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Development and Evaluation of the Altered Student Study Environment Tool: A Tool to Measure Nursing Student Concerns Relating to Academic Progression During the COVID-19 Pandemic

Fernandez, Ritin; Green, Heidi; Middleton, Rebekkah; Halcomb, Elizabeth; Moxham, Lorna

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Nursing Education Perspectives: 5/6 2022 - Volume 43 - Issue 3 - p 147-151
doi: 10.1097/01.NEP.0000000000000936
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Abstract

The emergence of the COVID-19 pandemic and associated public health measures implemented to reduce community transmission, such as physical distancing, led to widespread social and economic disruption (Nicola et al., 2020). Universities are no exception to the challenges generated by the pandemic; rapid changes have been required to align with restrictions (Carolan et al., 2020). The prompt cessation of face-to-face teaching in Australian universities at the end of March 2020 created an unexpected and unfamiliar situation for both staff and students (Crawford et al., 2020). The continued provision of education, although a priority, was influenced by the availability of information technology infrastructure, digital literacy, and capacity of e-learning platforms (Crawford et al., 2020; Wild et al., 2020). In addition, students were required to adopt online learning methods (Crawford et al., 2020) while coping with added personal pressures, such as home schooling for children and loss of employment.

Some students were readily able to adjust to the changes in educational delivery with limited negative effects. Others, with particular learning styles, struggled to adapt to online classes (Mupinga et al., 2006), causing increased levels of anxiety and stress. Stress among university students is a well-known phenomenon (Barboza & Soares, 2012; Thawabieh & Qaisy, 2012). The COVID-19 pandemic and associated consequences, such as mass unemployment and the unanticipated online learning environment, created additional stressors for students, a particular cause for concern in preregistration nursing students, who also were required to take part in clinical placements. A systematic review analyzing the sources of stress among undergraduate nursing students identified their three main stressors as academic, clinical, and personal/social (Pulido-Martos et al., 2012). The array of uncertainties with regard to academic progression, new study environments, clinical placement (Dewart et al., 2020), as well as the adjustments required in students’ personal and social lives undoubtedly affected their learning experience.

Concerns regarding the impact of altered study environments for undergraduate nurses could have both short- and long-term consequences for academic progression. Identifying student concerns was vital to developing strategies to minimize their impact. Validated scales have been published relating to barriers to online learning, but there are no published scales that measure students’ concerns relating to the impact of altered study environments on academic progression during a pandemic. The objectives of this study were to: 1) develop and test the psychometric properties of the Altered Student Study Environment Tool (ASSET) to measure concerns of preregistration nursing students about the impact of altered study environments on their academic progression and 2) investigate the relationship between students’ concerns, demographics, COVID-19-related knowledge, and communication received from the university about COVID-19.

METHOD

Development of the Tool

Items for the ASSET were developed based on a review of the literature and in conjunction with expert nurse academics and clinical facilitators. In Australia, a clinical facilitator is a registered nurse who is employed by the university to facilitate student learning in the clinical setting. Further consultation with a panel of experts, including experienced academics, clinical facilitators, and senior nurses, was undertaken to confirm content validity and make relevant modifications. The final ASSET consisted of 11 items, each of which was rated on a 5-point Likert scale, with scores ranging from strongly agree (1) to strongly disagree (5). The minimum score for the total scale was 11; the maximum was 55. Pilot testing was undertaken using a sample of five preregistration students, and no changes were required to the wording of any items.

Validation of the ASSET Tool

The study was undertaken at a regional university composed of a main campus and five satellite campuses across New South Wales, Australia. Two of the satellite campuses are situated in metropolitan areas; three are in regional/rural areas. Validation of the ASSET was undertaken in a prospective cross-sectional study using a convenience sample of currently enrolled preregistration nursing students. Students were eligible to participate if they were currently enrolled in either of the preregistration programs, namely, bachelor of nursing or bachelor of nursing (advanced). A total of 1,357 students were enrolled in these programs at the university during the study period.

Data Collection

An invitation to participate in the study was sent to all students through the university digital learning platform, which is subscribed to by all learners. In addition, student representatives were sent the invitation through student social media platforms and asked to disseminate the survey. The survey was also advertised on the student Facebook page. Data collection occurred during the peak of the pandemic in Australia (May to June 2020) when the country’s borders were closed to nonresidents, social distancing rules were imposed. and “nonessential” services were suspended.

Data were collected using a self-administered survey delivered via Survey Monkey©. Information collected included demographics, perceived impact of the altered study environment on academic progress using the 11-item ASSET, knowledge about COVID-19, and perceptions of information received about COVID-19 from the university. Demographic data collected included age, gender, employment status, current living arrangements, study pattern (full-time/part-time), student status, and year of study. Knowledge (four items) and communication received from the university about COVID-19 (one item) were assessed using investigator-developed questions; Students respond to these questions using a 5-point Likert scale (1 = strongly agree, 5 = strongly disagree). Students were also provided an option for open-ended responses; these were reported separately (Alomari et al., 2021).

Ethical approval for the study was obtained from the university’s human research ethics committee. Students were informed that no identifiable information would be obtained, that all responses were confidential, and that participation was voluntary. Completion of the survey was considered implied consent.

Data Analysis

All data were exported to SPSS© Version 25 for analysis. Relevant items were reverse-coded before analyzing to ensure that higher scores reflected greater concerns, higher knowledge, and greater communication from the university. Demographic data were summarized using descriptive analyses, including means, standard deviations, and frequency distributions.

Best practices in exploratory factor analysis using a multifactorial approach were used to assess the construct validity of the ASSET (Williams et al., 2012). First, distribution of the responses was assessed using response option frequency, mean, and standard deviations for each item. Second, confirmation of nonviolation of the assumptions of normality, linearity, and multicollinearity was undertaken. Third, exploratory factor analysis using principal components analysis was conducted, followed by varimax rotation. Components were extracted based on visual inspection of the scree plot and established criteria (Kaiser, 1960). The item loading was considered large if ≥0.80, moderate if between 0.79 and 0.41, and small if ≤0.40. The relationship between ASSET overall and subscale scores was checked for convergent validity using nonparametric correlation coefficient (Spearman’s rho: >0.7, good; between 0.7 and 0.4, moderate; and <0.40, weak). Internal consistency for each subscale and the overall scale was assessed using Cronbach’s alpha (≥.9, excellent; .8 to <.9, good; .7 to <.8, acceptable; .6 to <.7, questionable; .5 to <.6, poor; <.5, unacceptable).

Identified subscales were interpreted and named to reflect underlining constructs of the ASSET. The normality of continuous data was ascertained by examining the skewness and kurtosis indices against accepted values. One-way analyses of variance and t-tests were used to test differences between demographic variables and knowledge and communication from the university about COVID-19 and perceptions of the effects of altered study environments on academic progression. Pearson’s correlations were used to assess the relationships among continuous variables. Statistical significance was set at p < .05.

RESULTS

Student Demographics

Of the 231 students who completed the survey (response rate, 17 percent), most were female (n = 206, 96.7 percent); their mean age was 27.8 years (SD = 9.5 years). The majority (n = 217, 93.1 percent) were studying full-time and were domestic students (93.1 percent). Just under one third of respondents (n = 69, 29.6 percent) were undertaking their final year of study. Most respondents (n = 178, 76.7 percent) were employed, and 84 percent (n = 196) were living with their family or partner (see Supplemental Content 1 for details, available at https://links.lww.com/NEP/A321).

Validation of the ASSET

The mean total ASSET score was 38.1 (SD = 7.97). The lowest individual item was “I am worried because I don’t have access to the Internet to study online” (M = 2.10, SD = 1.04); the highest concern was for the item “Not being able to attend clinical placement will prevent me from progressing in my degree” (M = 4.16, SD =1.02; see Supplementary Content 2, available at https://links.lww.com/NEP/A322).

Factor Extraction, Exploratory Factor Analysis, Internal Consistency

The Kaiser-Meyer-Olkin test value was .758, and the Bartlett’s test of sphericity reached statistical significance, χ2(55, N = 226) = 1,185.57, p < .001, indicating that that the data were suitable for factor analysis (Tabachnick & Fidell, 2014). Responses were skewed to the left for 10 of the 11 items, with most participants responding either agree or strongly agree. One item, “I am worried because I don’t have access to the Internet to study online,” was skewed to the right; 72.7 percent of respondents indicated they were not worried about having access to the Internet.

Analysis of the ASSET revealed a three-factor solution with eigenvalues of >1, accounting for 66.3 percent of the total variance. All items had factor loadings of >0.4, and the scree plot revealed a clear departure from linearity consistent with a three-factor solution. All items loaded onto only one of the three factors, without any cross loading. The factors were descriptively labeled attending clinical placement (three items), completion of clinical placement (four items), and grade attainment (four items).

Internal consistency for the total ASSET was α = .830 (M = 38.2). Scale homogeneity assessed using the corrected item-to-total correlations was >.30 for 10 items and .29 for one item, demonstrating good internal consistency. Cronbach’s alphas for the three subscales, attending clinical placement, completion of clinical placement, and grade attainment, were .92, .77, and .71, respectively.

Concerns About Progression/Knowledge/Communication

The mean total score for the ASSET was 38.1 (SD = 7.97). The mean scores for the subscales attending clinical placement, completion of clinical placement, and grade attainment were 9.6 (SD = 3.33), 15.4 (SD = 3.58), and 13.2 (SD = 3.31), respectively. The majority of respondents (83.3 percent) agreed/strongly agreed that they had sufficient knowledge of COVID-19; 96.2 percent agreed/strongly agreed that they understood how to protect themselves during the pandemic. Almost all respondents knew that regular handwashing (97.8 percent) and appropriate social distancing (98.3 percent) can prevent the spread of COVID-19.

Three quarters of respondents (75 percent) agreed/strongly agreed that the university had provided them with sufficient information about COVID-19 (one item). Less than half (37.2 percent) stated that they got their information about COVID-19 from social media. In fact, most, students indicated they tried to avoid social media if it related to COVID-19; they used social media to stay connected to family, friends, and peers.

Demographics, Knowledge, Communication, and Concerns About Academic Progression

Univariate analysis demonstrated no statistically significant association among age, gender, employment status, international or domestic status, year of study, and the total ASSET scale and subscales. However, those studying full-time had significantly higher scores for the subscale completion of clinical placement compared to those working part-time, M = 15.53, SD = 3.6 vs. M = 13.68, SD = 3.1, respectively, t(229) = 1.99, p = .04.

There was a statistically significant negative correlation between communication received from the university and the total ASSET, r = −.312 (229), p < .001; those who had high scores for communication had lower total ASSET scores. There was also a statistically significant negative correlation between the subscale attending clinical placement and understanding how to protect oneself during the pandemic; those with higher knowledge had lower subscale scores, r = −.190 (229), p < .004; see Table 1.

Table 1 - Correlation Between the Altered Student Study Environment Tool, Knowledge, and Information Received From University
1 2 3 4 5 6 7
1. Attending clinical placement 1.00
2. Grade attainment .314* 1.00
3. Completion of clinical placement .396* .336* 1.00
4. Total concerns .762* .718* .775* 1.00
5. Sufficient knowledge of COVID-19 −0.08 0.09 −0.03 −0.01 1.00
6. Understand how to protect myself during pandemic −.190* −0.01 0.00 −0.09 .570* 1.00
7. University provided sufficient information about COVID-19 −.210* −.270* −.235* −.312* .131* .182* 1.00
*Significant correlation.

DISCUSSION

The COVID-19 pandemic brought an unprecedented need to rapidly alter learning environments to facilitate continuation of educational programs while maintaining social distancing. Nursing is a profession where graduates are expected to fill an international workforce shortage (Haddad et al., 2020). This study highlighted nursing students’ concerns about the impact of altered learning environments because of COVID-19 on their academic progression and developed a tool to assess the impact of these changes.

Participants in this study felt that they had sufficient knowledge of COVID-19 and how to protect themselves. In addition, they expressed that the university had provided them with sufficient information. Findings demonstrated a statistically significant negative correlation between communication received from the university and the total ASSET and its subscales. That is, participants who had high scores for communication had lower total scores for the ASSET and all three subscales. These results indicate that the university communication had indeed been sufficient to ameliorate participants’ concerns regarding their academic progress.

Universities have played an important role in supporting both staff and students during the pandemic (Sahu, 2020). Through the provision of quality support to transition to online learning, practical support for living, and mental health support for staff and students, universities have the potential to enhance educational and individual outcomes (Sahu, 2020). Without appropriate support, students are at risk of psychological and health consequences from the pandemic (Cao et al., 2020; Hajdúk et al., 2020; Savitsky et al., 2020; Wong et al., 2004).

The university in this study promptly communicated with students through emails and a specifically designed webpage on the university website. The webpage provides information on mental health and well-being support for students and staff, student financial assistance, changes to and support for the online learning environment, information technology support, and resources for the pandemic. In the early stages of the pandemic, communication was predominately received from the university through regularly occurring email, received at first every two to three days and eventually once each week. The communication was both targeted and specific, with nursing students receiving communications explicitly tailored to them, along with generalized communication from the university vice chancellor. The finding that few participants described accessing information via social media is in contrast to studies of university students that described high use of social media (Alzoubi et al., 2020).

Findings from this study demonstrate that students’ greatest concerns were about not being able to attend clinical placement, specifically, they were concerned that clinical placements would be canceled or postponed, preventing them from progressing in their degree. Australian students are mandated to complete 800 hours of clinical placement (Australian Nursing and Midwifery Accreditation Council, 2019) to obtain registration as a nurse. It is clear that not completing placements will impede course completion unless these standards are revised. Concerns around disruptions to nursing education have been reported internationally, as the value of placements is weighed against learner safety and ethical issues (Carolan et al., 2020; Dewart et al., 2020; Wild et al., 2020). Participants in our study expressed some concern about the risks associated with taking part in clinical placements. Other studies reported that nursing students are willing to accept the risks of exposure to COVID-19 if it means that they will be able to complete their course (Carolan et al., 2020; Dewart et al., 2020). Course completion is vital to provide additional nurses in the workforce, particularly at a time of high demand for frontline health professionals. However, it is important for educators and institutions to ensure that students are making decisions based on their individual circumstances rather than focusing solely on course completion.

To a lesser extent, participants were also concerned about the impact of COVID-19 on their grades and degree completion. It is well known that social networks in the form of study groups promote critical thinking, discussion, and debate, and this type of interactive environment promotes a deeper learning (Carvalho et al., 2017; Linn et al., 2013). University students have also indicated their networks enabled academic progression (Harrington, 2003). Moving to an altered study environment because of COVID-19 meant that some students may not have been able to study in groups, and their ability to engage with their networks was compromised.

STRENGTHS AND LIMITATIONS

A major strength of this study was the use of well-established techniques for the development and validation of the ASSET. Expert nurse academics and clinical facilitators with extensive clinical and research experience established content validity. Second, the study was undertaken during the COVID-19 pandemic, and student perceptions were in real time, thus mitigating recall bias.

Despite the rigor with which the study was conducted, some limitations must be acknowledged. First, the study was conducted using convenience sampling from a single university, which limits generalization to other institutions. Further testing of the ASSET is needed with preregistration nurses who attend different universities to establish psychometric properties in other settings. Second, the use of self-reported data is subject to social desirability bias and hence a limitation of the study. However, the online survey method might mitigate this factor as the identity of respondents was unknown. Another limitation is the low response rate, despite the use of strategies to increase participation. It is possible the low response rate is a result of student concerns around COVID-19 and potential disengagement with university studies. Some students may have been on leave when the survey was administered and not accessing university emails.

Despite these limitations, the ASSET can be used by researchers and educators to better understand the concerns of students in altered study environments. The ASSET can be adapted for use in other situations, such as natural disasters; in universities that experience changes in teaching environments; and in the case of terrorism, civil unrest, or other emergency situations. It can be used to inform the development of appropriate strategies to mitigate anxiety or stress because of concerns relating to academic progression.

CONCLUSION

The results of this study provide empirical support for the ASSET as a valid and reliable instrument to measure concerns relating to altered student study environments and academic progression. Students who felt that they received adequate communication from the university and students who knew how to protect themselves during the COVID-19 pandemic reported lower concerns regarding clinical placement. In general, students face a host of challenges associated with navigating the complexities of university environments, including difficulties associated with higher education learning. It is difficult enough for students during normal times, but during a global health pandemic, the challenges compound. Understanding the concerns from students’ perspectives using a valid and reliable instrument, as this study does, has implications for universities that are committed to students’ success by enabling them to develop strategies aimed at addressing factors that impact academic progression.

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REFERENCES

Alomari A., Hunt L., Lord H., Halcomb E., Fernandez R., Middleton R., Moxham L. (2021). Understanding the support needs of Australian nursing students during COVID-19: A cross-sectional study. Contemporary Nurse, 1–11. 10.1080/10376178.2021.1997147
Alzoubi H., Alnawaiseh N., Al-Mnayyis A., Abu- Lubad M., Aqel A., Al-Shagahin H. (2020). COVID-19: Knowledge, attitude and practice among medical and non-medical university students in Jordan. Journal of Pure and Applied Microbiology, 14(1), 17–24. 10.22207/jpam.14.1.04
Australian Nursing and Midwifery Accreditation Council. (2019). Registered nurse accreditation standards. https://www.anmac.org.au/sites/default/files/documents/RegisteredNurseAccreditationStandards2019.pdf
Barboza M., Soares M. (2012). Analysis of stress-causing factors in the final undergraduate year of the nursing course. Acta Scientiarum. Health Sciences, 34(2), 177–183. 10.4025/actascihealthsci.v34i2.9209
Cao W., Fang Z., Hou G., Han M., Xu X., Dong J., Zheng J. (2020, May). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934. 10.1016/j.psychres.2020.112934
Carolan C., Davies C. L., Crookes P., McGhee S., Roxburgh M. (2020). COVID 19: Disruptive impacts and transformative opportunities in undergraduate nurse education. Nursing Education in Practice, 46, 102807. 10.1016/j.nepr.2020.102807
Carvalho D., Azevardo I. C., Cruz G., Mafra G., Rego A., Vitor A. F., Santos V., Cogo A., Ferreira Junior M. A. (2017). Strategies used for the promotion of critical thinking in nursing undergraduate education: A systematic review. Nursing Education Today, 57, 103–107. 10.1016/j.nedt.2017.07.010
Crawford J., Butler-Henderson K., Rudolph J., Malkawi B. H., Glowatz M., Burton R. L., Magni P. A., Lam S. (2020, April). COVID-19: 20 Countries' higher education intra-period digital pedagogy responses. Journal of Applied Teaching and Learning, 3(1). 10.37074/jalt.2020.3.1.7
Dewart G., Corcoran L., Thirsk L., Petrovic K. (2020, May 28). Nursing education in a pandemic: Academic challenges in response to COVID-19. Nurse Education Today, 92, 104471. 10.1016/j.nedt.2020.104471
Haddad L. M., Annamaraju P., Toney-Butler T. J. (2020). Nursing shortage. In StatPearls [Internet]. https://www.ncbi.nlm.nih.gov/books/NBK493175/
Hajdúk M., Dančík D., Januška J., Svetský V., Straková A., Turček M., Vašečková B., Forgáčová Ľ., Heretik A., Pečeňák J. (2020). Psychotic experiences in student population during the COVID-19 pandemic. Schizophrenia Research, 222, 520–521. 10.1016/j.schres.2020.05.023
Harrington M. A. (2003). Navigating the university system: The effects of Chinese and Indian graduate students' social networks on academic progression [Doctoral dissertation, Virginia Tech]. https://vtechworks.lib.vt.edu/handle/10919/29920
Kaiser H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. 10.1177/001316446002000116
Linn W. D., Lord K. C., Whong C. Y., Phillips E. G. (2013). Developing effective study groups in the quest for the “holy grail”: Critical thinking. American Journal of Pharmaceutical Education, 77(8), 180. 10.5688/ajpe778180
Mupinga D., Nora R., Yaw D. (2006). The learning styles, expectations, and needs of online students. College Teaching, 54(1), 185–189. 10.3200/CTCH.54.1.185-189
Nicola M., Alsafi Z., Sohrabi C., Kerwan A., Al-Jabir A., Iosifidis C., Agha M., Agha R. (2020). The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International Journal of Surgery, 78, 185–193. 10.1016/j.ijsu.2020.04.018
Pulido-Martos M., Augusto-Landa J., Lopez-Zafra E. (2012). Sources of stress in nursing students: A systematic review of quantitative studies. International Nursing Review, 59(1), 15–25. 10.1111/j.1466-7657.2011.00939.x
Sahu P. (2020). Closure of universities due to coronavirus disease 2019 (COVID-19): Impact on education and mental health of students and academic staff. Cureus, 12(4), e7541. 10.7759/cureus.7541
Savitsky B., Findling Y., Ereli A., Hendel T. (2020). Anxiety and coping strategies among nursing students during the covid-19 pandemic. Nurse Education in Practice, 46, 102809 10.1016/j.nepr.2020.102809
Tabachnick B. G., Fidell L. S. (2014). Using multivariate statistics (6th ed.). Pearson Education.
Thawabieh A., Qaisy L. (2012). Assessing stress among university students. American International Journal of Contemporary Research, 2(2), 110–116.
Wild L. M., Congdon B., Boyle K., Provost V., Schlesinger M., Salyers V., Sonoda K., Hosey K. N., Nordgren M. (2020). Innovations in nursing education: Recommendations in response to the COVID-19 pandemic. https://nepincollaborative.org/wp-content/uploads/2020/08/Nursing-Education-and-COVID-Pandemic-March-30-2020-FINAL.pdf
Williams B., Brown T., Onsman A. (2012). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3), 1–13. 10.33151/ajp.8.3.93
Wong J. G., Cheung E. P., Cheung V., Cheung C., Chan M. T., Chua S. E., McAlonan G. M., Tsang K. W., Ip M. S. (2004). Psychological responses to the SARS outbreak in healthcare students in Hong Kong. Medical Teacher, 26(7), 657–659. 10.1080/01421590400006572
Keywords:

Academic Progression; Clinical Placement; COVID-19 Pandemic; Preregistration Nursing Students

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