Enrollment Decisions Research Articles

The ethical inadequacy of uninformed surrogate consent: advancing respect for persons in clinical research.

In clinical research, decision-making capacity is often equated with unspecified conceptions of autonomy, and autonomy is often equated with personhood. On this view, the loss of decision-making capacity is seen as a loss of autonomy, and the loss of autonomy subsumes a loss of personhood. An ethical concern arises at the intersection of those philosophical considerations with the legal considerations in informed consent. Because persons with inadequate decision-making capacity cannot provide legally effective consent, enrollment in research can occur only if a surrogate gives permission on the person's behalf. Federal regulations and resulting institutional policies allow permission from surrogates empowered under state law to consent to medical treatment procedures, typically in a hierarchy of legislatively prioritized relationships lacking regard for what the surrogate actually knows about the current research-related values and preferences of the potential subject. As a result, the research enterprise often countenances reliance on surrogates who have no relational or informational basis for an enrollment decision that aligns with the values and preferences of the subject. Arguing from the perspective that losing decision-making capacity does not alter the moral status of persons, and that respect for persons rather than respect for autonomy is the central ethical obligation, I assess the ethical implications of allowing persons with no knowledge of the values and preferences of the potential subject to make enrollment decisions, concluding that reliance on uninformed surrogates is not an ethically defensible approach to enrolling subjects in clinical research.

Towards net zero: Comprehensive approach for voluntary carbon trading among microgrids

In the context of growing focus over climate changes and promoting sustainability across a various range of fields, microgrids can play a significant role in global decarbonization endeavors, contributing to carbon neutrality and ultimately attaining net-zero emissions in the energy sector. The objective of this paper is to address the integration of voluntary carbon trading within microgrid communities, in the perspective to mitigate greenhouse gas (GHG) emissions and boost the integration of renewable energy sources (RES). Introducing five modular algorithms managing key aspects of carbon trading, the study engineers a comprehensive framework aiming to optimally orchestrate the Voluntary Carbon Market (VCM) within microgrids. Particularly, the developed algorithms address aspects such as market enrollment decision, optimal energy dispatch, managing the market transactions, sellers-buyers matching as well as the dynamic adjustment of carbon credit prices and emission taxes. The framework has been rigorously tested across three distinct scenarios. Results show that the developed VCM, with adequate configurations, has the potential to incentivize microgrids to curtail their GHG emissions, encourage the integration of more RES into their generation mix, and rewards the more proactive microgrids with substantial financial incentives.

The impact of being named the top party school on peer rankings and the academic profile of a university

ABSTRACT We explore how being named the top party school by the Princeton Review affects the U.S. News and World Report ranking, the peer ranking of an academic institution, and the academic profile of the university. We find that ‘winning’ the title of top party school lowers both the overall ranking and the peer ranking at the school. Additionally, the academic quality of students enrolling at the institution decreases. Our results suggest that the publicity of being named the top party school enhances a school’s undesirable reputation, as measured by lowered rankings, and influences student enrolment decisions, particularly (and negatively) among top academic performing students.

STEM Enrollment Decision Trees as Graduation Predictors for Community College Students Enrolled in Remedial Mathematics

Objective/Research Question: Community college graduation rates are typically quite low, and developmental mathematics enrollment and coursetaking patterns may constrain academic outcomes. To identify ways in which community college graduation rates may be improved, decision trees were utilized to examine the STEM coursetaking patterns of N = 5,065 students who matriculated in remedial mathematics. Methods: The research design was guided by Tinto’s academic and social integration framework, which provided an analytical lens for identifying how decision trees facilitate academic decision making when academic and social integration is limited. Decision trees identified course sequence rules to predict graduation, which can be used to formulate course pathways for community college advisors and their students. Results: Nine rules from the decision tree were identified, which could be used to advise community college students in coursetaking that aligns with career aspirations. The most important variable predicting graduation was completing College-Level Mathematics, which included Algebra II, Statistics, Precalculus, and survey mathematics courses. General education sciences courses such as Astronomy, Geology, Environmental Science, and Marine Biology were the most important science courses predicting graduation. Conclusions/Contributions: Results suggest the importance of College-Level Mathematics in providing the skills necessary for students to be successful in subsequent STEM coursework and persist to graduation. Designating specific academic pathways may improve social and academic integration and graduation rates, providing continuity as students work with different advisors to choose majors and plan course sequences. Transparent, accessible enrollment planning fosters programmatic consistency and student agency in selecting coursework that will maximize their success.

How important is studying languages for undergraduate students and why (not) study languages?

AbstractThis study examines the value undergraduate students (n = 4458) place on proficiency in languages other than English (LOTEs) in terms of their personal interests, major(s), and career plans. Combining quantitative and qualitative analyses of large‐scale survey data, the study further explores the reasons students outline for (not) enrolling in LOTE courses and what would motivate them to enroll in language courses in the future. Results indicate that students attached most value in relation to personal interests, followed by career plans and major. In addition, students' demographics and prior experience with language can also impact their future enrollment decisions. The results suggest that not only should institutions lead the way by emphasizing the importance of learning languages, but also that language programs need to listen to students' voices and help them establish clear links between their academic majors, their future career and study plans as well as their personal interests.

Model for increasing interest in enrolling in private universities based on a segmentation, targeting, and market positioning strategy in Indonesia

This study aims to examine the factors that influence interest in enrolling in private colleges in the DKI Jakarta area, with a focus on how the Segmentation, Targeting, and Positioning (STP) strategies of these colleges affect student enrollment decisions. The research addresses a gap in understanding how these marketing strategies impact enrollment in this specific region, which has not been widely studied. Using a survey method with a quantitative approach, the study explores aspects like accreditation, ranking, and clustering of colleges. Data were collected from 283 non-official and non-religious colleges, with a sample of 166 colleges, through questionnaires sent to policymakers. The data were analyzed using descriptive statistical methods and Structural Equation Modeling-Partial Least Squares (SEM-PLS) analysis. The results show that the segmentation strategy is particularly successful, while the targeting and positioning strategies are moderately effective. Unlike previous studies that generalize the effects of marketing strategies on college enrollment, this research offers a detailed analysis specific to the DKI Jakarta region. The hypothesis testing confirms that segmentation, targeting, and positioning strategies positively influence enrollment interest, both individually and together. However, the study is limited to one region and one type of college, indicating a need for further research in different contexts. The study concludes with recommendations to strengthen each part of the STP strategies by addressing identified weaknesses to improve their overall impact.

Predictors of early child development for screening pregnant women most in need of support in Brazil.

Home visiting programmes can support child development and reduce inequalities, but failure to identify the most vulnerable families can undermine such efforts. We examined whether there are strong predictors of poor child development that could be used to screen pregnant women in primary health care settings to target early interventions in a Brazilian population. Considering selected predictors, we assessed coverage and focus of a large-scale home visiting programme named Primeira Infância Melhor (PIM). We undertook a prospective cohort study on 3603 children whom we followed from gestation to age four years. We then used 27 potential socioeconomic, psychosocial, and clinical risk factors measurable during pregnancy to predict child development, which was assessed by the Battelle Developmental Inventory (BDI) at the age of four years. We compared the results from a Bonferroni-adjusted conditional inference tree with exploratory linear regression and principal component analysis (PCA), and we conducted external validation using data from a second cohort from the same population. Lastly, we assessed PIM coverage and focus by linking 2015 cohort data with PIM databases. The decision tree analyses identified maternal schooling as the most important variable for predicting BDI, followed by paternal schooling. Based on these variables, a group of 214 children who had the lowest mean BDI (BDI = -0.48; 95% confidence interval (CI) = -0.63, -0.33) was defined by mothers with ≤5 years and fathers with ≤4 years of schooling. Maternal and paternal schooling were also the strongest predictors in the exploratory analysis using regression and PCA, showing linear associations with the outcome. However, their capacity to explain outcome variance was low, with an adjusted R2 of 5.3% and an area under the receiver operating characteristic curve of 0.62 (95% CI = 0.60, 0.64). External validation showed consistent results. We also provided an online screening tool using parental schooling data to support programme's targeting. PIM coverage during pregnancy was low, but the focus was adequate, especially among families with longer enrolment, indicating families most in need received higher dosage. Information on maternal and paternal schooling can improve the focus of home visiting programmes if used for initial population-level screening of pregnant women in Brazil. However, enrolment decisions require complementary information on parental resources and direct interactions with families to jointly decide on inclusion.

In-person learning during the pandemic: Student take-up and school-level effects of remote and hybrid instruction on student outcomes

While studies have examined the effects of schools offering in-person learning during the pandemic, this study provides analysis of student enrollment decisions (remote versus in-person) in response to schools providing in-person learning opportunities. In Connecticut during the 2020-21 school year, we find that student take-up of in-person learning opportunities was low with students on average enrolled in-person for only half of the days offered, and take-up was even lower in schools with larger shares of disadvantaged students. The provision of in-person learning opportunities has been previously shown to mitigate pandemic learning losses. By exploiting data on actual enrollment, we show that the protective benefits of in-person learning are twice as large as previously estimated once we account for the low rates of student take-up. Finally, we provide evidence suggesting that a key mechanism behind the benefits of in-person learning is alleviating the burden faced by schools and teachers in delivering remote education. First, we show that the benefits to individual students of their in-person learning are substantially smaller than the overall benefits a student receives from their school average level of in-person enrollment. Second, we show that a combination of remote and in-person learning (hybrid) with a full-time on-line presence of students when at home was worse than hybrid learning with students never or only partially online. This second finding is consistent with qualitative evidence showing that teachers found hybrid learning especially challenging when having to manage both in-person and remote students for the entire class period.

Utilizing public relations for achieving success in enrollment: Observations drawn from an extensive study of higher educational institutions

This study explores how public relations (PR) can give universities an edge in today’s competitive landscape. By examining past research, conducting interviews in 10 diverse cities in Vietnam, and analyzing case studies, it reveals the powerful link between PR strategies and student involvement. The research shows that well-crafted PR activities, tailored to different student groups and utilizing digital platforms, significantly impact student perceptions and enrollment decisions. It delves deeper than simply confirming PR’s effectiveness, offering insights into how specific PR tactics can resonate with student needs and expectations. Furthermore, it explores how PR influences student retention, highlighting the long-term benefits for universities. This research is a valuable tool for institutions seeking to thrive. By understanding the power of PR in shaping student decisions, universities can tailor their outreach efforts more effectively. Additionally, the study emphasizes the lasting advantages of a strategic PR approach, contributing to a broader discussion on its importance in higher education. Ultimately, these findings benefit both institutions and students, who can expect improved transparency, engagement, and communication within their academic communities.

Beyond the model minority myth: Student–counselor interactions and college enrollment of Asian American students

AbstractDue to the model minority myth, scant attention has been given to the college preparation of Asian American (AA) students. Using the national sample of High School Longitudinal Study of 2009–2013, this study examined associations among student–counselor interactions, school connectedness, and college enrollment of AA students. The results of the structural equation modeling indicated that school connectedness fully mediated the association between student–counselor interactions and college enrollment. The findings from the current study suggest that when AA students interact with school counselors in the 9th grade, they tend to feel more connected to their school, which, in turn, leads to increased college enrollment decisions in the 12th grade. Implications for helping professionals in schools are discussed.

Factor influencing Secondary School Students’ Decision to Study for a Bachelor's Degree at Champasak Province, Lao PDR

This research is a study on the factors that influence the decision of high school students to study for a bachelor's degree in Champasak province, with the purpose of studying the factors that influence the decision to study for a bachelor's degree in Champasak province. A questionnaire survey method was used to collect data from 410 students from 9 districts and 1 city in Champasak Province, Laos. A logistic regression model was used to analyze the data. The research results show that factors influence the decision of high school students to attend Champasak University in Champasak Province. There are a total of nine important factors that affect the decision to choose Champasak University. First of all, there is the problem of the Lao ethnic group. Second, religious beliefs, especially Buddhism. In addition, parents' scholarship support, family members' educational level, parents' occupation, household monthly income, major in marketing, and access to university courses all affect enrollment decisions. Finally, students' expectations about job opportunities after graduation have a positive effect on their decision to enroll in Champasak University, which indicates the importance of providing education in accordance with the needs of the labor market.

Understanding uptake in demand-side broadband subsidy programs: The affordable connectivity program case

The Affordable Connectivity Program (ACP) represents a historic investment by the federal government to address the digital divide. Its goals are both to increase the rate of broadband adoption and make it easier for low-income households to sustain service. But what have been the drivers of ACP enrollment? We know a great deal about trends in adoption and the geography of enrollment among eligible households. But those metrics – especially a focus on enrollment rates among eligible households – are only so useful in explaining ACP sign-ups.This invites analysis that investigates the drivers of ACP enrollment in a comprehensive way, which this paper proposes to do. The paper hypothesizes that ACP enrollment decisions are not solely individual (i.e., that a household's enrollment decision is structured only by income level), but also influenced by community-wide considerations, such as housing costs, share of occupied houses, presence of anchor institutions such as public libraries, and population density (i.e., whether a place is urban or rural). The paper develops a regression model that predicts ACP enrollment rates among eligible households at the 5-digit zip code geography as a function of the variables discussed above, as well as others such as the racial and ethnic make-up of a zip code area. The analysis also controls for existing levels of broadband subscriptions and computer ownership in a given area. The difference between predicted and actual ACP enrollment rates at the 5-digit zip code level is proposed as a metric of ACP performance. These findings are supplemented with a geographically weighted regression (GWR) model that allows the relationship between each explanatory variable and ACP enrollment to vary by locality. This allows for analyzing and visualizing how these relationships vary across space.The empirical findings show that high levels of economic distress are a strong determinant of ACP enrollment in a given area, but social and community-wide indicators are important as well. The GWR results demonstrate that important differences in these relationships exist across geographies. Understanding spatial variations in ACP performance can help policymakers and other stakeholders better target resources to address the digital divide.

"I Advise, You Decide": How Academic Advisors Shape Community College Students' Enrollment and Credit Load Decisions

"I Advise, You Decide": How Academic Advisors Shape Community College Students' Enrollment and Credit Load Decisions

To SHARE or not to SHARE: Exploring incarcerated women's decisions about enrolling in exposure-based group therapy.

Exposure therapies effectively treat traumatic stress sequelae, including that which follows sexual violence victimization (SVV). Carceral facilities house women with significantly higher rates of SVV than community samples, yet they rarely implement this form of treatment. In this study, women with histories of SVV (n = 63) completed semistructured qualitative interviews about their decision to enroll or not enroll in an exposure-based group therapy called Survivors Healing from Abuse: Recovery through Exposure while incarcerated. All study participants were previously incarcerated in a prison, where they were offered the opportunity to enroll in Survivors Healing from Abuse: Recovery through Exposure. We used the theory of planned behavior to analyze factors that affected enrollment decisions. Results revealed that enrollment decisions among incarcerated women can be categorized within the theory of planned behavior framework. Interview responses indicated that recognizing current problems as related to experiences of SVV, holding positive attitudes about mental health treatment, observing peers engaging in help-seeking behaviors, and perceiving treatment as accessible were linked with enrollment. Negative perceptions of treatment, fear of judgment, and negative peer influence (e.g., distrust of peers) were linked to decisions not to enroll. While certain beliefs were influenced by contextual features of incarceration (e.g., peer interactions outside of group therapy), many overlapped with factors found to influence help-seeking among nonincarcerated populations. Findings have implications for how to engage members of underserved populations in resource-deprived contexts who have a great need for treatment of traumatic symptoms secondary to sexual violence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Online marketing and brand awareness for HEI: A review and bibliometric analysis

Background This study conducted a comprehensive bibliometric analysis to identify the gaps in the existing literature related to Online marketing and brand awareness strategies for HEI. It has evaluated the current state of the literature on the given topic showing the pivotal role of online marketing and brand awareness in higher education for enrollment. Methods The study used a web-based application, Biblioshiny, which comes in the bibliometrix package. The study used the Scopus database to create the data set, given its conventional construction and quality of the sources. The analysis done is descriptive. By using the bibliometrix software, the study showed the authors name, articles, sources, citations, relevant journals and co-citation from the year 2017 to 2022. The time period selected by the study was five years which means that articles published from 2017 to 2022 have been taken for the study. Results We found that HEI online marketing and brand awareness have not been explored much as it has not reached the stage of maturity. Most of the publication was done during the time of Covid-19. Also, the role of brand awareness in student enrollment decisions for HEI requires more investigation. Top most publications their sources and top authors are identified. Conclusions Bibliometric analysis has provided valuable insights into the seminal work, emerging trends, and the gap in the study. This area of study has been explored but not as much as challenges, and the effectiveness of online marketing tools like seo, sem,ppc and more has not been measured. Further, this paper allows researchers to study by examining the pattern of publications by seeing the different authorships, co-authors, collaborations, relevant sources, and citations. The insights of this paper will help education policymakers devise more creative strategies to increase enrollment, ensuring sustained relevance and competitive advantage in higher education institutions .

Addressing the Marketing Practices of Medicare Advantage Plans.

The Medicare Advantage (MA) Program, home to nearly half of the eligible Medicare population, has recently come under increased scrutiny. Recent investigations conducted by the United States Senate Committee on Finance and Centers for Medicare & Medicaid Services (CMS) have uncovered marketing practices of MA insurance agents that "were not complying with current regulation and unduly pressuring beneficiaries, as well as failing to provide accurate or enough information to assist a beneficiary in making an informed enrollment decision." These findings come at a time in which MA programs are under investigation for denials of prior authorization requests that fall within Medicare guidelines for covered health services. In this Commentary we consider the backdrop for the growing scrutiny of the MA program and the implications thereof to its future trajectory.

The impact of the COVID‐19 pandemic on business students’ future preference for online courses

AbstractThis study analyzes students’ future preferences for online business courses based on responses from a spring 2021student sample from a California public regional university. The timing of this research takes advantage of the COVID‐19 “sudden disruption” that provided a unique opportunity to examine factors (including challenges specific to COVID‐19) that affect student choices about course delivery modality. Academic background, remote‐learning experiences, and mental health significantly impacted future course enrollment decisions. Study results provide insights for both university administrators and faculty who will need to plan curriculum in the challenging postpandemic higher education setting.

Development of The Lupus Clinical Trials Enrollment Decision Aid: a pilot study

IntroductionIn this pilot study, we describe the development of a patient-centered Decision Aid (DA) for participation of SLE clinical trials called “The Lupus Clinical Trials Enrollment DA”.MethodsA draft DA was designed by a development working group using a collaborative, iterative process using the International Patient Decision Aid Standards (IPDAS) guidelines. The approved draft DA was then pilot tested and refined using semi structured interview with 10 lupus providers and 12 SLE patients. Descriptive statistics were calculated. Interviews/surveys were conducted until thematic saturation was achieved. Responses on usefulness were accumulated, and mean usefulness scores were calculated. Feedback from the semi-structured interviews were categorized into several themes as outlined in the results section.ResultsThe definition of treatments, side effects of each option, and expected improvement from each option was outlined. 90% of providers and 91.7% of patients reported that the definition of SOC treatment was clear. Additionally, the expected improvement for SOC (90% of providers, 100% of patients), clinical trial drug (70%, 91.6%), and placebo (70%, 100%) were noted to be clear. Side effects of SOC (80%, 100%), clinical trial drug treatment (80%, 100%), placebo (90%, 100%), were also noted to be clear. 100% of providers and patients thought that the figure outlining pros/cons of participating in clinical trials was appropriate. The mean usefulness scores for the DA were 4.45/5 for providers and 4.67/5 for patients.DiscussionThese data demonstrate that both patients and providers confirm that the newly developed The Lupus Clinical Trials Enrollment DA is useful and easy to use. Qualitative feedback from providers demonstrated concern that aspects of the DA, such as expected improvement and side effects might be unclear to patients; however, patients did not express the same concern in either the quantitative or qualitative feedback.

Partner Plan Choices and Medicare Advantage Enrollment Decisions Among Older Adults

This study examines the association of partner Medicare Advantage plan status over 1 year with beneficiary and plan characteristics.

Risk calculator for incident atrial fibrillation across a range of prediction horizons

The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years. We used secondary-care linked primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc and C2HEST scores. Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA2DS2-VASc and C2HEST scores. The models are available as a web-based FIND-AF calculator. The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study.