Promise Tewogbola

Persistent poor performance in mathematics among Nigerian secondary school students has contributed to increasing reliance on supplementary paid tutoring. While previous studies have examined factors associated with mathematics achievement, little is known about students' willingness to participate in supplementary tutoring when time commitment is considered as a behavioral cost. This study applied a behavioral economics framework to examine secondary school students' willingness to participate in paid mathematics tutoring and to quantify the amount of weekly tutoring time they were willing to commit. A cross-sectional survey was conducted among 62 secondary school students in Ibadan, Oyo State, Nigeria. A modified Hypothetical Purchase Task (HPT) was used to assess willingness across 16 hypothetical tutoring durations ranging from 0 to 15 hours per week (P0 to P15), assuming that parents or guardians covered the financial cost of tutoring. Demand curves were generated from the proportion of students willing to participate at each time-cost level. Generalized linear mixed-effects models were used to examine the effects of tutoring duration, gender, and educational level on willingness. Willingness was highest at lower time commitments, with 95.2% of students willing to participate at one hour per week. Demand declined progressively as tutoring duration increased, with willingness at 50% between 7 and 8 hours. The mixed-effects model showed that increasing tutoring duration significantly reduced willingness to participate (β =-0.329, p < .001). Gender was not significantly associated with willingness (p = .308), whereas senior secondary school students demonstrated significantly greater willingness than junior secondary school students (β = 0.83, p = .031). Time commitment is an important behavioral constraint influencing demand for supplementary mathematics tutoring. Behavioral economic approaches, such as the Hypothetical Purchase Task, provide a useful framework for understanding educational decision-making and may help inform the design of tutoring programmes that maximize student participation.

Background: Northern and central Nigeria face repeated violence linked to insurgency, farmer-herder conflict, banditry, and sectarian tensions. Debate has grown over whether U.S. military assistance could reduce insecurity, but less is known about how Nigerians evaluate such assistance when success is uncertain. Objective: This mixed-methods study examined how Nigerian support for U.S. military intervention changes as likelihood of success decreases and how participants explain conditional support or opposition. Methods: Study 1 adapted a Hypothetical Purchase Task with 106 Nigerian participants who indicated support across ten likelihoods of successful suppression of regional violence. Exponential demand curves were fit to pooled responses, and subgroups were analyzed. Study 2 used semi-structured interviews with 12 survey participants to interpret those response patterns. Results: About 35% of respondents gave categorical responses, either supporting or rejecting intervention at every likelihood level, while most shifted as success became less certain. The aggregate model showed moderate descriptive fit (R^2 = 0.62), with Qo = 61.85 and α = 1.55 × 10^-4. The model predicted 50% support at about 17% likelihood of successful suppression. Subgroup patterns varied by age, gender, residence, institutional trust, and religiosity. Interviews showed that participants weighed U.S. intervention against institutional distrust, sovereignty and harm concerns, competing explanations of violence, military alternatives, and broader non-military responses. Conclusions: Support for U.S. military intervention was conditional rather than fixed. It depended on expected effectiveness and was shaped by trust, proximity to violence, and beliefs about insecurity. External assistance may be more acceptable when Nigerian-led, transparent, limited in scope, and tied to clear goals.

This study investigated how delays and uncertainties shape the perceived value of hypothetical HIV vaccines under different cost conditions among sexual and gender minorities (SGMs). In Experiment 1 ( N = 260), participants chose between a 60% effective vaccine available immediately and a 99% effective vaccine with varying delays. Experiment 2 ( N = 246) assessed choices between a 55% effective vaccine with certain availability and a 95% effective vaccine with uncertain availability. Participants were randomly assigned to free or $150 fee conditions. Hyperbolic discounting models effectively described delay ( R² = 0.96–0.99) and probability discounting ( R² = 0.95–0.99). Vaccine cost did not significantly affect discounting, while age and STI testing history did, with effects varying by delay versus probability context. Gay or bisexual identity, health insurance status, and political orientation additionally predicted probability discounting. The findings demonstrate the utility of behavioral economic models for quantifying HIV vaccine valuation prior to market availability.

Health insurance coverage remains critically low in developing economies, with Nigeria’s National Health Insurance Scheme covering only 5% of the population. Understanding consumer demand patterns is essential for designing effective insurance policies, yet limited research has applied behavioral economic frameworks to health insurance decision-making in developing contexts. This mixed-methods study investigated factors influencing health insurance demand in Nigeria using behavioral economic principles, examining the effects of market structure (open vs. closed economy), demographic characteristics, and price sensitivity patterns on insurance purchasing decisions. Study 1 employed a hypothetical purchase task with 76 Nigerian participants randomly assigned to open- or closed-economy conditions, measuring willingness to purchase health insurance at 15 price points (₦5–₦560000). Exponential demand curves were fitted using a modified exponential demand model to assess demand intensity ( Q ₀ ) and price sensitivity ( α ). Study 2 involved focus group discussions with 5 participants who completed the purchase task, exploring decision-making processes through thematic analysis. The exponential demand model demonstrated strong predictive validity (median R ² = 0.87, IQR = 0.81–0.92) across demographic subgroups. Contrary to theoretical expectations, no significant differences emerged between open and closed economy conditions ( p > 0.05). Age, income, gender, and current insurance status were significantly associated with demand parameters. Younger participants showed higher demand intensity but greater price sensitivity, while low-income participants demonstrated higher demand intensity ( Q ₀ = 91.37) than high-income participants ( Q ₀ = 74.29). Qualitative findings revealed “reverse price sensitivity,” where participants rejected very low-priced options due to quality concerns, and identified a potential pricing corridor of ₦3,000–₦17,500 ($2–$12 USD) balancing affordability with quality signaling. Behavioral economic models may effectively characterize health insurance demand patterns in Nigeria, revealing complex price-quality relationships that challenge traditional economic assumptions. The null finding for market structure effects suggests that existing healthcare alternatives and institutional distrust may override theoretical market distinctions. Results support targeted subsidies for younger and lower-income populations and highlight the importance of pricing strategies that signal quality while maintaining affordability.

This study was an investigation of the utility of behavioral economic demand curves (quantitative models showing how consumption changes with price) in assessing acceptance of hypothetical HIV vaccines among sexual and gender minorities (SGMs). Two experiments used simulated purchase tasks (hypothetical scenarios measuring purchasing decisions). SGMs were recruited through Reddit and LGBTQ+ community organizations across the United States. In Experiment 1, participants were randomly assigned to nine instructional sets combining varying vaccine administration modes (oral, mucosal, or subcutaneous) with different dosage schedules (one dose, two doses, or one dose annually). Experiment 2 examined how bundling HIV vaccines with one of nine health commodities affected demand. Participants also responded to questions assessing demographics, HIV risk behaviors, experiences of racial discrimination, and trust in institutions. The results demonstrated that the exponentiated demand equation effectively modeled vaccine acceptance across conditions (median R ² = 0.92). Contrary to expectations, vaccine characteristics had a minimal influence on demand (Q₀: R ² = 0.007; log α: R ² = 0.001). Instead, individual factors significantly influenced demand intensity (consumption when price = 0; Q₀) and price sensitivity (sensitivity of consumption to increasing price; α). Significant predictors of Q₀ included injection drug use history, experiences of racial discrimination, and trust in science. Low household income was the strongest predictor of log α. Bundling HIV vaccines with other health commodities showed subtle effects on acceptance, with condoms and dental examinations significantly differing from the reference category. These findings suggest that behavioral economic approaches can inform policy decisions about pricing, bundling strategies and targeted interventions to maximize HIV vaccine uptake among SGMs who face disproportionate HIV risk without requiring exposure to non‐market‐ready vaccines.

The development of effective vaccines remains crucial for controlling infectious diseases, with behavioral economics offering insights into vaccine acceptance patterns. This study aimed to understand demand for HIV vaccines currently in development, using behavioral economics, examining cross-cultural differences between Nigerian ( n = 119) and United States ( n = 63) participants. They responded to three behavioural economic tasks: a simulated COVID-19 Vaccine Purchase Task (CVPT), HIV Vaccine Purchase Task (HVPT), and the Monetary Probability Discounting Task (MPDT). Demand curves were fitted using an exponentiated model with both purchase tasks demonstrating excellent fit ( R ² = .98). Multiple regression analyses examined relationships between behavioral economic indices and demographic factors. Nigerian participants showed significantly higher price sensitivity for both COVID-19 ( β = −1.10, p < .001) and HIV vaccines ( β = 0.90, p = .001) compared to U.S. participants, while baseline demand intensity and risk tolerance were similar between countries. Monetary risk-taking behavior predicted HIV vaccine demand ( β = −1.10, p = .02), and higher socioeconomic status was associated with lower price sensitivity ( β = 1.09, p = .04). The study demonstrates the utility of behavioral economic frameworks in modeling vaccine demand across cultures, revealing cross-cultural differences in price sensitivity and the potential relationship between COVID-19 and future HIV vaccine acceptance. These findings may have important implications for developing targeted public health interventions and policy frameworks for vaccine distribution, particularly in lower-income populations, to ensure equitable access to future HIV vaccines.

This study investigated how delay and probability discounting impact the perceived value of hypothetical HIV vaccines under different monetary cost conditions. Using hypothetical purchase tasks, two experiments assessed how sexual and gender minorities (SGMs) made trade-offs between immediate versus delayed vaccine access and certain versus uncertain availability. In Experiment 1 ( N = 260), participants chose between a 60% effective vaccine available immediately and a 99% effective vaccine with varying delays. Experiment 2 ( N = 246) involved a choice between a 55% effective vaccine with certain availability and a 95% effective vaccine with uncertain availability. In both experiments, participants were randomly assigned to conditions where the vaccine was either free or available for a $150 fee. Hyperbolic discounting models effectively described delay ( R ² = 0.96 − 0.99) and probability discounting ( R ² = 0.95 − 0.99). While vaccine cost did not significantly affect discounting, individual characteristics emerged as significant predictors. Age ( β = 0.01, p < 0.05) and prior STI testing ( β = −0.19, p < 0.05) influenced delay discounting, while probability discounting was influenced by age ( β = 0.01, p < 0.05), identifying as gay or bisexual ( β = −0.15, p < 0.05), health insurance status ( β = 0.33, p < 0.05), prior STI testing ( β = 0.18, p < 0.05), and political liberalism ( β = −0.004, p = 0.05). This research is among the first to model HIV vaccine acceptance using behavioral economic methodology. When designing vaccine distribution programs, public health strategies may benefit from considering factors such as age, STI testing behaviors, health insurance, and political views. Future research should explore more vulnerable populations such as sex workers and people who inject drugs (PWIDs), and investigate how the perceived value of HIV vaccines may intersect with other health interventions.

Background: Despite empirical evidence supporting vaccine effectiveness, vaccine hesitancy continues to thrive. Demand as a behavioral economic process provides useful indices for evaluating vaccine acceptance likelihood in individuals and groups. Using this framework, our study investigates the dynamics governing vaccine acceptance in two culturally dissimilar countries. Methods: Hypothetical purchase tasks (HPTs) assessed how Nigerian and US participants varied vaccine acceptance as a function of hospitalization risks due to vaccination ( N = 109). Aggregate and individual demand indices ( Q ₀ and P _max ) were computed with nonlinear regressions. Secondary analyses were conducted using repeated measures ANOVAs with vaccine type (COVID-19 and HIV) as the within-subject factor; country, age, and socioeconomic status as between-subjects factors; demand indices served as dependent variables. Results: Demand indices varied significantly as a function of vaccine type ( F (1, 57) = 17.609, p < .001, ). Demand for HIV vaccines was higher relative to COVID19 vaccines. Interactions between vaccine type and country of origin ( F (1, 56) = 4.001, p = .05, ) were also significant with demand for HIV vaccines among Nigerian respondents higher than that of COVID-19 vaccines. This was reversed for US participants. Interactions between vaccine type, country of origin and age were also significant ( F (2, 51) = 3.506, p < .05, ). Conclusions: These findings provide evidence that vaccine type can influence demand. The relationship between demand and vaccine type also varies as a function of country of origin and age. Significance, limitations, and future directions are also discussed.