Mobile Health Case Management System for Reducing Pediatric Treatment Abandonment
NCT ID: NCT03677128
Last Updated: 2023-05-09
Study Results
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View full resultsBasic Information
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COMPLETED
NA
75 participants
INTERVENTIONAL
2019-07-23
2022-04-22
Brief Summary
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Detailed Description
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For Aim 1, mNavigator development will initially focus on the two nationally-approved protocols for Burkitt lymphoma and retinoblastoma. The treatment for Diffuse large B-cell lymphoma (DLBCL) follows the Burkitt lymphoma treatment protocol. Using principles of persuasive system design and the Consolidated Framework for Implementation Research (CFIR), prompts that guide users through protocol implementation will be used as behavioral triggers to assist with perceived ease of use.
For Aim 2, allied health providers at BMC will receive training on using mNavigator as part of an in-country workshop led by the M-PIs. This training will be followed by supported implementation. Following this training period, mNavigator will be used to enroll pediatric patients at BMC with pre-clinical diagnosis of BL, Diffuse large B-cell lymphoma (DLBCL) or Rb, over a period of over one and a half years and manage their care for the duration of treatment (up to 3 months for BL and DLBCL, and 4 months for Rb). BMC receives and treats approximately 150 patients every year, with an estimated 50 patients annually with Burkitt lymphoma (BL), Diffuse large B-cell lymphoma (DLBCL) or Rb. To review historic compliance, files of patients diagnosed after 2015 with BL, Diffuse large B-cell lymphoma (DLBCL) and Rb (when protocols were introduced) will be abstracted by trained research assistants. Compliance with protocol-driven treatment will be monitored using mNavigator. System functionality will be assessed. Semi-structured assessments of provider system acceptance and usability will be conducted along with elucidating caregiver reported barriers to treatment completion.
Secondary objective is to describe factors that facilitate or inhibit implementation of mNavigator.
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
HEALTH_SERVICES_RESEARCH
NONE
Study Groups
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mNavigator
Allied health providers will use mNavigator to guide diagnosis and treatment for pediatric cancer patients at Bugando Medical Centre (BMC).
mNavigator
Allied health providers at BMC will use mNavigator to facilitate compliance with protocol-driven treatment and reduce patient abandonment for patients diagnosed with Burkitt lymphoma, Diffuse large B-cell lymphoma or retinoblastoma.
Historical controls
BL (DLBCL)/Rb retrospective patients (treated between 2015-2019) when standardized treatment protocols for BL (DLBCL) and Rb were introduced at BMC.
No interventions assigned to this group
Interventions
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mNavigator
Allied health providers at BMC will use mNavigator to facilitate compliance with protocol-driven treatment and reduce patient abandonment for patients diagnosed with Burkitt lymphoma, Diffuse large B-cell lymphoma or retinoblastoma.
Eligibility Criteria
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Inclusion Criteria
* Must be 18 years of age or older.
Exclusion:
\- Persons younger than 18 years of age.
Exclusion Criteria
* Patients with diagnoses other than Burkitt lymphoma, Diffuse large B-cell lymphoma or retinoblastoma.
B) For providers:
ALL
No
Sponsors
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National Cancer Institute (NCI)
NIH
Duke University
OTHER
Responsible Party
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Principal Investigators
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Kristin Schroeder, MD MPH
Role: PRINCIPAL_INVESTIGATOR
Duke University
Lavanya Vasudevan, PhD
Role: PRINCIPAL_INVESTIGATOR
Duke University
Locations
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Bugando Medical Centre
Mwanza, Lake Zone, Tanzania
Countries
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References
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Vasudevan L, Schroeder K, Raveendran Y, Goel K, Makarushka C, Masalu N, Zullig LL. Using digital health to facilitate compliance with standardized pediatric cancer treatment guidelines in Tanzania: protocol for an early-stage effectiveness-implementation hybrid study. BMC Cancer. 2020 Mar 29;20(1):254. doi: 10.1186/s12885-020-6611-3.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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Pro00094010
Identifier Type: -
Identifier Source: org_study_id
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