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Record W4319321993 · doi:10.2196/44122

Centering Frontline Health Care Workers in Digital Innovation Design to Inform the Optimization of an App for Improved Male Circumcision Follow-up in South Africa: Qualitative Usability Study

2023· article· en· W4319321993 on OpenAlexvenueno aff
Sarah Day, Vuyolwethu Ncube, Lactricia Maja, Beatrice Wasunna, Jacqueline Pienaar, Geoffrey Setswe, Evelyn Waweru, Caryl Feldacker

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchNational Institutes of Health
KeywordsUsabilityThematic analysisQualitative researchMedicineHealth careNursingQualitative propertyRandomized controlled trialMedical educationSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Voluntary medical male circumcision (VMMC) is a safe and effective HIV prevention strategy. However, adherence to recommended in-person, postoperative follow-up is inefficient for procedures with few adverse events. Two-way texting (2wT)-based follow-up appears to be a safe and an efficient alternative to scheduled clinic visits for low-risk patients who underwent VMMC. To ensure that 2wT responds to the needs of health care workers (HCWs) and patients, HCWs were closely involved in app design using a human-centered design (HCD) approach. OBJECTIVE: Embedded within an ongoing randomized controlled trial of 2wT in South Africa and complementary HCD processes of 2wT app optimization, this qualitative study aimed to use key informant interviews (KIIs) to explore the thoughts, suggestions, and opinions on and perceptions of 2wT's usability and acceptability among HCWs involved in 2wT implementation in both urban and rural South Africa. METHODS: A total of 7 HCWs using 2wT in Gauteng and the North West province participated in KIIs regarding the usability and acceptability of 2wT. HCWs were asked for their opinions on 2wT as a viable, useful, appropriate, and accessible method of postoperative VMMC care. They were also asked about 2wT-related working, exploring areas where 2wT could add to or reduce their daily tasks. The KII data were explored, coded, and analyzed by 3 qualitative researchers using thematic content analysis and the ATLAS.ti (ATLAS.ti Scientific Software Development GmbH) software. RESULTS: Most HCWs felt confident, comfortable, satisfied, and well supported using a 2wT-based follow-up as an alternative to in-person clinical reviews. They felt that 2wT was easy to use and required little technical support after initial mentoring on how to use the 2wT system. Few noted safety concerns, as men can receive clinical guidance, reassurance, and referral via 2wT. Although fewer in-person visits reduced the in-person review workload and eased clinical flow, HCWs noted the added burden of having to interact with clients via SMS text messages on evenings or weekends. HCWs reinforced the need for enhanced postoperative counseling to ensure that 2wT patients could recognize and understood how to respond to early signs of complications. HCWs suggested a rotation to spread the evening and weekend workload and ensure swift patient responses. CONCLUSIONS: In this formative qualitative study focused on HCWs, 2wT was a highly usable alternative to in-person postoperative reviews for patients who underwent VMMC in South Africa. The HCD processes likely improved the usability and acceptability of 2wT for HCWs. HCWs supported the scale-up of 2wT given the distance from the clinic to the men's homes and the potential for reducing workload. To ensure success, providers urged sensitizing patients to the fact that 2wT augments, but does not replace, the existing after-hours and emergency care services.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.167
GPT teacher head0.488
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2023
Admission routes1
Has abstractyes

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