academic pressure thesis

Caught between academic calling and academic pressure? Working time characteristics, time pressure and time sovereignty predict PhD students’ research engagement

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• Published: 08 September 2023

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• Theun Pieter van Tienoven   ORCID: orcid.org/0000-0003-1532-254X 1 ,
• Anaïs Glorieux   ORCID: orcid.org/0000-0002-8127-792X 1 ,
• Joeri Minnen   ORCID: orcid.org/0000-0002-7494-2004 1 &
• Bram Spruyt   ORCID: orcid.org/0000-0003-0573-724X 1  

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PhD students come to work in academic environments that are characterized by long working hours and work done on non-standard hours due to increasing job demands and metric evaluation systems. Yet their long working hours and work at non-standard hours are often seen as a logical consequence of their intellectual quest and academic calling and may even serve as a proxy for their research engagement. Against that background, quantitative data from 514 PhD students were used to unravel the complex relationships between different aspects of time use and PhD students’ work engagement. While the results support the academia as a calling thesis to some extent, they also show that the relationships between long and non-standard working hours and research engagement are partly negated by the fact that the same working time characteristics lead to perceived time pressure and lack of time sovereignty, which in turn negatively affects their engagement. Moreover, the mechanism behind this negation varies across scientific disciplines. These subjective working time characteristics are the same alarm signals that are flagged as risk factors in academic staff for occupational stress, burnout, and work-life imbalance and thus cannot be ignored.

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Introduction

Occupational stress in (early career) academics as a result of long working hours, non-standard work, the managerialism of work, and stressors outside the workplace is well documented in the academic literature (Lee et al., 2022 ; Sabagh et al., 2018 ; Watts and Robertson, 2011 ). PhD students, however, are hardly included in the occupational group of academics, presumably due to the lack of clarity about their employment situation (Flora, 2007 ). PhD scholarships are often fiscally exempted. Consequently, PhD students with university, external, or personal funds, or when hired as graduate teaching assistants, sign scholarship agreements which are not fully comparable to an employment contract. As a result, PhD students are much more often evaluated in terms of their motivation to pursue a PhD (Naylor et al., 2016 ; Skakni, 2018 ) and the obstacles, challenges, and hurdles they encounter on their ‘perilous journey’ (Woolston, 2019 , 2022 ). Similar, the assessment of their workload is often made in terms of combining a teaching assignment with doctoral research (Borrego et al., 2021 ; Muzaka, 2009 ) or being used as cheap labour for several research tasks (Zhao et al., 2007 ). The most specific hard numbers regarding PhD students’ time use and occupational stress come from the 2022 Nature Graduate Survey in which 43.1% of PhD students worldwide report working on average 50 h per week or more. Around 40% is not or not at all satisfied with their working hours, and almost half mentions their work/life balance in the top three of the most challenging issues when conducting PhD research (Nature Research, 2022 ). To the best of our knowledge, working hours of PhD students are seldom evaluated beyond these proxies. This is a knowledge gap: time use is a multidimensional phenomenon including more than how long PhD students work (i.e. duration), but also when they work (i.e. timing of work) or how work is embedded in their daily lives (i.e. sequence of work and other activities) (Zerubavel, 1985 ). Moreover, these temporal aspects of working time can give rise to experiences such as time pressure or time sovereignty. Such experiences result from the combination of objective characteristics of time use and the expectations regarding these characteristics. Only by documenting these different aspects of time use and subsequently unravelling their mutual relationships with regard to outcomes can scientists get a deep understanding of the relevance of working time characteristics for PhD students. This contribution aims to address this lacune in scientific knowledge by assessing objective and subjective working time characteristics and associating them with PhD students’ engagement in their PhD research.

This paper focusses on PhD students. However, due to the lack of thorough studies on working hours specific to PhD students, we first describe the characteristics of the working environment (i.e. academia) in which they conduct their research. This gives us a better grasp of the relevant aspects of working time characteristics and their association with work engagement.

Long working hours and weekend work in academia result from high academic job demands (Anderson, 2006 ; Kinman and Jones, 2008 ). Several challenges have been reported to contribute to increasing job demands. The need to balance teaching demands and research workload is a considerable challenge that can lead to role conflict (Sabagh et al., 2018 ) and time conflict (Tham and Holland, 2018 ). This is further aggravated by ‘corporatisation’ (Holmwood, 2014 ) or the ‘managerialism phenomenon’ (Erickson et al., 2021 ; Lee et al., 2022 ) which signifies universities’ high performance-based management focussed on high academic productivity and metric-driven performance markers. Consequently, academics report an increasing workload as well as an increase in the need to work outside contractual hours to meet work requirements (Fetherston et al., 2021 ; Houston et al., 2006 ; Kinman and Jones, 2008 ).

The excess working hours result in a ‘work-life merge’ which, according to a study by Fetherston et al. ( 2021 ), is largely considered necessary by academics to meet increasing job demands in the first place and a major cause of time pressure (Watts and Robertson, 2011 ). This undermines the idea of flexible working hours which has been suggested to be helpful to academic parents (Jakubiec, 2015 ). It also conflicts with the idea of the ‘academic calling’, i.e. academia being a vital part of who one is, where long working days are not experienced as such (Fetherston et al., 2021 ). In fact, high job demands, increasing workload, and work-life merge contribute to occupational stress (Lee et al., 2022 ), burnout (Sabagh et al., 2018 ), and severe disruption of work-life balance (Ashencaen Crabtree et al., 2021 ; Kinman and Jones, 2008 ). On the contrary, a well-balanced teaching load and research time are associated with significantly lower levels of emotional exhaustion (Gonzalez and Bernard, 2006 ). Similarly, a review by Sabagh et al. ( 2018 ) finds that engagement—the energetic and effective connection with one’s work (Schaufeli et al., 2006a )—can serve as buffer for the negative consequences of the increasing academic job demands. The above arguments further underscore that if we study the relevance of time allocation in academia, we should not only focus on its objective characteristics (e.g. number of hours) but also how these are experienced.

• PhD students

PhD students represent a particular and vulnerable academic group, not only because they are the lowest in the academic hierarchy, but also because their status as employee is not always clear (Flora, 2007 ). Their scholarships are often fiscally exempted, and scholarship agreements do not always fully correspond to the rights and benefits of employment contracts. More importantly, their progress and successful completion are highly dependent on the support they receive from their supervisor (Heath, 2002 ; Lee, 2008 ). Research shows that ultimately supervisors’ support is more important than their academic qualities in achieving a PhD (Dericks et al., 2019 ). However, it is precisely these academic qualities that supervisors are (increasingly) judged on in metric output-oriented academia (e.g. citation score, number of publications, amount and type of project funding, number of MA and PhD students under their supervision). There is ample reason to belief that the above-mentioned increasing job demands are reflected upon PhD students as well.

The existing research supports the latter assumption. PhD students across all scientific disciplines sometimes come into contact with exploitative supervisor behaviour (Zhao et al., 2007 ). This seems particularly true for graduate teaching assistants. Their increasing teaching load shifts the balance between teaching duties and research time even further resulting in substantial time pressure and a low expectation of obtaining their PhD at all (Glorieux et al., forthcoming ). In contexts where the teaching load is much more distributed amongst all PhD students, such as in the Netherlands and the UK (Park and Ramos, 2002 ; Sonneveld and Tigchelaar, 2009 ), the pressure is partly relieved for the specific group of teaching assistants. PhD students’ scholarship status, as opposed to employment status, means that completing their PhD trajectory is often studied in terms of motivational characteristics such as an intellectual quest or self-actualization (Naylor et al., 2016 ; Skakni, 2018 ). Such individualistic lens, however, neglects the relevance of the more structural characteristics of their work environment and how PhD students cope with them. As a result, not much knowledge exists on PhD students’ working hour characteristics. This contribution aims to provide an impetus to close this knowledge gap.

Additionally, it seems that working conditions of academics in (bio)medical sciences and sciences disciplines are traditionally more vocalized in scientific journals. This was once more demonstrated when discussing the consequences of the COVID-19 pandemic (see discussion in Van Tienoven et al., 2022 ). Although all disciplines face increasing job demands due to metric-driven productivity evaluations, each discipline comes with its particular characteristics of doing PhD research that impact working time.

Human sciences, for example, are characterized by more individual work. PhD students in these disciplines usually have to come up with their own research project. To secure their own funding, they have to write grant proposals (Torka, 2018 ) or—more than PhD students in other disciplines—take on teaching tasks (Groenvynck et al., 2011 ). Doctoral research in the human sciences is often quite isolated, in the sense that the PhD student is the only person that is appointed to the project (Torka, 2018 ), which could increase the pressure to get everything done. In addition, participating in public debates and writing commissioned reports—more common in the human sciences—can reduce the time they can spend on their PhD research. All this makes the development of a research plan with clear milestones and deadlines all the more important, as organic teamwork usually does not occur.

This is different in the natural sciences, where PhD students are usually part of a larger research team (Larivière, 2012 ; Torka, 2018 ) and usually receive more financial support through departmental programmes (Sverdlik et al., 2018 ). These PhD students often do not have their own individual projects but are responsible for part of a collective project. For example, PhD students in the natural sciences are more dependent on external factors (e.g. the progress of other people’s work, the availability of labs and equipment). As a result, the planning of their project depends on mutual agreements, and they often have much less control over the exact timing (Torka, 2018 ).

The above-mentioned differences in experience and needs with regard to the organization of working time lead to assess the potential moderating role of the scientific discipline for the relationships that we study.

Working time indicators

From the above, it becomes clear that working time can be conceptualised based on objective and subjective indicators. Objective then relates to calculable indicators such as the number of working hours, the times worked on non-standard hours, and the composition of the workload. In this study, objective time indicators are the number of working hours, the frequency of evening and weekend work, and the balance between teaching duties and research time. Yet following the ‘academic calling’ hypothesis, long working hours or working on non-standard work as such are not necessarily an issue for academics with high engagement in their work (Sabagh et al., 2018 ). For the latter, working long hours may be a means towards self-actualization. This, again, underscores the importance of including indicators of working time which tap into how working time is experienced such as the extent to which the workload and work-life merge lead to the feeling of constantly being pressed for time (Watts and Robertson, 2011 ) or the feeling of having no control or authority over one’s own time (Ashencaen Crabtree et al., 2021 ; Kinman and Jones, 2008 ).

Time pressure does not arise solely from having too little time but is also related to the aspirations that individuals have and the normative expectations that they experience to use their time (Kleiner, 2014 ). The latter are external to the individual and arise from the normative structures of their work environment. To measure the subjective experience of being pressed for time, we use an item scale that simultaneously gauges the feeling of not having enough time, the feeling of aspiring more than can be done in the current timeframe, and the feeling that normative expectations weigh too heavy on the allocation of time.

Additionally, the use of time is not limited to the work environment. We constantly face demands from different life spheres including our work life but, for example, also our family life and social life. The extent to which we can align these demands in function of our priorities and values depends on the extent to which we experience autonomy over our own time (Southerton, 2020 ). A lack of time sovereignty hampers setting boundaries and prioritizing activities that are meaningful and, thus, might result in an unhealthy integration of different life spheres.

In this study, we not only assess the relevance of these subjective indicators of working time, but also to what extent these indicators mediate the relationship between objective characteristics of time use and the outcome.

In summary, in this contribution, we analyse the objective and subjective working time indicators of PhD students and relate these characteristics to PhD students’ engagement in their doctoral research. The latter is a well-known predictor of the journey or intellectual quest in doctoral research. We assume that the ‘academic calling’ hypothesis holds for PhD students. However, we also acknowledge that once the number of working hours, the work done on non-standard hours, and the composition of the workload take the upper hand, issues such as time pressure and lack of time sovereignty come into play. We will test the hypothesis that the positive direct effect (i.e. the academic calling) is partially offset by a negative indirect effect that runs along indicators of subjective working time. Acknowledging potential differences in scientific disciplines, we also investigate to what extent we conclude differently on the hypothesis for different scientific disciplines.

Data and method

Data come from the 2022 PhD Survey held at the Vrije Universiteit Brussel (VUB) in Belgium ( n  = 836; response rate = 45.4%). This annual survey is commissioned by the Researcher Training & Development Office (RTDO) at the VUB and conducted by the Research Group TOR (Tempus Omnia Revelat) at the same university. The PhD Survey serves as a monitor instrument to evaluate the support provided to PhD students by RTDO and at the same time monitors aspects of well-being and job satisfaction of PhD students. As a result, the strength of the data lies in the heterogeneity of PhD students surveyed. PhD students across all disciplines, regardless of their teaching duties and funding nature (i.e. external scientific, internal scientific, industry, teaching assistant, personal funds, unfunded) are included.

The 2022 survey is the fifth wave of the annual PhD Survey since it piloted in 2017. All PhD students registered at VUB on the 1st of January preceding the launch of the next wave are invited. Typically, PhD students start in October or November, but it is possible to start at any time of the academic year. Doctoral research typically lasts for 4 years and ends with a successful oral defence of the thesis.

The PhD Survey exists of a single online questionnaire that is hosted on the data collection platform MOTUS and accessible through the MOTUS web application. Footnote 1 The PhD Survey takes place in the last 2 weeks of April and the whole month of May. PhD students across all faculties receive an email with login credentials to participate in the survey. Up to two reminders are sent. PhD students are explicitly asked to give their consent before starting the questionnaire. The design of the study was approved by the ethics committee of the VUB (file number ECHW_318).

Institutional context

The VUB is located in the Brussels Capital Region in Belgium. In the academic year 2020–2021, just over 20,000 students were enrolled in 172 study programmes of which almost one third is taught in English. About 10% of all students are enrolled in PhD programmes. To be admitted to these programmes, PhD students can rely on different funding opportunities, such as general or themed scholarships from (inter)national funding institutions (e.g. the National Research Council), research funding from a research project or multiple research projects in the name of the supervisor, or by combining PhD research with a position as graduate teaching assistant (GTA).

At the start, PhD students enroll in the compulsory Doctoral Training Programme which facilitates PhD students with the possibility to develop their (research) skills through, for example, courses, seminars, workshops, and career coaching. There are three different doctoral schools under which all faculties are divided. The Doctoral School of Natural Sciences and (Bioscience) Engineering (NSE) includes the Faculty of Engineering Sciences and the Faculty of Sciences and Biosciences Engineering. The Doctoral School of Human Sciences (DSh) includes the Faculty of Social Sciences and Solvay Business School, the Faculty of Arts and Philosophy, the Faculty of Psychology and Educational Science, and the Faculty of Law and Criminology. The Doctoral School of Life Science and Medicine (LSM) includes the Faculty of Medical Sciences and Pharmacy and the Faculty of Physical Education and Physiotherapy.

All PhD students are expected to engage in teaching for at most 20% of their time, except GTAs, who are expected to engage in teaching for at most 40% of their time. PhD students, including GTAs, are expected to use the remaining time for their research aimed at obtaining their PhD. Their doctoral research typically lasts for 4 years, or 6 years in case of GTAs, and ends with a successful oral defence of the thesis. Within Flanders, the Dutch-speaking community in Belgium and responsible for Dutch-language education, education is fairly equal. This also applies to the doctoral training. Universities apply equal admission conditions, and prestige differences between universities are much smaller than those known from Anglo-Saxon countries. Most doctoral students receive a similar salary. The universities in Flanders work in roughly the same way, which means that our findings can be extended to the Flemish context.

Explanatory variables

For the explanatory variables, we distinguish between objective and subjective indicators of working time. Objective means here that characteristics of the working time are questioned based on commonly shared and recognizable time indicators (e.g. the number of working hours, worked/not worked between 8 pm and 12 am). The answers to these questions remain the respondents’ estimates. Subjective means here that it concerns experienced characteristics of working time (e.g. experienced time pressure). They include a clear level of appreciation and result from the confrontation of the expected aspects of working time and its actual characteristics. The objective time indicators are the following.

Total working time. Estimated total working time in hours per week (scaled).

Share of non-research time . Expressed as a percentage and calculated as one minus the estimated time spent on research over the estimated total working time in hours per week. Outliers for time estimates are set at mean ± 1.5 times the interquartile range.

Non-standard working hours. A summation scale (ranging from 0 to 10) of the items ‘Work in evening (after 6 pm)’, ‘Work at night (after midnight)’, ‘Work on Saturday)’, and ‘Work on Sunday’ that were answered using a 5-point Likert scale ranging from 1 = never to 5 = always. A principal component analysis revealed one component with Eigenvalue = 2.494 and 62.3% of variance explained. Cronbach’s alpha equals 0.796, and the correlation between the factor score and summation score equals r  > 0.99.

The subjective time indicators are the following.

Experienced time pressure . Experienced time pressure is measured by a summation scale (ranging from 0 to 10) of the items ‘Too much is expected of me’, ‘I never catch up with my work’, ‘I never have time for myself’, ‘There are not enough hours in the day for me’, ‘I frequently have to cancel arrangements I have made’, ‘I have to do more than I want to do’, ‘I have no time to do the things I have to do’, and ‘More is expected from me than I can handle’ using a 5-point Likert scale ranging from 1 = strongly disagree to 5 = totally agree (Van Tienoven et al., 2017 ). A principal component analysis revealed one component with Eigenvalue = 4.661 and 58.3% of variance explained. Cronbach’s alpha equals 0.895, and the correlation between the factor score and summation score equals r  > 0.99.

Experienced lack of time sovereignty. Experienced lack of time sovereignty is measured by an inverted summation scale (ranging from 0 to 10) of the items ‘I have enough influence on my working hours’, ‘I can adjust my working time to my family life’, ‘I have ample opportunities to take time off whenever that suits me’, and ‘The VUB/my supervisor offers sufficient opportunities for employees to adjust their tasks depending on their private situation’ that were answered using a 5-point Likert scale ranging from 1 = strongly disagree to 5 = totally agree. A principal component analysis revealed one component with Eigenvalue = 2.577 and 64.4% of variance explained. Cronbach’s alpha equals 0.814, and the correlation between the factor score and summation score equals r  > 0.99.

Dependent variable

Most PhD students receive a grant, which means that their employment status is not always clear (Flora, 2007 ). Nevertheless, they end up in a professional work environment with job demands and responsibilities expected of an employee; the most important of which is conducting research. To measure the extent of engagement in PhD research , we therefore use the validated 9-item Utrecht Work Engagement Scale (UWES-9) in combination with three items that measure intrinsic motivation, which is also specific to the scholarship status of PhD students (Skakni, 2018 ). The UWES-9 measures vigour, dedication, and absorption based on three items per aspect of work engagement (Schaufeli et al., 2006b ). The items are the following: ‘At my job, I feel like bursting with energy’, ‘At my job, I feel strong and vigorous’, and ‘When I get up in the morning, I feel like going to work’ for vigour; ‘I am immersed in my work’, ‘I get carried away when I’m working’, ‘I am happy when I’m working intensely’ for absorption; and ‘I am enthusiastic about my job’, ‘I am proud of the work that I do’, ‘My job inspires me’ for dedication. The UWES-9 scale has demonstrated high internal consistency and validity (Schaufeli et al., 2006a ). Previous work with this scale revealed that people who score high on the work engagement scale, score lower on aspects of burnout, report lower levels of depression and distress, and score higher on job satisfaction and organizational commitment. High scores on the work engagement scale also correlate positively with job characteristics such as autonomy, performance feedback, and task variety (for a discussion, see Saks and Gruman, 2014 ).

Unlike most paid work, the PhD track has a clear finality that is motivated professionally, intellectually, or by a desire for self-actualization (Skakni, 2018 ). In social cognitive theory, this intrinsic motivation reflects the willingness and interest to pursue efforts and thus engage oneself in PhD research (Gu et al., 2017 ). To measure the specificity of engagement in PhD research in a more meaningful and relevant way, we therefore add three additional items that explicitly measure the intrinsic motivation to pursue a PhD. At the same time, this brings the construct of engagement more in line with the idea of an academic calling. The added items are the following: ‘I can make the world a better place with the work that I do’, ‘I’m helping science move forward with the work that I do’, and ‘I improve things with the work that I do’. All items were answered using a 5-point Likert scale ranging from 0 = I never have this feeling to 4 = I always have this feeling. Engagement is then measured based on a summation scale (ranging from 0 to10). A principal component analysis revealed one component with Eigenvalue = 6.076 and 50.6% of variance explained. Cronbach’s alpha equals 0.908, and the correlation between the factor score and summation score equals r  > 0.99.

Control variables

Given that the work-life merge is of much more concern for female academics (Toffoletti and Starr, 2016 ) and female academics are reported to be more vulnerable to the negative consequences of increasing job demands than male academics (Watts and Robertson, 2011 ), we control for sex using a dummy for female. Due to small numbers, PhD students that identify themselves as non-binary are omitted from the data ( n  = 3).

Where in Anglo-Saxon countries, the form of funding (e.g. fellowship, research assistant, teaching assistant) influences the amount of time available for research (Grote et al., 2021 ), the allocation of PhD students’ time over teaching and research is much more formally arranged in northwestern continental Europe. Acknowledging that research skills might be enhanced by teaching experience (Jucks and Hillbrink, 2017 ) and protecting PhD students from becoming means to mitigate increasing teaching demands, contracts in Belgium stipulate that PhD students are not expected to spend more than 20% of their time on teaching (e.g. guest lectures, grading, BA or MA thesis supervision). For GTAs, this is 40%. However, both regular PhD students and GTAs often indicate that when they also include preparation for teaching, they often spend much more time on it than expected (Machette, 2021 ). This applies in particular to younger PhD students. Since PhD students, regardless of their funding type, are expected to teach, we use a dummy variable to control for whether teaching exceeds contractual hours . PhD students estimated their weekly time spent on teaching activities in the PhD Survey. Outliers were set at over 38 h per week (i.e. the equivalent of a fulltime workweek). If the ratio time spent teaching over total working time exceeded 20% (or 40% in case of GTAs), PhD students are considered to teach more than contractually stipulated.

Analysis plan

We apply structural equation modelling in R with the lavaan package (Rosseel, 2012 ) to investigate whether and how objective and subjective indicators of working time associate with engagement in PhD research. First, an overall path model is fitted for the entire sample. Next, we aim to explore whether these associations vary by scientific discipline. Therefore, we stratify the models by doctoral schools at the VUB.

Model fit will be determined based on Chi-square, CFI, RMSEA, and SRMR. Cut-off points for fit measures are set following Hu and Bentler ( 1999 ): CFI > 0.90, RMSEA < 0.07, and SRMS < 0.05. The model fit statistics assess to what extent the patterns identified in this sample can be generalized to the underlying population. As the PhD survey is an annual survey, an alternative and arguably stricter test regarding the stability and generality of our models entails that we re-estimate our model on different samples. Therefore, in the Supplementary Material Appendix, Table A1, we provide the results for the data from the 2021 and 2020 edition of the PhD survey. These analyses confirmed the substantive conclusions derived from the analysis of the 2022 data. We test the equality of regression coefficients using Wald’s z -test (Paternoster et al., 1998 ). Table 1 shows the characteristics for the total sample and stratified by doctoral schools.

PhD students score 6.3 on 10 for their engagement in their PhD research, and this does not vary across doctoral schools nor does their score for working on non-standard hours (3.6 on 10). PhD students spend on average a third of their time on other tasks than their PhD research. In the doctoral school of NSE, this share is substantially lower. PhD students across all doctoral schools say to work just over 40 h per week. Experienced time pressure tends to be higher, and experienced time sovereignty tends to be lower in the doctoral school of LSM. Albeit the sample exists of equal shares of female and male PhD students, female PhD students are significantly underrepresented in the doctoral school of NSE. Finally, just under one in five PhD students report that their teaching exceeds contractual hours.

Working time experience and engagement in PhD research

Figure 1 shows the overall path model with standardized regression coefficients. The model fit indices show a good fit (chi-square = 11.323, CFI = 0.997, RMSEA = 0.016, SRMR = 0.024). Additionally, the overall path models for earlier waves of the PhD Survey (2021 and 2020) show that results are replicable (see Supplementary Material Appendix A, Table A1).

Path model (wave = 2022, n  = 514), *** p ≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05, (*) p ≤ 0.10

The variables that control the objective time indicators show that the hypothesized associations between sex and working on non-standard hours or total working time are not significant (see Table 2 ). Working on non-standard hours (β = 0.088), the share of total working time not spent on research (β = 0.334), and total working time (β = 0.168) significantly increase when teaching exceeds the number of hours stipulated in the contract. Total working hours (β = 0.162) and the extent of non-standard working hours (β = 0.211) are significantly and positively associated with the engagement in PhD research. All three objective indicators of working time associate significantly positively with subjective indicators of working time and, in turn, these subjective indicators associate significantly negatively with engagement in PhD research. The feeling of being pressed for time significantly increases with a larger share of total working time not spent on research (β = 0.222), with more work being done on non-standard hours (β = 0.190) and with total working time (β = 0.135). Similarly, the feeling of lacking control over one’s working time in function of other responsibilities also increases with more working time not spent on research (β = 0.135) or done on non-standard hours (β = 0.157) and with longer working weeks (β = 0.231). In turn, the more time pressure one experiences (β =  − 0.243) and the more lack of time sovereignty one experiences (β =  − 0.135), the lower one’s engagement in PhD research.

Table 3 shows that the total effect of working on non-standard hours on engagement in PhD research is β = 0.144, because the direct positive effect of working on non-standard hours (β = 0.211) is offset by the indirect negative effect of working on non-standard hours that runs along experienced time pressure (β =  − 0.046) and along experienced lack of time sovereignty (β =  − 0.021). Similarly, the total effect of total working time on engagement in PhD research is β = 0.098 because the direct effect (β = 0.162) is offset by negative indirect effects that run along experienced time pressure (β =  − 0.033) and experienced lack of time sovereignty (β =  − 0.031). The university-wide results confirm our hypothesis. Indeed, the positive direct effect parameter of working long and non-standard hours on engagement in PhD research is partially offset by a negative indirect relationship that runs along indicators of experienced time pressure and lack of time sovereignty.

Differences by doctoral schools

Table 4 shows the standardized regression coefficients of the path model stratified by doctoral schools. When we first look at the control variables, we see that there are no differences between female and male PhD students when it comes to working on non-standard working hours. Only in the DSh do female PhD students report lower total working time than their male peers (β =  − 0.157). In all doctoral schools, PhD students report higher total working hours and a higher share of working time not spent on research when their teaching exceeds the contractual hours. The pairwise comparison of regression coefficients shows that the size of the effects is not significantly different between doctoral schools. Only PhD students in the doctoral school of NSE score significantly higher on the scale of non-standard working hours when their teaching exceeds the contractual hours (β = 0.127).

Direct effects are found in all doctoral schools, except for the association between total working time and engagement in PhD research in the doctoral school of LSM. The pairwise comparison of regression coefficients shows no differences in effect sizes across all doctoral schools.

Before concluding on the indirect effects, we look at the separate effects between objective and subjective indicators on the one hand and subjective indicators and engagement on the other. We start with experienced time pressure. In the doctoral school of DSh, all three objective indicators of working time associate significantly positively with experienced time pressure. In the doctoral school of LSM, feelings of time pressure only significantly increase when the share of non-research time increases. The same holds for the doctoral school of NSE. However, here, the degree of working non-standard hours also leads to more perceived time pressure. Although feelings of time pressure are affected by objective working time indicators differently across the doctoral schools, it remains that time pressure reduces PhD students’ engagement in their research across all doctoral schools. The pairwise comparison of regression coefficients also shows that effect sizes are equal in all doctoral schools.

Next, we look at the lack of time sovereignty. The extent of work done on non-standard hours significantly increases the lack of time sovereignty for PhD students in the doctoral schools of DSh and NSE. The effect parameter for the doctoral school of DSh (β = 0.287) is the largest and significantly larger than for the doctoral school of LSM (Δβ = 0.311). In both the doctoral school of DSh and LSM does an increased share of non-research time significantly increase the lack of time sovereignty. Again, the effect parameter is the largest for the doctoral school of DSh (β = 0.248). Finally, the total working time only associates positively with lack of time sovereignty in the doctoral schools of LSM and NSE. For both doctoral schools, the effect parameters (β = 0.296 and β = 0.322, respectively) are significantly larger than in the doctoral school of DSh (Δβ = 0.260 and Δβ = 0.286, respectively). Albeit the difference between regression coefficients across doctoral schools is not different from zero, we only find that an increase in the experience of lack of time sovereignty reduces PhD students’ engagement in their research in the doctoral school of NSE.

To test our hypothesis, Table 5 decomposes the total effect of working on non-standard hours and total working time into its direct and its indirect effects. The positive, direct effects are as reported in Table 4 . The negative, indirect effect of non-standard work that runs along experienced time pressure is only significant in the doctoral school of DSh and the doctoral school of NSE (β =  − 0.070 and β =  − 0.032). The indirect effect of non-standard work that runs along experienced lack of time sovereignty is only significant in the doctoral school of NSE (β =  − 0.029). No indirect effects of working on non-standard hours are found for the doctoral school of LSM. The result is that the total effect of non-standard hours on engagement in PhD research is significant for the doctoral school of DSh and NSE (β = 0.134 and β = 0.142, respectively) but not for LSM.

The indirect effect of total working time that runs along experienced time pressure is only significant for the doctoral school of DSh (β =  − 0.054) whereas the negative indirect effect that runs along experienced lack of time sovereignty is only significant for the doctoral school of NSE (β =  − 0.064). Again, the doctoral school of LSM reports no significant indirect effects. As a result, the total effect of total working time on engagement in PhD research is not significant for the doctoral school of LSM. The significant direct effect of total working time in the doctoral school of DSh is offset by the indirect negative effect of total working time such that the overall effect is insignificant. Only for the doctoral of NSE we found an overall positive effect on engagement in PhD research (β = 0.131).

The stratification of the analysis by disciplines leads us to partially confirm our hypothesis. The next section will discuss the meaning hereof in more detail.

Large-scale comparative research indicates that a substantial share of PhD students is unsatisfied with their long working hours and has experienced trouble with their work-life balance (Nature Research, 2022 ). Yet, PhD students are seldom evaluated in terms of their working hours. The focus lies much more on the perilous journey they embark on, and the extent to which their intrinsic motivation can overcome barriers during their intellectual quest (Naylor et al., 2016 ; Skakni, 2018 ; Woolston, 2022 ). At the same time, though, PhD students are employed in an environment that is highly susceptible to occupational stress and reduced well-being because of the working hours’ characteristics (Lee et al., 2022 ; Sabagh et al., 2018 ; Watts & Robertson, 2011 ). It is therefore remarkable that PhD students are rarely studied in terms of their working time distribution and, if they are, rarely looked at beyond the number of hours worked. It is reasonable to assume that, as with academic staff, other characteristics of working time, such as non-standard work or subjective experiences such as the work-life merge, also play a role for PhD students.

This contribution aims to shed light on the working time characteristics of PhD students and the extent to which they impact their engagement with their PhD research. It contributes to the existing knowledge on working conditions and the well-being of PhD students in three ways. Firstly, it looks beyond the idea that PhD students embark on a journey with all its (intellectual) challenges (Naylor et al., 2016 ; Skakni, 2018 ) and views PhD students as employees entering an academic work environment that, due to its high job demands and metric-based assessment criteria, may well cause occupational stress and a work-life merge (Fetherston et al., 2021 ). We, thus, assume that working time characteristics of PhD students, both in objective terms such as non-standard hours and long working days as well as in subjective terms such as time pressure and lack of time sovereignty, affect their engagement in their PhD research. Secondly, rather than using a single measure of (the amount of) working time, our study acknowledges the multidimensionality of the allocation of working time. By distinguishing different dimensions and using structural equation modelling to unravel their mutual relationships and predictive power regarding our outcome, we offer a much more nuanced view on PhD students’ time use. Thirdly, we use a university-wide sample of PhD students. This allows us to investigate potential differences in the association between working time characteristics and engagement in PhD research across scientific disciplines under similar institutional conditions.

In this contribution, we showed that, in general, working non-standard hours and working long hours impact engagement in PhD research both directly and indirectly. The direct effects are positive, meaning that working long and non-standard hours are associated with higher engagement in PhD research. This concurs with the idea of PhD research being an academic calling (Sabagh et al., 2018 ). It signifies a certain degree of motivation and commitment which in turn may of course also feed the number of working hours. However, this academic calling (and the possible mutually reinforcing dynamic between academic calling and the number of working hours) has a downside. There are also indirect effects of working non-standard hours and working long hours which run along experienced time pressure and experienced lack of time sovereignty that negatively associate with engagement in PhD research. In other words, and this is a crucial insight, the expected positive direct relationship for engaged PhD students might be offset by the negative indirect effects of long working days and non-standard work. Albeit the total effect remains positive, we, thus, must be aware that when it comes to working time characteristics two opposite mechanisms are at play. Long working hours and atypical work characterize committed PhD students, but at the same time, they can cause negative work experiences such as time pressure and lack of time sovereignty, which actually reduce their commitment. This finding raises some important questions for future exploration. Is there a threshold at which the negative experiences of long and non-standard hours overtake the positive impact of seeing one’s research as an academic calling (Conway et al., 2017 )? Or is the downside of an academic calling that PhD students work long hours and are very engaged in their research, but as a result of which setbacks in their research or personal life have a much greater impact (Sonnentag et al., 2008 )?

There are some outstanding differences, however, when looking at different scientific disciplines. We used the university’s doctoral schools as proxies for scientific disciplines: human sciences, sciences and engineering, and life sciences and medicine. Remarkably, we did not find any significant direct or indirect effect parameter of long working hours on engagement in PhD research for PhD students in life sciences and medicine. We did find a direct effect parameter of non-standard working hours on their engagement in PhD research but that was offset by the indirect effects completely rendering the total effect statistically insignificant. Working hour characteristics, therefore, seem to affect engagement in PhD research the least in the life sciences and medicine. Possible explanations are that PhD students combine their PhD research with already less regular schedules of specialist training in the hospital. Especially in medicine, irregular and long working hours are part of the job and possibly already expected and anticipated by PhD students based on their BA and MA experiences.

The opposite is found for PhD students in sciences and engineering. Although working non-standard hours and long working days positively affect their engagement in PhD research, the effect parameters of both indictors are offset by negative indirect effects that run along experienced lack of time sovereignty. Additionally, the effect parameter of working non-standard hours is offset by the negative indirect effect that runs along experienced time pressure. Compared to the other disciplines, the indirect effect that runs along the experienced lack of time sovereignty is the largest for this discipline. Possible explanations are that PhD students in sciences and technology are often part of larger projects in which they carry out partial research. Moreover, they are much more dependent than other disciplines on fixed time slots for technical machines, devices, and laboratory settings for conducting experiments. The resulting time constraints and the fact that their research results serve a greater research project may diminish their control over their own time to a greater extent and impose a degree of time pressure.

When it comes to time pressure, the largest indirect effects are reported for PhD students in human sciences. The positive direct effect of long working hours on their engagement in their PhD research is offset by the negative indirect effect that runs along experienced time pressure, rendering the total effect of long working hours insignificant. Although the total effect of working non-standard hours remains positively significant, the direct effect is offset by a third by the indirect effect that runs along time pressure. Possible explanations are that the human sciences, more than other scientific disciplines, are in much more direct and much more contact with their stakeholders in society. PhD students in the human sciences are usually more involved in pure activism and social impact initiatives. Moreover, it is a branch of science that receives a lot of resources from research projects commissioned by governments or interest groups (e.g. on education, culture, media, politics). PhD students who are funded through such projects spend a lot of time on stakeholder and science communication. All these extra tasks may lead to more perceived time pressure to get everything done.

This contribution is not without its limitations. This survey uses self-reported estimates of working hour characteristics. It is known that time diary methodology is more reliable. However, it is also known to require longer fieldwork periods and more effort from respondents. As such, it is not in line with the current study design but worth considering in future iterations to get a more reliable grasp of the temporal characteristics of doing PhD research. In its current form, not much is known about attrition of the sample. PhD students that faced a severe impact from working hours characteristics on their work-life or well-being might have dropped out. In that case, we may be underestimating the problem. Linking future research with the university’s administrative data would provide more information about attrition due to drop-out.

PhD students come to work in academic environments that are characterized by long working hours and work done on non-standard hours due to increasing job demands and metric evaluation systems. They are motivated by an intellectual quest and an academic calling that makes them put up with long working days and non-standard work which signifies their engagement in their PhD research. However, there is a downside that needs attention. The same working hour characteristics could indirectly affect their engagement negatively because they result in experiencing time pressure and lack of time sovereignty. These are the same alarm signals that are flagged as risk factors in academic staff for occupational stress, burnout, and work-life imbalance.

Data Availability

Raw data cannot be shared publicly because of the institution’s privacy regulations. Data code necessary to replicate results are available from the Vrije Universiteit Brussel’s Institutional Data Access (contact via [email protected]) for researchers who meet the criteria for access to confidential data.

MOTUS research platform 2016–2022. Available from:  https://www.motusresearch.io/en .

Anderson, G. (2006). Carving out time and space in the managerial university. Journal of Organizational Change Management, 19 (5), 578–592.

Article   Google Scholar  

Ashencaen Crabtree, S., Esteves, L., & Hemingway, A. (2021). A ‘new (ab) normal’?: Scrutinising the work-life balance of academics under lockdown. Journal of Further and Higher Education, 45 (9), 1177–1191.

Borrego, M., Choe, N. H., Nguyen, K., & Knight, D. B. (2021). STEM doctoral student agency regarding funding. Studies in Higher Education, 46 (4), 737–749.

Conway, S. H., Pompeii, L. A., Ruiz, G., de Porras, D., Follis, J. L., & Roberts, R. E. (2017). The identification of a threshold of long work hours for predicting elevated risks of adverse health outcomes. American Journal of Epidemiology, 186 (2), 173–183.

Dericks, G., Thompson, E., Roberts, M., & Phua, F. (2019). Determinants of PhD student satisfaction: the roles of supervisor, department, and peer qualities. Assessment & evaluation in higher education, 44 (7), 1053–1068.

Erickson, M., Hanna, P., & Walker, C. (2021). The UK higher education senior management survey: A statactivist response to managerialist governance. Studies in Higher Education, 46 (11), 2134–2151.

Fetherston, C., Fetherston, A., Batt, S., Sully, M., & Wei, R. (2021). Wellbeing and work-life merge in Australian and UK academics. Studies in Higher Education, 46 (12), 2774–2788.

Flora, B. H. (2007). Graduate assistants: Students or staff, policy or practice? The current legal employment status of graduate assistants. Journal of Higher Education Policy and Management, 29 (3), 315–322.

Glorieux, A., Spruyt, B., Te Braak, P., Minnen, J., & van Tienoven, T. P. (forthcoming). When the student becomes the teacher: Determinants of self-estimated successful PhD completion among graduate teaching assistants.

Gonzalez, S., & Bernard, H. (2006). Academic workload typologies and burnout among faculty in seventh-day adventist colleges and universities in North America. Journal of Research on Christian Education, 15 (1), 13–37.

Groenvynck, H., Vandeveld, K., Van Rossem, R., Leyman, A., De Grande, H., Derycke, H., & De Boyser, K. (2011). Doctoraatstrajecten in Vlaanderen. 20 jaar investeren in kennispotentieel. Een analyse op basis van de HRRF-databank (1990–2009). Leuven: Academia Press.

Grote, D., Patrick, A., Lyles, C., Knight, D., Borrego, M., & Alsharif, A. (2021). STEM doctoral students’ skill development: Does funding mechanism matter? International Journal of STEM Education, 8 , 1–19.

Gu, J., He, C., & Liu, H. (2017). Supervisory styles and graduate student creativity: the mediating roles of creative self-efficacy and intrinsic motivation. Studies in Higher Education, 42 (4), 721–742.

Google Scholar  

Heath, T. (2002). A quantitative analysis of PhD students’ views of supervision. Higher Education Research & Development, 21 (1), 41–53.

Holmwood, J. (2014). From social rights to the market: Neoliberalism and the knowledge economy. International Journal of Lifelong Education, 33 (1), 62–76.

Houston, D., Meyer, L. H., & Paewai, S. (2006). Academic staff workloads and job satisfaction: Expectations and values in academe. Journal of Higher Education Policy and Management, 28 (1), 17–30.

Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6 (1), 1–55.

Jakubiec, B. A. E. (2015). Academic Motherhood:" Silver Linings and Clouds". Antistasis, 5 (2), 42–49.

Jucks, R., & Hillbrink, A. (2017). Perspective on research and teaching in psychology: Enrichment or burden? Psychology Learning & Teaching, 16 (3), 306–322.

Kinman, G., & Jones, F. (2008). A life beyond work? Job demands, work-life balance, and wellbeing in UK academics. Journal of Human Behavior in the Social Environment, 17 (1–2), 41–60.

Kleiner, S. (2014). Subjective time pressure: General or domain specific? Social Science Research, 47 , 108–120.

Larivière, V. (2012). On the shoulders of students? The contribution of PhD students to the advancement of knowledge. Scientometrics, 90 , 463–481.

Lee, A. (2008). How are doctoral students supervised? Concepts of doctoral research supervision. Studies in Higher Education, 33 (3), 267–281.

Lee, M., Coutts, R., Fielden, J., Hutchinson, M., Lakeman, R., Mathisen, B., Nasrawi, D., & Phillips, N. (2022). Occupational stress in university academics in Australia and New Zealand. Journal of Higher Education Policy and Management, 44 (1), 57–71.

Machette, A. T. (2021). Dialectical tensions of graduate teaching assistants. Texas Speech Communication Journal, 45 , 13–28.

Muzaka, V. (2009). The niche of graduate teaching assistants (GTAs): Perceptions and reflections. Teaching in Higher Education, 14 (1), 1–12.

Naylor, R., Chakravarti, S., & Baik, C. (2016). Differing motivations and requirements in PhD student cohorts: A case study. Issues Educ Res, 26 (2), 351–367.

Nature Research. (2022). Nature Careers Graduate Survey 2022. https://doi.org/10.6084/m9.figshare.21277575.v3

Park, C., & Ramos, M. (2002). The donkey in the department? Insights into the graduate teaching assistant (GTA) experience in the UK. Journal of Graduate Education, 3 (2), 47–53.

Paternoster, R., Brame, R., Mazerolle, P., & Piquero, A. (1998). Using the correct statistical test for the equality of regression coefficients. Criminology, 36 (4), 859–866.

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48 , 1–36.

Sabagh, Z., Hall, N. C., & Saroyan, A. (2018). Antecedents, correlates and consequences of faculty burnout. Educational Research, 60 (2), 131–156.

Saks, A. M., & Gruman, J. A. (2014). What do we really know about employee engagement? Human Resource Development Quarterly, 25 (2), 155–182.

Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006a). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66 (4), 701–716.

Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006b). Utrecht work engagement scale-9 (UWES-9). APA PsycTests . https://doi.org/10.1037/t05561-000

Skakni, I. (2018). Reasons, motives and motivations for completing a PhD: A typology of doctoral studies as a quest. Studies in Graduate and Postdoctoral Education, 9 (2), 197–212.

Sonnentag, S., Mojza, E. J., Binnewies, C., & Scholl, A. (2008). Being engaged at work and detached at home: A week-level study on work engagement, psychological detachment, and affect. Work & Stress, 22 (3), 257–276.

Sonneveld, H., & Tigchelaar, A. (2009). Promovendi en het Onderwijs [PhD Students and Education] . http://www.phdcentre.eu/inhoud/uploads/2018/02/Promovendienhetonderwijs.pdf

Southerton, D. (2020). Time scarcity: Work, home and personal lives. In D. Southerton (Ed.), Time, consumption and the coordination of everyday life (pp. 43–67). Palgrave Macmillan.

Chapter   Google Scholar  

Sverdlik, A., Hall, N. C., McAlpine, L., & Hubbard, K. (2018). The PhD experience: A review of the factors influencing doctoral students’ completion, achievement, and well-being. International Journal of Doctoral Studies, 13 , 361–388.

Tham, T. L., & Holland, P. (2018). What do business school academics want? Reflections from the national survey on workplace climate and well-being: Australia and New Zealand. Journal of Management & Organization, 24 (4), 492–499.

Toffoletti, K., & Starr, K. (2016). Women academics and work–life balance: Gendered discourses of work and care. Gender, Work & Organization, 23 (5), 489–504.

Torka, M. (2018). Projectification of doctoral training? How research fields respond to a new funding regime. Minerva, 56 (1), 59–83.

van Tienoven, T. P., Minnen, J., & Glorieux, I. (2017). The statistics of the time pressure scale . Vrije Universiteit Brussel, Research Group TOR.

van Tienoven, T. P., Glorieux, A., Minnen, J., Te Braak, P., & Spruyt, B. (2022). Graduate students locked down? PhD students’ satisfaction with supervision during the first and second COVID-19 lockdown in Belgium. PLoS ONE, 17 (5), e0268923.

Watts, J., & Robertson, N. (2011). Burnout in university teaching staff: A systematic literature review. Educational Research, 53 (1), 33–50.

Woolston, C. (2019). PhD poll reveals fear and joy, contentment and anguish. Nature, 575 , 403–406.

Woolston, C. (2022). Stress and uncertainty drag down graduate students’ satisfaction. Nature, 610 (7933), 805–808.

Zerubavel, E. (1985). Hidden rhythms: Schedules and calendars in social life . Berkeley: Univ of California Press.

Zhao, C. M., Golde, C. M., & McCormick, A. C. (2007). More than a signature: How advisor choice and advisor behaviour affect doctoral student satisfaction. Journal of Further and Higher Education, 31 (3), 263–281.

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Acknowledgements

The authors thank the members of the project steering committee for their constructive feedback on the ideas that led to this contribution. The responsibility for the content and any remaining errors remain exclusively with the authors.

This research is part of the project VUB PhD Survey funded by the Research Council of the Vrije Universiteit Brussel.

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van Tienoven, T.P., Glorieux, A., Minnen, J. et al. Caught between academic calling and academic pressure? Working time characteristics, time pressure and time sovereignty predict PhD students’ research engagement. High Educ (2023). https://doi.org/10.1007/s10734-023-01096-8

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Academic stress and suicidal ideation: moderating roles of coping style and resilience

Franca obiageli okechukwu.

1 Department of Home Science and Management, University of Nigeria, Nsukka, Nigeria

Kalu T. U. Ogba

2 Psychology Department, University of Nigeria, Nsukka, Nigeria

Juliet I. Nwufo

Miracle oluchi ogba.

3 Faculty of Law, Abia State University, Uturu, Umuahia, Nigeria

Blessing Nneka Onyekachi

Chinonso i. nwanosike, amuche b. onyishi, associated data.

The datasets generated and/or analyzed during the study are available from the corresponding author based on special request and the corresponding author should be contacted via this email: [email protected].

As a global phenomenon, suicide has generated a lot of concern. Scholars from various fields have conducted extensive research on the prevalence, causes, factors, and/or management or possible solutions to suicidal ideation. Despite the research efforts, suicidal cases worldwide still yell for more empirical attention. No doubt that some of the extant literature have specifically evidenced the causal links and factors in suicidal ideation. Yet, none had focused on the moderating roles of coping and resilience in an academic population. We therefore, examined the moderating roles of coping and resilience in the relationship between academic stress and suicidal ideation.

We used a cross-sectional design to sample 505 participants (329 males and 176 females) from three southern Nigerian universities. Participants who willingly indicated their participatory consent were administered a paper self-report questionnaire containing the Lakaev Academic Stress Response Scale (LASRS), Scale for Suicidal Ideation (SSI), Brief COPE (B-COPE), and Resilience Scale (RS-14). Hierarchical regression analysis was used to test the hypotheses of the study.

Academic stress ( r  = 0.17; p.001) was found to be positively associated with suicidal ideation, whereas resilience ( r  = −.22; p.001) was found to be negatively associated with suicidal ideation. Suicidal ideation had no significant correlation with adaptive coping style, but it did have a significant correlation with maladaptive coping ( r  = .15; p.001). The regression-based PROCESS macro showed that academic stress was a significant predictor of coping [Δ R 2  = .03, F (1, 502)  =  16.18, p  = .01]. Academic stress was positively associated with suicidal ideation at low or moderate levels of adaptive coping styles. At high levels of adaptive coping styles, the association between academic stress and suicidal ideation was not significant. However, resilience negatively predicted suicidal ideation [R = .29, (R 2  = .08), F(1, 499) = 19.94, p  = .00] with academic stress showing a positive association with suicidal ideation at low and moderate levels of resilience, but for those with high resilience, academic stress was not associated with suicidal ideation.

In sum, suicidal ideation is heightened by increased academic stress, with greater resilience ameliorating the tendency of academic stress resulting in suicidal ideation. Also, adopting maladaptive ways of coping promotes suicidal ideation among students, with resilience and adaptive coping strategies moderating the relationship between academic stress and suicidal ideation. It is therefore recommended that educational administrators, policy makers, lecturers, teachers, and tutors incorporate courses, teachings, and sessions that foster as well as inculcate resilience and efficient coping skills in pupils and students.

Introduction

Suicide is multifarious and a major concern for public health [ 58 , 74 ]. It is a diverse, less comprehensible, life-threatening phenomenon. This is because most victims of suicide hide or conceal their intentions [ 11 , 25 , 70 ], and this makes it difficult (if not impossible) for people to have knowledge of or even gain access to a potential suicide victim. As a result, WHO [ 73 ] noted that one person dies by suicide every 40 seconds despite progress in national prevention strategies. Consequently, it has become the second leading cause of death among youths. Snowdon and Choi [ 58 ] observed that reports of suicide are rare in children under the age of 10, but in the developed world, the prevalence begins to increase for youths between 10 and 14 years of age and in the 15 to 24 year age group [ 14 ]. Among their Nigeria counterparts, Adewuya and Oladipo [ 1 ] observed that the prevalence is 13–29 years, while the Nigeria National Youth Policy [ 43 ] discovered that the prevalence is in the 18–35 year age group. Due to cultural and developmental differences across individuals, there are inconsistencies as to the exact age at which suicidal ideation occurs. This could account for why scholars like [ 1 , 4 , 41 ] noted that evidence from 32 low and middle-income countries in sub-Sahara Africa have high suicide rates among adolescents and young people in general (without reference to a particular age bracket). Uganda, Botswana, Kenya, Zambia, and Nigeria have high prevalence of suicidal ideation among young people [ 55 ]. These youths within “transitory-into-productive” age(s), are seen to be moving from tertiary institutions into the uncertain world of labor markets in the developing (and in some western) worlds. Besides, suicide seems to have had multiple underlying causes [ 9 , 67 ], and therefore requires adopting multiple investigative approach. Hence, our study investigated the moderating impacts of coping and resilience on academic stress and suicidal ideation among students.

Stresses associated with completing tertiary education, as well as concerns about unemployment, poverty, destitution, economic crises, feelings of insecurity, marginalization (including biases), and economic disempowerment [ 8 , 34 , 44 ], are as prevalent in society as the need for adequate coping knowledge [ 8 , 34 , 44 ]. Failure to adequately cope greatly increases the chances of severing youths from the traditional values and moral regulations that seemed to have earlier provided moral foundation and guide, leading to thoughts of suicide. This could account for scholars’ reports (e.g. [ 27 , 36 ]) that suicidal thoughts are more common among younger age groups.

Stress is no longer new to people as it has permeated every aspect of humanity. Hence, the present study would emphasize academic stress. Undergraduateship is not devoid of challenges and stressful circumstances. These circumstances are not limited to adapting to a new academic environment, academic workload, academic performance, attending to lectures, overwork, future employment [ 22 , 49 ], nor social and financial stresses [ 19 ]. Whether these stressors are short-term or long-term, they have significant impact on undergraduates’ coping (either adaptive or maladaptive) capacity [ 19 ]. Productive (adaptive) coping protects students from suicide and suicidal ideation [ 10 , 18 ]; whereas ineffective/dysfunctional (maladaptive) coping skills among students experiencing persistent academic stress and negative emotions trigger higher risk of suicide. The relationship between academic stress and suicidal ideation has been well documented in literature (e.g [ 31 , 48 , 66 ]). Generally, the role of stressful life events in suicidal ideation, attempts, and completion has been a key area of study in the epidemiology of mental disorders [ 35 , 69 ]. There is a need to understand the moderating roles of some factors in the observed association [ 45 ] between academic stress and suicidal ideation in a bid to advance research knowledge on suicide, intervention, and treatment. This is an important contribution that the current study offers to the body of knowledge. Since stress has been implicated in suicide [ 31 , 48 ], with no drugs for identified victims of suicidal ideation, coping is very germane.

Lambert and Lambert [ 38 ] noted that coping is a conscious effort to reduce stress, and entailing masterful ways of tolerating, reducing, or minimizing stressful events. The conceptualization and categorization of different coping styles is inconsistent in literature (cf. [ 57 ]). Notwithstanding divergent opinions on conceptions of coping, coping has colossal impacts on stress (academic not exempted) and suicidal ideation. For instance, behavioural disengagement and self-blame increase suicidal vulnerability [ 30 ], deficient coping and problem solving skills heighten suicidal ideation [ 59 , 62 ], passive coping (usually fantasizing) fosters suicidal ideation [ 75 ], while ineffective coping skills and negative emotions trigger higher risk of suicide [ 15 ]. Coping skills such as active coping and positive reframing were negatively associated with suicide, whereas coping skills like self-distraction, substance abuse, behavioural disengagement, venting, and self-blame were positively associated with suicide (e.g. [ 39 ]).

Besides these direct associations, psychopathological factors, including depression [ 68 ], hopelessness [ 21 ], and psychological distress [ 63 ], have been tested as mediators between life stress and suicidal ideation, with fewer research enquiries involving resilience. Resilience is an individual’s tendency to bounce back to a previous state of normal functioning, or simply not showing negative effects after stress and adversity. Wagnild [ 71 ] noted that resilience is an ability to recover from stress. As a helpful behavioural disposition, it promotes an individual’s healthy survival and soothes the negative outcome of stress. Resilience is important as it ensures healthy social functioning, morale, and somatic health, as well as helps an individual maintain emotional stability in the midst of stress [ 64 ]. Hence, understanding resilience appears to provide homeostasis [ 51 ] and personal endurance [ 33 ]. A study [ 40 ] on the relationship between resilience and well-being associated resilience with a positive view of the self. Cleverly and Kidd [ 16 ] found youths’ perceived resilience related to less suicidal ideation, whereas higher psychological distress was associated with higher suicidal ideation. Furthermore, depression has been linked to suicidal ideation, with anxiety, mental health, resiliency, and daily stress playing important roles [ 32 ]. Again, resilience dimensions such as social resources and familial cohesion were strongly and negatively correlated with humiliation, interpersonal sensitivity, and depression in subjects with previous suicidal attempts [ 52 ].

To our knowledge, no study has combined coping and resilience as moderators of the relationship between academic stress and suicidal ideation. Rather, extant related literature have either focused on stress (not academic stress) and suicidal ideation [ 17 , 20 ] or coping and suicidal ideation [ 10 ]. Although Zimmerman [ 76 ] provided useful theoretical explanations and understandings as to how some ‘promotive factors’ could interrupt the pathways to mental health difficulties among youths, we believe it is necessary to investigate as many of these promotive factors (including coping and resilience) as possible with respect to suicidal ideation. The present study might support as well as enhance, and further the theoretical explanations of Zimmerman [ 76 ]. However, it is important to note that some studies have investigated coping as a moderator in relationship of stress (but not necessarily academic stress) and suicidal ideation (e.g. [ 17 , 20 , 68 ]). We assume that coping styles will have moderating impact on suicidal ideation and academic stress among undergraduates, especially for those who adopt functional or adaptive coping styles, compared to those who do not. In the same vein, we equally propose that resilience will moderate the link between academic stress and suicidal ideation. When confronted with the aforementioned potential stressors, a student who is stressed but adopts dysfunctional or ineffective coping styles (blaming oneself for problems, ignoring them, or escaping through fantasizing thoughts) may likely consider suicide as an option to end the perturbation [ 26 ]. Those who use effective or functional strategies (positive reevaluation, planning, and seeking help) are less likely to consider suicide [ 39 ]. In other words, coping could either increase or decrease the effect of academic stress on suicidal ideation, whereas resilience helps them bounce back after having adaptively coped with academic stress. Therefore, we hypothesized first, that academic stress would predict suicidal ideation; second, while adaptive coping style would not predict suicidal ideation, maladaptive coping style would; third, adaptive coping style would moderate the association between academic stress and suicidal ideation such that at low or moderate levels of adaptive coping styles, academic stress would be positively associated with suicidal ideation; but at high levels of adaptive coping style, the relationship of academic stress and suicidal ideation would not be significant. Finally, resilience would negatively predict suicidal ideation [ 54 ] as well as moderate the association between academic stress and suicidal ideation, such that academic stress would show a positive association with suicidal ideation for students at low and moderate levels of resilience, but for those with high resilience, academic stress would not be associated with suicidal ideation.

In comparison with most western societies, single studies on the moderating roles of coping, resilience on academic stress and suicidal ideation in a Nigerian sample are very rare. Also, studies with Nigerian (and perhaps other) samples have rather dominated the areas of protective and risk factors for suicidal behaviour and ideation (e.g. [ 1 , 2 , 46 , 53 ]). Our study is relevant because it advances the knowledge quest for preventive and management approaches for students and school administrators who may struggle to successfully navigate academic-related stress without deteriorating to suicidal ideation.

The understanding that suicidal ideation may decrease among undergraduates because of adaptive or functional coping skills; and that students who practice functional coping skills may suppress the negative experiences, anxiety, and psychological distress that emanate due to academic stress, is very crucial in proposing and inculcating a positive academic survival approach. This outcome could equally be transferred into other domains of students’ lives even after school. It is also essential to policymakers, educational administrators, parents, students, and society at large as no one is exempted from the scorching heat of rampant suicide among undergraduates- a generational transitory population. Therefore, the study encourages stakeholders to teach and practice adaptive coping skills as well as resilient techniques whose ripple effects not only reduce suicidal ideation but also help in healthy living.

Participants and procedure

The study adopted a cross sectional design to sample a total of 505 undergraduates from three South-Eastern universities in Nigeria. They consisted of 329 (65.1%) males and 176 (34.9%) females who were conveniently sampled at their clustering and administered a self-report battery of measures. Out of the five federal universities in the Southeast, three universities were randomly selected using a table of random numbers. The three universities were: the University of Nigeria, Nsukka (UNN), the Alex Ekwueme Federal University, Ndufu Alike Ikwo (AE-FUNAI), and the Michael Okpara University of Agriculture. The University of Nigeria, Nsukka was founded by Nnamdi Azikiwe in 1955 and formally opened in 1960. UNN has more than nine faculties, including the faculties of Agriculture, Arts, Biological Sciences, Education, Engineering, Pharmaceutical Sciences, Physical Sciences, Social Sciences, Veterinary Medicine, a School of General Studies, etc. The Alex Ekwueme Federal University Ndufu Alike Ikwo (AE-FUNAI) is located in Ndufu, Alike Ikwo in Ebonyi State, Nigeria. It was established in 2011. Courses offered include: Agriculture, Basic Medical Sciences, Education, Engineering and Technology, Humanities, Management Sciences, Social Sciences, Biological Sciences, Environmental Sciences, College of Medicine, Physical Sciences, Law, etc. The Michael Okpara University of Agriculture is located in Umudike, Abia State, Nigeria and was established as a specialized university in 1992. Education, Veterinary Medicine, Applied Food Science and Tourism, Agricultural Economics, Rural Sociology, Extension, Animal Science & Animal Production, Physical & Applied Sciences, Natural Resources & Environmental Management, Natural Sciences, Management & Social Sciences, Engineering & Engineering Technology, Crop & Soil Sciences, and Humanities [ 13 ].

In terms of setting, these universities were similar. In that, the establishment of a university automatically transforms even the most rural of places into an urban setting. However, these universities differed in terms of courses offered and socio-economic status. At the selected federal universities, participants were met at their various hostels and lecture quadrangles. Those who indicated their participatory consent prior to the creation of rapport were administered the self-report battery of measures. Age, sex, ethnic group, marital status, and educational qualifications were assessed through the self-report battery of measures. Participants were asked to indicate by ticking in the appropriate boxes their age (in years); sex (male and female); ethnic group (Igbo, Hausa, Yoruba, and others); marital status (single and married); and educational qualification. Educational qualification was removed from the analysis because the participants were still undergraduate students. The four instruments were prepared in a questionnaire format. A brief statement of consent that sought the participant’s consent was attached to the questionnaire. Participants were expected to first read through the brief consent letter and indicate their participatory consent by ticking on the appropriate boxes. Those who declined their interest in participation in the consent letter were asked to kindly return the questionnaire. The questionnaires were administered on a one-on-one basis and retrieved upon completion [ 29 ]. In addition to the consent letter, the questionnaires were distributed to students who willingly accepted to take part in the study, with a preceding self-introduction and explanation of the objective of the study. Participants were verbally appreciated. Out of the 530 copies of the questionnaire distributed, 523 were returned (98.7% return rate), while 18 were discarded due to improper completion. To preserve the homogeneity of the sample, all participants were undergraduates, irrespective of other demographic characteristics. Our procedures met relevant ethical guidelines and legal requirements in Nigeria to warrant the ethical approval obtained on (November 21, 2019) from the Institutional Review Board, University of Nigeria, Nsukka.

Lakaev academic stress response scale (LASRS [ 37 ])

The LASRS is a 21-item structured scale that measures students’ responses to stress in physiological, behavioural, cognitive, and affective domains. Respondents rated how much of the time they experienced symptoms on a 5-point Likert scale [ 37 ] with the anchors: None of the Time (1), A Little of the Time (2), Some of the Time (3), Most of the Time (4), and All of the Time (5). Items were summed for subscale scores, and subscales were summed for a total LASRS stress response score. Higher scores indicated a greater stress response. It has excellent psychometric properties with internal consistency ranging from .64 to .92 [ 37 ]. Our pilot testing of the scale yielded a Cronbach’s alpha of .83.

Scale for suicidal ideation (SSI [ 6 ])

SSI is a 19-item self-report scale designed to quantify the intensity of current conscious suicidal intent, by scaling various dimensions of self-destructive thoughts or wishes. The items assessed the extent of suicidal thoughts and their characteristics, as well as the respondent’s attitude towards them; the extent of the wish to die, the desire to make an actual suicide attempt, and details of plans, if any; internal deterrents to an active attempt; and subjective feelings of control or “courage” regarding a proposed attempt. Each item consisted of three alternative statements graded in intensity from 0 to 2. Suicidal ideation was analysed dimensionally with scores ranging from 0 (low ideation) to 38 (high ideation) [ 6 ]. In other words, a positive rating (> 1) on any of the ideation scale’s 19 items was considered as a potential indicator of suicide ideation. Out of 29 items, 16 had positive and significant item-total correlations, and a Cronbach alpha of .89 was obtained, which indicated the high reliability of the SSI and also supported the validity of this scale [ 6 ]. The validity of SSI was also indicated by the moderate correlations with clinical ratings of suicidal risk and self-harm [ 7 ]. The scale was pilot tested and the result yielded a Cronbach’s alpha of .82.

Brief COPE (B-COPE [ 12 ])

The B-COPE provides researchers a way to quickly assess potentially important coping responses. It consists of 14 sub-scales, each of two items. Therefore, B-COPE has a total of 28 items, which measure 14 conceptually differentiable coping skills. Some of these skills are known to be generally adaptive (such as active coping, planning, positive reframing, acceptance, humor, religion, emotional support-seeking, and instrumental support-seeking); others are known to be problematic or maladaptive (such as self-distraction, denial, venting, substance use, behavioral disengagement, and self-blame). The response options ranged from 0 (I haven’t been doing this at all) to 3 (I have been doing this a lot). Researchers have variously shown B-COPE to have had good psychometric properties [ 24 , 28 ]. All dimensions demonstrated good internal consistency (.70) in our pilot testing of the scale, with the exception of religion (=.63) and venting (=.61). We re-analyzed the adaptive and maladaptive dimensions, and they both showed high reliability (=.85 and.79, respectively). Higher score on the adaptive dimension indicates higher adaptive measures, while a lower or moderate score on the maladaptive dimension indicates adaptive coping.

Resilience scale (RS-14 [ 72 ])

RS-14 measures the capacity to withstand life stressors and derive meaning from them. It contains items which measure two major dimensions of psychological resilience: personal competence (as indicated in items 1, 2, 5, 6, 7, 8, 9, 11, 12, 14), and acceptance of self and life (as indicated in items 3, 4, 10, 13). It has a composite internal consistency reliability of .93. All the 14 items were positively worded, and participants responded on a 7-point scale that ranged from “strongly disagree” (1) to “strongly agree” (7). We obtained a Cronbach’s alpha of .90. A higher score on RS-14 indicates greater resilient capacity.

Statistical analysis

The research was a survey. A Pearson’s Correlation ( r ) analysis was conducted to examine the relationships between the demographic factors both with themselves and the other independent and dependent variables in the study. The reason for the choice of correlation is based on Urbina’s [ 65 ] assertion that correlations play a major role in demonstrating linkages between (a) scores on different tests, (b) test scores and non-test (demographic) variables, (c) scores on parts of tests and scores on whole tests, etc. [ 65 ]. Demographic variables such as gender were dummy coded before they were included in the correlation analysis. Dummy coding was recommended by experts in statistics as very important in correlation and regression as a “way of representing people using only zeros and ones” [ 23 ]. In order to clearly test the hypotheses, the study variables were submitted to a hierarchical regression analysis. Hierarchical regression analysis allows researchers to simultaneously examine the contributions of each of several predictor variables in one study. In the regression analysis, the demographic variable of marital status that was significantly correlated with suicidal ideation was first included in the analysis in order to control for its possible effect. This formed Step 1 in the analysis. Thereafter, academic stress was included in the regression to test for its predictive association with suicidal ideation, and this formed Step 2 of the analysis. Afterwards, the adaptive dimension of the coping strategy (which was considered as a separate entity) was included in the analysis, and this formed Step 3. Subsequently, the maladaptive dimension of the coping strategy was added to the analysis and this formed Step 4. Finally, resilience was added to the analysis and that formed Step 5. These variables were “entered” “step-by-step” (separately) into the analysis in order to examine the various respective accounts or percentage contributions of each predictor variable in the relationship [ 50 ].

The Hayes regression-based PROCESS macro was used to test for the moderation relationships. The PROCESS macro was chosen because it offers the opportunity to determine the interaction effect by generating a series of plots that can be later put together into a diagram or graph. The diagram further illustrates the conditional effect of X (main predictor) on Y (dependent variable), as a function of M (moderator variable). The moderating effects are thereafter examined using the regions of significance in accordance with the Johnson-Neyman technique. Process is a better choice for research where the variables are all directly measured (e.g., in clinical, health, and psychological settings that use hard data). All analyses were conducted using the Statistical Package for Social Sciences (SPSS) version 22 [ 42 , 61 ].

From the results of the brief descriptive statistics (Table  1 ) performed on the demographics like age, marital status, and religion, the ages of the participants ranged from 18 to 32 years, with a mean age of 25 years and a standard deviation of .45. A total of 492 (97.4%) were single, while 7 (1.4%) were married. The number of Christians in the sample was 486 (96.2%), traditional 17 (3.4%), and Islam 2 (.4%). Age, marital status, religion, etc., that have been either positively or negatively implicated in suicidal ideation [ 1 , 4 ], were included in the preliminary stage of the analysis. Inclusion criteria included full-time registered, non-working class undergraduate students of federal universities under study, while exclusion criteria included working class and postgraduate students who were known to be registered students of federal universities under study.

Descriptive statistics of the participants

Results in Table  2 showed that suicidal ideation had a positive association with marital status ( r  = .08, p.05) but did not correlate with gender, age, or ethnic group. Academic stress ( r  = .17; p.001) was found to be positively related to suicidal ideation, whereas resilience ( r  = −.22; p.001) was found to be negatively related to suicidal ideation. Gender, age, and ethnic group that did not correlate with suicidal ideation were excluded from the analysis, and marital status, which correlated with suicidal ideation, was controlled in the subsequent moderation analysis. Suicidal ideation had no significant relationship with adaptive coping style ( r  = −.02), but it did have a significant relationship with maladaptive coping ( r  = .15; p.001).

Mean, standard deviation and correlation results of academic stress, resilience and coping (Maldaptive and adaptive) on suicidal ideation

SD standard deviation, ACS adaptive coping style, MALCS maladaptive coping style, Str stress

* p  < .05

** p  < .01

*** p  < .001

Table  3 indicates that subscales of coping were correlated with suicidal ideation. The separation of B-COPE into adaptive and maladaptive styles was done after the various dimensions of adaptive and maladaptive coping styles were correlated with suicidal ideation as shown in Table ​ Table3. 3 . Subsequently, strategies that negatively correlated (active, planning, positive refraining, acceptance, religion, and emotional support) with suicidal ideation were indicated as protective or adaptive and were summed together, while strategies that positively correlated (humour, instrumental support, self-distraction, denial, venting, behavioural disengagement, self-blame, and substance use) with suicidal ideation were maladaptive and summed together. This categorization is in line with extant literature (e.g. [ 5 , 47 ]), which specifically suggested and categorized substance use (such as alcohol) as a maladaptive coping style because it impairs judgment and disinhibits impulses, and as such, users of such substances are more likely to harm themselves or die by suicide.

Correlation results between B-COPE and suicidal ideation

** p  < .001

Results in Table  4 showed that Step 1, which involved only the demographic variable (marital status), revealed no significant result. R = 08, (R2 = .01), F(1, 503) = 2.93. Step 2 yielded a significant result: R = .19, (R 2  = .04), F (1, 502) = 16.18, p  = .01. The results showed that the addition of academic stress accounted for an additional 3 % of significant variance in suicidal ideation. ΔR2 = .03, F (1, 502) = 16.18, p  = .01. However, Step 3 did not yield any additional significant results. Δ R 2  = .04, (R 2  = .06, F (1, 501) = .09. Step 4 produced a significant overall model, with R = .22, (R 2  = .05), F (1, 500) = 5.44, p  = .00. This means that the inclusion of a maladaptive coping style accounted for 1% of the significant variance in suicidal ideation, R2 = .01, F (1, 500) = 5.44, p  = .00. And finally, Step 5 yielded a significant result, R = .29, (R 2  = .08), F (1, 499) = 19.94, p  = .00. Furthermore, the inclusion of resilience accounted for an additional 4% variance in suicidal ideation, R2 = .04, F (1, 499) = 19.94, p  = .00.

Hierarchical regression model results of academic stress, resilience and coping (Maldaptive and adaptive) on suicidal ideation

ACS adaptive coping style, MALCS maladaptive coping style, B standardized beta coefficient, β unstandardized beta coefficient, t total, F f-ratio, R 2 R Squared

Results in Table ​ Table4 4 indicated that marital status, which was initially correlated with suicidal ideation, failed to predict suicidal ideation. However, academic stress was a significant predictor of suicidal ideation. At low (B = .12, t = 4.40, p  < .001) and moderate (B = .02, t = 3.19, p  < .01) levels of adaptive coping style, academic stress was positively associated with suicidal ideation, but the association between academic stress and suicidal ideation was not significant at high levels of adaptive coping style (B = .03, t = 1.41, p  < .16), (Fig.  1 ). Suicidal ideation, on the other hand, was negatively predicted by resilience (B = −.07, SE = .02, p.001). However, academic stress was positively associated with suicidal ideation at low (B = .12, t = 3.93, p  < .001) and moderate (B = .06, t = 2.91, p  < .01) levels of resilience; but for those students with high resilience, academic stress was not associated with suicidal ideation (B = .03, t = 1.08, p  < .281), (Fig.  2 ). To avoid potentially problematic high multi-collinearity with the interaction terms, the variables were centered and an interaction term between adaptive coping style and suicidal ideation as well as the interaction between resilience and suicidal ideation were created [ 3 ]. Examination of the interaction plots is illustrated in Figs.  1 and ​ and2 2 .

Adaptive coping style moderating the link between academic stress and suicidal ideation

Resilience moderating the link between academic stress and suicidal ideation

Our hypothesis that academic stress would significantly predict suicidal ideation was confirmed, and this finding is consistent with extant studies [ 10 , 18 , 39 ]. Other literature (e.g [ 31 , 48 , 66 ]) have also documented the significant relationship between academic stress and suicidal ideation. In line with our goal of examining the moderating roles of coping styles in furthering research knowledge about suicide, intervention, and treatment, we found that adequate coping with academic stressors was key to avoiding suicidal ideation among students. This finding is very important as educational administrators and policy makers should incorporate courses and teachings of effective coping skills into their programs, especially for young students since stressors are inherent in the lives of undergraduate students, especially in our society and at this perilous time.

Stressors have become so prevalent in undergraduate education [ 19 , 22 , 49 ] that adequate coping skills have become a panacea to the likelihood of impending suicidal ideation [ 31 , 48 ]. We found that adaptive coping styles did not significantly predict suicidal ideation, but moderated the relationship such that low or moderate coping with academic stress would most likely lead to suicidal ideation. Students are mostly confronted with the challenges of adapting to a new academic environment, academic workload, academic performance, attending to lectures, overwork, or thoughts of future employment after graduation [ 22 , 49 ], and most seriously, social, emotional, and financial stress [ 19 ]. This is also in consonance with worries about unemployment rates, poverty and destitution, economic crises, feelings of insecurity, marginalization, and economic disempowerment [ 8 , 44 ] that dominate our society today. It is made even worse when the student(s) loses their guardian/parents/sibling who pays their academic bills, or when the guardian/parents/sibling suffers a misfortune that renders him/her almost destitute.

Resilient students have the ability to recover from stress [ 71 ], but not without adequate coping strategies. Our study found that resilience was positively associated with academic stress and negatively predicted suicidal ideation. Thus, the hypothesis which stated that resilience would moderate the relationship between academic stress and suicidal ideation was confirmed. This simply means that those who cope well with academic stress have a better chance of bouncing back than those who do not, and they are less likely to consider suicide. In line with our findings, Tugade et al. [ 64 ] noted that resilient people have much more adaptive behaviours, particularly in the areas of social functioning, morale, and somatic health, and such people equally experience positive emotions amidst stress; given that moral and social functioning are anti-suicidal tonics. The resiliency theory proposed by Richardson [ 51 ] explains that qualities of resilience such as optimism, hopefulness, and meaningful engagement ensure higher immune levels than helplessness, hopelessness, and depression (which are precursors of suicide). Therefore, resilience promotes succor and adequate coping under threats of various academic stressors.

Our findings can be explained by Aaron Anthonovsky’s Salutogenic Model of Resilience. In its explanations of resilience, the salutogenic model ignores the whole notion of risk exposure as a prerequisite for being labelled “resilient” and instead places the emphasis on factors that contribute to health and wellbeing. The salutogenic model specifically focuses on factors that help identify coping resources that may contribute to resilience and effective adjustment, notwithstanding adversity and risk [ 60 ]. It is adequate coping skills that make resilient students able to quickly regain a sense of balance that keeps them going despite academic difficulty and trouble, and equally makes them find meaning amidst academic confusion and turmoil. Resilient students are self-confident and understand their own strengths and abilities. They do not feel a pressure to conform but take pleasure in being unique. Extant literature have documented the relationships between resilience and well-being [ 40 ]. Perceived resilience was associated with less suicidal ideation whereas higher psychological distress was associated with higher suicidal ideation [ 16 ], depression, anxiety, mental health, resiliency, and daily stresses had been linked to suicidal ideations and are noted to play significant role in suicidal ideation [ 32 ]. To our knowledge, it seems that no study had particularly evaluated the moderation of coping and resilience on the path of academic stress and suicidal ideation. Hence, our study becomes an interesting read for students, educational administrators, and some other non-governmental suicidal organizations.

Our study is not without limitations. For instance, the small sample size of our study may not have been large enough to account for generalizations across cultures. In the same vein, university differences in terms of courses offered, and socioeconomic status, which definitely would have ensured a more homogenous population, were not factored in the sampling process. Subsequent studies should consider such university differences and capture course types that might impact on academic stress and suicidality. Again, as a cross-sectional study, our data do not allow for full inferences about causal directionality. As a self-report measure was adopted in the study, there is the possibility of response biases as participants may either have made socially acceptable answers rather than being truthful or were unable to accurately assess themselves; all these threaten the reliability and validity of the measurement. Equally, tools employed in this study, like the Lakaev Academic Stress Response Scale, Scale for Suicidal Ideation, Brief COPE, and Resilience Scale, cannot be viewed as diagnostic tools, but only as screening tests to identify members of groups at risk for these conditions. The results arising from these tools tell us how the students perceive their health but are not in themselves evidence of medical concerns. Therefore, future studies should consider making more directional inferences, perhaps from a more controlled experimental investigation as well as cross cultural variances in suicidal ideation. We did not also take into account several ways people ideate about suicide (e.g., active ideation with plans, thoughts of suicide, and urges) as noted by Rizvi and Fitzpatrick [ 56 ]. There is a likelihood that the frequency, duration, intensity, and future possibility of these ways of ideating suicide could have been propagated by the academic environment and that most students at different times have the urges and thoughts (with or without) active plans. This area should be explored further. Finally, s election bias could undermine the internal validity of the study. However, the use of this approach might not have a significant impact on the outcome of this study. Nonetheless, this can only be ascertained when further studies are conducted while taking into consideration the issues raised. We acknowledge this as a limitation of the sampling technique adopted and advise the exercise of caution in making generalizations from these findings.

Based on the limitations stated above, it is recommended that future studies ensure adequate representativeness, increased homogeneity, etc. in order to foster generalizations of the findings.

Resilient students having the ability to recover from stress are only possible with adequate coping strategies even as resilience positively associated with academic stress and negatively predicted suicidal ideation. Our findings affirm the research trend that academic stress is associated with suicidal ideation, with resilient students able to bounce back from academic challenges. Good coping strategies also enable resilient students recover from stress, consequently reducing their likelihood to ideate about suicide. Our students must adopt positive coping strategies towards solving their academic problems and learn persistence in the midst of threatening academic situations.

Our findings contribute to the growing evidence that adequate coping with academic stressors and resilient skills are keys to avoiding suicidal ideation among young students. Resilient students with adequate coping strategies find it easier to recover from stress even as resilience is positively associated with academic stress and negatively predicted suicidal ideation. This simply indicates that those who cope well with academic stress have more chances of bouncing back than others who do not, and may not likely ideate about suicide.

Acknowledgments

Special thanks to the Heads, Department of Psychology and Department of Home Science and Management, University of Nigeria Nsukka and Dean Faculty of Law Abia State University Uturu for granting us all the necessary approval and support that saw us through the length of time the study lasted.

Informed consent

Written informed consent was duly obtained from all the participants. The informed consent was the first attached document to the questionnaire such that any participant who did not willfully accept to participate will either not be administered the questionnaire or if already administered, will be retrieved.

Authors’ contributions

OFO critically and constantly proof read this work. KTUO, performed the data coding, data analysis and interpretation of the results. OMO and NJI’s expertise were brought to bare in coining the topic, and putting together the introduction of this work. The discussion was however anchored by OBN. While NCI formatted the references, all authors joined OAB in study design, gathering of data and equally approved the final version of the manuscript for submission. The author(s) read and approved the final manuscript.

Authors’ information

Dr. Okechukwu Franca O. held from Anambra State, Nigeria. Obtained her B.Sc, M.Sc and PhD in Home Economics at University of Nigeria, Nsukka. A senior lecturer in Child Development and Family Studies. She teaches and supervises undergraduate and postgraduate students. Her research interest is on children and family related issues.

Ogba, Kalu Timothy. Uyor, is a PhD (Social Psychology) holder and lecturer at the Psychology Department, University of Nigeria, Nsukka where I have taught a number of courses. I belong to a number of professional, religious and social organizations. To my credit are numbers of publications that mainly centered on personality, home safety, suicide, health & wellbeing and other nagging societal issues.

My name is Dr.(Mrs) Juliet Ifeoma Nwufo, Diploma in Ed (UNN), Bsc Psycholog(UNN), M.Sc in Developmental Psychology (UNN), Ph.D in Developmental Psychology (UNN). A lecturer and a researcher at the Department of Psychology UNN. She teaches undergraduates and Msc students and a reviewer to many journals both local and international. She has published in many journals both local and international. Research interests includes: psychological issues in general and mainly on adolescent issues like aggression, violence, and addictive behaviours and most of her publications is on adolescent problem.

Miracle Oluchi Ogba is an indigene of Akanu Ohafia, Abia State of Nigeria. I am a lecturer and MSc/PhD student at the Faculty of Law, Abia State University, Uturu. I specialize in Corporate Organization and Law has won a number academic excellence awards, written and published widely, attended both local and international conferences.

Blessing N. Onyekachi Doctor of social psychology in the University of Nigeria, Nsukka. My research interest spans across social psychological problems, happiness and conflict resolution. A mother of three lovely children, with some publications in both local and international journals,

Chinonso Nwanosike is a Lecturer/ Social psychologist at the University of Nigeria Nsukka where she started the graduate social psychology program for years. Her publications are in the areas of mental health, gender issues, positive psychology, family and marital relations, ethics and sexuality, and domestic violence.

Onyishi Amuche Bonaventure is an experimental psychologist, and Assistant Lecturer at the Department of Psychology, University of Nigeria Nsukka, Enugu State, Nigeria. Amuche Onyishi is a young bright researcher with an interest in Learning, Memory, Cognition and Problem solving. He has published in reputable Journal such as Journal of Social Sciences.

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Availability of data and materials

Declarations.

The above referenced research project has been reviewed and approved in line with the Department of Psychology, University of Nigeria, Institutional Review Board. The reference number is listed beside the title.

In line with our procedures, this approval is valid for 1 year (21st November, 2019 - 22nd December, 2020). Any changes regarding the presented protocol will require reconsideration by the Review Board. You also require to complete and submit the termination form at the end of this project.

The Department of Psychology, University of Nigeria, Institutional Review Board hereby affirms our approval of all the experimental protocols as far as this project is concerned. Our approval was, of course, based on our confirmation that all methods are carried out in line with the relevant guidelines and regulations as stipulated by University of Nigeria, Institutional Review Board.

We declare that our study was carried out successfully without any relationships that would be understood as a potential conflict of or competing interest.

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Contributor Information

Franca Obiageli Okechukwu, Email: [email protected] .

Kalu T. U. Ogba, Email: [email protected] .

Juliet I. Nwufo, Email: [email protected] .

Miracle Oluchi Ogba, Email: moc.liamg@026alakoelcarim .

Blessing Nneka Onyekachi, Email: [email protected] .

Chinonso I. Nwanosike, Email: [email protected] .

Amuche B. Onyishi, Email: [email protected] .