2026-10-06T16:04:21Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34072543 2026-10-05T17:37:44Z category_4 category_146 category_7 category_12 category_21 category_45 category_734 portal_5 item_type_3 month_year_10_2026

<p>Cartridge or test procedure issues.</p> Kiara Lee (8779112) Enrique Chen Liang (25317010) Alejandra Tolentino (25317013) AuDuyen Trinh (25317016) Daniel Leon (5175353) Kyle Goodwin (13277346) Jennifer Sprecher (21781768) Fernando Rubinstein (6650612) Barry Lutz (5175350) Sarah Iribarren (21781771) Biochemistry Space Science Medicine Cell Biology Biotechnology Sociology Biological Sciences not elsewhere classified xlink "> tuberculosis visual content analysis study assessed real recent medication ingestion clearer interpretation protocols white ), yellow engineering design principles visual evidence consistent isoniazid metabolite consistent clear positives included based lfas connected atypical color outcomes 72 %) images photo quality issues common test artifact submitted lfa images submitted images tst ), cartridge design clear positive clear negative based reporting based reading color change world interpretability teal hues strip contamination strip artifacts reduce artifacts possible cross patient education newly diagnosed mobile phone mobile application long course improve performance eligible participants dye bleed despite challenges centered improvements aged 16 <div><p>Tuberculosis (TB) treatment requires strict adherence over the long course of treatment. To support adherence, we developed the TB Treatment Support Tools (TB-TST), which combines a urine-based lateral flow assay (LFA) with a mobile application for patient education, support, and communication with treatment supporters. In a pragmatic randomized controlled trial participants uploaded images of the LFA. A blue-purple color change indicates detection of an isoniazid metabolite consistent with recent medication ingestion. This study assessed real-world interpretability and usability of the TB-TST LFA by analyzing the quality and characteristics of user-submitted images. We conducted structured qualitative coding (visual content analysis) of 1,655 submitted test images to identify recurring issues affecting interpretation. Eligible participants were aged 16 or older, newly diagnosed with TB, and had access to a mobile phone. An iteratively developed codebook identified three primary issue categories: 1) color variations in the test or control strip, 2) photo quality issues, and 3) test cartridge/test-strip artifacts. Most (72%) images were consistent with a clear positive (blue-purple) color change or clear negative. Variations that were not clear positives included no color change (white), yellow/orange, and green/teal hues. Blurriness was the most common image quality issue. The most common test artifact was visual evidence consistent with dye bleed/possible cross-strip contamination between the control and the test strips. Despite challenges in image submission and test appearance, relatively few images were difficult to interpret, supporting the feasibility of user-submitted LFA images for monitoring recent isoniazid ingestion. Opportunities to improve performance and usability include enhanced user guidance for image capture, refinement to cartridge design to reduce artifacts, clearer interpretation protocols for atypical color outcomes, and automated image-based reading. Integrating qualitative image analysis with engineering design principles can inform user-centered improvements to home-based LFAs connected to digital adherence technologies.</p></div> 2026-10-05T17:37:29Z Dataset Dataset 10.1371/journal.pgph.0007182.t006 https://figshare.com/articles/dataset/_p_Cartridge_or_test_procedure_issues_p_/34072543 CC BY 4.0