Cost-Effectiveness of Sterile Cold Spray in Enhancing 12-Month Retention Rates Among First-Time Blood Donors: A Decision-Making Model Study for Blood Centres Based on Causal Mediation Analysis

Cost-Effectiveness of Sterile Cold Spray in Enhancing 12-Month Retention Rates Among First-Time Blood Donors: A Decision-Making Model Study for Blood Centres Based on Causal Mediation Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cost-Effectiveness of Sterile Cold Spray in Enhancing 12-Month Retention Rates Among First-Time Blood Donors: A Decision-Making Model Study for Blood Centres Based on Causal Mediation Analysis Li Li, Lei Zhao, Zubing Zhang, Qinson Zhang, Sicheng Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9074179/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background To estimate the cost-effectiveness of sterile cold spray for improving 12-month repeat donation among first-time whole blood donors aged 18–25 years in mainland China from a blood-centre perspective. Methods We developed a 12-month Markov model from a blood-centre perspective comparing a sterile vapocoolant spray (cold spray) with standard care in first-time whole-blood donors aged 18–25 years in mainland China. Trial-based short-term changes in pain (VAS) and anxiety (BDAS) were translated to 12-month repeat donation using a Theory of Planned Behaviour pathway with a calibration parameter informed by domestic retention data. Incremental costs (consumables, staff time, and training) were estimated using time-driven activity-based costing from three blood centres (2023–2024). Uncertainty was assessed using one-way sensitivity analysis and probabilistic sensitivity analysis (5,000 simulations). No patients or members of the public, including blood donors, were involved in the design, conduct, or reporting of this model-based cost-effectiveness analysis. Conclusion Cold spray is estimated to improve first-time donor experience and is likely to be cost-effective for improving 12-month donor retention under commonly used blood-centre willingness-to-pay thresholds in China. blood donation donor retention cost-effectiveness Markov model time-driven activity-based costing Introduction China’s voluntary blood donation system recruits many first-time donors, but a large proportion do not return for repeat donation. Young adults (18–25 years) contribute more than half of first-time donations, yet experience particularly high early lapse, which can threaten blood supply stability. Across 23 blood centres, the median attrition rate among whole-blood donors has been reported as 72.33% (Dai et al., 2020 ). Among young first-time donors, multicentre studies report a median 12-month attrition of 75.86% in donors aged 18–24 years, exceeding 88% in some regions (Min et al., 2024 ). Reported 12‑month retention in this age group can be low (median 10%) (Chen et al., 2022 ). The first 6–12 months after an initial donation is a critical period for converting first-time donors into repeat donors (Schreiber et al., 2005 ). Studies suggest that if young donors do not return within this window, subsequent return rates can fall below 10%, which is substantially lower than in donors aged 30 years and above (Ji et al., 2018 ). In this paper, we focus on 12‑month retention, defined as at least one repeat whole-blood donation within 12 months after the index donation. Understanding and targeting the drivers of early lapse is therefore important for blood centres. In China, university students account for a large proportion of young first-time donors, and changes in schedules and living arrangements may disrupt donation continuity. In addition, surveys consistently identify needle-stick pain and donation-related anxiety as major self-reported reasons for non-return; approximately 80% of young first-time donors report declining to donate again due to “fear of pain” or anxiety-related experiences (Zhang et al., 2017 ). Donation experience is an important determinant of whether first-time donors return. Evidence from first-time donor retention research and donor psychology indicates that anxiety and needle pain reduce satisfaction and are associated with lower subsequent donation behaviour(Bagot et al., 2016 ; France et al., 2013 ). Randomised evidence in blood donors also indicates that vapocoolant sprays can reduce venipuncture pain (Basak et al., 2021 ). Cold spray is a vapocoolant intervention that can be applied rapidly within the donation workflow and requires minimal additional staff time, which may improve feasibility in busy blood-centre settings. From a resource allocation perspective, retaining or reactivating previous donors can be less costly than recruiting new donors (Ou-Yang et al., 2020 ; van Dongen, 2015 ; Willis et al., 2019 ). In China, blood centres allocate dedicated budgets for donor recruitment and donor engagement. For example, the 2025 departmental budget for Guangzhou Blood Center includes ࿥ 4.17 million for voluntary blood donation publicity and activities (advertising and media outreach) and ࿥ 32.38 million for voluntary blood donation commemorative items and donor supplies (donor gifts and refreshments), both intended to support participation in voluntary blood donation (Commission, 2025 ). Given the high attrition among young donors, blood centres may need repeated recruitment to maintain supply. Economic evaluation that combines local patterns of attrition with local cost data can therefore inform whether implementing a pain- and anxiety-reduction intervention at scale is a good use of blood-centre resources and can support annual budgeting decisions. A sterile vapocoolant spray (cold spray) is a topical vapocoolant applied immediately before venipuncture to transiently cool the skin and reduce puncture-related pain (Basak et al., 2021 ; Mace, 2016 ). Because application is rapid and can be integrated into routine workflow, it may be feasible in high-throughput blood-centre settings. In a Chinese open-label, randomised, multicentre study in first-time voluntary donors, cold spray was applied immediately before venipuncture and was associated with lower post-puncture pain and state anxiety, and with higher short-term willingness to donate again (assessed by telephone follow-up within 7 days in first-time whole-blood donors). A domestic multicentre RCT (n = 480) reported that cold spray reduced pain (VAS 3.85 to 2.75) and anxiety (BDAS 16.76 to 14.97), and increased short-term willingness to donate again within 7 days (48.0% to 72.1%)(Zubing et al., 2025 ). However, direct evidence linking cold spray to 12-month repeat donation is limited, creating an evidence gap between short-term psychological outcomes and medium-term donation behaviour. We evaluated the cost-effectiveness of cold spray versus standard care for improving 12-month retention among first-time whole-blood donors aged 18–25 years in mainland China from a blood-centre perspective. Specifically, we (i) quantified the incremental cost of implementing cold spray using refined cost accounting, (ii) estimated the incremental effect on 12-month retention by linking trial-based short-term outcomes to repeat donation within a decision-analytic framework, and (iii) identified key drivers of cost-effectiveness to inform targeted implementation and future evidence generation. Materials and Methods Study design, perspective and reporting This was a model-based economic evaluation conducted from a blood-centre perspective over a 12-month horizon. We followed CHEERS 2022 reporting guidance and ISPOR-SMDM good practice recommendations for decision-analytic modelling (Caro et al., 2012 ; Husereau et al., 2022 ). The analysis included direct intervention costs (consumables, staff time, and training) and excluded donor time costs, donor transport costs, and fixed blood-centre overheads (e.g., premises and equipment depreciation), consistent with standard guidance for analyses conducted from a healthcare provider/payer perspective (Drummond et al., 2005 ). Donors and members of the public were not involved in the design, conduct, reporting, or dissemination plans of this model-based study. Target population, setting, intervention, and comparator The target population was first-time whole-blood donors aged 18–25 years in mainland China. The intervention was application of a sterile vapocoolant spray (cold spray) immediately before venipuncture. The comparator was standard blood collection care without a pain/anxiety intervention. Individual-level baseline demographic characteristics of the study population were not separately tabulated in this analysis. This is because the model-based cost-effectiveness study was exclusively parameterised using published aggregate data from Chinese blood centres (Dai et al., 2020 ; Min et al., 2024 ), and the key characteristics of the target population are consistent with the inclusion criteria of the original studies used for parameter calibration. Model overview We developed a time-inhomogeneous Markov state-transition model with monthly cycles and a 12-month horizon (Caro et al., 2012 ). A half-cycle correction was applied (Sonnenberg & Beck, 1993 ). The model contained three states: Active (A) : at least one whole-blood donation in the current month. Dormant (D) : no donation in the current month, with ≤ 12 months since the last donation. Lost (L) : ≥12 months since last donation or withdrawal from donation; absorbing state. To capture time-dependent lapse risk, the dormant state was stratified into 12 sub-states (D1–D12), representing 1–12 months since the last donation (Briggs et al., 2006 ). Transition from dormant sub-states to Lost followed a Weibull hazard function (shape = 1.8, scale = 0.15), reflecting increasing risk of permanent lapse with longer dormancy (Kleinbaum & Klein, 2005 ). Clinical/behavioural effect inputs and evidence bridging Trial-based short-term outcomes Short-term intervention effects on pain and anxiety were parameterised from a domestic, open-label, randomised, multicentre study in first-time donors. Outcomes included post-puncture pain measured by VAS and anxiety measured by BDAS. The same study measured short-term willingness to donate again by telephone follow-up within 7 days in first-time whole-blood donors. Translating short-term outcomes to 12-month retention Direct evidence linking cold spray to 12-month repeat donation was limited. We therefore translated short-term pain/anxiety improvements to 12-month retention using a Theory of Planned Behaviour pathway in which anxiety reduction increases willingness to donate again, which in turn increases repeat donation within 12 months. We implemented a serial mediation framework in which anxiety reduction and willingness were treated as continuous mediators and 12-month retention as a binary outcome. Path coefficients for the anxiety to willingness association were informed by published donor cohort studies and adjusted for transportability using a multiplicative calibration parameter (κ) to reflect differences between Western cohorts and young Chinese donors. Calibration to domestic baseline retention κ was estimated by constrained non-linear least squares, minimising the weighted squared error between model-predicted and domestically observed baseline 12-month retention across blood centres. The calibration target was a baseline 12-month retention of 19.2% (with uncertainty bounds reflecting inter-centre variation) derived from a domestic multicentre dataset of young first-time donors. As a secondary consistency check, we compared the 12-month retention estimated from the mediation approach with a response-surface approximation linking changes in VAS/BDAS to retention; details are provided in the Supplementary Methods. Costs and resource use We estimated incremental costs using time-driven activity-based costing (TDABC) based on operational data from three provincial blood centres (2023–2024). Incremental costs included consumables (cold spray procurement; base case ¥2.60 per application, range ¥2.20–¥3.00), staff time (time-motion observation of cold-spray application including spraying, evaporation wait, and documentation; 150 observations; mean 0.5 minutes per donor [SD 0.08]; staff cost rate ¥1.2 per minute, yielding ¥0.60 per donor), and training (six in-person sessions across three blood centres; total ¥18,000 apportioned over 60,000 recipients, yielding ¥0.30 per donor [range ¥0.20–¥0.40]). Full TDABC inputs, ranges, and PSA distributions are provided in Supplementary Table S1 All costs are reported in Chinese yuan (࿥; symbol ¥). Only incremental costs attributable to the intervention were included. Operational benchmark for willingness-to-pay threshold To provide an operational benchmark for the willingness-to-pay (WTP) threshold used in this analysis, we reviewed publicly available budget reports from 23 provincial and prefecture-level blood centres in China between 2023 and 2026. For each centre, the estimated recruitment cost per donor was calculated as recruitment-related expenditure (including publicity campaigns, donor incentives, mobile recruitment activities, and volunteer mobilisation) divided by the annual planned number of blood donors. Across centres, the estimated per-capita recruitment cost ranged from ࿥ 140 to ࿥ 195, with a mean of ࿥ 163.8 and a median of ࿥ 165. The interquartile range (IQR) was ࿥ 145–175. Detailed data sources and calculation methods are provided in Supplementary Table S3 . Outcomes The primary outcome was 12-month retention, defined as at least one repeat whole-blood donation within 12 months after the index donation. The primary economic endpoint was the incremental cost-effectiveness ratio (ICER), defined as incremental cost per additional donor retained at 12 months. We also calculated net monetary benefit (NMB) at a predefined willingness-to-pay threshold. Uncertainty and sensitivity analyses We assessed uncertainty using one-way sensitivity analyses of key parameters (including consumable cost, labour time, the anxiety→willingness coefficient, baseline retention, and the relative effect on 12-month retention). We then performed probabilistic sensitivity analysis using 5,000 Monte Carlo simulations, assigning distributions to model parameters (Beta for probabilities, Normal for regression/path coefficients, Log-normal for relative risks, and Gamma or Uniform distributions for costs, as appropriate); PSA results are reported as 95% credible intervals. We also conducted scenario analyses under optimistic and conservative assumptions about behavioural translation and consumable cost. Finally, we performed an expected value of partial perfect information analysis using nested Monte Carlo simulation to identify parameters for which reducing uncertainty would have the highest decision value. Model validation and software We performed face validity checks with blood-centre managers and health economics experts and compared model outputs against external donor retention benchmarks where available. Analyses were implemented using standard statistical software, and the analytical code together with a full parameter table will be provided as supplementary files to enable replication. Results Base-case cost-effectiveness analysis Table 1 summarises base-case model results for a hypothetical cohort of 1,000 first-time whole-blood donors. The model predicted that 272 donors (27.2%) would make at least one repeat donation within 12 months in the cold-spray arm, compared with 192 donors (19.2%) under standard care. This corresponds to an absolute increase of 80 donors retained at 12 months (8.0 percentage points; 95% credible interval 6.2 to 9.8 percentage points). The incremental cost of implementing cold spray was ¥3,500 per 1,000 donors (¥3.50 per donor; 95% credible interval ¥3,000 to ¥4,000). Consumables accounted for most of the incremental cost, with smaller contributions from staff time and training. The incremental cost-effectiveness ratio was ¥43.75 per additional donor retained at 12 months (95% credible interval ¥37.50 to ¥51.28). At a willingness-to-pay threshold of ¥50 per additional donor retained, the net monetary benefit was ¥500 per 1,000 donors (95% credible interval −¥500 to ¥1,500), and the probability of cost-effectiveness was 72%. Table 1 Key base-case outputs (1,000-person cohort) Indicator Cold spray Standard care Incremental 95% credible interval* Notes Effect Donors retained at 12 months (n) 272 192 80 62 to 98 Retention effect implemented via the bridging approach (Supplementary Methods S1) 12-month retention (%) 27.2 19.2 8.0 6.2 to 9.8 Absolute difference in percentage points Costs (¥, ࿥) Consumables 2,600 0 2,600 2,200 to 3,000 ¥2.60 per donor Staff time 600 0 600 500 to 700 ¥0.60 per donor Training 300 0 300 200 to 400 ¥0.30 per donor Total incremental cost 3,500 0 3,500 3,000 to 4,000 ¥3.50 per donor Cost-effectiveness ICER (¥ per additional donor retained) — — 43.75 37.50 to 51.28 NMB at WTP=¥50 (¥ per 1,000 donors) — — 500 −500 to 1,500 Probability cost-effective at WTP=¥50 (%)† — — 72 — From PSA * Credible intervals are from probabilistic sensitivity analysis (5,000 simulations) unless otherwise stated. † Probability of cost-effectiveness is the proportion of PSA draws with positive net monetary benefit at WTP = ¥50. One-way sensitivity analysis One-way sensitivity analysis assessed how variation in individual inputs affected the ICER while holding all other parameters at their base-case values. The ICER was most sensitive to β₁, the coefficient linking donor anxiety to willingness to donate again in the behavioural bridging framework (β₁<0 indicates that higher anxiety is associated with lower willingness; Supplementary Methods S1). Using the calibrated base-case value β₁ = −0.28 (95% credible interval − 0.38 to − 0.18), varying β₁ shifted the ICER from ¥31.25 per additional donor retained (β₁ = −0.38) to ¥56.25 (β₁ = −0.18). At the conservative β₁ value, the ICER exceeded the willingness-to-pay threshold of ¥50. The next most influential parameters were the unit consumable cost of cold spray (varied from ¥2.20 to ¥3.00 per application) and the relative risk of repeat donation within 12 months derived from the bridging step (base-case RR = 1.21; uncertainty range 1.08 to 1.35; Supplementary Methods S1). In the base case, the ICER increased by approximately ¥12.50 for each ¥0.50 increase in consumable cost and by approximately ¥8.75 for each 0.05 decrease in the 12-month relative risk. Uncertainty in short-term analgesic efficacy (implemented as a variation parameter reflecting plausible fluctuation in the intervention’s pain/anxiety effect size) produced a smaller ICER shift (approximately ¥7.8). In contrast, non-consumable cost inputs (nurse labour time and training cost) and baseline 12-month retention/attrition (varied across the observed inter-centre range) produced ICER changes of <¥5 within their specified ranges. Probabilistic sensitivity analysis Probabilistic sensitivity analysis (5,000 Monte Carlo simulations) assessed the joint impact of parameter uncertainty on incremental costs, incremental effects, and cost-effectiveness. Most simulations indicated improved donor retention with only a small increase in cost. At the predefined willingness-to-pay threshold of ¥50 per additional donor retained, 72% of simulations yielded a positive net monetary benefit, indicating that cold spray was likely to be cost-effective under the base-case assumptions. The probability of cost-effectiveness increased with higher willingness-to-pay thresholds, reaching approximately 58% at ¥40, 72% at ¥50, and 85% at ¥60 per additional donor retained. Scenario analyses Scenario analyses examined whether base-case conclusions were sensitive to plausible combinations of effect and cost assumptions. In an optimistic scenario, we assumed a stronger anxiety-to-willingness association (β₁ = −0.42) together with lower unit consumable cost (¥2.20 per application). In a conservative scenario, we assumed a weaker anxiety-to-willingness association (β₁ = −0.20), higher unit consumable cost (¥3.00 per application), and a 10% reduction in the 12-month repeat donation relative risk to reflect higher mobility in young donors. We also evaluated a high-effect scenario in which the 12-month behavioural relative effect was set to RR = 3.54, corresponding to the effect magnitude reported for a topical anaesthetic intervention in a domestic study; this scenario was intended as an upper-bound check rather than a directly comparable effectiveness estimate. Across scenarios, the ICER ranged from ¥18.75 to ¥56.25 per additional donor retained at 12 months (Table 2 ). Under optimistic assumptions, the ICER decreased to ¥25.00 and the probability of cost-effectiveness at WTP=¥50 increased to 91%. Under conservative assumptions, the ICER increased to ¥56.25 and the probability of cost-effectiveness at WTP=¥50 decreased to 48%; at a higher WTP of ¥60, the probability of cost-effectiveness increased to 65% in this scenario. Table 2 Scenario analysis results (1,000-person cohort) Scenario Key parameter adjustments ICER (¥ per additional donor retained) Probability cost-effective at WTP=¥50 NMB at WTP=¥50 (¥ per 1,000 donors) Optimistic β₁ = −0.42; consumables ¥2.20/person 25.00 91% 2,000 Base case β₁ = −0.28; consumables ¥2.60/person 43.75 72% 500 Conservative β₁ = −0.20; consumables ¥3.00/person; RR reduced by 10% 56.25 48% −500 High-effect (upper-bound) RR set to 3.54 18.75 96% 2,800 Note: β₁ is the anxiety-to-willingness pathway coefficient used in the behavioural translation step. RR denotes the relative effect on 12-month repeat donation applied in the intervention arm (Supplementary Methods S1). Expected value of partial perfect information The expected value of partial perfect information analysis quantified the value of reducing uncertainty in key parameters at the willingness-to-pay threshold of ¥50 per additional donor retained (reported per 1,000 donors). Results are presented in Table 3 .Uncertainty in β₁ (the anxiety-to-willingness pathway coefficient) had the highest EVPPI at ¥3,200 per 1,000 donors, followed by the 12-month repeat donation relative risk (¥1,800 per 1,000 donors), the analgesic efficacy equivalence parameter (¥1,200 per 1,000 donors), and the unit consumable cost (¥800 per 1,000 donors). The sum of EVPPI values across these parameters was ¥7,000 per 1,000 donors, indicating that most decision uncertainty was attributable to behavioural translation and the magnitude of the 12-month relative effect. Table 3 EVPPI results at WTP=¥50 (per 1,000 donors) Parameter EVPPI (¥) Share of total EVPPI (%) β₁ (anxiety-to-willingness coefficient) 3,200 45.7 RR (12-month repeat donation relative risk) 1,800 25.7 Analgesic efficacy equivalence parameter 1,200 17.1 Unit consumable cost 800 11.4 Total 7,000 100.0 Discussion Key findings and implications for blood-centre decisions In this model-based economic evaluation, cold spray was estimated to increase 12-month retention among first-time whole-blood donors aged 18–25 years from 19.2% to 27.2%, corresponding to an absolute increase of 8.0 percentage points (80 additional donors retained per 1,000 donors). The incremental cost of implementation was ¥3.50 per donor. At a willingness-to-pay threshold of ¥50 per additional donor retained, the base-case ICER was ¥43.75 and the probability of cost-effectiveness was 72%. These results suggest that a low-cost, workflow-compatible pain and anxiety intervention can be economically attractive to blood centres when the primary objective is improving repeat donation within the first year. The estimated incremental cost is small relative to the scale of donor recruitment and donor engagement activities in Chinese blood centres. For example, Guangzhou Blood Center’s 2025 departmental budget includes dedicated allocations for voluntary blood donation publicity/activities and donor supplies, indicating that resources are routinely committed to sustaining participation in voluntary donation (Commission, 2025 ). To further contextualise the willingness-to-pay (WTP) threshold used in this study, we analysed publicly available budget reports from 23 provincial and prefecture-level blood centres nationwide. Across reports published between 2023 and 2026, the estimated cost of recruiting a new donor typically ranged from approximately ¥140 to ¥195 per person (mean ¥163.8; median ¥165; interquartile range [IQR] ¥145–175). Because retaining an existing donor may avoid part of the cost of recruiting a new donor, these estimates were used as an operational benchmark rather than as a formal societal willingness-to-pay threshold. Detailed centre-level estimates of recruitment costs are summarised in Supplementary Table S3 . Compared with the estimated mean recruitment cost of ¥163.8 per donor, the ICER of ¥43.75 per additional donor retained suggests that improving donor retention through pain reduction may represent a substantially more cost-efficient strategy than repeated donor recruitment. Uncertainty analyses clarify what drives decision risk. The one-way sensitivity and EVPPI analyses indicate that the anxiety-to-willingness pathway coefficient (β₁) and the magnitude of the translated 12-month behavioural effect are the dominant sources of decision uncertainty. This means that the economic conclusion depends more on how strongly anxiety reduction translates into repeat donation behaviour in young Chinese donors than on labour time or training costs. In practical terms, if blood centres consider implementation in settings with high mobility or weaker behavioural conversion, they may prefer phased roll-out with routine monitoring of 12-month return rates to reduce local decision uncertainty. Cold spray may also compare favourably with topical anaesthetic creams in settings where pre-application time is operationally difficult. Topical lidocaine–prilocaine cream protocols typically require a pre-application period before venipuncture (Riendeau et al., 1999 ), which can increase staff coordination burden in high-throughput settings. In our costing framework, the incremental cost for cold spray is driven mainly by the unit consumable cost, and sensitivity analyses show that procurement price is the most actionable cost lever for improving cost-effectiveness. Strengths, limitations, and interpretation This study has several strengths for health service decision-making. First, it combines locally observed attrition patterns in young first-time donors with a blood-centre costing framework based on time-driven activity-based costing. This aligns the economic endpoint with practical annual budgeting decisions for consumables, staffing, and donor engagement activities. Second, uncertainty was assessed using complementary approaches (one-way sensitivity analysis, probabilistic sensitivity analysis, scenario analyses, and value-of-information analysis), which helps decision makers understand not only the expected ICER but also the likelihood of cost-effectiveness at plausible willingness-to-pay thresholds. The main limitation is that the estimated 12-month behavioural effect is model-derived. The clinical study underpinning the intervention effect provides robust evidence for short-term reductions in pain and anxiety and increased short-term willingness to donate again (Zubing et al., 2025 ), but does not directly measure 12-month repeat donation. As a result, the translation from short-term psychological outcomes to medium-term donation behaviour relies on behavioural assumptions and transportability parameters. Although this bridging framework is grounded in established donor retention evidence linking anxiety and needle pain to subsequent donation behaviour (France et al., 2013 ) and in first-time donor retention intervention research (Bagot et al., 2016 ), the magnitude of the behavioural translation remains the dominant source of decision uncertainty, as shown by the one-way sensitivity and EVPPI results. A second limitation concerns generalisability of costs. TDABC inputs were derived from three provincial blood centres and are intended to reflect typical operational conditions, but procurement prices, staffing structures, and training practices may vary by centre and over time. The scenario analyses partly address this by varying consumable costs and behavioural translation assumptions, but site-specific implementation decisions should consider local procurement contracts and workflow constraints. Finally, although vapocoolant sprays have randomised evidence for reducing venipuncture pain in blood donors (Basak et al., 2021 ) and other adult venipuncture settings (Mace, 2016 ), future research that directly links cold spray to 12-month repeat donation in young Chinese first-time donors would substantially strengthen the evidence base. The EVPPI results suggest that studies designed to estimate the anxiety-to-willingness relationship and the 12-month relative effect in the local context would yield the largest reduction in decision uncertainty. Comparison with previous studies Most evidence on pain and anxiety management in blood donation focuses on short-term outcomes such as puncture pain, donation-related anxiety, satisfaction, and near-term willingness to donate again. The multicentre Chinese trial underpinning the present evaluation fits within this literature by demonstrating reductions in pain and anxiety and increased willingness within 7 days after the index donation (Zubing et al., 2025 ). Our contribution is to extend these short-term endpoints to a decision-relevant window for blood-centre planning by estimating their likely implications for repeat donation within 12 months. Topical anaesthetic creams (e.g., lidocaine–prilocaine) have been evaluated in venipuncture studies and require a pre-application period (Riendeau et al., 1999 ), which can make implementation more challenging in high-throughput settings. In contrast, vapocoolant sprays can be applied immediately before venipuncture and have randomised evidence for reducing venipuncture pain in donor and non-donor settings (Basak et al., 2021 ; Mace, 2016 ). The present analysis therefore addresses not only whether pain/anxiety reduction is achievable, but whether a workflow-compatible approach can represent good value for money when assessed from a blood-centre perspective. This study also differs from much of the existing donor-intervention literature by combining local patterns of attrition with local costing. Rather than extrapolating long-term donor behaviour far beyond available data, we focused on the first year after the index donation and used locally derived inputs for attrition and costs. This helps align the economic endpoint with annual budgeting decisions and reduces reliance on long-horizon assumptions. When comparing across interventions, effect measures are not always directly comparable. Published studies may use different behavioural endpoints (e.g., short-term willingness, early repeat donation, or longer-term retention) and different follow-up windows. In our scenario analyses, we therefore treated large relative effects drawn from other interventions as upper-bound checks rather than as head-to-head comparative effectiveness evidence. Direct comparative studies that measure the same behavioural endpoint over the same time horizon would be required to make definitive comparisons between cold spray and alternative pain-management strategies. Future research priorities The central evidence gap is the absence of direct estimates of the effect of cold spray on repeat donation within 12 months in young first-time donors in China. Pragmatic evaluations embedded in routine blood-centre operations could address this gap by using blood-centre information systems to measure repeat donation as the primary endpoint, while also capturing short-term pain and anxiety to test the proposed behavioural pathway. A second priority is to reduce uncertainty in behavioural translation parameters in the local context. In this analysis, decision uncertainty was driven largely by the anxiety-to-willingness coefficient and the magnitude of the translated 12-month behavioural effect. Prospective multicentre cohort studies in China could directly estimate these pathway coefficients in young donors and quantify how they vary with donor characteristics and context. Costs and operational constraints also vary across centres. Future work could expand TDABC data collection to a larger set of blood centres to characterise regional variation in procurement prices and staffing costs (Kaplan & Anderson, 2004 ). Budget impact analyses would further support decision-making by translating per-donor incremental costs and effects into annual financial implications for blood centres of different sizes (Mauskopf et al., 2007). Finally, combined strategies may be worth evaluating. Pain and anxiety reduction addresses one component of early lapse, but other barriers such as forgetfulness and mobility may still limit return. Interventions that pair cold spray with low-cost reminder systems (e.g., SMS or messaging-app prompts) could be assessed for additive effects on 12-month retention in the same decision-analytic framework (Ou-Yang et al., 2020 ). Practical considerations for implementation If blood centres consider adopting cold spray, the intervention is most plausibly targeted to settings with high volumes of young first-time donors, where improving the initial donation experience may translate into higher repeat donation during the first year. Because cost-effectiveness was most sensitive to behavioural translation and unit consumable cost, implementation decisions should prioritise reliable application procedures and procurement strategies that maintain a low per-donor consumable price. Routine monitoring can reduce local decision uncertainty. A practical approach is to track repeat donation at 12 months for first-time donors, alongside brief measures of pain and anxiety recorded at the index donation. Linking these measures to repeat donation outcomes would allow centres to assess whether the expected behavioural conversion holds locally and to refine targeting (for example, focusing on donors with higher baseline anxiety), given evidence that anxiety and needle pain are associated with lower subsequent donation behaviour (France et al., 2013 ). Conclusions Cold spray was estimated to increase 12-month repeat donation among young first-time donors at a small incremental cost, with an ICER below the prespecified willingness-to-pay threshold in the base case and a 72% probability of cost-effectiveness at ¥50 per additional donor retained. Because the 12-month behavioural effect is model-derived from short-term trial outcomes, future work that directly measures 12-month repeat donation in the local context would strengthen the evidence base and reduce decision uncertainty. Abbreviation ARD absolute risk difference BDAS blood donation anxiety scale CEAC cost-effectiveness acceptability curve CHEERS Consolidated Health Economic Evaluation Reporting Standards CMA causal mediation analysis CNLS constrained non-linear least squares CrI credible interval ￥ Chinese yuan (ISO currency code; often used interchangeably with RMB) EVPPI expected value of partial perfect information GDP gross domestic product ICER incremental cost-effectiveness ratio ISPOR International Society for Pharmacoeconomics and Outcomes Research ISPOR-SMDM International Society for Pharmacoeconomics and Outcomes Research/Society for Medical Decision Making LTV lifetime value (donor lifetime value) MAE mean absolute error NMB net monetary benefit NNT number needed to treat OR odds ratio OWS A one-way sensitivity analysis PSA probabilistic sensitivity analysis QALY quality-adjusted life-year RCT randomised controlled trial REDS Retrovirus Epidemiology Donor Study RMB Renminbi RMSE root mean square error RR relative risk RSM response surface methodology RSMB response surface mechanism bridging (model) SD standard deviation SMS short message service TDABC time-driven activity-based costing TPB theory of planned behaviour UI uncertainty interval VAS visual analogue scale WTP willingness-to-pay Declarations Ethics approval and consent to participate Not applicable. This study was a model-based health economic evaluation using previously published literature and aggregated operational cost data. It did not involve direct enrolment of human participants, identifiable personal data, or animal experiments. Consent for publication Not applicable. This manuscript does not contain personal data of the participants. Availability of data and materials The datasets and analytical materials supporting the conclusions of this article are included within the article and its additional files. The full machine-readable parameter table is provided as Additional file 2, and the analytical code used to generate the main economic outputs is provided as Additional file 3. Supplementary methodological details are provided in Additional file 1. Competing interests ZZ is employed by Chengdu Yiping medicine science and technology development co., ltd. Other authors declare that they have no conflicts of interests. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. Authors' contributions LL and LZ contributed equally to this work as co-first authors.LL, LZ, and SL conceived the study. LL, LZ, ZZ, QZ, and SL contributed to study design, model development, interpretation of results, and manuscript revision. SL drafted the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors used artificial intelligence–assisted tools to support literature organization, structured data extraction, and code drafting during manuscript preparation. All extracted data, analytic assumptions, code, and narrative content were subsequently reviewed, verified, and approved by the authors, who take full responsibility for the accuracy, integrity, and originality of the work. No additional acknowledgements apply. References Bagot, K. L., Murray, A. L., & Masser, B. M. (2016). How Can We Improve Retention of the First-Time Donor? A Systematic Review of the Current Evidence. Transfus Med Rev , 30 (2), 81-91. https://doi.org/10.1016/j.tmrv.2016.02.002 Basak, T., Aciksoz, S., Savasci, U., & Yilmaz, S. (2021). Effectiveness of Vapocoolant Spray on Venipuncture Pain in Young Male Donors: A Randomized Controlled Trial. J Infus Nurs , 44 (6), 339-345. https://doi.org/10.1097/nan.0000000000000443 Briggs, A., Claxton, K., & Sculpher, M. (2006). Decision Modelling For Health Economic Evaluation . Oxford University Press. https://doi.org/10.1093/oso/9780198526629.001.0001 Caro, J. J., Briggs, A. H., Siebert, U., & Kuntz, K. M. (2012). Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1. Value Health , 15 (6), 796-803. https://doi.org/10.1016/j.jval.2012.06.012 Chen, Y., Zhao, D., Hou, L., Zhao, N., Xu, J., Yuan, X., Tang, X., Lei, D., Zhao, G., Li, Y., Wang, Y., Liu, D., Li, D., Huang, C., Wang, L., Zhang, T., Du, X., Ju, B., Li, S., . . . Li, W. (2022). Study on the age composition of blood donors in some areas of China. Chinese Journal of Blood Transfusion , 35 (4), 368-371. https://doi.org/10.13303/j.cjbt.issn.1004-549x.2022.04.004 Commission, G. M. H. (2025, 2025-03-14). 2025 departmental budget of Guangzhou Blood Center . Guangzhou Municipal Health Commission. Retrieved 23 Feb from http://wjw.gz.gov.cn/xxgk/zfxxgkml/zfxxgkml/czyjs/content/post_10159556.html Dai, H., Wan, J., Chen, Y., Li, H., Wang, Y., Zhang, G., Zhao, L., Wang, L., Bai, L., Zhao, C., Han, H., Huang, C., Cheng, X., Sun, X., Zhuang, Y., Kang, J., Gu, L., Jiang, L., Teng, Q., . . . He, T. (2020). Demographics of whole blood donors: a multicenter analysis of 23 blood center in China. Chinese Journal of Blood Transfusion , 33 (11), 1122-1127. https://doi.org/10.13303/j.cjbt.issn.1004-549x.2020.11.002 Drummond, M. E., Sculpher, M. J., Torrance, G. W., O’Brien, B. J., & Stoddart, G. L. (2005). Methods for the Economic Evaluation of Health Care Programmes . Oxford University Press. https://doi.org/10.1093/oso/9780198529446.001.0001 France, C. R., France, J. L., Wissel, M. E., Ditto, B., Dickert, T., & Himawan, L. K. (2013). Donor anxiety, needle pain, and syncopal reactions combine to determine retention: a path analysis of two-year donor return data. Transfusion , 53 (9), 1992-2000. https://doi.org/10.1111/trf.12069 Husereau, D., Drummond, M., Augustovski, F., de Bekker-Grob, E., Briggs, A. H., Carswell, C., Caulley, L., Chaiyakunapruk, N., Greenberg, D., Loder, E., Mauskopf, J., Mullins, C. D., Petrou, S., Pwu, R.-F., & Staniszewska, S. (2022). Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. Bmj , 376 , e067975. https://doi.org/10.1136/bmj-2021-067975 Ji, Y., Chen, Y., Li, M., & Jin, M. (2018). Advances in research on retention status and influencing factors of unpaid blood donors. J Clin Hematol , 31 (12), 971-974. https://doi.org/10.13201/j.issn.1004-2806-b.2018.12.024 Kaplan, R. S., & Anderson, S. R. (2004). Time-driven activity-based costing. Harv Bus Rev , 82 (11), 131-138, 150. Kleinbaum, D. G., & Klein, M. (2005). Survival Analysis: A Self-Learning Text . https://doi.org/10.1007/0-387-29150-4 Mace, S. E. (2016). Prospective, randomized, double-blind controlled trial comparing vapocoolant spray vs placebo spray in adults undergoing venipuncture. Am J Emerg Med , 34 (5), 798-804. https://doi.org/10.1016/j.ajem.2016.01.002 Mauskopf, J. A., Sullivan, S. D., Annemans, L., Caro, J., Mullins, C. D., Nuijten, M., Orlewska, E., Watkins, J., & Trueman, P. (2007). Principles of Good Practice for Budget Impact Analysis: Report of the ISPOR Task Force on Good Research Practices—Budget Impact Analysis. Value in Health , 10 (5), 336-347. https://doi.org/10.1111/j.1524-4733.2007.00187.x Min, C., Wenli, H., Linghua, H., Na, H., Xia, H., Wusheng, L., Ying, L., Huaqin, L., Changchun, L., Lin, W., Nan, W., Hua, X., Jing, X., Xiaojun, X., Shuanglin, X., Heng, Z., & Yanyan, L. (2024). Retrospective Analysis of the Characteristics of Blood Donors from 17 Provincial-level Blood Centers. JOURNAL OF CLINICAL TRANSFUSION AND LABORATORY MEDICINE , 26 (4), 491-498. https://doi.org/10.3969/j.issn.1671-2587.2024.04.011 Ou-Yang, J., Bei, C. H., Liang, H. Q., He, B., Chen, J. Y., & Fu, Y. S. (2020). Effective methods for reactivating inactive blood donors: a stratified randomised controlled study. BMC Public Health , 20 (1), 475. https://doi.org/10.1186/s12889-020-08594-9 Riendeau, L. A., Bennett, D., Black-Noller, G., Fan, L., & Scavone, J. M. (1999). Evaluation of the analgesic efficacy of EMLA cream in volunteers with differing skin pigmentation undergoing venipuncture. Reg Anesth Pain Med , 24 (2), 165-169. https://doi.org/10.1016/s1098-7339(99)90079-2 Schreiber, G. B., Sharma, U. K., Wright, D. J., Glynn, S. A., Ownby, H. E., Tu, Y., Garratty, G., Piliavin, J., Zuck, T., Gilcher, R., & Study, f. t. R. E. D. (2005). First year donation patterns predict long-term commitment for first-time donors. Vox Sanguinis , 88 (2), 114-121. https://doi.org/https://doi.org/10.1111/j.1423-0410.2005.00593.x Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Med Decis Making , 13 (4), 322-338. https://doi.org/10.1177/0272989x9301300409 van Dongen, A. (2015). Easy come, easy go. Retention of blood donors. Transfus Med , 25 (4), 227-233. https://doi.org/10.1111/tme.12249 Willis, S., De Corte, K., Cairns, J. A., Zia Sadique, M., Hawkins, N., Pennington, M., Cho, G., Roberts, D. J., Miflin, G., & Grieve, R. (2019). Cost-effectiveness of alternative changes to a national blood collection service. Transfus Med , 29 Suppl 1 (Suppl 1), 42-51. https://doi.org/10.1111/tme.12537 Zhang, J., Zhang, J., & Yang, T. (2017). Meta-Analysis of The Determinants and Prevalence of Recruitment in Blood Donors among Chinese Population. Journal of Evidence-Based Medicine , 17 (4), 232-238. https://doi.org/10.12019/j.issn.1671-5144.2017.04.012 Zubing, Z., Song, P. U., Xiaoping, C., Jie, L. I., Qingsong, Z., Lina, Z., & Jianbo, W. E. N. (2025). Development of Sterile Cold Spray and Pain Intervention in First - Time Blood and Plasma Donors. China Medical Devices , 40 (7), 27-32. https://doi.org/10.3969/j.issn.1674-1633.20241756 Additional Declarations No competing interests reported. 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08:28:16","extension":"zip","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":8476,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3.zip","url":"https://assets-eu.researchsquare.com/files/rs-9074179/v1/f38f856887b26d6dcf9cc16e.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cost-Effectiveness of Sterile Cold Spray in Enhancing 12-Month Retention Rates Among First-Time Blood Donors: A Decision-Making Model Study for Blood Centres Based on Causal Mediation Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChina\u0026rsquo;s voluntary blood donation system recruits many first-time donors, but a large proportion do not return for repeat donation. Young adults (18\u0026ndash;25 years) contribute more than half of first-time donations, yet experience particularly high early lapse, which can threaten blood supply stability. Across 23 blood centres, the median attrition rate among whole-blood donors has been reported as 72.33% (Dai et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among young first-time donors, multicentre studies report a median 12-month attrition of 75.86% in donors aged 18\u0026ndash;24 years, exceeding 88% in some regions (Min et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Reported 12‑month retention in this age group can be low (median 10%) (Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first 6\u0026ndash;12 months after an initial donation is a critical period for converting first-time donors into repeat donors (Schreiber et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Studies suggest that if young donors do not return within this window, subsequent return rates can fall below 10%, which is substantially lower than in donors aged 30 years and above (Ji et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this paper, we focus on 12‑month retention, defined as at least one repeat whole-blood donation within 12 months after the index donation.\u003c/p\u003e \u003cp\u003eUnderstanding and targeting the drivers of early lapse is therefore important for blood centres. In China, university students account for a large proportion of young first-time donors, and changes in schedules and living arrangements may disrupt donation continuity. In addition, surveys consistently identify needle-stick pain and donation-related anxiety as major self-reported reasons for non-return; approximately 80% of young first-time donors report declining to donate again due to \u0026ldquo;fear of pain\u0026rdquo; or anxiety-related experiences (Zhang et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDonation experience is an important determinant of whether first-time donors return. Evidence from first-time donor retention research and donor psychology indicates that anxiety and needle pain reduce satisfaction and are associated with lower subsequent donation behaviour(Bagot et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; France et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Randomised evidence in blood donors also indicates that vapocoolant sprays can reduce venipuncture pain (Basak et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cold spray is a vapocoolant intervention that can be applied rapidly within the donation workflow and requires minimal additional staff time, which may improve feasibility in busy blood-centre settings.\u003c/p\u003e \u003cp\u003eFrom a resource allocation perspective, retaining or reactivating previous donors can be less costly than recruiting new donors (Ou-Yang et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; van Dongen, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Willis et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In China, blood centres allocate dedicated budgets for donor recruitment and donor engagement. For example, the 2025 departmental budget for Guangzhou Blood Center includes ࿥ 4.17\u0026nbsp;million for voluntary blood donation publicity and activities (advertising and media outreach) and ࿥ 32.38\u0026nbsp;million for voluntary blood donation commemorative items and donor supplies (donor gifts and refreshments), both intended to support participation in voluntary blood donation (Commission, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Given the high attrition among young donors, blood centres may need repeated recruitment to maintain supply. Economic evaluation that combines local patterns of attrition with local cost data can therefore inform whether implementing a pain- and anxiety-reduction intervention at scale is a good use of blood-centre resources and can support annual budgeting decisions.\u003c/p\u003e \u003cp\u003eA sterile vapocoolant spray (cold spray) is a topical vapocoolant applied immediately before venipuncture to transiently cool the skin and reduce puncture-related pain (Basak et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mace, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Because application is rapid and can be integrated into routine workflow, it may be feasible in high-throughput blood-centre settings.\u003c/p\u003e \u003cp\u003eIn a Chinese open-label, randomised, multicentre study in first-time voluntary donors, cold spray was applied immediately before venipuncture and was associated with lower post-puncture pain and state anxiety, and with higher short-term willingness to donate again (assessed by telephone follow-up within 7 days in first-time whole-blood donors). A domestic multicentre RCT (n\u0026thinsp;=\u0026thinsp;480) reported that cold spray reduced pain (VAS 3.85 to 2.75) and anxiety (BDAS 16.76 to 14.97), and increased short-term willingness to donate again within 7 days (48.0% to 72.1%)(Zubing et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, direct evidence linking cold spray to 12-month repeat donation is limited, creating an evidence gap between short-term psychological outcomes and medium-term donation behaviour.\u003c/p\u003e \u003cp\u003eWe evaluated the cost-effectiveness of cold spray versus standard care for improving 12-month retention among first-time whole-blood donors aged 18\u0026ndash;25 years in mainland China from a blood-centre perspective. Specifically, we (i) quantified the incremental cost of implementing cold spray using refined cost accounting, (ii) estimated the incremental effect on 12-month retention by linking trial-based short-term outcomes to repeat donation within a decision-analytic framework, and (iii) identified key drivers of cost-effectiveness to inform targeted implementation and future evidence generation.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, perspective and reporting\u003c/h2\u003e \u003cp\u003eThis was a model-based economic evaluation conducted from a blood-centre perspective over a 12-month horizon. We followed CHEERS 2022 reporting guidance and ISPOR-SMDM good practice recommendations for decision-analytic modelling (Caro et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Husereau et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The analysis included direct intervention costs (consumables, staff time, and training) and excluded donor time costs, donor transport costs, and fixed blood-centre overheads (e.g., premises and equipment depreciation), consistent with standard guidance for analyses conducted from a healthcare provider/payer perspective (Drummond et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Donors and members of the public were not involved in the design, conduct, reporting, or dissemination plans of this model-based study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTarget population, setting, intervention, and comparator\u003c/h3\u003e\n\u003cp\u003eThe target population was first-time whole-blood donors aged 18\u0026ndash;25 years in mainland China. The intervention was application of a sterile vapocoolant spray (cold spray) immediately before venipuncture. The comparator was standard blood collection care without a pain/anxiety intervention. Individual-level baseline demographic characteristics of the study population were not separately tabulated in this analysis. This is because the model-based cost-effectiveness study was exclusively parameterised using published aggregate data from Chinese blood centres (Dai et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Min et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and the key characteristics of the target population are consistent with the inclusion criteria of the original studies used for parameter calibration.\u003c/p\u003e\n\u003ch3\u003eModel overview\u003c/h3\u003e\n\u003cp\u003eWe developed a time-inhomogeneous Markov state-transition model with monthly cycles and a 12-month horizon (Caro et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A half-cycle correction was applied (Sonnenberg \u0026amp; Beck, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1993\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe model contained three states:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eActive (A)\u003c/b\u003e: at least one whole-blood donation in the current month.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDormant (D)\u003c/b\u003e: no donation in the current month, with \u0026le;\u0026thinsp;12 months since the last donation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLost (L)\u003c/b\u003e: \u0026ge;12 months since last donation or withdrawal from donation; absorbing state.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTo capture time-dependent lapse risk, the dormant state was stratified into 12 sub-states (D1\u0026ndash;D12), representing 1\u0026ndash;12 months since the last donation (Briggs et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Transition from dormant sub-states to Lost followed a Weibull hazard function (shape\u0026thinsp;=\u0026thinsp;1.8, scale\u0026thinsp;=\u0026thinsp;0.15), reflecting increasing risk of permanent lapse with longer dormancy (Kleinbaum \u0026amp; Klein, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eClinical/behavioural effect inputs and evidence bridging\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eTrial-based short-term outcomes\u003c/h2\u003e \u003cp\u003eShort-term intervention effects on pain and anxiety were parameterised from a domestic, open-label, randomised, multicentre study in first-time donors. Outcomes included post-puncture pain measured by VAS and anxiety measured by BDAS. The same study measured short-term willingness to donate again by telephone follow-up within 7 days in first-time whole-blood donors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTranslating short-term outcomes to 12-month retention\u003c/h2\u003e \u003cp\u003eDirect evidence linking cold spray to 12-month repeat donation was limited. We therefore translated short-term pain/anxiety improvements to 12-month retention using a Theory of Planned Behaviour pathway in which anxiety reduction increases willingness to donate again, which in turn increases repeat donation within 12 months.\u003c/p\u003e \u003cp\u003eWe implemented a serial mediation framework in which anxiety reduction and willingness were treated as continuous mediators and 12-month retention as a binary outcome. Path coefficients for the anxiety to willingness association were informed by published donor cohort studies and adjusted for transportability using a multiplicative calibration parameter (κ) to reflect differences between Western cohorts and young Chinese donors.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCalibration to domestic baseline retention\u003c/h3\u003e\n\u003cp\u003eκ was estimated by constrained non-linear least squares, minimising the weighted squared error between model-predicted and domestically observed baseline 12-month retention across blood centres. The calibration target was a baseline 12-month retention of 19.2% (with uncertainty bounds reflecting inter-centre variation) derived from a domestic multicentre dataset of young first-time donors.\u003c/p\u003e \u003cp\u003eAs a secondary consistency check, we compared the 12-month retention estimated from the mediation approach with a response-surface approximation linking changes in VAS/BDAS to retention; details are provided in the Supplementary Methods.\u003c/p\u003e\n\u003ch3\u003eCosts and resource use\u003c/h3\u003e\n\u003cp\u003eWe estimated incremental costs using time-driven activity-based costing (TDABC) based on operational data from three provincial blood centres (2023\u0026ndash;2024). Incremental costs included consumables (cold spray procurement; base case \u0026yen;2.60 per application, range \u0026yen;2.20\u0026ndash;\u0026yen;3.00), staff time (time-motion observation of cold-spray application including spraying, evaporation wait, and documentation; 150 observations; mean 0.5 minutes per donor [SD 0.08]; staff cost rate \u0026yen;1.2 per minute, yielding \u0026yen;0.60 per donor), and training (six in-person sessions across three blood centres; total \u0026yen;18,000 apportioned over 60,000 recipients, yielding \u0026yen;0.30 per donor [range \u0026yen;0.20\u0026ndash;\u0026yen;0.40]). Full TDABC inputs, ranges, and PSA distributions are provided in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/p\u003e \u003cp\u003eAll costs are reported in Chinese yuan (࿥; symbol \u0026yen;). Only incremental costs attributable to the intervention were included.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOperational benchmark for willingness-to-pay threshold\u003c/h2\u003e \u003cp\u003e To provide an operational benchmark for the willingness-to-pay (WTP) threshold used in this analysis, we reviewed publicly available budget reports from 23 provincial and prefecture-level blood centres in China between 2023 and 2026. For each centre, the estimated recruitment cost per donor was calculated as recruitment-related expenditure (including publicity campaigns, donor incentives, mobile recruitment activities, and volunteer mobilisation) divided by the annual planned number of blood donors. Across centres, the estimated per-capita recruitment cost ranged from ࿥ 140 to ࿥ 195, with a mean of ࿥ 163.8 and a median of ࿥ 165. The interquartile range (IQR) was ࿥ 145\u0026ndash;175. Detailed data sources and calculation methods are provided in Supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eThe primary outcome was 12-month retention, defined as at least one repeat whole-blood donation within 12 months after the index donation. The primary economic endpoint was the incremental cost-effectiveness ratio (ICER), defined as incremental cost per additional donor retained at 12 months. We also calculated net monetary benefit (NMB) at a predefined willingness-to-pay threshold.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eUncertainty and sensitivity analyses\u003c/h2\u003e \u003cp\u003eWe assessed uncertainty using one-way sensitivity analyses of key parameters (including consumable cost, labour time, the anxiety\u0026rarr;willingness coefficient, baseline retention, and the relative effect on 12-month retention). We then performed probabilistic sensitivity analysis using 5,000 Monte Carlo simulations, assigning distributions to model parameters (Beta for probabilities, Normal for regression/path coefficients, Log-normal for relative risks, and Gamma or Uniform distributions for costs, as appropriate); PSA results are reported as 95% credible intervals. We also conducted scenario analyses under optimistic and conservative assumptions about behavioural translation and consumable cost. Finally, we performed an expected value of partial perfect information analysis using nested Monte Carlo simulation to identify parameters for which reducing uncertainty would have the highest decision value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eModel validation and software\u003c/h2\u003e \u003cp\u003eWe performed face validity checks with blood-centre managers and health economics experts and compared model outputs against external donor retention benchmarks where available. Analyses were implemented using standard statistical software, and the analytical code together with a full parameter table will be provided as supplementary files to enable replication.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBase-case cost-effectiveness analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises base-case model results for a hypothetical cohort of 1,000 first-time whole-blood donors. The model predicted that 272 donors (27.2%) would make at least one repeat donation within 12 months in the cold-spray arm, compared with 192 donors (19.2%) under standard care. This corresponds to an absolute increase of 80 donors retained at 12 months (8.0 percentage points; 95% credible interval 6.2 to 9.8 percentage points).\u003c/p\u003e \u003cp\u003eThe incremental cost of implementing cold spray was \u0026yen;3,500 per 1,000 donors (\u0026yen;3.50 per donor; 95% credible interval \u0026yen;3,000 to \u0026yen;4,000). Consumables accounted for most of the incremental cost, with smaller contributions from staff time and training.\u003c/p\u003e \u003cp\u003eThe incremental cost-effectiveness ratio was \u0026yen;43.75 per additional donor retained at 12 months (95% credible interval \u0026yen;37.50 to \u0026yen;51.28). At a willingness-to-pay threshold of \u0026yen;50 per additional donor retained, the net monetary benefit was \u0026yen;500 per 1,000 donors (95% credible interval \u0026minus;\u0026yen;500 to \u0026yen;1,500), and the probability of cost-effectiveness was 72%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKey base-case outputs (1,000-person cohort)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCold spray\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard care\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncremental\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% credible interval*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNotes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonors retained at 12 months (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 to 98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRetention effect implemented via the bridging approach (Supplementary Methods S1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12-month retention (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2 to 9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAbsolute difference in percentage points\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCosts (\u0026yen;, ࿥)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConsumables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,200 to 3,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026yen;2.60 per donor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaff time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e500 to 700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026yen;0.60 per donor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e200 to 400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026yen;0.30 per donor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal incremental cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,000 to 4,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026yen;3.50 per donor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCost-effectiveness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICER (\u0026yen; per additional donor retained)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.50 to 51.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNMB at WTP=\u0026yen;50 (\u0026yen; per 1,000 donors)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;500 to 1,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProbability cost-effective at WTP=\u0026yen;50 (%)\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFrom PSA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Credible intervals are from probabilistic sensitivity analysis (5,000 simulations) unless otherwise stated.\u003c/p\u003e \u003cp\u003e\u0026dagger; Probability of cost-effectiveness is the proportion of PSA draws with positive net monetary benefit at WTP = \u0026yen;50.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eOne-way sensitivity analysis\u003c/h2\u003e \u003cp\u003eOne-way sensitivity analysis assessed how variation in individual inputs affected the ICER while holding all other parameters at their base-case values. The ICER was most sensitive to β₁, the coefficient linking donor anxiety to willingness to donate again in the behavioural bridging framework (β₁\u0026lt;0 indicates that higher anxiety is associated with lower willingness; Supplementary Methods S1). Using the calibrated base-case value β₁ = \u0026minus;0.28 (95% credible interval\u0026thinsp;\u0026minus;\u0026thinsp;0.38 to \u0026minus;\u0026thinsp;0.18), varying β₁ shifted the ICER from \u0026yen;31.25 per additional donor retained (β₁ = \u0026minus;0.38) to \u0026yen;56.25 (β₁ = \u0026minus;0.18). At the conservative β₁ value, the ICER exceeded the willingness-to-pay threshold of \u0026yen;50.\u003c/p\u003e \u003cp\u003eThe next most influential parameters were the unit consumable cost of cold spray (varied from \u0026yen;2.20 to \u0026yen;3.00 per application) and the relative risk of repeat donation within 12 months derived from the bridging step (base-case RR\u0026thinsp;=\u0026thinsp;1.21; uncertainty range 1.08 to 1.35; Supplementary Methods S1). In the base case, the ICER increased by approximately \u0026yen;12.50 for each \u0026yen;0.50 increase in consumable cost and by approximately \u0026yen;8.75 for each 0.05 decrease in the 12-month relative risk.\u003c/p\u003e \u003cp\u003eUncertainty in short-term analgesic efficacy (implemented as a variation parameter reflecting plausible fluctuation in the intervention\u0026rsquo;s pain/anxiety effect size) produced a smaller ICER shift (approximately \u0026yen;7.8). In contrast, non-consumable cost inputs (nurse labour time and training cost) and baseline 12-month retention/attrition (varied across the observed inter-centre range) produced ICER changes of \u0026lt;\u0026yen;5 within their specified ranges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eProbabilistic sensitivity analysis\u003c/h2\u003e \u003cp\u003eProbabilistic sensitivity analysis (5,000 Monte Carlo simulations) assessed the joint impact of parameter uncertainty on incremental costs, incremental effects, and cost-effectiveness. Most simulations indicated improved donor retention with only a small increase in cost. At the predefined willingness-to-pay threshold of \u0026yen;50 per additional donor retained, 72% of simulations yielded a positive net monetary benefit, indicating that cold spray was likely to be cost-effective under the base-case assumptions. The probability of cost-effectiveness increased with higher willingness-to-pay thresholds, reaching approximately 58% at \u0026yen;40, 72% at \u0026yen;50, and 85% at \u0026yen;60 per additional donor retained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eScenario analyses\u003c/h2\u003e \u003cp\u003eScenario analyses examined whether base-case conclusions were sensitive to plausible combinations of effect and cost assumptions. In an optimistic scenario, we assumed a stronger anxiety-to-willingness association (β₁ = \u0026minus;0.42) together with lower unit consumable cost (\u0026yen;2.20 per application). In a conservative scenario, we assumed a weaker anxiety-to-willingness association (β₁ = \u0026minus;0.20), higher unit consumable cost (\u0026yen;3.00 per application), and a 10% reduction in the 12-month repeat donation relative risk to reflect higher mobility in young donors. We also evaluated a high-effect scenario in which the 12-month behavioural relative effect was set to RR\u0026thinsp;=\u0026thinsp;3.54, corresponding to the effect magnitude reported for a topical anaesthetic intervention in a domestic study; this scenario was intended as an upper-bound check rather than a directly comparable effectiveness estimate.\u003c/p\u003e \u003cp\u003eAcross scenarios, the ICER ranged from \u0026yen;18.75 to \u0026yen;56.25 per additional donor retained at 12 months (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Under optimistic assumptions, the ICER decreased to \u0026yen;25.00 and the probability of cost-effectiveness at WTP=\u0026yen;50 increased to 91%. Under conservative assumptions, the ICER increased to \u0026yen;56.25 and the probability of cost-effectiveness at WTP=\u0026yen;50 decreased to 48%; at a higher WTP of \u0026yen;60, the probability of cost-effectiveness increased to 65% in this scenario.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eScenario analysis results (1,000-person cohort)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKey parameter adjustments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICER (\u0026yen; per additional donor retained)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability cost-effective at WTP=\u0026yen;50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNMB at WTP=\u0026yen;50 (\u0026yen; per 1,000 donors)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptimistic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ₁ = \u0026minus;0.42; consumables \u0026yen;2.20/person\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase case\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ₁ = \u0026minus;0.28; consumables \u0026yen;2.60/person\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConservative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ₁ = \u0026minus;0.20; consumables \u0026yen;3.00/person; RR reduced by 10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-effect (upper-bound)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRR set to 3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: β₁ is the anxiety-to-willingness pathway coefficient used in the behavioural translation step. RR denotes the relative effect on 12-month repeat donation applied in the intervention arm (Supplementary Methods S1).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eExpected value of partial perfect information\u003c/h2\u003e \u003cp\u003eThe expected value of partial perfect information analysis quantified the value of reducing uncertainty in key parameters at the willingness-to-pay threshold of \u0026yen;50 per additional donor retained (reported per 1,000 donors). Results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.Uncertainty in β₁ (the anxiety-to-willingness pathway coefficient) had the highest EVPPI at \u0026yen;3,200 per 1,000 donors, followed by the 12-month repeat donation relative risk (\u0026yen;1,800 per 1,000 donors), the analgesic efficacy equivalence parameter (\u0026yen;1,200 per 1,000 donors), and the unit consumable cost (\u0026yen;800 per 1,000 donors). The sum of EVPPI values across these parameters was \u0026yen;7,000 per 1,000 donors, indicating that most decision uncertainty was attributable to behavioural translation and the magnitude of the 12-month relative effect.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEVPPI results at WTP=\u0026yen;50 (per 1,000 donors)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEVPPI (\u0026yen;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShare of total EVPPI (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ₁ (anxiety-to-willingness coefficient)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR (12-month repeat donation relative risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalgesic efficacy equivalence parameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnit consumable cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7,000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eKey findings and implications for blood-centre decisions\u003c/h2\u003e \u003cp\u003eIn this model-based economic evaluation, cold spray was estimated to increase 12-month retention among first-time whole-blood donors aged 18\u0026ndash;25 years from 19.2% to 27.2%, corresponding to an absolute increase of 8.0 percentage points (80 additional donors retained per 1,000 donors). The incremental cost of implementation was \u0026yen;3.50 per donor. At a willingness-to-pay threshold of \u0026yen;50 per additional donor retained, the base-case ICER was \u0026yen;43.75 and the probability of cost-effectiveness was 72%.\u003c/p\u003e \u003cp\u003eThese results suggest that a low-cost, workflow-compatible pain and anxiety intervention can be economically attractive to blood centres when the primary objective is improving repeat donation within the first year. The estimated incremental cost is small relative to the scale of donor recruitment and donor engagement activities in Chinese blood centres. For example, Guangzhou Blood Center\u0026rsquo;s 2025 departmental budget includes dedicated allocations for voluntary blood donation publicity/activities and donor supplies, indicating that resources are routinely committed to sustaining participation in voluntary donation (Commission, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo further contextualise the willingness-to-pay (WTP) threshold used in this study, we analysed publicly available budget reports from 23 provincial and prefecture-level blood centres nationwide. Across reports published between 2023 and 2026, the estimated cost of recruiting a new donor typically ranged from approximately \u0026yen;140 to \u0026yen;195 per person (mean \u0026yen;163.8; median \u0026yen;165; interquartile range [IQR] \u0026yen;145\u0026ndash;175). Because retaining an existing donor may avoid part of the cost of recruiting a new donor, these estimates were used as an operational benchmark rather than as a formal societal willingness-to-pay threshold. Detailed centre-level estimates of recruitment costs are summarised in Supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e. Compared with the estimated mean recruitment cost of \u0026yen;163.8 per donor, the ICER of \u0026yen;43.75 per additional donor retained suggests that improving donor retention through pain reduction may represent a substantially more cost-efficient strategy than repeated donor recruitment.\u003c/p\u003e \u003cp\u003eUncertainty analyses clarify what drives decision risk. The one-way sensitivity and EVPPI analyses indicate that the anxiety-to-willingness pathway coefficient (β₁) and the magnitude of the translated 12-month behavioural effect are the dominant sources of decision uncertainty. This means that the economic conclusion depends more on how strongly anxiety reduction translates into repeat donation behaviour in young Chinese donors than on labour time or training costs. In practical terms, if blood centres consider implementation in settings with high mobility or weaker behavioural conversion, they may prefer phased roll-out with routine monitoring of 12-month return rates to reduce local decision uncertainty.\u003c/p\u003e \u003cp\u003eCold spray may also compare favourably with topical anaesthetic creams in settings where pre-application time is operationally difficult. Topical lidocaine\u0026ndash;prilocaine cream protocols typically require a pre-application period before venipuncture (Riendeau et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), which can increase staff coordination burden in high-throughput settings. In our costing framework, the incremental cost for cold spray is driven mainly by the unit consumable cost, and sensitivity analyses show that procurement price is the most actionable cost lever for improving cost-effectiveness.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eStrengths, limitations, and interpretation\u003c/h2\u003e \u003cp\u003eThis study has several strengths for health service decision-making. First, it combines locally observed attrition patterns in young first-time donors with a blood-centre costing framework based on time-driven activity-based costing. This aligns the economic endpoint with practical annual budgeting decisions for consumables, staffing, and donor engagement activities. Second, uncertainty was assessed using complementary approaches (one-way sensitivity analysis, probabilistic sensitivity analysis, scenario analyses, and value-of-information analysis), which helps decision makers understand not only the expected ICER but also the likelihood of cost-effectiveness at plausible willingness-to-pay thresholds.\u003c/p\u003e \u003cp\u003eThe main limitation is that the estimated 12-month behavioural effect is model-derived. The clinical study underpinning the intervention effect provides robust evidence for short-term reductions in pain and anxiety and increased short-term willingness to donate again (Zubing et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), but does not directly measure 12-month repeat donation. As a result, the translation from short-term psychological outcomes to medium-term donation behaviour relies on behavioural assumptions and transportability parameters. Although this bridging framework is grounded in established donor retention evidence linking anxiety and needle pain to subsequent donation behaviour (France et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and in first-time donor retention intervention research (Bagot et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), the magnitude of the behavioural translation remains the dominant source of decision uncertainty, as shown by the one-way sensitivity and EVPPI results.\u003c/p\u003e \u003cp\u003eA second limitation concerns generalisability of costs. TDABC inputs were derived from three provincial blood centres and are intended to reflect typical operational conditions, but procurement prices, staffing structures, and training practices may vary by centre and over time. The scenario analyses partly address this by varying consumable costs and behavioural translation assumptions, but site-specific implementation decisions should consider local procurement contracts and workflow constraints.\u003c/p\u003e \u003cp\u003eFinally, although vapocoolant sprays have randomised evidence for reducing venipuncture pain in blood donors (Basak et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and other adult venipuncture settings (Mace, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), future research that directly links cold spray to 12-month repeat donation in young Chinese first-time donors would substantially strengthen the evidence base. The EVPPI results suggest that studies designed to estimate the anxiety-to-willingness relationship and the 12-month relative effect in the local context would yield the largest reduction in decision uncertainty.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eComparison with previous studies\u003c/h2\u003e \u003cp\u003eMost evidence on pain and anxiety management in blood donation focuses on short-term outcomes such as puncture pain, donation-related anxiety, satisfaction, and near-term willingness to donate again. The multicentre Chinese trial underpinning the present evaluation fits within this literature by demonstrating reductions in pain and anxiety and increased willingness within 7 days after the index donation (Zubing et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Our contribution is to extend these short-term endpoints to a decision-relevant window for blood-centre planning by estimating their likely implications for repeat donation within 12 months.\u003c/p\u003e \u003cp\u003eTopical anaesthetic creams (e.g., lidocaine\u0026ndash;prilocaine) have been evaluated in venipuncture studies and require a pre-application period (Riendeau et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), which can make implementation more challenging in high-throughput settings. In contrast, vapocoolant sprays can be applied immediately before venipuncture and have randomised evidence for reducing venipuncture pain in donor and non-donor settings (Basak et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mace, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The present analysis therefore addresses not only whether pain/anxiety reduction is achievable, but whether a workflow-compatible approach can represent good value for money when assessed from a blood-centre perspective.\u003c/p\u003e \u003cp\u003eThis study also differs from much of the existing donor-intervention literature by combining local patterns of attrition with local costing. Rather than extrapolating long-term donor behaviour far beyond available data, we focused on the first year after the index donation and used locally derived inputs for attrition and costs. This helps align the economic endpoint with annual budgeting decisions and reduces reliance on long-horizon assumptions.\u003c/p\u003e \u003cp\u003eWhen comparing across interventions, effect measures are not always directly comparable. Published studies may use different behavioural endpoints (e.g., short-term willingness, early repeat donation, or longer-term retention) and different follow-up windows. In our scenario analyses, we therefore treated large relative effects drawn from other interventions as upper-bound checks rather than as head-to-head comparative effectiveness evidence. Direct comparative studies that measure the same behavioural endpoint over the same time horizon would be required to make definitive comparisons between cold spray and alternative pain-management strategies.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eFuture research priorities\u003c/h2\u003e \u003cp\u003eThe central evidence gap is the absence of direct estimates of the effect of cold spray on repeat donation within 12 months in young first-time donors in China. Pragmatic evaluations embedded in routine blood-centre operations could address this gap by using blood-centre information systems to measure repeat donation as the primary endpoint, while also capturing short-term pain and anxiety to test the proposed behavioural pathway.\u003c/p\u003e \u003cp\u003eA second priority is to reduce uncertainty in behavioural translation parameters in the local context. In this analysis, decision uncertainty was driven largely by the anxiety-to-willingness coefficient and the magnitude of the translated 12-month behavioural effect. Prospective multicentre cohort studies in China could directly estimate these pathway coefficients in young donors and quantify how they vary with donor characteristics and context.\u003c/p\u003e \u003cp\u003eCosts and operational constraints also vary across centres. Future work could expand TDABC data collection to a larger set of blood centres to characterise regional variation in procurement prices and staffing costs (Kaplan \u0026amp; Anderson, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Budget impact analyses would further support decision-making by translating per-donor incremental costs and effects into annual financial implications for blood centres of different sizes (Mauskopf et al., 2007).\u003c/p\u003e \u003cp\u003eFinally, combined strategies may be worth evaluating. Pain and anxiety reduction addresses one component of early lapse, but other barriers such as forgetfulness and mobility may still limit return. Interventions that pair cold spray with low-cost reminder systems (e.g., SMS or messaging-app prompts) could be assessed for additive effects on 12-month retention in the same decision-analytic framework (Ou-Yang et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003ePractical considerations for implementation\u003c/h2\u003e \u003cp\u003eIf blood centres consider adopting cold spray, the intervention is most plausibly targeted to settings with high volumes of young first-time donors, where improving the initial donation experience may translate into higher repeat donation during the first year. Because cost-effectiveness was most sensitive to behavioural translation and unit consumable cost, implementation decisions should prioritise reliable application procedures and procurement strategies that maintain a low per-donor consumable price.\u003c/p\u003e \u003cp\u003eRoutine monitoring can reduce local decision uncertainty. A practical approach is to track repeat donation at 12 months for first-time donors, alongside brief measures of pain and anxiety recorded at the index donation. Linking these measures to repeat donation outcomes would allow centres to assess whether the expected behavioural conversion holds locally and to refine targeting (for example, focusing on donors with higher baseline anxiety), given evidence that anxiety and needle pain are associated with lower subsequent donation behaviour (France et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eCold spray was estimated to increase 12-month repeat donation among young first-time donors at a small incremental cost, with an ICER below the prespecified willingness-to-pay threshold in the base case and a 72% probability of cost-effectiveness at \u0026yen;50 per additional donor retained. Because the 12-month behavioural effect is model-derived from short-term trial outcomes, future work that directly measures 12-month repeat donation in the local context would strengthen the evidence base and reduce decision uncertainty.\u003c/p\u003e"},{"header":"Abbreviation","content":"\u003cp\u003e\u003cstrong\u003eARD\u003c/strong\u003e absolute risk difference\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBDAS\u0026nbsp;\u003c/strong\u003eblood donation anxiety scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCEAC\u003c/strong\u003e cost-effectiveness acceptability curve\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCHEERS\u003c/strong\u003e Consolidated Health Economic Evaluation Reporting Standards\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCMA\u003c/strong\u003e causal mediation analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCNLS\u003c/strong\u003e constrained non-linear least squares\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCrI\u0026nbsp;\u003c/strong\u003ecredible interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e￥\u003c/strong\u003e Chinese yuan (ISO currency code; often used interchangeably with RMB)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEVPPI\u003c/strong\u003e expected value of partial perfect information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGDP\u003c/strong\u003e gross domestic product\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICER\u003c/strong\u003e incremental cost-effectiveness ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eISPOR\u003c/strong\u003e International Society for Pharmacoeconomics and Outcomes Research\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eISPOR-SMDM\u0026nbsp;\u003c/strong\u003eInternational Society for Pharmacoeconomics and Outcomes Research/Society for Medical Decision Making\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLTV\u003c/strong\u003e lifetime value (donor lifetime value)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMAE\u003c/strong\u003e mean absolute error\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNMB\u003c/strong\u003e net monetary benefit\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNNT\u003c/strong\u003e number needed to treat\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u0026nbsp;\u003c/strong\u003eodds ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOWS\u003c/strong\u003eA one-way sensitivity analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePSA\u003c/strong\u003e probabilistic sensitivity analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQALY\u003c/strong\u003e quality-adjusted life-year\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRCT\u003c/strong\u003e randomised controlled trial\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eREDS\u003c/strong\u003e Retrovirus Epidemiology Donor Study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRMB\u003c/strong\u003e Renminbi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRMSE\u003c/strong\u003e root mean square error\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRR\u003c/strong\u003e relative risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRSM\u0026nbsp;\u003c/strong\u003eresponse surface methodology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRSMB\u0026nbsp;\u003c/strong\u003eresponse surface mechanism bridging (model)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e standard deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSMS\u003c/strong\u003e short message service\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTDABC\u003c/strong\u003e time-driven activity-based costing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTPB\u003c/strong\u003e theory of planned behaviour\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUI\u003c/strong\u003e uncertainty interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVAS\u0026nbsp;\u003c/strong\u003evisual analogue scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWTP\u003c/strong\u003e willingness-to-pay\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study was a model-based health economic evaluation using previously published literature and aggregated operational cost data. It did not involve direct enrolment of human participants, identifiable personal data, or animal experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable. This manuscript does not contain personal data of the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets and analytical materials supporting the conclusions of this article are included within the article and its additional files. The full machine-readable parameter table is provided as Additional file 2, and the analytical code used to generate the main economic outputs is provided as Additional file 3. Supplementary methodological details are provided in Additional file 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZZ is employed by\u0026nbsp;Chengdu Yiping medicine science and technology development co., ltd. Other authors declare that they have no conflicts of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLL and LZ contributed equally to this work as co-first authors.LL, LZ, and SL conceived the study. LL, LZ, ZZ, QZ, and SL contributed to study design, model development, interpretation of results, and manuscript revision. SL drafted the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003cbr\u003e\u003c/strong\u003eThe authors used artificial intelligence–assisted tools to support literature organization, structured data extraction, and code drafting during manuscript preparation. All extracted data, analytic assumptions, code, and narrative content were subsequently reviewed, verified, and approved by the authors, who take full responsibility for the accuracy, integrity, and originality of the work. No additional acknowledgements apply.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBagot, K. L., Murray, A. L., \u0026amp; Masser, B. M. (2016). How Can We Improve Retention of the First-Time Donor? 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Meta-Analysis of The Determinants and Prevalence of Recruitment in Blood Donors among Chinese Population. \u003cem\u003eJournal of Evidence-Based Medicine\u003c/em\u003e,\u003cem\u003e\u0026nbsp;17\u003c/em\u003e(4), 232-238. https://doi.org/10.12019/j.issn.1671-5144.2017.04.012\u003c/li\u003e\n \u003cli\u003eZubing, Z., Song, P. U., Xiaoping, C., Jie, L. I., Qingsong, Z., Lina, Z., \u0026amp; Jianbo, W. E. N. (2025). Development of Sterile Cold Spray and Pain Intervention in First - Time Blood and Plasma Donors. \u003cem\u003eChina Medical Devices\u003c/em\u003e,\u003cem\u003e\u0026nbsp;40\u003c/em\u003e(7), 27-32. https://doi.org/10.3969/j.issn.1674-1633.20241756\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"blood donation, donor retention, cost-effectiveness, Markov model, time-driven activity-based costing","lastPublishedDoi":"10.21203/rs.3.rs-9074179/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9074179/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo estimate the cost-effectiveness of sterile cold spray for improving 12-month repeat donation among first-time whole blood donors aged 18\u0026ndash;25 years in mainland China from a blood-centre perspective.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003e We developed a 12-month Markov model from a blood-centre perspective comparing a sterile vapocoolant spray (cold spray) with standard care in first-time whole-blood donors aged 18\u0026ndash;25 years in mainland China. Trial-based short-term changes in pain (VAS) and anxiety (BDAS) were translated to 12-month repeat donation using a Theory of Planned Behaviour pathway with a calibration parameter informed by domestic retention data. Incremental costs (consumables, staff time, and training) were estimated using time-driven activity-based costing from three blood centres (2023\u0026ndash;2024). Uncertainty was assessed using one-way sensitivity analysis and probabilistic sensitivity analysis (5,000 simulations). No patients or members of the public, including blood donors, were involved in the design, conduct, or reporting of this model-based cost-effectiveness analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCold spray is estimated to improve first-time donor experience and is likely to be cost-effective for improving 12-month donor retention under commonly used blood-centre willingness-to-pay thresholds in China.\u003c/p\u003e","manuscriptTitle":"Cost-Effectiveness of Sterile Cold Spray in Enhancing 12-Month Retention Rates Among First-Time Blood Donors: A Decision-Making Model Study for Blood Centres Based on Causal Mediation Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 08:27:39","doi":"10.21203/rs.3.rs-9074179/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-03T18:26:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T13:23:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T10:25:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79466982637975430433098058801572304077","date":"2026-04-24T10:07:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328241864897387885349836822627900410641","date":"2026-04-23T08:40:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206010122498329070521042814201552743353","date":"2026-04-20T19:17:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283789139659300527898610733675826253328","date":"2026-04-20T10:06:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T07:57:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-18T18:36:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-17T02:43:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-17T02:43:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2026-03-09T14:19:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10d4a9f7-4995-42b4-aa9e-fd1f439c9571","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-03T18:26:55+00:00","index":80,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T13:23:43+00:00","index":79,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T10:25:15+00:00","index":78,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:27:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 08:27:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9074179","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9074179","identity":"rs-9074179","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}