Despite measures taken to improve enrolment in higher education, the Portuguese national target of 40% by 2020 was not achieved, and the rate of students enrolling in tertiary studies (e.g., 30% in bachelor programmes) remains considerably lower than the EU-27 average (40.3%) (European Commission, 2020). Moreover, the 29% dropout rate of Portuguese students (Portuguese Directorate-General for Education and Science Statistics, 2018) and Eurostudent (2019) data underline the vulnerability of Portuguese students to academic difficulties. 

It is also relevant to consider that dropping out of higher education perpetuates financial dependency and delays progress in developmental stages of the life cycle, such as leaving the parental home and starting a family. Due to the economic constraints imposed by the recent covid-19 pandemic, as well as the upsurge in armed conflicts internationally, this outcome is very likely to increase and have a significant psychological and social impact on this generation and, hence, on society as a whole. 

In line with these concerns, the present study aimed to answer the following research question: “Which sociodemographic, economic, and psychosocial correlates influence students’ intention to dropout from university in the post-pandemic period?”. More specifically, it focused on exploring the impact of students’ background characteristics on dropout intentions (e.g., parental educational attainment, socioeconomic background) and current financial difficulties, as well as less explored psychosocial determinants of academic dropout, such as professional and caregiving responsibilities, perception of social support, and social connectedness to the campus. 

The study sample included 1.404 university students, of whom 54.4% were female and 45.4% were male. The majority of students were under 25 years old. With regard to marital status, 83.5% of the respondents were single, while 12.3% were living with a partner, married or not. About half of the respondents lived away from their main residence (50.6%). In terms of lower education attainment, fathers outnumbered mothers (41.6% vs 31.1%). In terms of having a university degree, mothers outnumbered fathers (35% vs 24%). In terms of professional status, 76.1% of fathers and mothers were paid workers. Concerning their geographical distribution, the majority of students were from Lisbon (36.2%) or the North region (33.8%).

The majority of respondents were studying at university institutions (76.4% vs polytechnics: 23.6%) from the public sector (79.8% vs private sector: 20.2%), attending a bachelor’s degrees (65.3% vs 34.7% master’s degrees) and were in their first-choice course (82.1%). With regard to area of knowledge, the distribution was as follows: Science and Technology: 49.1%; Social and Economic Sciences: 29.9%; Languages and Humanities: 12.3%, and Arts: 8.7%. The sample comprised students from the first to the fifth academic year. More specifically, 23.7% of students were in the first year, 29.8% in the second, 26.3% in the third, 9.9% in the fourth, and 10.3% in the fifth. The majority of students (84.3%) attended daytime classes (vs evening classes: 15.7%). About half of the respondents lived away from their family residence (50.6%). Displaced students lived mainly in houses shared with other people (57%), but also in university residences (16%), with other family members (14.6%), and alone (10.7%).

About 40% of students combined studies and work (37.9%), working an average of 24.9 hours per week: <10 h: 19.7%; 11-20 h: 26.9%; 21-35 h: 24.6%, and >35 h: 28.8%. Families continued to be the primary source of income for students (65.5%). Regarding monthly education expenses (e.g., tuition, study materials, transportation, accommodation, and food), students reported an average spend of 538 euros; ≤100 euros: 8.9%; ≤200 euros: 23.9%; ≤300 euros: 38.7%; ≤400: 50.7%; ≤500: 67%; <600 euros: 74.9%; >800 euros: 16%, and >1.000 euros: 6.7%. These figures need to be considered in the light of the fact that, although 67.5% of students responded with “Don’t know/No answer”, 35.3% of the sample reported that the family’s monthly income was around 1,000 euros, or less. Furthermore, 37.8% of the sample reported having additional personal income from a professional occupation. Of these, 12.2%: ≤500 euros; 13.3%: 500-1,000 euros; 5.8%: 1,000-2,000 euros. Moreover, about 20% of students reported receiving some kind of economic support from the Government, such as student scholarships. 

Students in the public sector spent less than their counterparts in the private sector. On average, students in the public sector spent 509 euros per month, while those in the private sector spent 656 euros. It is important to note that 17.4% of our respondents reported having caregiving responsibilities, mostly for children (42.6% of this percentage), but also for parents or other relatives. With regard to post-pandemic family income, 43.5% of the sample stated that their personal or family income had become “Slightly worse” or “Considerably worse”. Additionally, nearly 21% of the students reported “High” or “Many” economic difficulties in covering expenses, such as daily living expenses, course materials and tuition fees. Moreover, almost a quarter of students (24.1%) reported “Moderate difficulties” with the same issues. However, 55.1% of students responded that they had “Slight difficulties” or “No difficulties”. 

The study reveals that male students, displaced students, students with caregiving responsibilities, students of Languages and Humanities, and students in mainland Portugal report higher dropout intentions.

There were statistically significant main effects for gender, displacement, study cycle, caregiving responsibilities, area of knowledge, and national region. Thus, on a scale from 1 (low) to 5 (high), male students (mean score [M] = 2.32), displaced students (M = 2.32), bachelor students (M = 2.29) and those with caregiving responsibilities (M = 2.68) reported higher dropout intentions. Students in the area of Languages and Humanities reported higher intentions to drop out (M = 2.45) when compared to students from Science and Technology (M = 2.13). Results indicated that the mean score for Madeira (M = 1.16) was significantly different from North (M = 2.26), Centre (M = 2.23), Lisbon (M = 2.14, Alentejo (M = 2.29), and Algarve (M = 2.36). Moreover, the mean score for Azores (M = 1.32) was significantly different from North (M = 2.26), Alentejo (M = 2.29), and Algarve (M = 2.36). Students from Madeira and Azores reported lower dropout intentions. There were no differences regarding the education system, type of institution, being a working student, or attending day or evening classes. 

Considering sociodemographic, economic, and psychosocial variables, the findings indicate that academic exhaustion, difficulties in vocational academic adaptation, and a low perception of social connectedness to the campus are the most important determinants of self-reported dropout intention. Furthermore, male gender, studying a bachelor’s degree, having low academic self-efficacy, and being displaced are all significant predictors of dropout. Therefore, the variables that predicted dropout intention, from highest to lowest contribution, were: academic exhaustion, difficulties in academic vocational adaptation, lower social connectedness to the campus, male gender, pursuing a bachelor’s degree, lower academic self-efficacy, and being displaced. 

The purpose of this research was to identify which features influence dropout throughout the entire academic course, not only in the first year. It comprised students from different Portuguese higher education institutions (public and private; university and polytechnic; bachelor’s and master’s degrees), and different geographical areas of Portugal. It is important to note that the major sociodemographic and educational characteristics of the sample are consistent with those described in national/Government reports. 

More specifically, the study sample size was 1.404 university students, mostly female, under 25 years of age and single. About half of the respondents live away from their main residence. In terms of parents’ educational level, fathers have higher percentages of low educational levels while mothers have higher educational levels than fathers. Most students come from densely populated areas and attend the state university education system. The highest percentage of students are in their first-choice course, mainly related to Science and Technology, and Social Economic Sciences, usually in their first or second academic year. Approximately half of the respondents who are displaced live in houses shared with other people, in university residences, with other family members, or by themselves. 

Family remains the main source of income for these students, even though more than a third combine their studies with a professional occupation. Family income, excluding students’ own income, tends to be in the range of 1.000 euros or less. Conditions caused by the pandemic made it harder to cover daily expenses. In terms of intention to drop out, male students, displaced students, students who are also caregivers, graduates in Languages and Humanities, and students studying in mainland Portugal have higher intentions to drop out. Moreover, about half of the sample is made up of displaced students living in houses with other people, which may represent an increased economic effort that might justify the need to drop out. Government economic support is reported for less than a quarter of the sample, and a lower percentage of students live in university residences. Some indicators of risk ‒ such as being male, a displaced student, a caregiver, a Languages and Humanities student, or resident in mainland Portugal ‒ were also highlighted. 

According to the data obtained, the most significant predictors of dropout intention are academic exhaustion, difficulties in vocational academic adaptation, and a low sense of social connectedness to the university. Studying for a bachelor’s degree (compared with a master’s degree) and having lower academic self-efficacy were also significant predictors of dropout intention. 

The study builds on and extends previous research, while informing how to address the national gap in providing solutions that meet the needs of students at risk of dropping out in adequate and cost-effective ways. The authors find it innovative that, according to the results, the most important determinants of self-reported dropout intention were not economic aspects, considered the most relevant in the literature, but rather aspects more directly linked to institutional features. 

The results of the study have two main implications: (a) the determinants of self-reported dropout intention can be modified, and (b) academic institutions can play a role in this modification. The authors suggest strengthening and improving mentoring programmes. Provided these are broad in scope and well designed, they can have a positive impact on all these determinants. It is relevant to notice that several Portuguese academic institutions ‒ especially private ones ‒ are not yet members of the national mentoring network. Mentoring programmes should invest in the academic component, but also in the social one, so that students feel accepted and have better social connectedness, which is especially important for displaced students who need to build a whole new relational network. 

Since the results suggest that dropout can occur throughout the first cycle of studies, mentoring should cover all academic years and not just the first one. More specifically, in order to reduce academic exhaustion, it should also increase the perception of academic self-efficacy. In other words, mentoring should put in place measures that ensure a balance between the challenges faced by students with dependents and the need to achieve learning goals and, at the same time, offer the opportunity to enjoy the academic experience and context. In particular, establishing partnerships with flexible childcare services would lessen the burden felt by students with dependents and facilitate their academic engagement. Given that starting higher education means facing a new set of tasks, which demand much more autonomy and taking on new routines, it would be useful to offer workshops to improve personal and professional skills (e.g., time and stress management). To reduce difficulties in vocational academic adaptation, a volunteer programme could be developed within academic institutions, where students could have practical experiences and observation periods, improving the link between theory and practice in their vocational field. 

Finally, the authors stress that the transition to higher education should be prepared in such a way that there is a better articulation between higher and secondary education institutions. In particular, careers guidance should be strengthened in the final years of secondary education, while the above-mentioned strategies should be introduced with the aim of enhancing autonomy and self-regulation competencies. 

In view of the above conclusions, the following limitations of this study should be mentioned. 

1.    This study used self-reported intention of dropout as a proxy for university dropout, but the authors did not investigate the actual dropout behaviour. 

2.    Time and budget constraints did not allow for the use of the stratified random sampling method originally planned. Despite the multisite sampling process adopted, the convenience quota method used in data collection, as a non-random method, prevented the representativeness of all students, potentially limiting the external validity of the results. 

3.    Specific comparisons should be interpreted with caution given the limited number of students in specific subgroups (i.e., Madeira, Azores, Algarve). 

4.    Two data collection modalities were used: by phone and online. Although this dual methodological approach may have widened participation in the study, it is also possible that data had been influenced. More specifically, the interaction between participant and interviewer, or the participant’s use of the digital format to answer on their own might have influenced their responses. 

5.    The cross-sectional research design precluded the establishment of causality among study variables. Therefore, caution is required when interpreting regression results. 

While the sample comprises students from different academic years, future longitudinal studies may better understand the contribution of these psychosocial variables (e.g., social connectedness) to dropout decisions, since changes are expected throughout the student university experience. Additionally, some aspects of recent academic experience (e.g., percentage of online classes) were not assessed and may contribute to variability in results. 

Although this study collects objective and subjective measures of economic stress, future studies should map the contribution of economic factors (e.g., family financial stress) in greater depth. Despite the above-mentioned limitations, this project is innovative for several reasons: (a) it focuses on a particularly vulnerable time for dropout (post-pandemic era, increased armed conflicts, energy crisis/socioeconomic crisis); (b) it involves a broader risk and protection framework of dropout that goes beyond existing literature, and (c) it uses a large and diverse sample that mirrors the main sociodemographic and academic characteristics of the Portuguese higher education population. 

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