Reason for Survey ("Reflection")

After recognizing that engaging directly with end users and risk groups could pose ethical challenges, we faced a dilemma: How can we design a test focused on our intended users if direct engagement is not appropriate? This survey provided the solution. It allowed us to explore unmet needs, preferences, values, and more - without placing anyone in a potentially negative situation. The results summarized here reflect over 300 individual opinions, values, and expectations. By integrating these insights into our project, we are confident that we are developing a product that truly centers on the user’s needs.

Methods

Survey Design ("Responsibility")

Although online surveys allow respondents to answer from wherever and whenever they prefer in a fully anonymous way, they still qualify as human subject research. This means that responsibility in design, distribution, and analysis is essential. Based on iGEM’s guidelines and resources on survey-based research, local regulations on informed consent, and feedback from engagements, we carefully integrated the following elements into our survey design:

  • Informed Consent: All participants were presented with a clear explanation of the survey’s purpose, expected duration, voluntary nature, and anonymity. Proceeding with the questionnaire was taken as an active indication of consent.
  • Following the 3 R’s: Reflection (see “Reason for Survey”), Responsibility (this section) and Responsiveness (see “Integration”)
  • Stakeholder Feedback: We submitted our survey questions to iGEM HQ for feedback, focusing on identifying leading, unclear, or ethically sensitive questions, ensuring appropriate language, and spotting any missing topics.
  • Health-Sensitive Questions: We avoided asking questions about health status or any topics that would require formal approval from an ethics committee.

Data Preprocessing

All data processing and analyses were performed in R (version [insert version]) using the tidyverse package suite. The raw dataset was imported from CSV format. Initial preprocessing included:

  1. Workspace Setup: All objects in the environment were cleared prior to analysis (rm(list = ls())).
  2. Handling Missing Data: Empty string entries were converted to NA. Columns containing only NA values (such as timing counters or unused metadata) were removed.
  3. Variable Renaming: Metadata columns (e.g., respondent ID, date of submission, language, timing measures) were standardized. Survey question columns were renamed systematically to concise, descriptive variable names.
  4. Exclusion Criteria:
    • Respondents who did not complete at least Section 1 of the survey were excluded.
    • Respondents with missing age information were excluded, as we could not verify whether they were ≥18 years old.
    • A single respondent (id = 367) was removed due to evidence of non-serious responses.
  5. Data Restructuring: The dataset was transformed from wide format (one row per respondent with many question columns) to long format (df_long) using pivot_longer(). In the long format, each row represents one respondent’s answer to one survey question, with the following key columns:
    • id: respondent identifier
    • question: the survey item label
    • response: the recorded response

Analysis Strategy

On a per-question basis, the following steps were applied:

  1. Filtering: Responses for the specific survey item(s) of interest were selected from df_long. Missing values were excluded.
  2. Merging Demographics: For subgroup analyses (e.g., stratification by age, sex, or region), demographic variables were re-joined to question responses using respondent id.
  3. Summarization: For each question, responses were grouped to calculate absolute counts and proportions. Proportions were defined as the number of responses in a category divided by the total number of valid responses for that item or subgroup.
  4. Response Ordering: Where applicable, response categories were ordered logically (e.g., from negative to positive attitudes, or from low to high agreement).
  5. Visualization: Results were visualized using bar plots created with ggplot2. Consistent color palettes were applied across plots.

For analyses by age group, the 55+ group was not regarded due to the small number of participants.

Results

Section 1: About the Respondents

  1. How old are you?
  2. What sex were you assigned at birth (on official documents)?
    Survey Figure Survey Figure
    Fig. 1A-B: Age and Sex Demographics of Survey Participants.

    Most survey respondents (262) were aged 18–24, a key target group for STI testing. 55 respondents were aged 25–34, 24 were 35–54, and 9 were older. Women were overrepresented, with a ratio of approximately 2:1 compared to men.

  3. Where do you currently live?
    Survey Figure
    Fig. 2: Residence of Participants by Country and Region.

    A total of 176 respondents live in urban areas, 88 in suburban areas, and 78 in rural areas. Most respondents (303) live in Switzerland, while 44 reside abroad. Other countries of residence include Germany, the United States, the United Kingdom, France, and others.

Section 2: Testing Context and Behavior

  1. How often do you get tested for sexually transmitted infections (STIs)? (Note: In some countries such as Switzerland, some people get tested for HIV during military recruiting, which may be relevant for some respondents).
    Survey Figure Survey Figure Survey Figure Survey Figure
    Fig. 3 A-D: Testing Frequency of Participants in Percentage, Overall and grouped by Age, Sex, and Region of Residence.

    The majority of respondents (46.9%) reported never having been tested, followed by those who had been tested once (24.3%) and occasionally (19.7%). Only 8% reported regular testing.

    The proportion of never or occasional testers was particularly high among the youngest group, and highest among respondents aged 25–34, though rates for those aged 35–54 were similar.

    There were also some differences by sex: men more often reported having been tested once in their life, while women more frequently reported never having been tested. The share of regular testers was similar across both groups.

    Finally, testing rates were highest in urban areas.

  2. How do you currently access STI testing? (Select all that apply)
    Survey Figure Survey Figure
    Fig. 4 A-B: Percentage of Methods used by Participants to access STI Testing, Overall and grouped by Sex.

    A total of 153 respondents reported never having accessed an STI test, followed by 136 who accessed testing at clinics and 45 at testing centers. 21 respondents reported military testing, and 7 reported home testing.

    Men reported fewer clinic-based tests and slightly more testing center use than women. The largest difference was observed for military testing, with a ratio of approximately 6:1 men to women.

  3. What prevents you from getting tested / getting tested more frequently? (Select all that apply)
    Survey Figure Survey Figure Survey Figure
    Fig. 5 A-C: Barriers preventing Participants from STI Testing, Overall and grouped by Sex and Testing Frequency.

    The most common barriers to STI testing were “no perceived need” (33.4%), “never thought about it” (21.8%), cost (21.5%), lack of time (8.2%), and stigma (7.2%). Stigma was cited twice as often by men as by women, while most other reasons were reported at similar rates across both sexes.

    Among non-frequent testers, the main reasons were “no perceived need” (32.5%), “never thought about it” (32%), cost (13%), stigma (8%), and lack of time (7.5%).

  4. How much do cultural, family, or community attitudes influence your decision to get tested for STIs?
    Survey Figure
    Fig. 6: Perceived Importance of Family, Cultural or Community Influences on personal STI Testing Behavior.

    For most respondents (52.8%), cultural, family, or community attitudes did not influence their decision to get tested for STIs. Another 22.2% reported little influence, 20.1% said they were somewhat influenced, and 4.9% indicated a strong influence.

  5. How satisfied are you with current STI testing options?
    Survey Figure Survey Figure
    Figure 7: Satisfaction of Participants with the current STI Testing Options, Overall and grouped by Age.

    Overall satisfaction with current STI testing options was neutral, with a slight trend toward positive. Satisfaction was lowest among respondents aged 18–35 and highest among those aged 35–54.

  6. Are you aware that fully at-home self-tests exist, but currently only for HIV?
    Survey Figure Survey Figure
    Figure 8: Percentage of Participants aware or unaware of the Existence of the HIV Self-Test, Overall and grouped by Sex.

    When asked whether they were aware that fully at-home self-tests currently exist only for HIV, 77% of respondents said they were not aware. Awareness was highest among those aged 25–35, while respondents aged 18–24 showed the lowest awareness. Men were generally more aware of this than women.

Section 3: Opintions on At-Home Self-Testing

At the beginning of this section, participants were provided with some context regarding our project:

“The self-test we are developing would work similarly to a pregnancy or COVID-19 test, using an encased paper strip. It would detect the following STIs: Chlamydia, Gonorrhea, Syphilis, HPV (Human Papillomavirus), and Trichomonas vaginalis.”

  1. Would you consider using an at-home STI self-test if it were available and you were aware of it?
    Survey Figure Survey Figure Survey Figure Survey Figure Survey Figure Survey Figure
    Figure 9 A-D: Level of Consideration for Using STI Self-Tests if Available, Overall and by Age, Sex, and Region of Residence.

    47% of respondents said “certainly yes,” and 34.6% “probably yes.” Another 12.4% answered “maybe,” while only 4.4% said “probably not” and 1.7% “no.” This trend was consistent across sex, age groups, and regions. Interestingly, infrequent testers were more likely to respond “yes” or “probably yes” (a combined 82.6%) compared to frequent testers (72.8%), who were more uncertain (“maybe”: 22.7% vs. 11.3% among infrequent testers).

  2. How might access to an at-home self-test affect how often you test?
    Survey Figure Survey Figure
    Figure 10 A-B: Perceived Effect the Access to STI Self-Tests would have on the Participants personal Testing Frequencies, Overall and grouped by Age.

    79% of respondents said they might or would likely test more often, while 21% said it would not change their behavior. Only one respondent indicated they would likely test less often. Younger respondents were more likely to report increased testing, showing an inverse correlation between age and positive changes in testing frequency.

  3. How much would you be willing to pay for such a self-test?
    Survey Figure
    Figure 11: Highest Price Range Participants would be willing to pay for an STI Self-Test.

    Most respondents indicated a price range of 5–20 CHF (37.6%) or 20–40 CHF (47.6%) as an upper limit. Smaller proportions reported being willing to pay 40–60 CHF (9.3%) or more than 60 CHF (1%). Only 4.5% of respondents indicated they would want the test for free.

  4. If at-home STI self-tests were available, what would your preference be regarding testing methods?
    Survey Figure
    Figure 12: Preferred STI Testing Method of Participants.

    Most respondents (58%) said they would like the option of self-testing but would also use other testing methods as needed. A smaller group (35.4%) preferred self-testing and would use it as their main testing method. Very few respondents would only use testing performed by qualified professionals (4.5%) or would not get tested at all (2.1%).

  5. How important to you are the following features in a self test?

    (1= not important at all, 5= very important, prefer not to answer)

    Survey Figure
    Figure 13: Importance Rating of different Features of a possible STI Self-Test in Percentage.

    Respondents rated accuracy, confidentiality, clear instructions, privacy, and test accessibility as the most important. Follow-up options, reimbursement, environmental friendliness, and discreet packaging were also considered important, but to a lesser extent. The least important feature was a test that does not require a blood sample.

  6. At what point does a self-test take too long for you to consider using it?
    Survey Figure Survey Figure
    Figure 14: Maximal Duration Participants deem acceptable in Percentage.

    12.3% of respondents said over 15 minutes would be too long, 41.9% indicated over 30 minutes, 23.6% said over 45 minutes, and 18.2% considered over 1 hour too long. A small group (3.9%) chose “Other.” Overall, the largest proportion of participants (41.9%) indicated that a self-test taking more than 30 minutes would be too long for them to consider using.

  7. Where would you prefer to obtain this self-test? (Select all that apply)
    Survey Figure
    Figure 15: Preferred Ways of Participants to Access STI Tests.

    Respondents most frequently chose pharmacies (228), followed by online (193) and grocery stores (163). Doctors were selected by 110 respondents, vending machines by 105, and only 4 respondents indicated no preference.

  8. Please indicate your level of agreement with the following statements: (1: strongly disagree, 2: disagree, 3: neutral, 4: agree, 5: strongly agree)
    Survey Figure
    Figure 16: Agreement Rating of different Statements regarding STI Testing in Percentage.

    Only 23.7% reported that they would get tested at a clinic without known exposure or symptoms, while 58.3% said they would use an at-home self-test like the one we are developing. A large majority, 80.8%, felt that at-home testing would be more convenient than clinic testing. Nearly all respondents (96.95%) indicated that they would seek medical advice after a positive test result. Confidence in self-sampling was high (measured as respondents answering “agree” or “strongly agree”): 90.5% felt confident taking a urine sample, 83.6% felt confident taking a throat sample, 81.1% felt confident taking a finger-prick blood sample, and 63.3% felt confident taking genital or anal samples. Most respondents (69.1%) said they would feel reassured by a negative test result, even after recent exposure risk. Additionally, 69.2% believe that self-tests could help reduce the stigma associated with STI testing.

  9. What, if anything, would make you uncomfortable using an at-home STI test? (Select all that apply)
    Survey Figure Figure 17: Number of Participants agreeing that these Reasons make them feel uncomfortable about using an STI Self-Test.

    The main concerns about STI testing, in descending order of importance, were accuracy of results, uncertainty in sampling, cost, and uncertainty about the next steps after a positive result.

  10. What is your level of trust in synthetic biology or biotech-based diagnostic tools (like the self-tests being developed)?
    Survey Figure
    Figure 18: Trust Level of Participants in Synthetic Biology and Biotech-based Diagnostic Tools in Percentage.

    Most respondents reported trust in synthetic biology-based diagnostic tools, with 50.5% expressing some trust and 41.1% expressing high trust.

  11. Do you have any disabilities or specific needs (e.g., visual, hearing, mobility, cognitive) that affect your ability to use medical tests or self-tests?

    Out of all participants, three respondents mentioned something specific: severe visual impairment (-11 diopters, but corrected with glasses), ADHD, and dyslexia - they noted that a video or audio instruction would be very helpful, as well as small illustrative images.

Discussion

This survey reveals critical insights into current STI testing behaviors and the potential impact of at-home self-testing technologies on public health outcomes. The findings demonstrate both significant gaps in current testing practices and strong receptivity to innovative testing solutions, particularly among young adults who constitute the highest-risk demographic for STI transmission.

Current Testing Landscape and Barriers

The most striking finding is that nearly half (46.9%) of respondents have never been tested for STIs, with an additional 44% testing only once or occasionally. This alarmingly low testing rate, particularly pronounced among the 18-24 age group who paradoxically represent the highest-risk population, underscores a fundamental failure of current public health approaches to STI prevention. The gender disparity in testing behaviors – with women more frequently reporting never having been tested despite typically higher healthcare engagement—suggests that traditional clinic-based testing models may not adequately address the unique barriers faced by different populations.

The identified barriers to testing reveal a complex interplay of psychological, practical, and social factors. The predominance of "no perceived need" (33.4%) and "never thought about it" (21.8%) as primary barriers indicates a fundamental awareness gap rather than merely logistical challenges. This finding is particularly concerning given that many STIs remain asymptomatic, suggesting that risk perception does not align with actual risk exposure. The economic barrier of cost (21.5%) further compounds accessibility issues, while the gender disparity in stigma perception – with men reporting stigma twice as frequently as women – highlights how social pressures differentially impact testing behaviors across demographics.

The Promise of At-Home Self-Testing

The overwhelming enthusiasm for at-home self-testing, with 81.6% of respondents indicating they would "certainly" or "probably" use such tests, represents a potential paradigm shift in STI prevention strategies. Remarkably, this enthusiasm is even stronger among current non-testers and infrequent testers (82.6% positive response), suggesting that self-testing could effectively reach populations currently underserved by traditional testing infrastructure. The finding that 79% of respondents would likely test more frequently with at-home options indicates that convenience and privacy are not merely preferences but critical determinants of testing behavior.

The high confidence levels in self-sampling across various specimen types (ranging from 63.3% to 90.5%) demonstrate that technical competency is not a significant barrier to self-test adoption. This finding, coupled with the near-universal intention to seek medical advice following a positive result (96.95%), alleviates concerns about self-testing potentially disconnecting individuals from healthcare systems. Instead, self-testing appears poised to serve as a bridge to care rather than a replacement for professional medical services.

Implementation Considerations and Market Viability

The price sensitivity analysis reveals realistic market expectations, with 85.2% of respondents willing to pay between 5-40 CHF for self-tests. This price point, comparable to existing pregnancy and COVID-19 tests, suggests commercial viability while maintaining accessibility. The preference for pharmacy (228) and online (193) distribution channels aligns with established consumer health product pathways, facilitating rapid market penetration without requiring new infrastructure development.

The prioritization of accuracy, confidentiality, and clear instructions as essential features reflects sophisticated consumer understanding of diagnostic test requirements. Notably, the relatively lower importance placed on blood-free sampling suggests users prioritize reliability over comfort, indicating mature consumer attitudes toward health diagnostics. The acceptance of 30-minute test duration by the majority aligns with established rapid test formats, confirming feasibility of current technological approaches.

Implications for Public Health Strategy

The survey data strongly supports integrating at-home self-testing into comprehensive STI prevention strategies. The preference for hybrid testing approaches – with 58% wanting self-testing as an option alongside professional testing – suggests that self-tests should complement rather than replace existing services. This integrated model could optimize resource allocation by redirecting routine screening to self-testing while preserving clinical capacity for treatment and complex cases.

The potential for self-testing to reduce stigma, as believed by 69.2% of respondents, represents an underappreciated public health opportunity. By normalizing STI testing through private, accessible methods similar to pregnancy testing, self-tests could fundamentally shift cultural attitudes toward sexual health screening. The high trust levels in biotechnology-based diagnostics (91.6% expressing some or high trust) further supports the acceptability of novel synthetic biology approaches in this space.

Limitations and Future Directions

While these findings are encouraging, several limitations warrant consideration. The survey population skews young and female, potentially overestimating acceptance among older or male populations. The hypothetical nature of the questions may not fully capture real-world adoption patterns, and the predominantly Swiss sample limits generalizability to other healthcare contexts. Future research should examine actual usage patterns following product launch and investigate strategies to address the concerning gender disparities in stigma perception and testing behaviors.

Integration

We actively incorporated participant feedback into various aspects of our project:

  • Business Planning: Insights on user needs informed our entrepreneurship strategy and business plan.
  • Epidemiological Modeling: Data on demographics and testing behavior helped refine our epidemiological simulations.
  • Communication & User Experience: Small illustrative images and clearer guidance were added to the product page to enhance usability.
  • Product Design: Feedback on accessibility (e.g., visual impairment, ADHD, dyslexia) led us to include video instructions.

References

Tools and Packages Used for Survey Administration and Data Analysis

  1. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2024. Available from: https://www.R-project.org/
  2. LimeSurvey GmbH. LimeSurvey: An Open Source Survey Tool. Available from: https://www.limesurvey.org
  3. Tidyverse. Wickham H, Averick M, Bryan J, et al. Welcome to the tidyverse. J Open Source Soft. 2019;4(43):1686. doi:10.21105/joss.01686.
  4. Scales. Wickham H. scales: Scale Functions for Visualization. R package version 1.2.0. Available from: https://cran.r-project.org/package=scales
  5. Ggplot2. Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York; 2016.
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