Cost of living is one of the key factors in residency selection among U.S. medical graduates, given rising student loan debt. No studies have investigated anesthesiology stipends relative to regional cost of living. This study aimed to compare anesthesiology resident stipends nationwide using the Cost-of-Living Index (COLI) to assess purchasing power. The AAMC directory was queried to obtain accredited anesthesiology residency programs for the 2024-2025 academic year. CA1 (post graduate year 2) stipends were collected via internet search and residency programs were assigned to metro areas using region specific COLI metrics. City, state, geographic region, and reputation ranking were recorded and absolute and relative discrepancies were calculated. Of 174 anesthesiology residency programs, 118 (67.8%) were analyzed. The national average CA-1 stipend was $70,757 ± $9,718, with medians of $66,137 in low COLI areas and $74,046 in high COLI areas (median difference $7,909, [95% CI $5,969-$12,728, p < 0.001]. California showed the largest adjusted deficit (-$26,969, -30.98%), whereas Oklahoma had a $13,096 surplus (+ 21.00%). In the 10 major cities, average stipends decreased from $76,052 ± $10,860 to $59,499 ± $11,252 after COLI adjustment (-21.8%, p < 0.001). The absolute discrepancy between small and medium programs was not significant (-$3,498, p = 0.19), while large programs faced a 12.82% shortfall ($9,742) despite higher unadjusted salaries. Among the top 12 programs based on reputation ranking, stipends were higher in high COLI regions with half showing > 30% loss after COLI adjustment. Anesthesiology residency stipends showed substantial variation after adjusting for regional cost of living, with many high COLI areas experiencing marked reductions in real purchasing power.Given rising educational debt, applicants should consider COLI adjusted stipends when evaluating programs to better assess regional affordability and financial impact. N/A.

Abstract Lowering a borrower's interest rate is one of the most effective ways to reduce a borrower's debt burden. Mortgage refinancing offers a chance to shift debt balances from high‐interest loans into a low‐interest mortgage through “cashing out” some of the home's equity. Using anonymized data on mortgage refinancing behavior, we find that over half of borrowers with high‐interest loans and available home equity do not take advantage of their cash‐out opportunities. While the cash‐out “surcharge” can rationalize this pattern, we leverage a policy change at Fannie Mae that eliminated this surcharge for student‐loan borrowers and find that the presence of a student loan does not significantly affect borrowers' propensity to cash out.

Recent federal student loan reforms proposed under the One Big Beautiful Bill Act (OBBBA) would redefine “professional degree programs” for purposes of federal borrowing limits, excluding Master of Social Work (MSW) and Doctor of Social Work (DSW) degrees from eligibility for higher loan caps. This policy analysis examines the potential consequences of reclassifying social work degrees as non-professional, with particular attention to educational access, workforce sustainability, and equity. Guided by a normative, advocacy-oriented evaluative framework and an ecological lens, the analysis draws on federal rulemaking documents, workforce projections, accreditation standards, and existing research on student debt and enrollment behavior. Findings suggest that reduced federal loan access may suppress MSW and DSW enrollment, disproportionately affect first-generation, low-income, and BIPOC students, and exacerbate behavioral health workforce shortages. The analysis concludes that the proposed reclassification risks undermining both social work education infrastructure and community well-being, and it offers policy-relevant considerations to better align loan reform with workforce and equity priorities.

Bursaries are an integral component of WP strategies within UK Higher Education. Therefore, it is imperative that they succeed in accomplishing their goal; even more so at a time where UK students are increasingly struggling financially. While the (light) evidence suggests bursaries can help students from lower-income families ‘get on’ at university in the same way as their more affluent peers, there is a lack of research on how ‘place’ affects bursary effectiveness; this study aims to fill that gap. We compare student survey data and education and employment outcomes using two very different Russell Group universities as case studies to better understand how bursary delivery context affects the bursary’s effectiveness. While bursaries provided a substitute for earned income or family resources in both universities, our analysis also showed that bursary holders differed significantly from non-holders in only one of the two case study universities in other areas, such as perceptions of financial position and post-university outcomes. The findings show that bursaries work, albeit to different extents in different places, confirming a spatial element to bursary provision. The characteristics of the cohort overall may alter the way in which bursaries are perceived. Finally, we consider how the results are impacted by changing student finances since our surveys.

Coerced debt is an important but understudied form of intimate partner violence. It occurs when abusive partners use fraud, coercion, or manipulation to incur debt in their partners' names. For the current study, we sampled 187 women who had recently divorced an abusive husband and their combined 2,833 credit accounts to answer the questions: (1) On what types of credit accounts and using what types of transactions (i.e., fraud, coercion, and manipulation) did ex-husbands create coerced debt in their partners' names? (2) How much money was spent and what items were purchased? and (3) What reasons did ex-husbands give for pressuring participants to open accounts in their names that resulted in coerced debt? We collected data via an online survey and telephone interview. We analyzed quantitative data with descriptive statistics and responses to open-ended questions with inductive thematic analysis. The findings indicated that coerced debt is a common and expensive problem with a wide variety of presentations. The 116 participants with coerced debt had a mean of 4.4 and a maximum of 24 such debts and owed a combined total of over 12.5 million dollars. The most common types of accounts with coerced debt were credit cards, vehicle loans, mortgages, personal loans, and student loans. Coercive transactions were much more common than debt created by fraudulent transactions. Coerced debt was used for basic necessities, lifestyle purchases, transportation, the ex-husbands' personal interests, financial needs and obligations, and other household members' needs. The most common reason ex-husbands gave for putting accounts in their partners' names was personal resource adequacy. This study indicates the need for future research on the effects of coerced debt and the effectiveness of interventions to address it; screening tools and practices for use in direct service settings; and laws that address debt created by coercive transactions.

Student Loan Debt and Higher Education Disruptions During COVID-19

The rising deployment of artificial intelligence in public services is constrained by computational costs and limited domain-specific data, particularly in multilingual contexts. This study proposes a generalizable Agentic AI pipeline for developing question–answer chatbot systems using small language models (SLMs), demonstrated through a case study on the Thai Student Loan Fund (TSLF). The pipeline integrates four stages: OCR-based document digitization using Typhoon2-3B, agentic question–answer dataset construction via a clean–check–plan–generate (CCPG) workflow, parameter-efficient fine-tuning with QLoRA on Typhoon2-1B and Typhoon2-3B models, and retrieval-augmented generation (RAG) for source-grounded responses. Evaluation using BERTScore and CondBERT confirmed high semantic consistency (FBERT = 0.9807) and stylistic reliability (FBERT = 0.9839) of the generated QA corpus. Fine-tuning improved the 1B model’s domain alignment (FBERT: 0.8593 → 0.8641), while RAG integration further enhanced factual grounding (FBERT = 0.8707) and citation transparency. Cross-validation with GPT-5 and Gemini 2.5 Pro demonstrated dataset transferability and reliability. The results establish that Agentic AI combined with SLMs offers a cost-effective, interpretable, and scalable framework for automating bilingual advisory services in resource-constrained government and educational institutions.

This study provides a general review explores global trends in of behavioural, economic, and psychosocial aspects of student loan repayment systems. It synthesizes empirical literature published between 2020 and 2025 from databases including Scopus, Web of Science, and Google Scholar. The review identifies six key themes: (1) rising interest in behavioural and psychosocial aspects of repayment; (2) financial self-efficacy and financial literacy have a strong influence on repayment outcomes, while minority groups suffer from disproportionate debt burdens; (3) income-driven repayment models effectively in reducing delinquency but are challenged by administrative complexity and unequal access; (4) psychological stress, financial strain, and low self-efficacy exacerbate repayment struggling, with structural barriers and pandemic shocks widen inequities; (5) targeted subsidies and need-based grants are more equitable than broad loan forgiveness, with a service-linked forgiveness enhancing workforce outcomes; and (6) policy innovations such as behavioural nudges, risk-sharing mechanisms, and streamlined administration can enhance sustainability and equity of repayment. This study offers a multifaceted synthesis that incorporates behavioural, financial, and policy perspectives worldwide with a focus on underrepresented regions and psychological aspects. As policy implication, the study highlights the importance of integrated behavioural interventions, simplified repayment structures, and culturally sensitive policies to promote the sustainability of repayments and wellbeing of borrowers.

ABSTRACT We exploit an episode of plausibly random debt discharge due to the loss of paperwork for thousands of defaulted borrowers to examine the effects of private student debt relief on borrower outcomes. We find that borrowers who receive debt relief (treated) experience declines in debt balances and delinquency rates on other accounts, and increases in mobility and income relative to those who bear the costs of default like wage garnishment and collections (control). Borrowers in both groups contribute to our findings through different mechanisms. While our estimates may not directly apply to blanket student loan forgiveness, they speak to the benefits of forgiveness in reducing the consequences of debt burden for distressed borrowers.

ABSTRACT This article analyzed the impact of a Colombian subsidized student loan program, ACCES, on the dropout and completion hazard rates of socioeconomically disadvantaged undergraduate students. Using administrative data and considering the selection and the dynamic nature of loan assignment, we estimate the policy’s average treatment effect. The program successfully prevented dropouts among socially vulnerable students during the peak attrition periods in the Colombian higher education system. Also, it promoted the completion of studies with a relatively short delay. Nevertheless, support for low socioeconomic students’ persistence until graduation requires more than just financial aid; comprehensive support is crucial for their success.

Fewer cards, less credit: The role of student loans in credit access, generally and among racial and ethnic groups

Research methodology This case was developed using secondary sources, including online news outlets, academic databases and academic textbooks. Case overview/synopsis In early 2025, amid sweeping federal policy changes under President Trump’s second term, Melanie Storey, the newly appointed President and Chief Executive of the National Association of student Financial Aid Administrators (NASFAA), faced a complex leadership challenge. The administration’s executive orders, including efforts to dismantle the U.S. Department of Education and transfer oversight of the $1.7 trillion student loan portfolio to the Small Business Administration, created uncertainty for millions of student loan borrowers and financial aid professionals. The resulting disruption, including widespread federal staff layoffs and technical failures in financial aid systems, intensified concerns about access to student loans and repayment options. As the leader of NASFAA, Storey had to navigate these turbulent changes while ensuring that her constituents had the guidance and resources needed to adapt. To succeed, she needed to apply change management principles to craft an effective multi-stakeholder communication strategy and highlight quick wins to maintain stakeholder confidence. This case challenges students to think strategically about how leaders can manage change amid uncertainty, engage stakeholders and build momentum for long-term solutions in a high-stakes policy environment. Complexity academic level This case is designed for upper-level undergraduate strategic communication students, particularly those in courses that dedicate time to leadership and change management communications. It should be taught after students have been introduced to concepts related to stakeholder theory and strategic communication planning so that they can integrate those foundational concepts in the activity and discussion.

This study aims to overcome the inefficiency and lack of structure in the manual academic system at the Ummi Lubuk Pakam Education Foundation (YP), particularly in the management of student data, finances, and registration. The approach used is the Rapid Application Development (RAD) method to build a responsive and integrated Academic Information System (SIA). The scope of development includes modules for student data, new student admissions, grades, and finances, implemented using the Laravel framework. The results of the study show the success of the developed system. The AIS has been proven to reduce data processing time by 62.1% compared to manual methods, demonstrating a significant increase in efficiency. In addition, the system achieved a data accuracy rate of 94.79%, validating the RAD method's ability to produce systems with minimal errors. In conclusion, the implementation of the RAD-based AIS has successfully improved the effectiveness, efficiency, and accuracy of academic operations at YP Ummi Lubuk Pakam.

This study evaulates trends in federal loan use among US medical students and how they may be affected by the One Big Beautiful Bill Act, which eliminated Graduate PLUS loans for medical students.

Using data from the 2021 National Financial Capability Study, this study examines the association between spousal student debt and the financial satisfaction of nonborrowing partners. While the literature has established that student debt is associated negatively with financial satisfaction, this study explicitly examines the financial satisfaction of individuals without student debt who have spouses with student debt. The findings suggest that nonborrowing spouses whose partners carry student debt report significantly lower financial satisfaction and greater financial insecurity compared with those whose partners have no student debt. These associations remain significant after adjusting for demographic and socioeconomic covariates. The results have implications for student loan holders, policymakers, and financial service professionals, specifically focusing on the use of active listening, reframing, and developing a shared financial language.

Educational banking plays a crucial role in supporting the academic aspirations of students by providing financial aid in the form of student loans. Bank of Baroda, being one of India’s leading public sector banks, offers a range of educational loan schemes to support higher education in India and abroad. This study leverages Machine Learning (ML) and Deep Learning (DL) techniques to analyze, evaluate, and forecast the performance and impact of educational banking services provided by Bank of Baroda. By applying intelligent data-driven approaches, this research aims to extract meaningful insights from loan approval data, repayment patterns, customer satisfaction surveys, and academic success linked to financial assistance. The system developed can assist in predictive analytics, default risk assessment, and policy enhancement, making educational finance more efficient and targeted.This study aims to explore and evaluate the role of Bank of Baroda in providing educational banking services, particularly focusing on educational loan schemes, student financing mechanisms, and the technological advancements that facilitate access to education financing. With the growing demand for higher education and the rising cost of academic programs, the need for structured and accessible financial support has become more critical than ever. Public sector banks like Bank of Baroda play a pivotal role in bridging the gap between students and educational opportunities through tailored financial products.The research examines how effectively Bank of Baroda addresses the financial needs of students through its educational loan offerings, interest rate structures, repayment flexibility, and digital processing of applications. It also investigates customer awareness, satisfaction, and challenges faced in the loan approval process. In addition, the study integrates Machine Learning (ML) and Data Analytics perspectives, where applicable, to demonstrate how predictive models could enhance credit assessment, reduce defaults, and improve loan disbursement efficiency.

The development of financial technology (fintech) has brought significant changes to people's transaction patterns, particularly among university students, with the increasing use of digital wallets. This phenomenon is influenced by various factors, including digital literacy, financial attitude, herd behavior, and these factors impact on financial well-being. Therefore, this study aims to construct a structural model of digital wallet usage and how it impacts the financial well-being of students. This research uses a quantitative approach with the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method to examine the relationships between variables. Data was collected through the distribution of questionnaires to students who actively use digital wallets. The results show that digital literacy has the largest total effect on financial well-being through two pathways: a direct influence and an indirect influence through the use of digital wallets. The total effect of digital literacy is high, making it the dominant predictor in the model. The research results show an R² value for the digital wallet usage variable of 0.508, which falls into the moderate category, while for the financial well-being variable it is 0.723, which falls into the high category. Digital literacy (LD) has established itself as the most fundamental determinant in the digital financial ecosystem. It serves not only as the primary driver of digital wallet (PDD) adoption by enhancing perceived usefulness and ease of use, consistent with the extended technology acceptance model, but also contributes directly and significantly to improving financial well-being (FWB) by facilitating access to financial information and products, aligning with the digital divide theory.

The primary theme of the study is to evaluate strategies to reduce student attrition of public and private universities in Sierra Leone. The specific objective of the study was to identify the strategies to reduce student attrition in Sierra Leonean universities. This study examined Spady's Theory of Student Departure (1971) as a theoretical framework. A descriptive research design was employed. Data collection instruments included a structured questionnaire, a structured interview guide, campus observations, and a documentary review. The target population included 459 students. Data analysis involved frequencies and percentages, cross-tabulations, and correlation and regression analyses, using SPSS, Excel, and Organisation Network Analysis (ONA) data collection tools from 1 March 2025 to 30 September 2025. A five-point Likert scale (1932) was used during data analysis. The validity and reliability of the instruments were tested at other universities in Sierra Leone using Cronbach's Alpha, which yielded a coefficient of 0.86, indicating good validity; 5% of the questionnaires were pretested at other institutions. The key findings of the study include, among others, that the majority of respondents were enrolled in public universities, most were male students,70% of respondents are in self-employment, 85% are single, 66% consider student attrition a very significant issue in Sierra Leonean universities. The study would help the Government of Sierra Leone increase the grants-in-aid quota, fast-track undergraduate student loan schemes, and introduce stipends/allowances at universities. Future research should focus on all public and private universities, polytechnics, and Teachers Training Colleges in Sierra Leone.

Abstract We analyse whether financing higher education through student loans or grants affects the college major choices of students in Chile where either type of financing is allocated based on a standardised test. Students who are marginally eligible for grants are more likely to enrol in high-paying fields such as STEM. Complementing the reduced form results, we estimate a discrete choice model on data for narrowly defined higher education programmes. The results indicate that, holding other programme characteristics constant, grant recipients place higher value on fields with high earnings growth potential, while being less concerned about a lower graduation probability.

Academic Practice with Extramural Faculty Private Practice.