Current practices for assessing usability of novel point-of-care diagnostics for infectious diseases: a scoping review protocol

Abstract

Introduction

Novel diagnostics, particularly point-of-care (POC) tests, play a crucial role in the early detection and management of infectious diseases, especially in resource-limited settings. Ensuring test performance and quality while minimising the risk of human error becomes more relevant when shifting testing tasks from highly controlled settings like centralised laboratories to people with minimal training. Applying usability and human factors engineering principles can reduce the challenges related to human errors. Despite existing frameworks and tools, the practical application of usability guidelines remains variable across different settings.

Methods and analysis

This scoping review protocol outlines a systematic investigation of current practices in assessing the usability of novel diagnostics, particularly POC tests for infectious diseases intended for use in low-income and middle-income countries. The review will analyse original research studies of all designs and product dossiers that report on the usability evaluation or validation of a diagnostic test for an infectious disease. A qualitative synthesis of the data extracted from the articles will be conducted. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols and the Joanna Briggs Institute guidelines for this scoping review.

Ethics and dissemination

No ethical approval is required because individual patient data will not be included. The findings will be disseminated through publication in a peer-reviewed journal.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• The scoping review encompasses a comprehensive and extensive search of the available evidence on the usability evaluation or validation of diagnostic tests for infectious diseases, encompassing both literature and product dossiers.

• No time limit or language restrictions will be applied.

• Limitations are the possible challenges in defining inclusion and exclusion criteria due to the variable definitions of point-of-care testing and usability.

• As a scoping review, the quality or risk of bias of individual studies will not be assessed.

Introduction

Decentralised diagnostics, including point-of-care (POC) tests used in settings such as primary care, communities, pharmacies or even at home, can facilitate early detection and prompt treatment, as well as reducing the transmission of infectious diseases.¹ They can help remove access barriers and improve health outcomes, particularly in settings where healthcare providers are scarce.^{2 3} The value of decentralised testing in different regions, especially in low-income and middle-income countries (LMICs), has been recognised for conditions like malaria, HIV and other sexually transmitted infections.⁴,⁶ However, the significance of decentralised testing became particularly apparent during the COVID-19 crisis, prompting stakeholders to further appreciate its importance in non-hospital settings.⁷

A growing number of POC tests are becoming more accessible in LMICs, with potential for implementation in a variety of settings, such as the community or primary care level. However, this development also introduces a set of complex challenges and a new dimension of risk. Unlike the highly regulated environments where trained medical technologists or healthcare providers are responsible for sample collection, processing and testing, decentralised testing shifts these tasks to individuals with minimal training. This shift carries consequences for test performance and patient safety as it may increase the risk of human error and complicate quality control.⁷

The development and evaluation of POC diagnostic tests for use in resource-limited environments have traditionally been guided by the ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free and Deliverable to end-users).⁸ More recently, expanded frameworks such as REASSURED and REST-ASSURED have been proposed to reflect emerging priorities, including Real-time connectivity, Ease of specimen collection and Sustainability, as well as integration with digital and data systems.^{8 9} These updated frameworks underscore the growing diversity of POC diagnostics, especially with the advent of digital diagnostics, and the resulting complexity to assess usability which needs to consider not only the human interaction with physical but also digital components.

Beyond user-friendliness, interactions between the user and the technology, specifically how the user perceives, interprets and processes information from the device, can also impact result interpretation and other critical steps, ultimately affecting the accuracy of tests in real-world settings. Human factors research is a methodology aimed at understanding human–device interactions and optimising the development of novel technologies, including diagnostics.¹⁰ Usability, as defined by Nielsen et al,¹¹ emerges as an important concept throughout the development process and for the implementation of the final market-ready product. It comprises five dimensions: learnability, efficiency, memorability, errors and satisfaction.^{11 12} Learnability refers to how easy it is to learn and use the system so that the user can quickly start working with it. Efficiency ensures high levels of productivity once the user has mastered the system. Memorability refers to how simple a testing procedure is to remember, allowing a casual user to return to it after a period of inactivity without having to relearn it. In addition, the system should have a low error rate, and users should find it simple to recover from errors. The dimension of satisfaction comprises the subjective perception of how pleasant it is to use.¹²

Standardised tools such as the System Usability Scale¹³ have been developed, validated and widely used for assessing the usability of medical technologies, including diagnostics. These tools facilitate data collection and analysis. However, they do not assess all of Nielsen’s components of usability.¹⁴ The US Food and Drug Administration’s (FDA) guidance documents, such as ‘Applying Human Factors and Usability Engineering to Medical Devices’, and the standards of International Organization for Standardization (ISO) 9241 provide a framework for developers to perform and report usability testing of new diagnostics.¹⁰ The ‘Recommendations for Clinical Laboratory Improvement Amendments of 1988 (CLIA) Waiver Applications for Manufacturers of In Vitro Diagnostic Devices’ also refers to study designs to assess human factors, the risk and the impact of user errors in POC testing. Further, the ISO 9241 standard provides guidance for the design and evaluation of interactive systems and elaborates on appropriate satisfaction, effectiveness and efficiency measurements.¹⁵ Yet, the translation of these standards into the practice of usability testing remains largely unexplored, particularly for investigators and developers outside of industry settings.

This study therefore aims to describe the current practices for assessing the usability of novel molecular diagnostics and immunoassays intended for use at POC in LMICs. These POC tests encompass a wide range of formats, such as lateral flow assays, dipsticks and portable devices, and vary in how results are displayed, including visual indicators like lines or colour changes, or digital readouts.¹⁶,¹⁸ We will further explore the gaps between existing guidance documents and their practical application, as shown in the literature. Through this scoping review, we seek to identify key elements of usability and human factors evaluations, as well as common methodological approaches for the evaluation of the usability of novel POC diagnostics. The ultimate goal is to generate a set of standards and guidance for developers and early implementers of novel POC tests, bridging the divide between existing standards and their effective application in real-world scenarios.

Methods and analysis

This scoping review protocol will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines¹⁹ and the Joanna Briggs Institute guidance for scoping reviews.^{20 21} The final publication will follow the recommendations from the PRISMA extension Scoping Reviews (PRISMA-ScR).²²

Definitions

During this work, we will adhere to the following definitions:

• Diagnostic test: “A test used to determine, verify or confirm a patient’s clinical condition as a sole determinant.”²³

• POC test: A technology that can be used by minimally trained healthcare providers at the location of patient care and outside of central laboratory testing facilities (eg, near the patient, community).²⁴ These may include molecular, antigen or antibody tests, which generate test results and timely care decisions within a patient visit.

• Self-testing: A process in which an individual collects their own specimen, conducts a test and interprets the test result.²⁵

• Human factors engineering: “The application of knowledge about human behavior, abilities, limitations, and other characteristics of medical device users to the design of medical devices including mechanical and software driven user interfaces, systems, tasks, user documentation, and user training to enhance and demonstrate safe and effective use.”¹⁰ This term can be considered a synonym for usability engineering.

• Usability: According to ISO, usability is the “extent to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use”.²⁶ Usability and human factors engineering also refer to methods for improving ease of use during the design process.^{11 27}

• User-centred design (also human-centred design): An iterative, collaborative and people-centred approach for products, services and systems design. It is an approach proposed as particularly well-suited for solving complex challenges.²⁸

Eligibility criteria

Inclusion criteria

Research studies of all designs, which report on the usability evaluation or validation of a diagnostic test for an infectious disease, are included. Only diagnostic tests intended for use within the care cascade prior to treatment (eg, diagnostic, screening or pretreatment tests) will be eligible. No restrictions on the intended use will be applied. Usability evaluations reported within larger clinical studies (eg, diagnostic performance) or product dossiers with usability information are also eligible.

During the development stage, both prototype and design-locked tests are eligible. We will include any POC molecular, antigen or antibody test that

• Can be either instrument-free or instrument-based.

• Can be used at lower levels of the healthcare system with basic to no laboratory infrastructure, including

  • Self-testing (eg, at home).

  • Level 0: community.

  • Level 1: primary care.

  • Level 2: district hospital lab.

• Can be operated by individuals with none to basic technical skills (eg, community health workers/field agents, laboratory technicians, self-testing users).

Exclusion criteria

Editorial comments, conference abstracts, opinion papers, letters and preprints. Review articles of any type (eg, systematic reviews, scoping reviews, narrative reviews, meta-analyses, umbrella reviews) will be excluded.

Despite the increasing role of digital technologies in diagnostic workflows, the present review focuses on the diagnostic tests themselves, rather than on the broader digital platforms with which they may be integrated.

Information sources

These will include peer-reviewed published scientific literature in indexed journals, grey literature and usability evaluations submitted to regulatory agencies as part of product dossiers.

Search strategy

An independent librarian will conduct the search in PubMed/MEDLINE, Embase and Web of Science. Two independent investigators (CAM-Q and HMI) will conduct the search in Google Scholar and grey literature databases. For Google Scholar and grey literature databases (LILACS, WHOiris, PAHOiris and EBSCO), different combinations of the search terms will be used per database, and all the hits will be exported and combined before removing duplicates using Zotero (https://www.zotero.org/). Online supplemental table S1 describes all the search term combinations and the final list of references after removing duplicates.

No search restrictions on publication time, language, setting or population will apply; however, the searches will be carried out in English. If necessary, translations will be done with the assistance of Google Translate, chatGPT and/or DeepL.

Websites from regulatory agencies, non-profit organisations and public–private initiatives will be searched for product dossiers, package inserts and information on usability. If the website contains product dossiers, a pilot search of 10 dossiers will be conducted to determine if they contain information regarding usability. Online supplemental table S2 provides a list of the websites selected for the scoping review.

Table 1 provides an overview of the search strategy used for PubMed/MEDLINE, including a partial list of illustrative search terms. The complete search strategies, including all terms and database-specific adaptations, are available in online supplemental table S1. Search terms will be adapted as necessary for the different databases.

Table 1. Search strategy for PubMed/MEDLINE according to the PCC framework for the research question.

Component of the search strategy (PCC question)		Search terms
Population	Healthcare providers with minimal to superior training (eg, community health workers/field agents, laboratory technicians)	Not included as part of the search strategy
Concept	1. Infectious diseases	“Communicable Diseases"[Mesh] OR ((Communicable[tw] OR infect*[tw] OR contagio*[tw]) AND (Disease*[tw] OR condition*[tw] OR disorder*[tw])) OR "Tuberculosis"[Mesh] OR Tuberculo*[tw] OR TB[tw] OR "Malaria"[Mesh] OR malaria[tw] OR "HIV"[Mesh] OR "Acquired Immunodeficiency Syndrome"[Mesh] OR hiv[tw] OR aids[tw] OR "lower respiratory infection*"[tw] OR […]
	2. POC testing, self-testing, near-patient, rapid diagnostic tests	"Point-of-Care Testing"[Mesh] OR "Point Of Care"[tw] OR "Bedside Test*"[tw] OR "Self-Testing"[Mesh] OR "Self Test*"[tw] OR Selftest*[tw] OR "Point-of-Care Testing"[Mesh] OR (("point of care*"[tw] OR “nearpatient”[tw] OR "bedside*"[tw] OR "rapid*"[tw] OR "in vitro"[tw]) AND ("test*"[tw] OR "diagnos*"[tw]))
	3. Type of test: molecular and antigen-based diagnostic with/without automated component for generation of result and/or result interpretation	"Molecular Diagnostic Techniques"[Mesh] OR "Molecular Diagnos*"[tw] OR "Molecular Test*"[tw] OR "Rapid Diagnostic Tests"[Mesh] OR "Direct-To-Consumer Screening and Testing"[Mesh]OR Antigen*[tw] OR "Lateral flow*"[tw] OR RDT[tw] OR ((Rapid*[tw] OR "direct to consumer*"[tw]) AND (Screen*[tw] OR Test*[tw] OR diagnos*[tw])) OR "Nucleic Acid Amplification Techniques"[Mesh] OR "Nucleic Acid Amplification"[tiab] OR "Line Probe Assay"[tiab] OR […]
	4. Usability	"User-Centered Design"[Mesh] OR “ease of use"[tw] OR "User Centered Design*"[tw] OR "human factor*"[tw] OR "Formative evaluation*"[tw] OR Usability[tw] OR "user experience"[tw] OR "user satisfaction"[tw]
Context	Low levels of health system in low-income and middle-income countries	Not included as part of the search strategy
Full search term		2 OR 3
	1 AND (2 OR 3) AND 4

The symbol […] indicates that additional terms were used in each category. The full search strategy, including all terms and Boolean operators, is available in online supplemental table S1.

PCC, population, concept and context.

Study records

All retrieved articles will be collated using Zotero (https://www.zotero.org/), and duplicates will be removed. For the screening process, Rayyan (https://www.rayyan.ai/) software will be used. Two reviewers (HMI and CAM-Q) will independently screen the titles and abstracts of the search results against the defined eligibility criteria. After the initial search, full-text screening will be performed by the same reviewers. The reference lists of the selected manuscripts will also be explored to identify additional articles of interest. Any discrepancies that emerge during the screening process will be resolved through consensus or by a third reviewer.

Data collection process

A customised extraction form will be used for data charting (table 2). Two reviewers will extract data from the selected reports, and any discrepancies will be resolved through consensus; if consensus cannot be reached, a third member of the research team will make the final decision. If necessary, additional information sources, such as the test developer’s website or the corresponding author of the articles, will be used to acquire any missing or additional data. Up to two contact attempts within 2 weeks will be made.

Table 2. Data extraction strategy.

Evidence source details and characteristics	Type of field (open-text description unless otherwise specified) and categories
Citation details	For example, author/s, date, title, journal, DOI
Country where study was conducted
Details extracted from source of evidence
Study setting	Multiple selection: self-testing; level 0 (L0)—community; level 1 (L1)—primary care; level 2 (L2)—district hospital lab; level 3 (L3)—regional/provincial lab; level 4 (L4)—reference/national lab; research lab; other (describe)
Participants	Community health workers/field agents; laboratory technicians; medical technicians; nurses; other (describe)
Type of test	Molecular test; antigen test; antibody test; other (describe)
Intended use setting	Multiple selection: Self-testing (eg, at home); level 0 (L0)—community; level 1 (L1)—primary care; level 2 (L2)—district hospital lab
Study design	[Text field]
Type of data collected	Multiple selection: quantitative; qualitative
Type of evaluation (if described)	Formative evaluation (eg, early prototype); validation (eg, design-locked); nested in a larger study (eg, as part of a diagnostic performance study)
Details of procedures in source of evidence
Sample size	[Number]
Method for sample size estimation and sampling	[Text field]
Description of critical tasks and use scenarios included in testing	[Text field]
Test environment	Real-life (describe); simulated (describe)
Data collection tools (quantitative)	Standardised/validated survey: [Description—text field] Non-standardised questionnaire: [Description—text field] Other (describe): [text field]
Methods for documenting observations and interview responses	[Text field]
Reported outcomes and metrics
Safety	[Text field]
Effectiveness	[Text field]
Efficiency	[Text field]
Acceptability	[Text field]
Satisfaction	[Text field]
Learnability	[Text field]
Memorability	[Text field]
Usability score	[Text field]
Ease of use score	[Text field]

Risk of bias in individual studies

In this scoping review, we will not assess risk of bias as the goal is to summarise and describe current practices in usability assessment for diagnostic tests for infectious diseases, rather than to evaluate the quality or outcomes of individual studies.

Data synthesis and analysis

We will conduct a narrative synthesis and descriptive analysis in line with the objectives of this scoping review and current methodological guidance, including the PRISMA-ScR framework and the Synthesis Without Meta-analysis reporting guideline.^{22 29} To guide analysis and interpretation, we will draw on established regulatory and human factors frameworks,^{10 26 30} as well as Nielsen’s usability attributes,¹¹ to provide an analytical lens to assess usability evaluation practices.

Studies will be grouped and synthesised based on shared characteristics such as type of test, usability evaluation method, user profile and healthcare system level. This will allow for meaningful comparisons and highlight variation across settings and technologies. We will systematically extract and synthesise data to provide a structured overview of

• Characteristics of diagnostic tests, including type, target pathogen, intended users and relevant technological features.

• Usability evaluation methods, including study design, evaluation type (eg, formative, summative) and tools used.

• Study contexts, such as geographical setting, level of healthcare system and test implementation environment.

• User and sample characteristics, including participant roles and sample size.

• Reported usability outcomes, including effectiveness, efficiency, satisfaction and reported barriers or facilitators.

A thematic analysis approach will be used to identify and organise recurring concepts and usability domains, such as user characteristics and training, task complexity, use environment, data collection methods and reported outcomes. Given the distinct usability considerations involved, self-testing will be analysed separately from healthcare worker-performed testing to account for differences in user interaction, training and contextual factors that may influence test performance and interpretation. This structured synthesis will allow for comparison against regulatory expectations and implementation-relevant considerations.

Discussion

This scoping review will provide the first comprehensive synthesis of how usability is evaluated in diagnostic tests for infectious diseases, with a particular focus on LMICs. While existing reviews have largely focused on digital health and electronic health records,³¹,³³ the usability of diagnostic tests, and especially those designed for use in decentralised settings, has not been systematically examined. By mapping current evaluation practices across diverse diagnostic technologies, study designs and implementation contexts, this review will address a key evidence gap.

A major strength of the review lies in its comprehensive and inclusive search strategy. By combining peer-reviewed literature with selected grey literature sources, including regulatory product dossiers, the review is positioned to capture a broad range of relevant studies. Usability-related terminology was also intentionally expanded to reflect interdisciplinary variation, increasing the likelihood of identifying studies that may not explicitly use the term ‘usability’. To guide data synthesis, we will draw on established regulatory and human factors frameworks, including FDA human factors guidance, ISO 62366-1, ISO 9241-210^{10 26 30} and Nielsen’s usability attributes.¹¹ These frameworks will allow for structured comparisons across tests, settings and user types, and will support thematic analysis of key evaluation domains such as critical task identification, user training and usability outcomes.

This review also has limitations. Despite the broad search strategy, some relevant studies may be missed due to the inconsistent terminology or the exclusion of non-English search terms, even though no language restrictions will be applied at the screening stage. Although the search strategy included a range of general and specific terms for infectious diseases, the exclusion of certain keywords and broader category terms (eg, ‘influenza’ or ‘respiratory infection*’) may have limited the comprehensiveness of the retrieved literature. Moreover, as is standard in scoping reviews, no formal assessment of study quality or risk of bias will be performed, which may affect the interpretability of findings.

The perspective of this review is framed by the ASSURED criteria,⁸ which have long guided the development and selection of diagnostics for resource-limited settings. However, we recognise that more recent frameworks such as REST-ASSURED⁹ emphasise evolving priorities, including digital connectivity, sustainability and health system integration. While these dimensions introduce new usability considerations for digital diagnostics, their detailed assessment falls beyond the scope of this review.

Finally, we acknowledge that additional regulatory sources for novel diagnostics such as the FDA’s 510(k) and De Novo databases were not included in this review.³⁴,³⁶ However, while the list is not exhaustive, the inclusion of key sources like the WHO prequalification and the European Union regulatory listings provides meaningful insights into usability evaluation practices across diagnostic technologies. These findings will form the basis for a subsequent Delphi consensus process aimed at developing methodological guidance for usability evaluation of novel diagnostic tests, supporting both developers and implementers working in LMICs.

Ethics and dissemination

No ethical approval is required because individual patient data will not be included, and the sources are in the public domain. The results from the scoping review will be fully published in peer-reviewed journals.