messages. They can validate responses and send error messages. Researchers should develop a protocol to append and correct data in order to improve consistency with data handling. At the time of enrollment, researchers should ensure that participants can receive and respond to messages. Researchers should address privacy concerns and plan for service interruptions by obtaining alternate participant contact information and providing participants with a backup data collection method. Conclusions: Careful planning and execution can reward clinicians and investigators with complete, timely and accurate data sets.

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Section: The Datamentioning

confidence: 99%

“…Researchers should have a preset plan in place for how to capture supplemental data. A study in Los Angeles utilizing a large electronic data collection system for HIV self-management and prevention/engagement of HIV-negative youth quickly realized that staff needed open-ended running notes to log ad-hoc interactions with participants [24].…”

Section: The Datamentioning

confidence: 99%

Best practices for collecting repeated measures data using text messages

Shimoni

Nippita

Castaño

2020

BMC Med Res Methodol

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“…We anticipate a higher proportion of women in our sample from New Orleans and that while most youth from New Orleans will be African American, youth in Los Angeles will also be Latino and White and predominately GBTY. Further details on each of the ATN CARES studies may be found in the corresponding study protocol papers [112,[115][116][117][118]. Recruitment Process.…”

Section: Peer Support Via Social Mediamentioning

confidence: 99%

Text-Messaging, Online Peer Support Group, and Coaching Strategies to Optimize the HIV Prevention Continuum for Youth: Protocol for a Randomized Controlled Trial (Preprint)

Swendeman¹,

Arnold²,

Harris³

et al. 2018

Preprint

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Background: The rate of HIV has doubled in the last 15 years among young people to 22% of HIV cases. Scientific advances in biomedical HIV prevention strategies have not been utilized by youth. Methods/Design: Young people aged 12 -24 years old (n= 1500) are being recruited from community-based organizations (CBO) and clinics serving gay, bisexual, and transgender youth, homeless youth, youth on probation or released from incarceration, and youth in other high-risk venues (e.g., bars and clubs). Youth are randomized in a factorial design to: 1) an automated messaging and monitoring intervention (AMMI) using text messages (n = 900); 2) AMMI plus peer support via private social media (n = 200); 3) AMMI plus strengths-based coaching (n = 200); and 4) AMMI, peer support, and coaching (n = 200). At four-month intervals over 24 months, interviewers monitor: uptake of the steps in the HIV Prevention Continuum (linkage to health care and adherence to pre-or post-exposure prophylaxis or 100% condom use), and conduct repeat rapid diagnostic tests for HIV, sexually transmitted infections (STI), drugs and alcohol use. Weekly automated monitoring via text (or email) in AMMI includes questions on acute HIV and STI symptoms for immediate follow-up by interviewers to provide HIV and STI testing, STI treatment, and partner therapy. Discussion: The greatest impacts are expected among youth receiving the most intensive intervention (i.e., AMMI, peer support, and coach). However, the youth's concurrent mental health, substance abuse, and housing and food security are expected to be significant covariates that influence the uptake of the HIV Prevention Continuum. This study operationalizes the guidelines of the Centers of Disease Control and Prevention (CDC) regarding the prevention of HIV among the highest risk youth, using community-based point of care diagnostics supported by scalable technology-mediated interventions. Similarly, over 90% of adolescents under age 18 go online daily, more than half several times a day which is facilitated by access to smartphones among 75% of youth of each ethnicity, crossing the digital divide [28]. Much of this online activity is driven by social media use, particularly via smartphones -for example, over 70% of adolescents under 18 years use Facebook, while about half also use Instagram and Snapchat [28]. The interventions in this study use text messaging and social media to engage "youth where they are" in the digital environment. This approach has resulted in four intervention arms which vary in intensity and costs. In order of increasing intensity and costs, the interventions are: 1) automated text-messaging and weekly monitoring probes; 2) peer support via social media; 3) paraprofessional coaching; and 4) all three combined. This study's automated and interpersonally-mediated technology-based interventions will be based on the shared features of existing EBI -we will not create a new app nor an EBI with a manual to be replicated with 6 fidelity [14,33,34]. In the last 25 years, over...

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“…We hypothesize that by providing rapid STI testing among high-risk adolescent populations, we will find a high prevalence of STIs. We also expect that by providing same-day testing results, we will be able to [20][21][22][23][24].…”

Section: Objectivesmentioning

confidence: 99%