6-steps to align your medical device with users’ physical capabilities and characteristics

Before the most appropriate technical solution and the best test methodology can be identified, it is important to define what question the data generated should answer. For example, if evaluating the cap removal force for an autoinjector, is the question “what is the peak force that a user can apply to the cap”? Or is the question, “what removal force is most acceptable to the user”? Data can be generated to help answer either question, but to do so may require different test instruments and methodologies so it’s important to define the purpose up front.

Defining the characteristics of intended users is a key aspect of any human factors (HF) process.

If the medical device under development is to be used by users with specific characteristics, they of course need to be represented in the test sample. However, the device is more of a platform product like an autoinjector which will be used for various indications, a range of different user characteristics across the sample may be more appropriate.

Whichever is the case, ensuring that the test sample is representative of the intended users is imperative if valid data is to be gathered.

To ensure valid data, the test instrument developed to be used in any evaluation of user capabilities and characteristics must have minimal, or ideally no, impact on user behaviour and performance during use. In addition, the test instrument must generate accurate, reliable and appropriate data. Therefore, bespoke test instruments which are tailored to the specific application are often developed. However, to reduce the development burden, a range of calibrated and tried and tested core technologies can be utilised including the below:

• Electronic solutions: wireless or wired solutions which can provide real-time data on a handheld display or a live force trace or device angle on a laptop; these can used to evaluate aspects such as peak pull force (e.g. when removing a needle cover) or the ability of a user to sustain a hold force (e.g. during an injection).
• Mechanical solutions: these are typically used for measuring aspects such as cap pull-off force (utilising magnets or copper wires), cap twist force (utilising torque screwdrivers) as well as user acceptability and preference.
• Imaging solutions: combine electronic sensors with ultrasound probes to measure the characteristics of injection sites (e.g. subcutaneous fat depth).

These core technologies can then be ‘housed’ within a custom body which looks and feels reasonably representative of a commercial product in terms of its appearance, size, shape, texture and even basic device feedback and functionality.

For the data collected to be valid, it is imperative that the test instruments are reliable and produce accurate and repeatable data. Therefore, before, during and after a user evaluation, it is important that checks are performed to a defined method and acceptance criteria to ensure the test instruments are functioning as intended.

Appropriate documentation should be produced for quality assurance purposes (e.g. CAD drawings, build documents and records) to demonstrate the reliability and accuracy of the test instruments.

Developing and documenting an appropriate methodology is key to successfully conducting the user evaluation. During planning, careful consideration needs to be given the points below.

• Pilot study: conducting at least one pilot study is recommended as it can inform help inform the selection of the most appropriate test methodology. It allows test methodology to be rehearsed and the test instruments to be checked in use and modified if needed before more in-depth user testing is conducted.
• Sample size: depending on the required statistical analysis, a minimum sample size of n=30 is the general rule, but in some cases, a larger sample size may be needed to achieve the desired level of confidence and power (e.g. if the population is highly variable or the statistical test is very sensitive).
• Participant familiarisation: allowing participants to interact with the test instrument before first use can help ensure that any data collected collect on subsequent attempts is less likely to be influenced by users merely familiarising themselves with how the test instrument works.
• Number of attempts: allowing participants to have multiple attempts with each test instrument is typically recommended. This allows more data to be gathered from each participant which can in turn increase the statistical power of the sample for later analysis (without an associated increase in sample size) and/or allows a participant multiple attempts to generate their ‘true’ best effort.
• Order affect: if more than one test instrument is being evaluated (e.g. different forces), the order of which the test instruments are presented to participants should be carefully considered and balanced to reduce any impact that presentation order may have on participant performance or response.
• Minimising user fatigue: if multiple test instruments and/or attempts are being evaluated, the impact that this may have on user fatigue must be carefully considered to avoid impacting on the validity of the data. This is especially important for test participants who may have manual dexterity or strength issues.
• ALOCA+ principles: data should be collected in accordance with ALCOA+ principles to ensure that the test data is reliable, trustworthy, and traceable.
• Anthropometric measurements: in order to demonstrate that representative users and a range of capabilities have been evaluated, consider measuring participant’s hand size and strength – this data can then be compared against published anthropometric data to benchmark participants within a given population.

Once data collection is complete, the final step is to analyse and report the results.

Any analysis conducted should be tailored to the nature of the data, whether quantitative, qualitative, or a combination of the two, and to answering the test question posed initially.

Analysing data statistically, where appropriate, allows the analysis to move beyond describing what happened in the study and instead extrapolates findings to the broader population. For example, statistical methods can be used to:

• determine the recommended upper specification limit.
• identify which device enables users to exert the higher peak forces, helping to inform down selection of components.
• evaluate the validity of the study data by assessing the influence of extraneous variables such as age, gender and fatigue.

If the data allows, qualitative analysis can help build a more complete picture of the user experience instead of just measuring forces. This captures not just what users can do, but what they feel, expect and find acceptable. This type of analysis is particularly valuable for understanding subjective factors that influence usability and design decisions such as:

• participant preferences for different cap or needle cap designs.
• acceptability of different forces, helping to ensure that device specifications align with user expectations and physical comfort.

The final test report should summarise the test methodology followed, the test instruments used, the test sample achieved, the analysis conducted and the test findings and be suitable for submission to regulatory authorities if required.

This 6-step process ensures medical device developers gather reliable, representative data that supports confident design decisions and regulatory submissions, leading to better outcomes for users and developers alike.