Large Campus Research Articles

Mixed-methods process evaluation of a residence-based SARS-CoV-2 testing participation pilot on a UK university campus during the COVID-19 pandemic

BackgroundRegular testing for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an important strategy for controlling virus outbreaks on university campuses during the COVID-19 pandemic but testing participation rates can be low. The Residence-Based Testing Participation Pilot (RB-TPP) was a novel intervention implemented at two student residences on a large UK university campus over 4 weeks. The aim of the pilot was to increase the frequency of asymptomatic SARS-CoV-2 saliva testing onsite. This process evaluation aimed to determine whether RB-TPP was implemented as planned and identify implementation barriers and facilitators.MethodsA mixed-methods process evaluation was conducted alongside the RB-TPP. Evaluation participants were students (opting in, or out of RB-TPP) and staff with a role in service provision or student support. Monitoring data were collected from the intervention delivery team and meeting records. Data were collected from students via online survey (n = 152) and seven focus groups (n = 30), and from staff via individual interviews (n = 13). Quantitative data were analysed descriptively and qualitative data thematically. Barriers and facilitators to implementation were mapped to the ‘Capability, Opportunity, Motivation–Behaviour’ (COM-B) behaviour change framework.ResultsFour hundred sixty-four students opted to participate in RB-TPP (98% of students living onsite). RB-TPP was implemented broadly as planned but relaxed social distancing was terminated early due to concerns relating to national escalation of the COVID-19 Delta variant, albeit testing continued. Most students (97.9%) perceived the period of relaxed social distancing within residences positively. The majority engaged in asymptomatic testing (88%); 46% (52% of testers) were fully compliant with pre-determined testing frequency. Implementation was facilitated by convenience and efficiency of testing, and reduction in the negative impacts of isolation through opportunities for students to socialise. Main barriers to implementation were perceived mixed-messages about the rules, ambivalent attitudes, and lack of adherence to COVID-19 protective measures in the minority.ConclusionsThis process evaluation identifies factors that help or hinder the success of university residence-based outbreak prevention and management strategies. RB-TPP led to increased rates of SARS-CoV-2 testing participation among students in university residences. Perceived normalisation of university life significantly enhanced student mental wellbeing. The complexity and challenge generated by multiple lines of communication and rapid adaptions to a changing pandemic context was evident.Trial registration numberUKAS 307727–02-01; Pre-results. ClinicalTrials.gov Identifier: NCT05045989; post-results (first posted, 16/09/21).Ethical approvalFaculty of Medicine & Health Sciences Research Ethics Committee, University of Nottingham (Ref: FMHS 96-0920)

Network methods and design of randomized trials: Application to investigation of COVID-19 vaccination boosters.

Network science methods can be useful in design, monitoring, and analysis of randomized trials for control of spread of infections. Their usefulness arises from the role of statistical network models in molecular epidemiology and in study design. Computational models, such as agent-based models that propagate disease on simulated contact networks, can be used to investigate the properties of different study designs and analysis plans. Particularly valuable is the use of these methods to assess how magnitude and detectability of intervention effects depend on both individual-level and network-level characteristics of the enrolled populations. Such investigation also provides an important approach to assessing consequences of study data being incomplete or measured with error. To address these goals, we consider two statistical network models: exponential random graph models and the more flexible congruence class models. We focus first on an historical use of these methods in design and monitoring of a cluster randomized trial in Botswana to evaluate the effect of combination HIV prevention modalities compared to standard of care on HIV incidence. We then present a framework for the design of a study of booster vaccine effects on infection with, and forward transmission of, SARS-CoV-2 variants. Motivation for the study is driven in part by guidance from the United Kingdom to base approval of booster vaccines with "strain changes" that target variants on results of neutralizing antibody tests and information about safety, but without requiring evidence of clinical efficacy. Using designs informed by our agent-based network models, we show it may be feasible to conduct a trial of novel SARS-CoV-2 vaccines in a single large campus to obtain useful information regarding vaccine efficacy against susceptibility and infectiousness. If needed, the sample size could be increased by extending the study to a small number of campuses. Novel network methods may be useful in developing pragmatic SARS-CoV-2 vaccine trials that can leverage existing infrastructure to reduce costs and hasten the development of results.

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Issues and Innovation for Setting and Infrastructure Management in the Islamic University of Lebanon in the Time of Pandemic

The Islamic University of Lebanon (IUL) is committed to providing faith and knowledge as a source of inspiration for the Lebanese nation, citizen, state and society as a whole. IUL has paid special attention to the environment and to the green metrics when establishing the new campus in Wardanieh, the rules related to green buildings and the preservation of the environment were taken into account. The COVID-19 pandemic has created the largest disruption of education systems in human history, affecting nearly 1.6 billion learners in more than 200 countries. In this paper we will describe how the setting and infrastructure of Wardanieh campus has helped in managing the Covid-19 crisis at the university through different levels: the physical distancing, the effect of the large campus buildings area according to the campus population, moreover the large forest spaces, the natural ventilation of buildings, the sanitization and sterilization procedures with setting guidelines for Covid-19 such as the obligation of wearing masks. Furthermore, we will describe the influence of ICT technologies into education in many different ways for distance learning, and how the university has evolved its ICT infrastructure to support the increase in demand on the internet capacity and on university servers.Keyword: IUL university, Green, SDGs, Covid-19 prevention, education, settings and infrastructure

Subspace Differential Privacy

Many data applications have certain invariant constraints due to practical needs. Data curators who employ differential privacy need to respect such constraints on the sanitized data product as a primary utility requirement. Invariants challenge the formulation, implementation, and interpretation of privacy guarantees. We propose subspace differential privacy, to honestly characterize the dependence of the sanitized output on confidential aspects of the data. We discuss two design frameworks that convert well-known differentially private mechanisms, such as the Gaussian and the Laplace mechanisms, to subspace differentially private ones that respect the invariants specified by the curator. For linear queries, we discuss the design of near-optimal mechanisms that minimize the mean squared error. Subspace differentially private mechanisms rid the need for post-processing due to invariants, preserve transparency and statistical intelligibility of the output, and can be suitable for distributed implementation. We showcase the proposed mechanisms on the 2020 Census Disclosure Avoidance demonstration data, and a spatio-temporal dataset of mobile access point connections on a large university campus.

Harvesting Local Energy: A Case Study of Community-Led Bioenergy Development in Galena, Alaska

Community-led bioenergy projects show great promise to address a range of issues for remote and Indigenous Arctic communities that typically rely on diesel for meeting their energy demands. However, there is very little research devoted to better understanding what makes individual projects successful. In this study, we analyze the case of the Galena Bioenergy Project (Alaska)—a biomass heating project that uses locally sourced woody biomass to help meet the heating demands of a large educational campus. Using project documents and other publicly available reports, we evaluate the project’s success using three indicators: operational, environmental, and community level socio-economic benefits. We find that the project shows signs of success in all three respects. It has a reliable fuel supply chain for operations, makes contributions towards greenhouse gas reductions by replacing diesel and has improved energy and economic security for the community. We also examine enabling factors behind the project’s success and identify the following factors as crucial: community-level input and support, state level financial support, access to forest biomass with no competing use, predictable demand and committed leadership. Our findings have important implications for other remote communities across the Boreal zone—especially those with nearby forest resources. Our examination of this case study ultimately highlights potential pathways for long-term success and, more specifically, shows how biomass resources might be best utilized through community-led initiatives to sustainably support energy security in Arctic communities.

Buildout and integration of an automated high-throughput CLIA laboratory for SARS-CoV-2 testing on a large urban campus.

In 2019, the first cases of SARS-CoV-2 were detected in Wuhan, China, and by early 2020 the first cases were identified in the United States. SARS-CoV-2 infections increased in the US causing many states to implement stay-at-home orders and additional safety precautions to mitigate potential outbreaks. As policies changed throughout the pandemic and restrictions lifted, there was an increase in demand for COVID-19 testing which was costly, difficult to obtain, or had long turn-around times. Some academic institutions, including Boston University (BU), created an on-campus COVID-19 screening protocol as part of a plan for the safe return of students, faculty, and staff to campus with the option for in-person classes. At BU, we put together an automated high-throughput clinical testing laboratory with the capacity to run 45,000 individual tests weekly by Fall of 2020, with a purpose-built clinical testing laboratory, a multiplexed reverse transcription PCR (RT-qPCR) test, robotic instrumentation, and trained staff. There were many challenges including supply chain issues for personal protective equipment and testing materials in addition to equipment that were in high demand. The BU Clinical Testing Laboratory (CTL) was operational at the start of Fall 2020 and performed over 1 million SARS-CoV-2 PCR tests during the 2020-2021 academic year.

Patient-Flow Analysis for Planning a Focused Hospital Layout: Tampere Heart Hospital Case.

The objective of this study is present how a patient movement-based patient-flow analysis is performed for planning the new Heart Hospital of Tampere University Hospital and how patient transfer distances can be shortened by this method. The Heart Hospital had served patients as a service line organization for years. However, the Heart Hospital layout rather looked like functional layout instead of service line layout because the units of the Heart Hospital have been spread out around the large university hospital campus. The flow routes of patients treated over the course of 1 year were analyzed by information technology systems in the hospital planning phase. Then, the proximity ranking of the main functions of the Heart Hospital was made. Layout planning was performed based on the proximity ranking. Nine months after the opening of the new Heart Hospital, the distances between the various hospital functions were calculated for the old Heart Hospital and the new one. In the old Heart Hospital, patients' transfer distance was 5,654 km (3,513 miles), while the corresponding figure for the new Heart Hospital was 3,797 km (2,359 miles), which means the distance was reduced by 33%. The patient-flow analysis works as it generated substantially shorter patient transfer distances in the new Heart Hospital. Shorter distances have supported more fluent patient flows that, in turn, has contributed higher productivity and quality of care.

Decision-based interactive model to determine re-opening conditions of a large university campus in Belgium during the first COVID-19 wave

BackgroundThe role played by large-scale repetitive SARS-CoV-2 screening programs within university populations interacting continuously with an urban environment, is unknown. Our objective was to develop a model capable of predicting the dispersion of viral contamination among university populations dividing their time between social and academic environments.MethodsData was collected through real, large-scale testing developed at the University of Liège, Belgium, during the period Sept. 28th-Oct. 29th 2020. The screening, offered to students and staff (n = 30,000), began 2 weeks after the re-opening of the campus but had to be halted after 5 weeks due to an imposed general lockdown. The data was then used to feed a two-population model (University + surrounding environment) implementing a generalized susceptible-exposed-infected-removed compartmental modeling framework.ResultsThe considered two-population model was sufficiently versatile to capture the known dynamics of the pandemic. The reproduction number was estimated to be significantly larger on campus than in the urban population, with a net difference of 0.5 in the most severe conditions. The low adhesion rate for screening (22.6% on average) and the large reproduction number meant the pandemic could not be contained. However, the weekly screening could have prevented 1393 cases (i.e. 4.6% of the university population; 95% CI: 4.4–4.8%) compared to a modeled situation without testing.ConclusionIn a real life setting in a University campus, periodic screening could contribute to limiting the SARS-CoV-2 pandemic cycle but is highly dependent on its environment.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Understanding SARS-CoV-2 Transmission: Linking Traditional Contact Tracing with Genomic Surveillance of a SARS-CoV-2 Student Cluster on a Large Urban Campus

Understanding SARS-CoV-2 Transmission: Linking Traditional Contact Tracing with Genomic Surveillance of a SARS-CoV-2 Student Cluster on a Large Urban Campus

An evaluation of the healthier dining programme effects on university student and staff choices in Singapore: A cluster-randomized trial

The Healthier Dining Programme (HDP) was launched to increase the availability and accessibility of healthier foods and beverages at food centers in Singapore. Our study's objective was to evaluate effects of the HDP on out-of-home dietary intakes of consumers at an institute of higher learning using a cluster-randomized trial. Six food centers at a large university campus were randomly assigned to the intervention or control arm. Participants were university students or staff aged ≥ 18 years (n = 247) who frequently dined at these centers. Out-of-home food consumption was assessed using a 7-day food diary before and after 10 weeks of intervention. Modified Poisson regression was used to assess differences in healthier dish intakes between the two study arms. Participants in the intervention arm were found to be more likely to have at least one healthier out-of-home dish per week than those in the control arm (84% vs. 65%, relative risk: 1.29; 95% confidence interval: 1.08, 1.54). This difference was due mainly to higher consumption of dishes prepared with healthier oil blends (1.47; 1.19, 1.82) and lower-sodium salt (3.25; 1.56, 6.78) in the intervention arm. While saturated and polyunsaturated fat intakes in the two arms were comparable, participants in the intervention arm had lower total fat (−1.27 g/1000 kcal, −2.48, −0.06) and monounsaturated fat (−0.50 g/1000 kcal, −0.94, −0.06) intakes, from out-of-home dishes as compared with the control arm. These findings suggest that environmental interventions at institutes of higher education to increase healthier food availability can improve dietary intake from out-of-home foods.

Crime and place: differences in spatial relationship between calls for service and recorded incidents for municipal and campus law enforcement

ABSTRACT With the advent of more law enforcement open data, researchers are exploring the use of calls for service (CFS) as a proxy for recorded incident information by law enforcement. However, indications are that law enforcement activities are mediated by the agency’s goals with its data. Using data from two different types of law enforcement agencies within the same community, CFS and incident reports for property crimes were tested for spatial association using the co-location quotient. Findings from this study show there is a modest amount of detectable clustering of CFS for the municipal law enforcement agency. However, the large university campus agency did not show any detectable spatial association for these events. This suggests that the movement towards using open data in research will need to take greater care in the selection of data to understand if assumptions about the data can be supported.

In Their Own Words: A Study on COVID-19-Related Concerns and Perceptions of Risk Among Older University Employees

The purpose of this qualitative study was to examine COVID-19-related concerns and risk perceptions among older employees aged 50+ related to reopening a large state university campus during the COVID-19 pandemic. Recruitment focused on older employees from diverse backgrounds and job classifications. Six focus group interviews, with a total of 24 participants, were conducted using Zoom video conferencing. Interviews were transcribed using Zoom and were double-checked for accuracy. Transcripts were coded and analyzed using ATLAS.ti 9 after establishing inter-rater reliability among two coders. During the campus reopening, older employees reported several concerns and perceptions of risk focused on COVID-19 exposure and transmission to others, individual health and health of other household members, mental health and stress, and job security. Findings were used to inform the development of intervention strategies and resources to promote the health and well-being among older employees during the pandemic.

Prevalence and predictors of mask use on a large US university campus during the COVID-19 pandemic: A brief report

This observational study was conducted to determine the prevalence and correlates of wearing masks at a large Midwestern US university during the COVID-19 pandemic. A total of 7,237 individuals were observed over 24 hours. Overall mask use prevalence was 90.6% (95% confidence interval: 89.9, 91.2); mask use was significantly associated with being indoors (vs outdoors), female (vs male), and at the athletic center (vs the student union).

An App-Based Surveillance System for Undergraduate Students' Mental Health During the COVID-19 Pandemic: Protocol for a Prospective Cohort Study.

BackgroundThe COVID-19 pandemic is a public health emergency that poses challenges to the mental health of approximately 1.4 million university students in Canada. Preliminary evidence has shown that the COVID-19 pandemic had a detrimental impact on undergraduate student mental health and well-being; however, existing data are predominantly limited to cross-sectional survey-based studies. Owing to the evolving nature of the pandemic, longer-term prospective surveillance efforts are needed to better anticipate risk and protective factors during a pandemic.ObjectiveThe overarching aim of this study is to use a mobile (primarily smartphone-based) surveillance system to identify risk and protective factors for undergraduate students’ mental health. Factors will be identified from weekly self-report data (eg, affect and living accommodation) and device sensor data (eg, physical activity and device usage) to prospectively predict self-reported mental health and service utilization.MethodsUndergraduate students at Western University (London, Ontario, Canada), will be recruited via email to complete an internet-based baseline questionnaire with the option to participate in the study on a weekly basis, using the Student Pandemic Experience (SPE) mobile app for Android/iOS. The app collects sensor samples (eg, GPS coordinates and steps) and self-reported weekly mental health and wellness surveys. Student participants can opt in to link their mobile data with campus-based administrative data capturing health service utilization. Risk and protective factors that predict mental health outcomes are expected to be estimated from (1) cross-sectional associations among students’ characteristics (eg, demographics) and key psychosocial factors (eg, affect, stress, and social connection), and behaviors (eg, physical activity and device usage) and (2) longitudinal associations between psychosocial and behavioral factors and campus-based health service utilization.ResultsData collection began November 9, 2020, and will be ongoing through to at least October 31, 2021. Retention from the baseline survey (N=427) to app sign-up was 74% (315/427), with 175-215 (55%-68%) app participants actively responding to weekly surveys. From November 9, 2020, to August 8, 2021, a total of 4851 responses to the app surveys and 25,985 sensor samples (consisting of up to 68 individual data items each; eg, GPS coordinates and steps) were collected from the 315 participants who signed up for the app.ConclusionsThe results of this real-world longitudinal cohort study of undergraduate students’ mental health based on questionnaires and mobile sensor metrics is expected to show psychosocial and behavioral patterns associated with both positive and negative mental health–related states during pandemic conditions at a relatively large, public, and residential Canadian university campus. The results can be used to support decision-makers and students during the ongoing COVID-19 pandemic and similar future events. For comparable settings, new interventions (digital or otherwise) might be designed using these findings as an evidence base.International Registered Report Identifier (IRRID)DERR1-10.2196/30504

SARS-CoV-2 Epidemiology on a Public University Campus in Washington State.

BackgroundWe aimed to evaluate a testing program to facilitate control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission at a large university and measure spread in the university community using viral genome sequencing.MethodsOur prospective longitudinal study used remote contactless enrollment, daily mobile symptom and exposure tracking, and self-swab sample collection. Individuals were tested if the participant was exposed to a known SARS-CoV-2-infected person, developed new symptoms, or reported high-risk behavior (such as attending an indoor gathering without masking or social distancing), if a member of a group experiencing an outbreak, or at enrollment. Study participants included students, staff, and faculty at an urban public university during the Autumn quarter of 2020.ResultsWe enrolled 16 476 individuals, performed 29 783 SARS-CoV-2 tests, and detected 236 infections. Seventy-five percent of positive cases reported at least 1 of the following: symptoms (60.8%), exposure (34.7%), or high-risk behaviors (21.5%). Greek community affiliation was the strongest risk factor for testing positive, and molecular epidemiology results suggest that specific large gatherings were responsible for several outbreaks.ConclusionsA testing program focused on individuals with symptoms and unvaccinated persons who participate in large campus gatherings may be effective as part of a comprehensive university-wide mitigation strategy to control the spread of SARS-CoV-2.

Rapid, Large-Scale Wastewater Surveillance and Automated Reporting System Enable Early Detection of Nearly 85% of COVID-19 Cases on a University Campus.

ABSTRACTWastewater-based surveillance has gained prominence and come to the forefront as a leading indicator of forecasting COVID-19 (coronavirus disease 2019) infection dynamics owing to its cost-effectiveness and its ability to inform early public health interventions. A university campus could especially benefit from wastewater surveillance, as universities are characterized by largely asymptomatic populations and are potential hot spots for transmission that necessitate frequent diagnostic testing. In this study, we employed a large-scale GIS (geographic information systems)-enabled building-level wastewater monitoring system associated with the on-campus residences of 7,614 individuals. Sixty-eight automated wastewater samplers were deployed to monitor 239 campus buildings with a focus on residential buildings. Time-weighted composite samples were collected on a daily basis and analyzed on the same day. Sample processing was streamlined significantly through automation, reducing the turnaround time by 20-fold and exceeding the scale of similar surveillance programs by 10- to 100-fold, thereby overcoming one of the biggest bottlenecks in wastewater surveillance. An automated wastewater notification system was developed to alert residents to a positive wastewater sample associated with their residence and to encourage uptake of campus-provided asymptomatic testing at no charge. This system, integrated with the rest of the “Return to Learn” program at the University of California (UC) San Diego-led to the early diagnosis of nearly 85% of all COVID-19 cases on campus. COVID-19 testing rates increased by 1.9 to 13× following wastewater notifications. Our study shows the potential for a robust, efficient wastewater surveillance system to greatly reduce infection risk as college campuses and other high-risk environments reopen.IMPORTANCE Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks. The highly automated sample processing to reporting system enabled dramatic reduction in the turnaround time to 5 h (sample to result time) for 96 samples. Furthermore, miniaturization of the sample processing pipeline brought down the processing cost significantly ($13/sample). Taken together, these results show that such a system could greatly ameliorate long-term surveillance on such communities as they look to reopen.Author Video: An author video summary of this article is available.

Increasing Perianesthesia Nurse Competency in Selected Critical Care Modalities

<h3>Introduction</h3> A large academic center's satellite campus Pre/Post unit rarely sees patients needing certain critical care modalities; the need to establish and maintain competencies in these modalities has been identified. <h3>Identification of the problem</h3> The unit identified the need to improve competency for selected high risk, low frequency critical care modalities. Challenges to increasing competency include varying critical care experience among staff and the infrequency with which these modalities occur in practice on the unit. <h3>QI question/Purpose of the study</h3> Develop an effective education strategy to improve competency in Pre/Post nurses for selected critical care modalities. <h3>Methods</h3> Per the QSEN Institute, competency is the knowledge, skills, and attitude (KSA) needed to provide safe and effective care. Expectations for the selected critical care modalities were derived from ASPAN's CBO. A sequential, tiered education strategy was developed. First, nurses completed pre-intervention surveys to capture baseline self-reported competency using a Likert scale based on Patricia Benner's "From Novice to Expert" theory. Second, staff completed didactic prework validated by quizzes that primarily consisted of policy and procedure review. Third, staff will attend skills stations to gain haptic experience with associated supplies and equipment. Finally, staff will be precepted by ICU nurses to gain hands-on experience with critically ill patients. <h3>Outcomes/Results</h3> At the interventions completion, the survey will be re-administered to assess changes in self-reported competency. Analysis of pre- versus post-intervention surveys will be available during the first quarter of 2021. <h3>Discussion</h3> Pending analysis of pre- and post-intervention surveys. <h3>Conclusion</h3> It is the ethical responsibility of Pre/Post leadership to ensure safe and effective care is provided. Whether the tiered education strategy will be effective in improving competency in Pre/Post nurses for the selected modalities is pending analysis of pre- and post-intervention surveys. <h3>Implications for perianesthesia nurses and future research</h3> This education strategy addresses improving competency. Future research is needed for an effective education strategy to maintain competency and mitigate knowledge/skill decay. This education strategy uses pre- and post-intervention surveys of self-reported competency to assess the intervention's effect on attitudes; further research using other competency validation methods is needed to better assess the intervention's effect.

The mobility of experiential learning pedagogy: transferring ideas and practices from a large- to a small-campus setting

ABSTRACT In this article, we examine the development of a new, experiential learning human geography and planning course at a smaller campus in Newfoundland, Canada. Our interest is twofold: to consider how pedagogical approaches can be transferred between a large urban campus and a small-town location; and to examine the benefits and complications of such transfers through a reflective examination of the resulting experiential learning program. The article captures the experiences of students, faculty, and university engagement staff in the deployment of the course. From these perspectives, we situate the decision to transfer an existing program across universities, the nuances of adapting such programs to the local context, and the challenge of meeting student desires for experiential learning amidst experimental pedagogical approaches. The paper concludes by suggesting that transferring pedagogical models across locations requires flexibility in terms of ensuring that new modules fit existing program constraints, and that such transfers have the potential to both challenge and positively transform experiential learning processes.