Preferences and willingness-to-pay for expanded carrier screening programmes in the general population: An integrative systematic review and meta-analysis

This integrative systematic review and meta-analysis synthesizes data from 31 studies to characterize the general population's preferences for expanded carrier screening program attributes and estimates a median willingness-to-pay of $107, despite noting a high risk of bias in most included studies.

The Gist

Imagine you and your partner are planning to build a house together. Before you lay the first brick, you'd probably want to check the blueprints to make sure there aren't any hidden structural flaws that could cause the roof to collapse later.

In the world of having children, Expanded Carrier Screening (ECS) is like that blueprint check. It's a genetic test that looks to see if you or your partner carry "hidden instructions" for certain genetic diseases. Usually, these diseases only happen if both parents carry the same instruction. If only one does, the child is usually fine. But if both do, there's a risk the child could inherit a serious condition.

This paper is a massive "report card" that gathered opinions from thousands of people across the globe to answer one big question: "If we offer this blueprint check to everyone, what do people actually want, and how much are they willing to pay for it?"

Here is the breakdown of what they found, using some everyday analogies:

1. The "Who" and "Where" (Healthcare Providers)

People want their blueprint check done by someone they trust, not a stranger.

• The Analogy: Imagine you need a car inspection. In some countries (like the US and Europe), people want to go to their local mechanic (the General Practitioner) or the specialist who knows their car history best (the OB/GYN). In other places (like China and Thailand), people prefer going to the big, fancy dealership (the Hospital) because they feel it's more authoritative.
• The Takeaway: There is no "one size fits all." The person doing the test needs to be someone the patient already trusts and feels comfortable talking to.

2. The "How" (Counseling)

Before you buy a complex piece of software, you want a human to explain how it works, not just a PDF manual.

• The Analogy: Most people (over 90%) said they want in-person counseling. They want to sit down with a real person, ask questions, and get reassurance. They generally didn't want to just click through a website or watch a webinar.
• The Takeaway: If you roll out this testing program, you can't just send people a link. You need real humans to guide them through the scary parts.

3. The "Who Gets Tested" (Individual vs. Couples)

Should you check your own blueprint first, or check you and your partner together?

• The Analogy:
  • The "Solo Traveler" View: In the US and Europe, many people prefer to check their own "blueprint" first. Why? Because if they are single right now, they want to know their status before they find a partner. It's like checking your own car before you buy a new one.
  • The "Team Player" View: In China, most people prefer to check the couple together. They see it as a joint decision.
• The Takeaway: The system needs to be flexible. Some people want to know their status alone; others want to know the status of the "team."

4. The "What" (Which Diseases?)

If you are checking the blueprint, do you want to know about every possible crack, or just the ones that could bring the whole house down?

• The Analogy: People generally want to know about the "big, scary cracks"—diseases that are severe, untreatable, or shorten a child's life. They were less interested in minor issues or diseases that might not show up until the child is 80 years old.
• The Takeaway: People want a comprehensive list, but they care most about the conditions that are truly life-altering.

5. The "When" (Timing)

When should you get this check?

• The Analogy: Most people said, "Check the blueprint before you start building." They prefer testing before pregnancy (preconception) rather than waiting until they are already pregnant.
• The Takeaway: If you wait until the baby is on the way, you have fewer options. Doing it early gives couples the most time to make choices.

6. The "Price Tag" (Willingness to Pay)

This is the part where the researchers did some heavy math. They asked people, "How much would you pay for this peace of mind?"

• The Analogy: Imagine a group of people bidding on a lottery ticket that guarantees you won't have a specific tragedy.
  • The Result: The average person said they would pay about $107 (in 2024 dollars).
  • The Catch: The numbers were "skewed." This means a few people said they would pay a lot (like $1,000), which pulled the average up, but the typical person is closer to the $107 mark.
  • The "Free" Crowd: About 9% of people said, "I won't pay a single cent." They believe this should be free, like a public health service.
• The Takeaway: If a government or insurance company wants to offer this, they can't expect everyone to pay full price. A "co-pay" (a small fee) of around $100 seems reasonable for many, but for others, it needs to be fully covered to ensure fairness.

The Big Picture

This paper is essentially a user manual for the future of genetic testing.

It tells policymakers: "Don't just build the test and hope people show up."

• Do offer it early (before pregnancy).
• Do have real humans explain it.
• Do let people choose how they want to be tested (alone or as a couple).
• Do keep the cost low or subsidized, because if it's too expensive, the people who need it most might not get it.

The authors are basically saying: "We have the technology to check the blueprint. Now, let's make sure the system is built in a way that people actually want to use it."

Technical Summary

1. Problem Statement

Expanded Carrier Screening (ECS) utilizes next-generation sequencing to identify the risk of transmitting autosomal or X-linked recessive genetic disorders in the general population, regardless of ethnicity or family history. While professional societies support ECS, its integration into routine preconception healthcare faces challenges regarding:

• Service Delivery: How to structure programs (e.g., timing, counseling methods, provider types) to align with public preferences.
• Economic Viability: Determining the financial sustainability of these programs, specifically the public's Willingness-to-Pay (WTP) and the potential for cost-sharing (copayments) without exacerbating health inequities.
• Evidence Gap: A lack of synthesized data on population-level preferences and economic valuation to guide health policy and implementation strategies.

2. Methodology

The study employed a rigorous integrative systematic review and meta-analysis approach, registered with PROSPERO (CRD420250655372) and adhering to PRISMA guidelines.

• Data Sources: A comprehensive search of PubMed, CINAHL, and Scopus (1995–2025) for peer-reviewed studies on carrier screening for recessive conditions in adult general populations.
• Inclusion Criteria: Studies eliciting preferences on ECS design/delivery attributes (e.g., screening method, provider, timing) or WTP.
• Exclusion Criteria: Studies focused on specific high-risk families, moral/ethical views only, adult-onset conditions (e.g., cancer), or mild morbidity conditions.
• Data Synthesis:
  • Qualitative Integration: Qualitative findings were mapped to quantitative preference attributes to provide contextual depth.
  • Quantitative Meta-Analysis (WTP): A Bayesian multilevel modeling approach was used to analyze WTP data.
    • Handling Censoring: WTP responses were treated as latent variables within bounded intervals (e.g., $0, $1–$100, $100+).
    • Standardization: All monetary values were converted to 2024 USD.
    • Modeling: Used the brms package in R with No-U-Turn-Sampler (NUTS) to estimate posterior distributions, accounting for study-level random intercepts.
• Quality Assessment: The Risk of Bias in studies of Values and Utilities (ROBVALU) tool was applied to assess the reliability of preference elicitation methods.

3. Key Contributions

• First Integrative Meta-Analysis: This is the first study to synthesize both qualitative and quantitative data on ECS preferences across the general population, specifically focusing on WTP.
• Advanced Statistical Modeling: The application of Bayesian multilevel modeling to handle censored and bounded WTP data provides a more robust estimation of population value than traditional mean/median calculations.
• Policy-Relevant Metrics: The study provides specific, evidence-based estimates for copayment levels and identifies critical service design attributes (e.g., counseling modality, screening timing) that influence public uptake.

4. Key Results

Study Characteristics:

• Volume: 31 studies included (16 quantitative, 11 qualitative, 4 mixed-methods) involving 4,671 WTP responses.
• Geography: USA, Australia, Netherlands, China, Belgium, UK, Slovenia, Thailand.
• Risk of Bias: Most studies demonstrated a high risk of bias, primarily due to incomplete representation of preference options or selective data collection.

Population Preferences:

• Healthcare Provider: Preferences vary by health system.
  • USA/EU: Strong preference for Obstetricians/Gynecologists (OB/GYNs).
  • Australia: Preference for General Practitioners (80%).
  • Asia: Preference for hospital-based delivery (China) or provincial hospitals (Thailand).
• Counseling: Overwhelming preference for in-person pre-test counseling (81–94%) over online or written materials. Participants desire sufficient time to discuss concerns and test appropriateness.
• Screening Method:
  • China: Strong preference for couple-based screening (69–83%).
  • USA/Europe: Preference for individual or stepwise screening (49–62%), driven by relationship fluidity and the desire for individual carrier status before conception.
• Conditions Screened: High preference for including severe, life-altering, untreatable conditions, and those causing early death or disability. Participants generally prefer comprehensive panels but expressed doubt regarding late-onset conditions.
• Timing: Strong preference for preconception or premarital screening to allow time for reproductive decision-making.

Willingness-to-Pay (WTP):

• Distribution: Right-skewed distribution.
  • 9% of participants were unwilling to pay anything ($0).
  • Median WTP: $107 USD (2024).
  • Interquartile Range (IQR): $41 –$226.
  • Mean WTP: $191 (SD $282).
  • Probability: 92% probability that WTP is below $500.
• Regional Variance: Highest WTP observed in Europe (Slovenia/Netherlands); lowest in China and Australia.
• Affordability: A significant portion of participants (e.g., 54% in USA, 77–88% in Thailand/Slovenia) believe screening should be government-funded or insurance-covered to prevent inequities.

5. Significance and Implications

• Service Design: Health systems should structure ECS programs to offer preconception testing with in-person counseling delivered by trusted local providers (e.g., GPs or OB/GYNs depending on the region).
• Economic Policy: The median WTP of $107 suggests that if ECS is subsidized, a copayment around this level may be acceptable to the majority. However, given the 9% zero-WTP group and concerns about equity, universal coverage or sliding-scale subsidies are recommended to ensure access.
• Implementation Strategy: Programs must navigate cultural differences in screening methods (couple vs. individual) and ensure that turnaround times are minimized to reduce stress, particularly for couples pursuing IVF or those with prior pregnancy losses.
• Future Research: The study highlights gaps in understanding post-test decision-making, the impact of legal frameworks (e.g., PGT regulations), and the potential role of digital tools to supplement, rather than replace, in-person counseling.

In conclusion, this paper provides a critical evidence base for policymakers to design ECS programs that are not only clinically effective but also economically viable and culturally acceptable to the general population.