Understanding University Students during COVID-19: A Longitudinal Mixed-Methods Analysis of Their Experiences of Online Learning, Mental Health, Academic Engagement, and Academic Self-Efficacy

Abstract

Introduction

Research has consistently demonstrated that the COVID-19 pandemic, and resulting sudden shift to online learning (OL), had detrimental impacts on the motivation and mental health of university students. To date however this research has been cross-sectional and quantitative.

Method

This study employed a mixed-methods design to examine the experiences of students at a large national Australian University both at the outset of the pandemic in 2020 (n = 824) and again 6 months later (n = 254) at the conclusion of their academic year.

Results

Key findings from this study highlighted that despite quantitative findings suggesting poorer attitudes toward learning during the pandemic, qualitatively students perceived both positives and negatives to studying online. The qualitative results further highlighted that this experience was not the same for all and suggests the need to reconsider the standard approaches to offering support for students.

Conclusion

Students reported poor mental health in both time points, but outlined avenues which improved not only their mental health but also their motivation for studying such as increased peer engagement and self-care activities. Students reported that OL negatively impacted on both their engagement with studies and their mental health, highlighting the need for universities to prioritize supporting their students' mental health as much as their development of academic skills.

Online Learning during COVID-19

Due to safety measures implemented to tackle the novel Coronavirus (COVID-19), many universities in Australia and worldwide had to make an urgent transition to online learning (OL) [1]. OL is defined as an educational delivery system that takes place over the Internet and helps students join in an educational opportunity without physically existing in the same setting as the teacher [2]. Research before and during the COVID-19 pandemic has highlighted the advantages and disadvantages of OL for students. Benefits of OL for students in both circumstances include flexibility, avoiding commuting to university [3, 4, 5], greater time for other commitments (i.e., work and family) [6, 7], and learning content at the student's own pace [3, 8, 9].

Despite these positives of OL, emerging research has suggested that the urgent unplanned switch to OL due to the pandemic resulted in several significant challenges for students. The rapid transitions to OL left students experiencing challenges similar to those experienced in a typical OL environment including a lack of motivation to learn and technological issues [6, 10]. However, some challenges appear to be due to OL being unplanned, including students lacking technological equipment, lacking digital skills, unstructured content, missing human interaction, and lacking support from family [11]. Students also reported having greater distractions, poorer focus, minimal support from academic staff, and increased workload [12]. Overall, the rapid rollout of OL left students dissatisfied with their learning experience, and experiencing increased anxiety about how the pandemic would affect their studies [13, 14]. As such, the challenges of OL were found to not only impact on the learning experience of students but had consequences for their mental health.

Mental Health

Prior to the pandemic, studies had suggested university students experience heightened levels of mental health problems [15, 16]. It was estimated that 12–46% of all university students suffer mental health disorders, with anxiety, mood, and substance use disorders cited as the most common [17]. Mental health in students worsened during the pandemic, with early in the pandemic (May–June 2020) more than half (61.30%) of respondents to a cross-national survey in Europe reporting greater perceived stress, along with increased anxiety (30%) and depressive symptoms (40.30%) [18]. These high prevalence rates were sustained throughout the pandemic (July 2021) with rates found of mental health problems found to be as high as 75% in some student samples [19]. Potential reasons for university students experiencing poorer mental health include complex and conflicting demands such as academic expectations, managing finances, and balancing a personal life [20, 21]. Whilst protective factors such as peer interaction and remaining healthy have been found to bolster well-being [22, 23], OL does not always facilitate these protective factors for university students.

Students who have switched to OL often report feeling isolated from their peers and are required to learn new techniques and skills to adapt to OL platforms that can be stressful [24]. Furthermore, recent research has highlighted that majority of university students undertaking urgent unplanned OL experienced an increase in stress, anxiety, and depression [13, 25]. In particular, students engaged in urgent unplanned OL expressed that some of the factors that contributed to their poorer well-being were worrying about lack of social support, difficulty concentrating, disruptions to sleep patterns, decreases in social interactions, and worries about academic delays and academic performance [13, 26]. This evidence demonstrates how the transition to urgent unplanned OL impacted on mental health. It is also expected that these mental health challenges negatively impacted on academic success. Longitudinal research has demonstrated a reciprocal relationship between mental health and academic success, whereby poorer well-being at time one predicts poorer academic engagement at time two, and that poorer academic engagement at time one predicts poorer well-being [27]. Given these reciprocal relationships, it is important to look at the impact that the transition to OL had on both mental health challenges and key academic skills such as academic engagement and academic self-efficacy (ASE).

Academic Engagement and Self-Efficacy

Aguilera-Hermida [6] argued that in the context of implementing urgent unplanned OL, individual characteristics of students, such as level of academic engagement and self-efficacy, are important in determining their experience of OL. Academic engagement is a multifaceted construct, which is broadly defined as the extent to which a learner is interested in and participates in an educational initiative [28]. When a student is engaged in their learning, they demonstrate interest, sustained effort, and persistence and engage in self-regulation with the intention to engage in active learning [29]. Understanding the extent to which students were actively engaged in their learning at the beginning of the urgent transition to OL and after a period of adjustment is important.

An additional factor that has consistently been demonstrated to have an association with academic engagement and academic performance, irrespective of learning environment, is ASE. ASE is defined as a person's confidence that they can successfully complete academic tasks, based on previous experiences, abilities, and attitudes [30]. Studies have illustrated that lower ASE is associated with poorer engagement and poorer academic performance when studying face to face [31] and online [32, 33]. Mental health has been shown to negatively impact on ASE, with individuals experiencing higher levels of stress and poorer social support having lower of levels of ASE [34, 35]. Given that those students who believe that they are not capable of completing certain academic tasks appear to have poorer academic outcomes, understanding the complete experience of students, and factors such as mental health that might hinder the development of their ASE is important.

Purpose of the Present Study

With the ongoing pandemic, and the resulting lack of stability and predictability with students being required to study OL, it is important to understand the long-term impact that OL has on the entire student experience including their perceptions of OL, their mental health, and their engagement with learning. To date most studies examining each of these aspects have utilized cross-sectional designs immediately post the introduction of urgent unplanned OL and employed quantitative methods. Investigating the student experience across multiple time points is important to understand whether students were able to adapt to the changes in their experience that originally occurred with the rapid transition to OL. Furthermore, taking a mixed-methods approach will allow for a deeper understanding of the student experience.

Therefore, the aim of the current research is to investigate the university student experience across Australia at two time points in 2020. Utilizing a large national sample of students from an Australian University (AU), a mixed-method approach was taken to investigate the benefits, challenges, and adaptations in the student experience during the first year of the pandemic. This study will also investigate how the pandemic initially and continued to affect mental health, and academic engagement and ASE during the first year of the pandemic. By investigating the good, the bad, and the different of the student experience, this research will be able to provide greater clarity on what students need from their learning experience as we continue to live with pandemic uncertainty.

Method

Participants

Time Point 1

Eight hundred and twenty-four students attending an AU from different states (campuses in NSW, VIC, QLD, and ACT) participated in this study from mid-May to the beginning of June 2020. Students at undergraduate and postgraduate levels were invited to participate via announcements on their learning platforms. Participants were offered either course credit or entered into a voucher draw depending on the course they were enrolled in. The majority of participants were from the Faculty of Health Sciences (>90%). The average age of participants was 22.76 years (SD = 6.48) with 85% identifying as female. At the conclusion of the questionnaire, participants were invited to provide their contact details if they wished to be contacted to participate in future research, with 501 (60.8%) providing their contact information.

Time Point 2

A total of 254 participants who agreed to be contacted again at time point 1 (T1) participated in time point 2 (T2) (50.7% of those contacted) from mid to end of October 2020. Of those who agreed to participate, 82.3% identified as female, and the mean age was 23.25 years (SD = 7.17). Of participants who completed the study, 60.9% were able to return to campus for some (but not all) face-to-face classes, whilst 39.1% remained completing online only. There were no significant differences in age, gender, or chosen degree between those who did and did not choose to participate in the follow-up suggesting no systematic bias in the sample. See Table 1 for demographic data.

Table 1.

Demographic characteristics of participants (%) at T1 (N = 824) and T2 (N = 254)

Demographics	T1, % (n)	T2, % (n)
Current residence
VIC	43.7 (360)	54.3 (138)
NSW	38.5 (317)	35.8 (91)
QLD	14.1 (116)	7.1 (18)
ACT	3.5 (29)	2.8 (7)
Study load
Full time	92.6 (763)	92.9 (236)
Part time	7.4 (61)	7.1 (18)
Highest level of education
High school	48.4 (399)	44.9 (114)
<High school	0.4 (3)	0.4 (1)
Commenced university	26.9 (222)	34.3 (87)
Undergraduate	12.6 (104)	10.2 (26)
TAFE	9.2 (76)	8.3 (21)
Postgraduate	2.4 (20)	2.0 (5)
Living arrangements
Home with parent/s	62.5 (515)	65 (165)
Renting with others	21.5 (177)	20.1 (51)
Homeowners with others	5.1 (42)	5.5 (14)
Paying board	4.7 (39)	5.5 (14)
Renting alone	3.9 (32)	2.4 (6)
Homeowners living alone	0.5 (4)	0.8 (2)
Other	1.8 (15)	0.8 (2)
Current hours of paid work (weekly)
0−7	58.9 (485)	48.8 (124)
7−14	14.3 (118)	20.1 (51)
15−21	13.6 (112)	13.0 (33)
22−28	6.6 (54)	9.8 (25)
29−35	3.9 (32)	4.3 (11)
36+	2.8 (23)	3.9 (10)

Measures

Survey

Participants completed an online survey taking approximately 30 min to complete as part of a larger study. Only demographic information and the questionnaires relevant for this study are reported.

Student Experience Open-Ended Questions

T1. Participants were asked to respond to two open-ended questions. These were: “What have been the best parts of learning online?” and “What have been the hardest parts of learning online?”

T2. Participants were asked to respond to five open-ended questions. These questions were:

1. What were the best parts of online study?

2. What were the worst parts of online study?

3. Knowing the challenges to keep yourself motivated in semester one, what have you done to maintain and/or increase your motivation levels for semester two?

4. What was your experience of return to face-to-face classes?

5. If you are returning to University in 2021, what are the aspects that you would definitely want to be part of that experience?

Depression Anxiety Stress Scale 21-Item [36]

The Depression Anxiety Stress Scale 21-Item (DASS-21) is a 21-item scale with three subscales measuring presentation of depression, anxiety, and stress with seven items on each. Participants responded on a 4-point Likert scale from 0 = “did not apply to me at all” to 3 = “applied to me very much, or most of the time” to statements such as “I felt I was close to panic” and “I felt down-hearted and blue.” The items of each subscale are added with higher scores, indicating higher levels of depression, anxiety, and stress. Internal consistency is good with Cronbach's alpha found to be >0.84 across all subscales for both time points.

Academic Engagement

Participants were provided with nine statements regarding their experiences of academic engagement prior to and during COVID-19 and OL. Questions relating to student engagement pre-COVID-19 were completed retrospectively at T1, whilst post-COVID-19 questions were answered regarding their current experience at T1 and T2. Statements were rated on a 5-point Likert scale from 1 = “never” to 5 = “always” and included questions on keeping up with weekly course content, completing assignments and weekly readings, and feeling supported by staff and students. Example statements are “Pre-covid I kept up with the weekly course content” and “Post-covid I kept up with the weekly course content.”

Self-Efficacy for Learning Form [37]

The Self-Efficacy for Learning Form (SELF) questionnaire provides a measure of students' ASE by assessing self-regulatory processes present during academic learning, particularly, in studying, note taking, and test preparation. Participants answered 19 questions such as “When you miss a class, can you find another student who can explain the lecture notes as clearly as your teacher did?” rated on a 5-point Likert scale from 1 = “definitely cannot do it” to 5 = “definitely can do it.” The questionnaire was summed with a higher score representing greater ASE. Previous psychometric analyses have determined SELF to have high internal reliability and validity with Cronbach's alpha in this study found to be >0.91, suggesting high internal consistency for T1 and T2.

Procedure

The procedure at both time points was identical. Both surveys were completed by participants as a part of a larger study at the conclusion of first and second semesters of 2020. The study was completed anonymously via the online survey platform Qualtrics in participants own time. Following consent, participants completed a series of demographic questions, along with questions about their engagement with their studies and the open-ended questions about their experiences. The DASS-21 and SELF were then completed in a randomized order along with other questionnaires in the study.

Quantitative Analysis

To examine the levels of academic engagement experienced by students prior to and during COVID-19, one-way repeated measures ANOVAs were conducted on each item of the engagement scale, comparing means from pre-COVID-19, and during COVID-19 at T1 and T2. Additionally, paired samples t tests were conducted between T1 and T2 data to examine time-point differences on ASE, and the subscales of the DASS-21.

Qualitative Coding

To understand the responses to our open-ended questions, content analysis was conducted. Content analysis involves developing codes from the responses of participants, using words or phrases that are used by the participants to create major themes/categories that other responses fall into [38, 39]. For this research, three team members (MKMN, OM, RG) utilized the NVIVO software (QRS International, 2020), reviewed responses, and identified common themes present in responses. Codes were then created based off these themes, which were reviewed collaboratively by the research team to ensure validity of data as well as refinement of codes and the development of congruent themes as necessary. Following consolidation of data, the decision was made by the research team to combine responses to two questions in T2 to create a more meaningful understanding of participants. This is discussed further in the results.

Transparency and Openness

We describe our sampling plan, all data exclusions, all manipulations, and all measures in the study. Data are not available as they are being included as part of the analysis for an additional study. Processed data will be made available upon request. Data were analysed using IBM SPSS version 28 and NVIVO software [40]. This study's design and its analysis were not preregistered due to the urgent rollout of the survey early in the COVID-19 pandemic.

Results

Mental Health

Paired samples t tests were conducted to understand how student mental health changed over the course of the pandemic. Examination of the DASS subscales revealed that there was no significant difference in depression for T1 (M = 14.81, SD = 10.51) and T2 (M = 15.62, SD = 10.7), t (234) = −1.38, p = 0.168, d = −0.09. However, there was a significant small difference in anxiety, with anxiety decreasing from T1 (M = 17.07, SD = 10.17) to T2 (M = 14.99, SD = 10.42), t (234) = 3.48, p < 0.001, d = 0.23. Additionally, there was a significant small difference in the stress subscale, with stress increasing from T1 (M = 16.14, SD = 10.26) to T2 (M = 17.49, SD = 10.16), t (234) = −2.49, p = 0.013, d = −0.16.

Academic Engagement and ASE

To examine changes in student engagement with their studies, a series of one-way repeated measures ANOVAs were conducted comparing pre-T1 to T1 and T2. In cases of a violation of sphericity, a Huynh-Feldt correction has been used. Significant omnibus ANOVAs were found across all questions, indicating differences in student engagement with their studies across the time points (see Table 2). Bonferroni-adjusted comparisons revealed that for keeping up with weekly content (Q1), would read lecture slides (Q2), I would do assignments well in advance (Q5), I would submit my assignments on time (Q6), I felt supported by the academic staff (Q8), and I felt supported by the university as a whole (Q9), students reported significantly lower levels of engagement at both T1 and T2 in comparison to pre-T1, with no difference reported between T1 and T2. For would do weekly readings (Q3), I would attend my classes (Q4), and I would talk with my fellow students about my units (Q7), students reported significantly lower levels of engagement at both T1 and T2 in comparison to pre-T1; however, T2 levels were found to be significantly higher than T1, suggesting a rebound in levels of engagement however not to the level of pre-T1.

Table 2.

Means, standard deviations, and within-subjects effects of student engagement across time points

	Pre-T1		T1		T2		df	F	Pairwise comparisons
	M	SD	M	SD	M	SD
Q1: kept up with weekly course content	4.14	0.86	3.25	1.21	3.40	1.16	2, 486	72.6**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2: ns
Q2: would read the lecture slides	4.38	0.84	3.58	1.30	3.66	1.17	2, 486	61.69**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2: ns
Q3: would do weekly readings	3.19	1.30	2.32	1.26	2.58	1.15	1.86, 453.06	70.79**	T1 < pre-T1 ** T2 < pre-T1 ** T1 < T2**
Q4: I attended my classes	4.64	0.66	3.97	1.17	4.15	0.95	1.91, 463.78	49.68**	T1 < pre-T1 ** T2 < pre-T1 ** T1 < T2*
Q5: I would do assignments well in advance	3.39	1.29	3.04	1.35	2.94	1.34	1.92, 465.96	13.32**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2: ns
Q6: I would submit my assignments on time	4.73	0.61	4.43	1.03	4.30	1.13	2, 486	25.50**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2: ns
Q7: I would talk with fellow students about my units	4.16	1.25	3.09	1.41	3.30	1.38	2, 486	75.09**	T1 < pre-T1 ** T2 < pre-T1 ** T1 < T2*
Q8: I felt supported by the academic staff	4.07	0.99	3.25	1.28	3.11	1.27	1.94, 471.58	77.37**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2:ns
Q9: I felt supported by the university as a whole	3.85	1.11	2.93	1.33	2.81	1.26	1.91, 464.76	91.65**	T1 < pre-T1 ** T2 < pre-T1 ** T1 − T2:ns

ns, non-significant.

^*p < 0.05.

^**p < 0.001.

Paired samples t tests were conducted to understand how student ASE changed over the course of the pandemic. There was no significant difference between ASE scores between T1 (M = 63.73, SD = 11.72) and T2 (M = 63.88, SD = 12.64), t (241) = −0.24, p = 0.808, d = −0.02.

Student Experiences

Best Aspects

At both T1 and T2, participants were asked to provide their opinions regarding the best aspects of OL. At T1, there were a total of 11 themes identified compared to 7 at T2. These were combined to include a total of 12 major themes representing responses across the pandemic (see Table 3).

Table 3.

Best aspects of OL % reported at T1 (N= 824) and T2 (N = 254)

Theme	% (n)		Description	Quote
	T1	T2
1. Increased convenience	50(412)	61.07(80)	This theme refers to aspects such as extra time available due to no travel, greater control over time and place to study, and enjoying learning in a comfort space	“enjoying studying from the comfort of my own home” − T1 “no travel; can choose when/where to study; doing less unnecessary things” − T2
2. Flexibility	38.59 (318)	38.93(51)	This includes being able to choose schedules more freely and incorporating a study/work/life balance that is more tailored to the individual	“the flexibility to come back and do catch up work when needed” − T1 “being able to attend most classes without clashing with work arrangements” − T2
3. Increased well-being	15.29(126)	−	Being able to address well-being needs more easily due to OL. This included spending more time with loved ones and engaging in self-care	“it has been much more relaxed, and it feels like less pressure” − T1
4. Increased self-efficacy	12.28(101)	−	Students more in control of their learning, including feeling greater interest in content and increased confidence in their academic abilities	“As I am in front of my laptop and working independently, which develops my critical thinking analysis, which allows me to participate more online” − T1
5. Increased support	9.71 (80)	8.4 (11)	Students feeling that support from tutors and lecturers in particular was helpful regarding communication and assessments during the pandemic	“constant support and genuine care from all my tutors and lecturers” − T1 “The context lecturers are putting up to heal with exams and assignments has been more helpful and informative …” − T2
6. Peer connection	9.59 (79)	6.12 (8)	Largely involving getting to know peers who they may not have met on campus and feeling a sense of comradery with those dealing with a similar situation. Also involved working together with peers on assessments and developing study groups	“interacting with peers I previously would not have due to sitting next to the same people in class” − T1 “… getting to communicate with peers through social media and creating study groups …” − T2
7. Technology use	−	9.16 (12)	Referring to OL technology such as break out rooms and access to recorded lectures	“Being able to look back on content I have missed …” − T2
8. Nothing	7.89 (65)	5.34 (7)	Many responses simply stating that there were no best aspects or that their preference was for face-to-face learning	“None of it, I learn better in classes” − T1 “Nothing” − T2
9. Decreased academic stress	5.83 (48)	5.34 (7)	Involved feeling less stressed about getting assessments completed and having more time to spend on them	“Less stressed about completing other work” − T1 “… having exams online has been a lot less stressful for me …” − T2
10. Reduced general stress	2.43 (20)	−	Encompassed stress/anxiety associated with the social aspect of university that was no longer an issue. Also included feeling more relaxed and happier to learn	“I'm less socially anxious learning online” − T1
11. Quick university response	2.18(18)	−	Participants felt the university accommodated for the pandemic quickly and appreciated that they were able to continue their studies	“Able to continue learning in this environment” − T1
12. Everything	0.36 (3)	−	All parts of OL were good	“Everything” − T1

A comparison of themes revealed six common positive aspects of OL across the two time points. The two most frequent responses, increased convenience and increased flexibility, were the top two for both T1 and T2. However, increased convenience had a greater response rate at T2 with 10% more responses than T1. Participants at both time points offered similar responses, describing the lack of commute and ability to choose times that suited individual needs to study as positives of OL. The other common themes across time points included increased support, peer connection, nothing, and decreased academic stress. For each of these, the frequency at T2 was less than T1, but included similar responses including support from lecturers and tutors (increased support), making new friends through zoom tutorials (peer connection), and feeling more at ease completing assessments and engaging in online discussions (decreased academic stress).

Examining the dissimilar aspects between time points, it can be seen that there were five themes that participants identified at T1 that were not mentioned at T2. Of note, increased well-being and increased self-efficacy, third and fourth common at T1, were not mentioned. These themes included responses referring to engaging in self-care activities such as exercising and spending time with family (increased well-being), as well as thriving in an independent work environment (increased self-efficacy). As for themes unique to T2, there was only one, technology use. Participants at T2 felt that as OL continued, teachers gained a better understanding of online technologies and created a better learning experience.

Hardest Aspects

Participants were also asked to share their opinions regarding the hardest aspects of OL. There were thirteen themes identified at T1, and nine at T2. These created a total of 15 themes across time points and are presented in Table 4. For hardest aspects, there were seven themes that endured. The most common response at both T1 and T2 was lacking motivation with a slight increase in frequency at T2. Participants revealed that they struggled to both increase and maintain motivation, often reporting that it decreased instead. They expressed a certain feeling of monotony at attending online classes, particularly during lockdown periods. Engagement was a second theme that was common to both but had a higher percentage at T2. This theme was categorized with difficulty attending to class content as well as assessments.

Table 4.

Hardest aspects of OL % reported at T1 (N = 824) and T2 (N = 254)

Theme	% (n)		Description	Quote
	T1	T2
1. Motivation	33.5 (276)	35 (49)	This theme categorized by experiences of lack of energy and difficulty focusing amid concerns of the pandemic. Participants had difficulty with maintaining a more independent learning style	“staying motivated has been undoubtedly the hardest part, everyday feels like the same day. It is difficult to keep motivated” − T1 “just trying to stay motivated and trying to stay alert and fully aware throughout classes has been difficult” − T2
2. Engagement	21.6 (176)	30.71 (43)	Difficulty attending to class content online, including struggling to understand assignments and focusing on coursework. Some noted an increase in distractions in the home environment	“I find it more difficult to stay focused during these classes when not engaged in a physical class” − T1 “not engaging in the content as well as normal and thus not being able to understand content easily” − T2
3. Online set up not working	29.13 (240)	−	Included connection issues, teachers not utilizing the platform to capacity, and students not engaging in class discussions by having their camera off and sound muted. This was distinct from specific technological issues	“Zoom tutorials are sometimes difficult in regard to allowing people to talk and free flowing conversation as there is often a lag and people will talk all at once” − T1
4. Lack of university support	21.97(181)	28.57 (40)	This theme is classified by students feeling as though the university was not providing adequate support emotionally or academically. Also included inadequate communication from lecturers as well as the university itself	“no support from the university in terms of being communicated with what is happening” − T1 “lack of support from teachers, feels very disassociated from us so it's difficult to connect. Also everything we need to do ourselves and learn ourselves making it a lot more difficult” − T2
5. Social isolation	25.85 (213)	25.71 (36)	Related to feelings of loneliness and inability to connect closely with others both in their course and with family and friends. Having reduced social interactions greatly impacted the university experience for many students	“I have really struggled with the zoom tutorials and not being able to make friends/connect socially” − T1 “reduced feeling of group engagement, feeling a bit isolated from my peers and the staff, lack of face-to-face interaction” − T2
6. Self-sabotage	25.61 (211)	22.86 (32)	This theme refers to students experiencing difficulty setting up the required space to work and then fully participating without being distracted by other things. It also involves the mind set the students were in and encouraging themselves to learn	“… working at home effects my learning negatively as I don't have the same structure, or location setting to feel encouraged to study” − T1 “Getting myself to attend my zoom classes and do my work/assignments” − T2
7. Creating own pace	21.97(181)	−	Associated with difficulty taking control of their own learning and creating a pace that was both manageable and sustainable. The lack of structure associated with OL was challenging	“it is so overwhelming for me to maintain a schedule and do work and stay on one task” − T1
8. Technical issues	14.8 (122)	6.43 (9)	Largely categorized by difficulties connecting to Internet, including problems with sound and video not working for online lectures and tutorials	“Technological or issues with internet connections” − T1 “internet issues, never being able to hear anyone talking and missing vital information …” − T2
9. Lack of appropriate study environment		7.86 (11)	References students creating a study space free from distractions, particularly those created by other household members	“Trying to concentrate with (at times) the whole family being home” − T2
10. Difficulties with placement	t 9.34 (77)	−	Included not having the required skills to attend placements due to not having practical classes on campus	“not being able to physically attend my practical nursing classes at university and learn the content practically” − T1
11. Mental health troubles	7.89 (65)	−	Feeling an increased sense of disruption that has impacted mental capacities including knowledge retention as well as increase stress and worry	“I am feeling under a lot of pressure with online study as I am a person who cannot understand the concepts” − T1
12. Less value for money	4.13 (34)	−	Students feeling classes were shorter and that they were spending more time teaching themselves class content than should be necessary	“Having to teach myself every step of the way when I pay for a quality education and teachers.” − T1
13. Nothing	2.43 (20)	3.57 (5)	Most answers responding with simply nothing, and some elaborating that their preference is for online study	“Nothing, found it a lot easier and prefer it actually” − T1 “I didn't find anything hard I liked online learning” − T2
14. Other obligations	3.28 (27)	−	Included a variety of responses including balancing study with parenting or other familial responsibilities, or with increased responsibility at work such as for frontline workers	“Having my 6 year old run around/home schooling him while trying to do classes and assignments” − T1
15. Everything	−	1.43 (2)	Referring to all aspects of OL	“Everything. Lectures, poor efforts of tutors, assignments, working conditions” − T2

Three other common themes with similar response rates were lack of university support, social isolation, and self-sabotage. At both time points, students felt that the university and their lecturers were not providing adequate support, including not communicating effectively (lack of university support). Further, participants struggled with being socially isolated from peers, friends, and family, with lack of connection to peers particularly affecting their study experience (social isolation). Across the year, participants were also affected by their own inability to reduce distractions and maintain a self-efficacious attitude to learning (self-sabotage).

At T1, participants had also identified six themes that were not pervasive to T2. Most common of these were online set up not working and creating their own learning pace. This referred to difficulties with peers and staff engaging with the online platform as well as each other, and trouble engaging in highly autonomous learning. Other uncommon themes present at T1 included difficulties with placement, mental health issues, less value for money, and other obligations (such as managing familial and work responsibilities). Furthermore, there were only two themes new to T2 which were struggling with a lack of appropriate study environment and feeling as though the entirety of OL was a hard aspect.

Extended Questions

To gain a better understanding of student experiences during OL at T2, participants were asked to elaborate on a few additional areas that had not been addressed at T1. Due to the high concern for motivation at T1, participants at T2 were asked to describe how they had increased or maintained motivation in semester two. Six key themes emerged: effective study strategies, engaging in self-care, motivation decreased, connecting with others, goal reminders, and no change in motivation. Table 5 presents percentages, descriptions, and quotations for each theme.

Table 5.

Strategies for increasing or maintaining motivation at T2

Theme	% (n)	Description	Quote
1. Effective study	43.86 (50)	Characterized by implementing effective strategies to help engage with studies. These may include study plans, doing weekly readings, and creating a distraction-free workspace	“I have tried to set up a good working spot for myself in my room so I am able to get work done …” and “I studied every week and did pre-reading”
2. Self-care	32.46 (37)	Largely included activities such as exercise, mindfulness exercises, and engaging in health eating and sleeping habits. Participants tried to ensure that they were looking after themselves physically and mentally	“exercise more to maintain better mental health and lessen my anxiety” and “dedicated a day for myself to recharge from the workload … sit down for an hour and do some crafting work or bullet journaling”
3. Motivation decreased	15.79(18)	Referred to participants reporting that they were experiencing considerably lower motivation than in the first semester	“I have lost all motivation, I am tired, I just want a break” and “I just try to keep up with my work weekly but my motivation has decreased substantially because I'm bored and have nothing stimulating to do”
4. Connecting with others	11.40(13)	Categorized by participants seeking out connections with peers to help each other get through the semester. Included creating study groups and communicating with others in the same boat	“Made stronger connections with friends in the same units as me” and “I have set goals with friends where we check in and make sure we have all done the work”
5. Goal reminders	10.53(12)	Participants reminding themselves of what goals they had regarding academic achievement or degree completion	“Kept reminding myself of the end goal” and “strive to get better results”
6. No change	5.26 (6)	This theme encompassed students who had not identified any issues with motivation and did not reflect on any strategies that may have helped	“I enjoyed online learning, motivation was not an issue for me” and “I was always pretty motivated to study, I don't need to have face-to-face classes to know that I need to be studying”

To try and bolster motivation, participants found implementing study plans, pushing themselves to do prescribed readings, and removing distractions from their workspace to be most effective. Following this, engaging in both physical and mental well-being activities such as exercising, following a healthy diet, and mindfulness was helpful in maintaining motivation. Spending time with friends and family when possible was a positive motivating factor for participants as well as working together with peers. Another motivation strategy was also participants reminding themselves of their goals for study whether it was to achieve a certain grade for a unit or completion of their degree. Some students, however, felt that they had not had difficulties with motivation at all and did not provide strategies for improvement. Despite the solid strategies, many students felt that motivation had decreased further in semester two and were overwhelmed, understimulated, and lonely, or otherwise felt that motivation had neither increased nor decreased since semester one.

Additionally, participants were asked to share their experiences of returning to face-to-face learning in semester two (where it had been possible), and what their hopes were for learning delivery in the future. These questions, whilst presented separately to participants, were later combined to provide a more comprehensive understanding of students' feelings regarding return to face-to-face learning. Responses were coded into five key themes: return to face to face, social interaction, choice of online versus face to face, more support from the university, and concern for new normal (see Table 6).

Table 6.

Experiences of and hopes for return to university at T2

Theme	% (n)	Description	Quote
1. Return to face to face	56.15 (105)	This theme was categorized by student's being grateful to return to campus if they had had the opportunity, or that they hoped that they may be able to return to campus in the following year	“it was a massive relief; I really preferred f2f classes as I learn better; engaged better; and genuinely enjoy uni a lot more” and “go back to face to face, even if it means social-distancing and masks etc would have to be implemented”
2. Social interaction	17.65(33)	This included both enjoying having in-person peer interactions again if it had been possible, and hoping that there would be more opportunities for social activities in the future	“seeing people again would be great. I kinda miss chatting to random people from tutorials” and “… I found the learning very beneficial and the social contact really valuable”
3. Choice of online versus face to face	16.58 (31)	Refers to participants acknowledging the benefits and limitations of both online and face-to-face learning, and posits that having a choice of learning format would be appreciated	“I would like to have to have the option for classes to remain online” and “the ability to choose online lectures, rather than relying on terrible lecture recordings of pre-COVID times”
4. More support from university	11.76(22)	Included having greater access to staff, better organization, and more leniency regarding assessment submission	“More supportive staff and flexible with assignments submission …” and “more support and better communication”
5. Concern for new normal	10.16(19)	Categorized mostly by fear of infection and adapting to COVID-19 safety measures on campus	“Feel unsafe and scared of infection as it can affect my placemen t completion” and “it was weird to get used to all the Covid restrictions and restraints that were put on the university and in the classrooms”

Over half of respondents reported that they would like to return to face-to-face learning with those who had had the opportunity to already come back reporting that it was an immense relief to return to campus. Similarly, those who had not yet returned responded that they hoped they would be able to for the following academic year. Furthermore, participants suggested that being able to have the choice of returning to campus or remaining online would be appreciated.

Participants also reported that they would greatly appreciate increasing their social connections through university as well as being able to interact with others outside the academic setting post-pandemic. Additionally, some participants replied that increased support from university staff including greater compassion for student struggles would be valuable. A few participants also expressed some concern for what the new normal would be in returning to campus with regard to the pandemic and managing infection risks. Those that had already returned to face-to-face shared that mask wearing and sanitization were considered good measures employed by the university.

Discussion

The aim of the current study was to examine the mental health, academic engagement, ASE, and experiences of OL for university students at two time points during the COVID-19 pandemic. This study utilized a large national sample from an AU and applied a mixed-methods longitudinal approach to understanding the experiences of university students. There were no significant differences in ASE and depression between the two time points. Anxiety was found to significantly decrease from T1 to T2; however, stress was found to significantly increase from T1 to T2. Students reported significant decreases across the board in engagement with their studies at both time points compared to before COVID-19 highlighting the impact that the urgent transition to OL had on their studies. When examining their subjective experiences of studying during the pandemic, students reported a range of positives and negatives of OL. Whilst a number of these positive and negative aspects of OL remained constant across the two time points, some themes, such as increased well-being, increased self-efficacy, use of technology, and managing other obligations, rescinded or emerged, which suggests that students adapted to their learning environment or that their attitudes towards OL changed. These outcomes will be discussed in turn.

Mental Health

Cross-sectional research has consistently demonstrated that there were increases in the prevalence of psychological distress for university students during the pandemic [18, 19]. In this study, students on average fell into the mild to moderate scores for depression, anxiety, and stress across both time points. The longitudinal nature of this finding suggests that these high rates of psychological distress did not just peak at the outset of the pandemic and then return to normal levels, but rather that this was sustained across time. This goes against the finding by Robinson et al. [25] who found that mental health outcomes had returned to “pre-covid” levels by mid-2020. Anxiety was found to be significantly higher in T1 compared to T2, with the average in the “severe” range. This may be a factor of the novelty and fear of COVID virus itself, combined with the sudden and dramatic change to the way of life that occurred at T1. Six months later at T2, the decrease in anxiety could reflect a reduction in this fear; however, it is important to note that average levels of anxiety remained within the moderate range. Understanding and acting on these sustained mental health concerns is critical given that long-term mental health disorders account for 3.2–11.4% of university non-completions [41]. It is necessary for universities to adopt measures to better support the mental health needs of their students, and that these measures need to be sustained over time, rather than implement as a single quick fix.

Academic Engagement and ASE

Across all questions, students reported poorer engagement in their studies at both T1 and T2 compared to retrospectively reported pre-covid levels. Broadly students reported being unable to keep up with their weekly content and their assessment tasks, and feeling reduced support from staff and the university. This is consistent with findings that students struggled to engage with their studies when they transitioned to OL [13]. Novel to this study however is that for some activities, including doing weekly reading, attending classes, and engaging with fellow students, there was a rebound effect with significant increases in these behaviours from T1 to T2. Whilst the level of these activities was not back to pre-covid levels, this finding does suggest that students adapted to their learning environment. This aligns with the qualitative analysis related to the strategies that students implemented to increase their motivation to study, whereby students reported that they were pushing themselves to do the required readings and engaging with peers more. Together this highlights that students engaged more with certain activities because they felt these activities improved their motivation to study. It is important to acknowledge however that the questions related to academic engagement were developed for the purpose of this study and as such they do no encompass all of the signs of engagement such as acquisition of deeper learning [29]. Future research should attempt to capture not just participation in learning activities but also how whether there are signs of sustained effort and self-regulation.

ASE is an important predictor of student outcomes regardless of learning environment [31, 33]. This study found no significant difference in ASE between T1 and T2. This finding suggests that even following an additional 6 months of OL, students did not report growing confidence in their academic skills. Given the significant moderate relationship between ASE and academic performance [31], it would be important to understand whether stagnant growth in ASE has long-term impacts on academic performance. Similarly, it would be prudent to determine if OL is a casual factor in this lack of improvement in ASE, given that many universities have continued to remain OL or in a blended-learning format.

Student Experiences

Best Aspects of OL

This study built on the emerging research into the benefits and challenges of urgent unplanned OL during the pandemic by taking a qualitative approach to examining student experiences. When asked about the best aspects of learning online, students identified 11 different themes at T1 and seven themes at T2. Overwhelmingly across both time points, the best part of OL was the increased convenience, followed by flexibility. Convenience and flexibility are common positives of OL even prior to the pandemic [12, 42]. What is important to know however is that in this study all participants had not originally chosen to study online and were enrolled in face-to-face learning. The fact that convenience holds as the most frequently reported benefit of OL at both time points suggests that these perceived benefits of OL are not a novelty. This may have longer term implications for how students will prefer to study moving forward and whether they will be willing to return to face-to-face classes. For example, commonly cited by participants was the significant reduction in perceived time wasted due to travelling to campus, and issues with rigidity of their schedule with face-to-face classes.

Both increased support from staff and connection with peers were also consistently reported by between 5 and 10% of students across the two time points. In opposition to the quantitative results, this suggests that almost 10% of the sample at both time points reported that since moving to OL, they have received more support from both staff and the university more broadly. Approximately 10% of students reported that through OL they felt classes were more personal and had a greater level of connection and contact with teaching staff. Maintaining that sense of connection and personal contact in the new “COVID-normal” learning environment is going to be important.

Similar to the findings related to support from staff and the university, there is a juxtaposition between the quantitative findings and the qualitative findings related to peer collaboration. The largest decrease in the academic engagement findings was related to interaction with peers at T1; however, approximately 10% of students reported that they felt a greater connection with peers since moving online. Students reported that they experienced an increase in peer collaboration, including feeling their peers were more willing to support each other and work together effectively. This is advantageous, as the achievement of positive learning outcomes in OL for students is facilitated by social connection with others [43].

Whilst the above themes were present at both time points, there were some differences between the time points. In a change for the positive, approximately 10% of students reported that technology platforms used such as zoom supported and improved their learning at T2, whilst at T1, these technologies were seen as a hindrance to learning as everyone adapted to the technologies. Changes in themes between T1 and T2 however were not always positive, with students no longer reporting that positives of OL included increased well-being and increased self-efficacy. In T1, 12–15% of students reported that OL improved their overall well-being and increased their confidence in their academic abilities; however, no students reported either of these outcomes at T2. This could be a reflection of students having adapted to their learning environment, that they no longer perceived OL as a factor affecting their well-being overall. In T1, students reported that OL afforded them the opportunity to engage in more self-care, exercise, and time with loved ones which are known to improve well-being [23]. Highlighting these benefits to students when studying OL might assist in improving well-being.

It is also important to note that a small percentage of participants stated that they did not believe there to be any positive aspects to OL at both time points. This highlights the difficulties that some students can experience when forced into a learning environment that does not work for them and they have not chosen.

Hardest Aspects of OL

When asked about the best aspects of learning online, students identified 13 different themes at T1 and nine themes at T2. The two most common themes reported at both T1 and T2 were a lack of motivation and engagement. Research into factors affecting OL argued that this lack of motivation and reduced engagement could be due to students experiencing high levels of stress related to COVID-19 impacts, such as health of vulnerable loved ones, financial stability, lack of social support, and academic delays [13, 26]. This study showed however that lack of motivation was sustained, and reduced engagement actually increased over time, which demonstrates that factors related to the novelty of the onset of the pandemic were not the only issues causing these to occur. Lack of motivation is not unique to OL during the pandemic, with past studies demonstrated to be a factor of the OL environment, and is often the cause of failing to engage and dropping out of OL [44]. Maintaining motivation and increasing engagement levels for students in an OL environment are an ongoing challenge for universities and one that needs to be resolved so to facilitate student retention. Suggestions put forward by students on how they improved their own motivation and increased engagement are discussed in more detail below.

Two common and consistently reported issues with OL across both time points were social isolation and lack of university support. Interestingly, this is at odds with the participants who reported that OL better facilitated peer connections. For those who struggled with the lack of social interaction, they reported missing regular in person interaction with peers. Research highlights that perceived lack of social interaction whilst engaging in OL is one of the most common predictors of dropout and lack of engagement [43]. Unfortunately, COVID-19 and lockdown measures likely exacerbated this feeling of social isolation whilst completing OL for participants in this study.

Minimal support from the university was another hard aspect of OL reported by over a fifth of students at both time points and increased from T1 to T2. Again, this is in keeping with the quantitative findings but at odds with approximately 10% of students who found that support improved during this time. As research has shown that students are currently experiencing heightened stress, especially around uncertainty about delays in university courses due to COVID [45], it is important that students have clear instructions of course expectations and timelines related to course completion.

Self-sabotage was reported as an issue by over a fifth of students in both time points. This theme referred to students reporting on experiencing difficulty with establishing and engaging with good study practices at home. Of interest, lack of appropriate study environment emerged as a theme in T2 only. Whilst both themes contain notions of distraction being problematic for students, self-sabotage refers to a mindset related to study, whereas lack of environment refers to a physical space. While at T1 some students might have been experiencing difficulty with getting into the mindset to study due to a lack of physical space, it appears that in T2 participants further understand the impact that the physical environment and lack of dedicated study space had on their learning. Understanding this nuance highlights the importance that providing students with study spaces might have on enabling them to get into the right mindset.

Whilst some negative issues were consistent across both time points, students did demonstrate adaptability to the OL environment. At T1, students commonly reported that their online set-up was not working, they struggled to create their own learning pace, and mental health troubles. These factors had all disappeared in T2, suggesting that students were able to adapt to the OL and learnt skills such as how to create their own pace whilst studying online. In T2, students were asked further questions to understand how they were able to adapt to the challenges of OL, and these are presented below.

Motivation

One of the key additional areas of investigation in T2 was determining what strategies students used to increase or maintain motivation given that it was the primary challenge with OL cited at T1. Most commonly students named ways in which they implemented better study strategies such as creating study plans, doing weekly readings, and creating distraction-free workspaces. These findings suggest that whilst students are self-engaging in core academic skills which is demonstrative of good ASE at T2, they are not seeing improvements in their perceived ASE from T1 to T2. The nuance of the comparison between the qualitative and quantitative findings here suggests that whilst some students might be engaging in these skills, they may not be recognizing the benefit it has on improving their capability. Given that students reported engaging in these skills had an impact on their motivation and engagement with study, it is important to ensure that all students are taught not only how to do these study skills but also the benefits of implementing them. Research has demonstrated that embedding these skills into subject-specific content can be beneficial at improving student engagement with the learning of these skills [46].

Students reported that motivation to study increased through non-study-related self-care. Research into self-care in students has found that engaging in more self-care practices reduces academic stress [47, 48], with the findings from this study extending on this to highlight that this engagement in self-care is perceived to improve motivation to study. It is important to note though that the quantitative findings are still demonstrating elevated levels of mental health scores, including stress, in our population. So, whilst a third of the sample recognizes the importance of engagement in self-care and the benefits to improving motivation to study, this did not necessarily translate to better mental health outcomes. An important caveat however is that an idiographic analysis of the mental health quantitative data in comparison to the qualitative data was not conducted in this study, which means that it is not known whether those individuals who did engage in self-care as a motivational strategy also reported lower psychological distress.

Social isolation had arguably the greatest negative impact on mental health during the pandemic [49, 50]. Isolation was reported by over a quarter of the students in this study as being one of the hardest aspects of OL. For a small portion of students, they cited that re-engaging and strengthening relationships with peers was an important factor in improving their motivation during T2. It is important for universities regardless of learning environment to highlight the importance of peer relationships not only for their mental health but also for their academic success.

Students also acknowledged that reminding themselves of their goals for study was a good motivator. The research on whether goal reminder interventions improve student outcomes is mixed, with some studies demonstrating that goal-related interventions improve grades [51] and others demonstrating no discernible impact on grades [52]. The evidence from this qualitative data however demonstrates that for a small but important portion of the student population goal reminders are beneficial. Of note however is that over 20% of students reported that their motivation did not improve or that it decreased in T2. This corresponds with the finding aforementioned that challenges with motivation were the most commonly reported negative aspect of OL in both time points. Unfortunately, this suggests that for almost a fifth of students, OL not only significantly impacted on their motivation to study, but that they could not determine strategies that would assist them to increase their motivation.

Looking to the Future for Universities

Students were asked what they want their future study experience to consist of and overwhelmingly students reported that they wanted to return to face-to-face learning because they were missing social interactions with their peers. Given that social interactions are an important buffer against psychological distress [21, 53], returning to campus and engaging with peers could improve learning and mental health outcomes. Universities have an important role to play in helping reduce social isolation and improve feelings of connection in the “COVID-normal” world by facilitating avenues for students increased engagement with fellow-peers. Universities could invest in spaces aimed at hot-desking that allow students to connect whilst on campus even if they have chosen an OL course.

Returning to face-to-face learning however will need to be balanced with the competing needs for students who are desiring choices in their learning environment. For many students, benefits of OL such as increased convenience and flexibility may make them reconsider whether they will “bother to spend time travelling” to attend face-to-face classes at a set time. This may require universities to think about whether it is now time to move to a permanent blended learning delivery.

Universities can develop strategies aimed at improving mental health and academic engagement. Students reported that increasing interactions with peers and loved ones as well as engaging in self-care practices are beneficial to improving not only mental health but motivation to study. Universities should invest in online psychosocial programs interventions which have been demonstrated to be efficacious at improving mental health outcomes [54]. Implementing this kind of intervention can have the dual benefit of improving both mental health and academic outcomes. Universities both have challenges and opportunities moving forward to provide more options to their students to better support their learning and mental health needs.

Study Limitations

Whilst this study provided an opportunity to examine the experiences of university students, it is worth noting that every university took different approaches to their transition to OL. Whilst there would be similarities in these approaches, the AU examined in this study may have had unique aspects which may have impacted on the student experience. This may impact on the generalizability of the results reported in this study. Furthermore, it is worth noting that whilst this study included a large sample from different states across the country, it was limited in other demographic factors including gender and discipline of study. The majority of the students in this study were female, studying full time and from the faculty of health sciences (which includes degrees such as nursing, psychology, allied health, and exercise science). Given that these degrees are focused on health sciences, there may be differences in levels of understanding factors such as the importance of mental health and self-care due to the nature of their studies. As such, there may be differences in the experiences of this demographic cohort, which may limit the generalizability of these findings. Future research would benefit from taking a more targeted approach to investigate the different demographic cohorts in order to identify student populations that may be at an increased risk of mental health concerns and challenges with study.

Future Research

As the world has begun to transition to a “COVID-normal” way of life, students are engaging in varied learning environments, with some continuing with OL, some doing blended learning and others returning to face-to-face learning. It is important for future research to capture how students are experiencing this new normal. It would be particularly important to determine how students are finding the return to face-to-face learning given that many cited that this was their desired method of learning. It would be useful to know whether this return to face-to-face provides the improvement in mental health outcomes, academic engagement, ASE, and ultimately academic performance. Furthermore, a comparison where appropriate between these different learning modalities on their impact of these factors would be beneficial in shaping how universities progress into the future.

One of the key strengths of this research was in the use of a mixed-method design, which allowed for quantitative and qualitative analysis of student concerns during the transition to OL during COVID-19. The combination of these approaches allowed for the identification of population-based issues such as heightened levels of psychological distress and disengagement with studies, whilst simultaneously understanding that from an idiographic perspective, not all students experienced negative mental health outcomes as a result of this transition to OL. In fact, for a small proportion of the student population, this move to OL afforded them an improvement in their well-being. This mixed-method analysis approach should be considered in future research especially when trying to plan the way forward for student learning as it is evident from these findings that a “one size fits all” approach may not be appropriate.

Implications and Conclusions

The findings from this research have important implications for universities. Consistently across both time points, students reported that they were experiencing mental health concerns and that they did not feel supported by their university. Students are craving additional support from both individual teaching staff and the university more broadly. What is unknown however is what that support looks like and whether what students are asking for is reasonable in terms of the impact that it may have on staff to provide such support. Identifying the greatest areas of need for students to feel supported is therefore necessary. This study highlights that three of these areas of need could be: choice in their study (OL v face-to-face), better strategies to increase motivation, and better overall support for their mental health. Universities need to examine their capacity for provision of different learning environments and determine the feasibility of blended-learning options as they move forward. Furthermore, universities should consider the implementation of online psychosocial interventions. This form of intervention will strike a balance between supporting improvements in student mental health outcomes and provide self-care strategies to improve motivation, whilst simultaneously removing the burden on staff to be the providers of such care.

Importantly though, students need to be educated that support from outside of the university is equally important to both improving motivation to study and well-being whilst studying. The qualitative responses from participants within this study highlighted that engaging with good self-care and spending time with friend and family were as important for increasing their well-being and supporting their motivation to study as doing the weekly readings and connecting with peers. Promoting the interconnected nature between overall mental health and academic outcomes is therefore necessary if students are to achieve their academic goals.

Statement of Ethics

This study was approved by the ACU Human Research Ethics Committee (2020-110E) and in accordance with the World Medical Association Declaration of Helsinki. Participants in this study provided their written consent before data collection started.

Conflict of Interest Statement

The authors report that there are no completing interests to declare.

Funding Sources

No funding is associated with this report.

Author Contributions

All the listed authors, Morgan Nicholson, Dr. Joanne Bennett, Dr. Oscar Modesto, and Rachael Gould, contributed significantly to each the development, research, and written components of the present manuscript. The weight of contribution is signified by the order in which the author's names are presented. All parties have consented to their name being placed on the publication.

Data Availability Statement

Data are not available as they are being included as part of the analysis for an additional study. Processed data will be made available upon request.

Funding Statement

No funding is associated with this report.