Online Learning and Mental Well-Being of Academic Staff in Kenyan Universities: Exploring Stress, Workload, Work-Life Balance, and Demographic Variations

Online Learning and Mental Well-Being of Academic Staff in Kenyan Universities: Exploring Stress, Workload, Work-Life Balance, and Demographic Variations

*¹Boniface Kimwere., ²Dr. Mary Mwanzia, PhD

¹Master’s Student: Knowledge Management and Innovation, KCA University

²Lecturer in Strategic Management /Marketing, KCA University

*Correspondence Author

DOI: https://doi.org/10.51584/IJRIAS.2025.10030046

Received: 05 March 2025; Accepted: 13 March 2025; Published: 10 April 2025

ABSTRACT

This qualitative research study explores the impact of remote or online learning on the mental well-being of academic staff in Kenyan universities. The study addresses the deterioration of mental well-being among these professionals due to the introduction of online learning models. The research paper highlights key problems faced by academic staff, including increased stress levels, workload, and work-life balance issues, which are exacerbated by the radical shift to remote teaching that gained considerable attention during and after the Coronavirus Pandemic. The study involved 15 academic staff members drawn from both private and public universities and utilized questionnaires to collect data that was analysed through thematic analysis. The findings disclosed a split among respondents regarding being overwhelmed by demands of online teaching. In this study, 53.3% affirmed that they felt overwhelmed due to increased online time, technical issues, and slow internet. The outcomes also showed that academic staff members reported considerable mental health issues due to online teaching. Accordingly, 66.7% revealed that increased workload adversely affected their mental wellness, citing multiple stressors, including large class sizes, tight deadlines, and technical issues. Significantly, 80% of these respondents reported experiencing burnout due to excessive academic responsibilities, comprising constant availability to students and administrative burdens. Apart from this, work-life balance also emerged as a crucial concern, with 76.9% of the respondents disclosing that work commitments often interfered with their typical daily and personal activities. The shift to online learning has blurred the lines between personal and professional time, leading to academic staff working late into the night and during weekends. Based on the explained findings, this research study makes multiple recommendations, implementing comprehensive support systems for online teaching, introducing mental health and well-being programs for academic staff, creating clear work-life balance policies, and providing targeted support for different demographic groups. Furthermore, the study emphasises the need for Kenyan universities to recognize the mental health and wellness of their academic staff and understand how this plays a role in their long-term success.

Keywords: Academic Staff, Burnout, Demographic Groups, Mental Well-being, Online Learning, Remote Teaching, Stress Levels, Work-Life Balance, Workload

INTRODUCTION

Background and Context

Technological advances have produced remarkable changes in the education segment, allowing students who cannot attend physical classrooms to engage with instructors remotely. Undeniably, as scholars have pointed out, higher education is currently being pursued by an unprecedented number of increasingly non-traditional students (Zamecnik et al., 2021). Universal access to information and adult education has emerged as a crucial component of emerging information society. In the context of remote learning, higher education establishments can adopt two primary configurations: a hybrid or blended model that incorporates face-to-face classrooms with online learning and a pure online framework (Sudhakar et al., 2023).

The evidence of distance learning can be traced to the 18^th century when schools organised learning through an intricate exchange of letters. Caleb Phillips, an American entrepreneur, developed a creative idea that letters could facilitate education when transferred to recipients through messenger services (Farnsworth & Bevis, 2006). Phillips, in 1728, capitalised on this unique idea, leading to the birth of the correspondence approach to learning and teaching shorthand courses. Despite his pioneering efforts and costly advertisements, experts cannot establish the number of students that enrolled. However, this was the first attempt to create distance learning.

Remarkably, 116 years later, in 1840, Sir Isaac Pitman started teaching students using mail and fashioning his instructions to benefit adults who had no time to attend physical classes (Farnsworth & Bevis, 2006). The success of this learning model compelled universities to adopt correspondence courses. For example, the University of London adopted the same approach in 1856. Correspondence courses continued to become popular until the mid-1900s. As new technologies emerged, educational establishments adopted video conferencing between the 1950s and 1960s. The 1950s and 1980s were characterised by the adoption and use of teleconferencing. Interestingly, from the 1990s to the present, institutions have adopted and continue to use web-based instruction.

As of 2012, 69% of academic leaders in the United States affirmed that online education was a crucial long-term strategy for educational establishments (Kentnor, 2015). Before 2020, educational organisations were incorporating online learning to supplement traditional learning arrangements. Many critics within the higher education sector, as Kentnor (2015) notes, have opposed this method of learning due to its perceived inability to guarantee the quality of education and the necessary tools to inspire and motivate students, as witnessed in physical learning sessions. For instance, in the decade leading to 2020, only 30% of professors approved distance learning (Ruth, 2018). Instructors also voiced their opposition to online learning, suggesting that students in online settings were likely to engage in collaborative learning, and this approach limited faculty-student interactions (Dumford & Miller, 2018). In South Africa, the adoption of blended learning after a series of protests affecting universities produced a mix of advantages and disadvantages (Czerniewicz et al., 2019). Lecturers challenged this learning model, suggesting that major limitations were evident in content and pedagogy (Czerniewicz et al., 2019). In the Kenyan context, the adoption of online learning was fraught with challenges, with institutions facing social, technical, organisational, and national problems (Kibuku et al., 2020).

While addressing the issues facing online learning adoption in Kenya, Mutisya et al. (2016) affirmed that the primary issues facing lecturers were heavy workloads, insufficient internet connectivity, limited information and communication technology skills, insufficient time for online learning interactions, inadequate computer laboratories, and lack of incentives to fully engage in online instruction. Mutisya et al. (2016) also pointed out problems facing students, including a lack of internet connectivity and computers to participate in online learning. As of 2016, Makokha and Mutisya (2016) reported that most Kenyan universities lacked senate backing for online learning policies. At the time, only 10% of courses were offered online, and all Kenyan universities had only 35% and 32% of students and lecturers using the online learning approach (Makokha & Mutisya, 2016).

In many cases, learning on digital platforms only involved (87%) submission of lecture notes and had no online-based interactions. Makokha and Mutisya (2016) concluded that most Kenyan universities lacked the requisite infrastructure, and instructors did not have the necessary ICT skills to facilitate online learning. To highlight the challenges during this period, a study reveals that in 2014, Kenyan universities had 16,174 student lab computers that were available for 423,664 students learning in over 30 universities (Tarus et al., 2015). Fortunately, in the Kenyan higher education segment, 53% of students had acquired laptops, easing their online learning activities (Tarus et al., 2015). The development has helped students by addressing challenges related to accessing online lessons.

Unfortunately, studies focusing on online learning as it pertains to the Kenyan context have failed to highlight the resulting mental impact of this education system on academic staff. Numerous studies, such as Chu and Li (2022), Lemay et al. (2021), Gonzalez-Ramirez et al. (2021), and Kelly (2022), have focused on how the COVID-19 pandemic impacted students who had to switch to online learning, explaining student life stress, psychological distress, and physical inactivity. Academic staff face major mental issues with the closure of learning institutions and the dramatic shift to online learning (Zheng et al., 2022). In Kenya, institutions and faculty members were ill-prepared for this transition, and academic staff were found struggling with online instructions, increasing workloads, emotional distress, and lack of internet bandwidth (Wekullo et al., 2024). Regrettably, a major emphasis has been placed on the technical challenges facing academic staff, with little attention on how the transition continues to affect their mental well-being.

Problem Statement

The primary problem that this study seeks to address is the continued deterioration of mental well-being among academic staff in Kenyan universities due to the introduction of online learning models. A majority of studies in the Kenyan context have revealed that most universities lack the requisite infrastructure to sustain remote learning and that most academic staff do not have ICT skills to ensure that they can deliver personalised instruction to learners (Kibuku et al., 2020; Mutisya et al., 2016). As of 2016, only 35% of academic staff delivered online instructions, with 87% of these engagements only involving the upload of lecture notes as opposed to online interactions with students (Makokha & Mutisya, 2016). Besides, many lecturers have revealed their opposition to online learning, suggesting that it could affect the quality of learning (Ruth, 2018). As a result, prior to 2018, only 30% of lecturers in Kenya supported online learning (Ruth, 2018). Before the pandemic, the lack of support and the presence of multiple challenges in providing online education likely created stress and anxiety for academic staff who were either required or felt pressured to engage in these modalities despite lacking the necessary skills, infrastructure, and institutional backing. This situation could have led to feelings of inadequacy, increased workload, and frustration, thereby negatively impacting their mental well-being. The current body of literature has confirmed that the transition had mental effects on both students and academic staff. Excessive workloads, work-related stress, work-life balance, and demographic factors have not been adequately discussed and explored. Unless Kenyan universities understand the emotional toll that online learning takes on academicians, it is unlikely that management teams will gather the necessary resources to provide support to staff.

Research Questions

The current research paper has four primary questions:

1. How do lived experiences of academic staff in Kenyan universities reveal the nature of stress associated with engaging in online learning?
2. In what ways do the narratives of academicians in Kenyan universities articulate the influence of the perceived increase in workload due to online teaching on their mental well-being?

• How do the accounts of academic staff in Kenyan universities describe the challenges to their work-life balance arising from the implementation of online learning models?

1. What patterns emerge in the perspectives of different demographic groups of academic staff in Kenyan universities regarding their experiences with online learning and its perceived impact on their mental well-being?

LITERATURE REVIEW

Online Learning in the Kenyan University Context

Technology continues to revolutionise the education sector in Kenya and beyond. Despite this, most universities that have benefited from online learning are in North America and Europe. In Africa, one of the first institutions that embraced distance learning, which entailed offering courses by correspondence, was the University of South Africa (UNISA) (Nyerere et al., 2012). UNISA launched correspondence courses in 1946, spurring similar arrangements across Africa (Nyerere et al., 2012). Kenya has recorded an unparalleled demand for education, which is not evident in other East African nations. Consequently, universities have continued adopting e-learning as a method of transferring knowledge and skills to more learners without needing extra physical facilities.

Adopting e-learning or remote learning in Kenya has been fraught with challenges. In 1964, the Ominde Commission recommended that Kenya develop open and distance learning. The Kenyan Parliament created the Board of Adult Education in 1966, which worked as part of the University of Nairobi (Nyerere, 2016). The country witnessed subsequent education commissions, including the Gachathi Report (1976) and the Koech Report (2000). All these commissions underlined the need for the Kenyan government to invest in and support open and distance learning as a crucial alternative to traditional modes of education. In 2005, the government established the National Open University through the Sessional Paper No. 1 of 2005 (Nyerere, 2016). Overall, this project has not been implemented to date; despite this, both public and private universities in Kenya have adopted online learning approaches as they become more viable and beneficial to learners and instructors.

Before the Coronavirus Pandemic, the adoption of e-learning among Kenyan universities was low. According to Makokha and Mutisya (2016), East African countries have not exploited the full potential of e-learning. The study found that academic staff in Kenya and other East African nations lacked relevant skills and inadequate human capacity to contribute to desired e-learning implementation. One key factor affecting e-learning was limited internet bandwidth and the lack of official harmonisation policies that affected the adoption of these approaches. The Kenyan academic staff also focused on uploading reading materials online instead of delivering learner-centred instructions. The author joined demands that digitising books in Kenyan universities and offering lecture notes did not qualify as e-learning (Makokha & Mutisya, 2016). At the time, students were not actively engaged and did not desire to utilise e-learning platforms.

The Coronavirus Pandemic impacted the Kenyan economy, and every sector, including education, was shocked by this event. The Kenyan government imposed a series of measures to contain the spread of this virus, including closing universities and other educational establishments. During this period, it became imperative for Kenyan universities to adopt remote teaching to support students who were unsure when they would resume traditional, face-to-face learning (Ngwacho, 2020). Effective implementation of remote teaching approaches was inevitable in reducing the disruptions that the pandemic had brought to Kenyan higher learning institutions. As a result, most Kenyan universities currently enrol students for pure online and hybrid courses and have invested in the latest technologies to deliver student-centred online instruction. Despite this, challenges continue to affect remote learning, with most academic staff highlighting internet issues, lack of ICT skills, and other challenges as being crucial hurdles to adopting and implementing remote teaching in the Kenyan context.

Learning Stress Levels Among Kenyan University Academic Staff

The academic staff in various Kenyan universities must contend with the increasing pressure to continue offering high-quality, learner-centred education. Kinuthia et al. (2022a) reveal that higher education teaching is highly attractive due to multiple benefits, including job tenure, light workloads, and other perks, such as overseas trips for academic conferences. Unfortunately, Kinuthia et al. (2022a) disclosed that academic staff reports high stress levels, qualifying to become among the most stressed professionals. In another study, Kinuthia et al. (2022b) suggested that the stress levels are primarily due to multiple factors, including the ever-increasing workload, the pressure to get more publications to earn promotions, and the growing number of untenured lecturers. The study also disclosed that studies in other regions have shown that high-stress levels could also be attributed to changing job roles, low salaries, time constraints, inadequate participation in management, insufficient funding and resources, low salaries, and lack of recognition (Kinuthia et al., 2022b). For example, lecturers had a light workload in the past due to the two-semester academic year (running for eight months). However, current changes have made universities offer three-semester academic years (full year), which rob lecturers of the time to perform other personal duties like engaging with community members and going for further studies.

Surveys conducted on Kenyan universities have highlighted the issue of high stress levels among academic staff. For instance, a study by Leiyan and Kaamara (2017) revealed that 84.3% of lecturers at the Jomo Kenyatta University of Agriculture and Technology (JKUAT) felt stressed out by their work. Occupational stress is a prevalent challenge in public and private institutions, a situation that has not been adequately addressed by these establishments. The situation worsened after the Coronavirus pandemic as working conditions deteriorated and some teaching staff lost their jobs (Kathukumi et al., 2023). The increased stress levels among academic staff members have further dented Kenya’s higher education credentials, which are already plagued by chronic underfunding and deteriorating quality of education.

A careful analysis of studies that have been written on this topic reveals interesting outcomes. Prominently, limited studies focus on occupational stress levels among academic staff in Kenyan universities. As a result, there are limited statistics regarding stress levels among these workers. Second, it is apparent that the Coronavirus Pandemic increased academicians’ stress levels as they found themselves in unfamiliar terrains. For example, lockdowns prevented academic staff from engaging in their work duties. Remote work has become a new reality, and some staff lack the ICT skills to offer quality education. Regrettably, the highlighted conditions, coupled with a lack of ICT resources and support from universities, meant that academic staff had higher stress levels compared to when they were providing physical instructions in various higher education establishments. The higher stress levels among academic staff negatively impact their mental well-being and ability to deliver quality education in Kenyan universities.

Workload Levels among Kenyan University Academic Staff

Workload explains the overall assignments that individuals need to complete within the assigned time. In the field of academia, the workload for staff members depends on multiple factors, including the number of courses offered in their discipline, total contact and credit hours, instructional and non-instructional hours, administrative and community services, scholarly activities, and student-teacher ratios (Muramalla et al., 2019). The authors affirmed that there are challenges in assigning equitable workloads to academic staff. For example, the workload for faculty members changes over time due to variations in the number of students enrolled at a particular period, the commercialisation of specialised programmes, research-related performance appraisals, and expectations for these professionals to get external research grants (Muramalla et al., 2019). The workload for academic staff members covers different responsibilities, including preparation for class teaching, designing assessments, execution of research projects, publication of research works, and involvement in different administrative services.

As disclosed, Kenya had less than five universities at the beginning of 1990. However, the number would triple by 2007 and grow astronomically by 2022. A sharp increase in the number of students in Kenyan universities has characterised the explained growth levels. Consequently, the rapid increase in the number of universities and students likely led to a significantly higher student-to-faculty ratio, potentially increasing the workload and stress experienced by academic staff. For example, in the past decade, the student enrolment rate in Kenyan universities has increased by 70% (Kinuthia & Kiragu, 2024). However, in the same period, the number of professors in these establishments has only grown by 10% (Kinuthia & Kiragu, 2024).

Commission for University Education (2016) report revealed that Kenya had 539,749 students in various public and private universities. During this period, 86% of students were in public universities, leaving only 14% in private universities. Specifically, during the same period, Kenyan universities had 16,001 academic staff in both private and public universities (CUEA, 2016). Mathematically, this reveals a ratio of 1:34, meaning that one academic staff had to support at least 34 students. Excessive workload might be more pronounced in public universities, where only 11,282 teaching staff had to support 86% of students in this segment. Based on this, online learning can increase workload and stress due to the added demands of technical issues, constant online availability, adapting teaching methods for a virtual environment, managing online interactions, and the blurring of work-life boundaries, potentially exacerbating mental health challenges rather than easing them

Studies focusing on excessive workload in Kenyan universities have failed to explore how remote work has impacted this segment. Indeed, researchers have revealed that academic staff members continue to report more workload, especially as the number of students rises dramatically. Remote work could increase workload by stretching the number of hours instructors work. Moreover, the research studies have not highlighted the connection between workload and mental health in the Kenyan context. Most studies have focused on how workload impacts students’ stress levels and the resulting performance issues. Despite this, it is apparent that excessive workload impacts the mental well-being of academic staff, who are likely to experience burnout and stress due to this problem.

Work-Life Balance for Kenyan University Academic Staff

Work-life balance explains a combination of interactions in a worker’s life in their workplace, with the advantages and disadvantages connected with the balance or imbalance impacting different levels of employees’ required roles (Makori et al., 2019). A study has defined work-life balance as the desire to have separate time and resources that people allocate to work-related duties and family-related matters (Agunda et al., 2024). Work-life balance entails people spending adequate time at their workstations while also spending sufficient time pursuing other personal activities like hobbies and engaging with friends and family members (Makori et al., 2019). Work-life balance is the ability to strike a healthy balance between work and other crucial aspects of life (Gundi et al., 2024). Work-life balance reflects the need for workers to balance their work and lives, regardless of whether they have or do not have daily family responsibilities.

Generally, work-life balance has emerged as a crucial issue in the context of modern organisations. Unlike in the past, personal and work-life boundaries have increasingly blurred. Despite this, organisations have continued to underline the essence of work-life balance as they seek to promote employee engagement and performance (Agunda et al., 2024). In advanced economies, flexible and remote work environments have become instrumental in attaining optimal work-life balance and enhancing employees’ overall performance (Agunda et al., 2024). Work-life balance has also emerged as a crucial strategic tool in helping organisations retain workers (Gundi et al., 2024). Hence, it is unexpected that Kenyan universities have adopted flexible working arrangements to benefit academic staff members.

Multiple studies have explored the current work-life balance situation in Kenyan universities. Gundi et al. (2024) examined the impact of work-life balance on employee retention in Kenyan universities. Agunda et al. (2024) also focused on how work-life balance can impact academic staff performance in Kenyan universities. Ngela and Kamaara (2025) have also examined the impact of work-life balance on the performance of workers in public entities, specifically the Nairobi County Government. Unfortunately, in all these studies, little attention has been placed on how work-related activities affect work-life balance. However, recent studies have disclosed the side effects of remote working arrangements.

According to Palumbo (2020), remote working activities affect public servants, who are increasingly suffering from more work-to-life and life-work conflicts. The author reveals that telecommuting from home has triggered increased work-related fatigue, worsening the perceived work-life balance. Indeed, Palumbo et al. (2021) confirm this occurrence by showing that online and remote work is blurring the boundaries between everyday life and work. Workers now face work-life conflicts, increasing the negative implications of working from home. Experts have found that remote working can affect work-life balance and result in a poor psycho-emotional state for affected workers (Lonska et al., 2021). In this study, scholars found that this work arrangement violated established laws related to rest and maximum weekly work time. During remote working activities, the boundaries between private and work time become more blurred, making it challenging to distinguish between rest periods and work time (Lonska et al., 2021). The outcome concludes that working remotes could make workers work longer hours, have less predictable and irregular schedules, and have fewer rest periods. All these issues could affect their mental well-being.

In summation, the Kenyan higher education sector has existed since the 1950s, when the colonial government established the Royal Technical College of East Africa, a constituent college of Makerere University. Fortunately, when Kenya became independent, it joined forces with other East African countries to establish the East Africa University, with the Royal Technical College becoming a constituent. However, the worsening ties between these countries resulted in the Royal Technical College becoming the University of Nairobi in 1970. The Moi administration would go on to establish three other public universities. In the 1990s, Kenya witnessed phenomenal growth in private universities that offered higher education to Kenyans who were not fortunate to be admitted to the few public universities.

The review reveals that the Kenyan government was advised to start open and distance learning studies in the 1960s. However, successive Kenyan governments did not understand the essence of remote learning, which continued until the Coronavirus Pandemic. The pandemic presented a watershed moment, where Kenyan universities, facing prolonged closure, had to adopt remote or online learning as an alternative to face-to-face meetings on campus. Unfortunately, remote learning has been characterised by many challenges that have affected students and academic staff members. Despite these drawbacks, limited studies have focused on how remote learning continues to affect academic staff in Kenyan universities. The review has demonstrated that academic staff members report increased stress levels as they engage in their daily work. Besides, there are work-life balance issues as remote teaching blurs the previously clear lines between work and life. Remote learning has also increased workload among academic staff as they continue to work long hours without adequate rest periods. The analysis has also shown apparent demographic differences among academic staff in Kenyan universities. All these online learning-related issues will likely impact academic staff’s mental well-being.

METHODOLOGY

This section provides an overview of the procedures that the researchers will use to carry out the research study. As a result, the section covers multiple issues, including the research design, target population, sampling techniques, data collection instruments, data analysis, and ethical considerations.

Research Design

The current research paper explored the problem through the use of qualitative research design. Braun et al. (2021) affirm that the qualitative methodology promotes flexibility and openness to deal with a variety of research questions that are of interest to researchers. In such contexts, this approach enables scholars to access data that concentrates on individuals’ experiences, subjective views, and material practices (Braun et al., 2021). Recent debates have underlined the need for researchers to leverage the benefits of qualitative research methods, primarily since the dominance of the quantitative approach has led to little diversity in data collection and analysis (Hendren et al., 2023). In fact, Braun et al. (2021) argue that qualitative design is exciting and offers different tools that pose advantages to both researchers and research participants. The adoption of specific safeguards, like member checking, enhances the rigorousness of this approach and deals with inherent weaknesses that could affect the trustworthiness of research data (Motulsky, 2021). Hence, the qualitative research design was ideal for collecting and analysing rich data that highlighted the current mental well-being of academicians within Kenyan universities.

Target Population

Kenya has over 60 public and private universities, which also have multiple constituent colleges. As highlighted earlier, these institutions of higher learning employ at least 14,349 workers (CUEA, 2023). Specifically, this is the target population, given that most of these academic staff either provide instruction physically or through online platforms. The study targets lecturers, assistant lecturers, and graduate assistants working in these institutions. The academic staff by gender includes 9,382 and 5,058 male and female, respectively (CUEA, 2023). The study consisted of both male and female academic workers in universities to understand the effects of remote working on their mental well-being.

Sample Size and Sampling Techniques

The primary objective of obtaining a sample is to have a desirable representative of the entire population (Lakens, 2022). A good sample allows a researcher to collect and analyse quality data that can be generalised to the whole population. Sample size should be determined based on resource constraints, and plans must be made for the desired accuracy (Lakens, 2022). Due to the nature of this study, the purposive sampling technique is the most desirable. The highlighted sampling approach is a non-probability framework that entails getting participants based on their knowledge, experiences, and characteristics (Nyimbili & Nyimbili, 2024). Undeniably, sampling and the selected approach can present both epistemological and ontological problems. A researcher must understand how many people they must interact with to gain adequate knowledge about the whole population (Nyimbili & Nyimbili, 2024). Social research, just like this study, is grounded in the constructivist paradigm. As a result, this kind of research can even be conducted on one person or element. Nyimbili and Nyimbili (2024) also affirm that qualitative studies should be manageable and should not be exaggerated since researchers are likely to reach data saturation even before they are done with the sampled groups. The current study had a sample size of 15 cases, given that researchers accept 11 cases to be the minimum number of cases that any researcher could adopt to have statistical power over their data (Vasileiou et al., 2018). Briefly, the study adopted a purposive sampling technique to get the 15 participants required for this study.

Data Collection Instruments

The research study used questionnaires to collect primary, raw data. The researchers designed questionnaires that were distributed online. Google Forms provided a desirable tool to create these questionnaires online. The approach made it easier for the researchers to interact with participants across Kenya. The use of semi-structured questionnaires allowed detailed and rich information beyond the typical, surface-level responses. The methods helped provide a comprehensive understanding of the subject matter. Appendix 1 shows the research questionnaire used in this research study.

Data Analysis and Presentation

The researchers utilised the thematic analysis to analyse the data collected during this process. Thematic analysis is a unique kind of qualitative research design that allows researchers to identify recurring patterns and highlight themes within a set of qualitative data (Christou, 2022,). The analysis entailed examining the data collected to extract key ideas and concepts. Thematic analysis was beneficial in helping focus on the more profound meaning and ensuring that insights from the data emerge organically. The key steps utilised in the thematic analysis included familiarising data, generating initial codes, searching for themes, reviewing themes, and defining these themes.

Ethical Considerations

The researchers briefed each of the participants about the research objectives and the intended outcomes. The respondents were assured of their privacy and confidentiality. The researchers did not collect personal details, and individuals were briefed on the need to avoid disclosing personal information. The researchers got the necessary approval from relevant bodies to promote honesty. In all engagements, the researchers retaliated for voluntary participation and respect for respondents. As a result, participants had the freedom to withdraw from this research study at any point. The online questionnaire promoted informed consent by briefing participants about the research study’s primary purpose, procedures, potential benefits and risks, and their right to withdraw before they agree to participate in this study.

RESULTS

The researchers distributed the questionnaires to potential respondents through multiple approaches, including emails, Facebook posts, and WhatsApp messages. Despite this, it was challenging to engage with university academic staff due to the lack of a centralised platform within which the researchers could engage with the target population. For example, it was challenging to find a forum made up of academic staff, unlike institutional mechanisms like group chats on WhatsApp. The described issue made it challenging to follow up on academic staff who had received the questionnaires and failed to submit responses.

The researchers utilized thematic analysis to examine the qualitative data collected through questionnaires. This method was chosen as a qualitative research design that allows for the identification of recurring patterns and the highlighting of themes within the data. The process involved examining the collected data to extract key ideas and concepts, focusing on the more profound meaning to ensure that insights emerged organically. The specific steps undertaken in the thematic analysis included familiarizing themselves with the data, generating initial codes, searching for themes, reviewing the identified themes, and finally defining those themes. This systematic approach allowed the researchers to analyse the rich data obtained and understand the mental well-being experiences of academicians in Kenyan universities in relation to online learning.

Figure 1. The academic rank.

The number of respondents in this research study was 15. The explained number is adequate for qualitative research studies, where researchers have explained it takes a minimum of 12 responses to reach data saturation (Vasileiou et al., 2018). Based on this, the sample of 15 was deemed adequate for this qualitative study and the overall scale of this study. Among the 15 respondents, eight were lecturers, and four were senior lecturers (see Figure 1). Two of the respondents did not reveal their academic rank. Unfortunately, it was challenging to find professors and associate professors to participate in this study. Hence, the majority of respondents in this study were lecturers.

Figure 2. Years of Teaching Experience

Apart from this, it was interesting to understand the number of years that these professionals had served in their respective universities. 50% of the respondents had served between 5 and 10 years, while 8.3% have been teaching in the higher education segment between 11 and 15 years. Significantly, 16.7% have worked between less than 5 years, and 25% have worked more than 15 years. The figure above highlights the years of teaching experience among the academic staff.

Figure 3. University type.

Indeed, it was also vital to understand the university type, given that the researchers were keen to understand if the problems affected academic staff in both private and public universities. The distribution in this category was 75% worked in private establishments, and the remaining 25% worked in public universities.

Figure 4. Responses to being overwhelmed by online teaching.

In the first part, the study was interested in understanding online learning-related stress and academic staff mental well-being. In the first question, where respondents were asked if they felt overwhelmed by the demands of online teaching, 53.3% affirmed that they felt overwhelmed, while 46.7% suggested that this was not the case (see Figure 4). Some of the reasons that these respondents cited as making them feel overwhelmed included increased time spent online, slow internet, technical challenges, the need to adapt constantly, difficulties balancing online teaching demands, and the need to remain vigilant at all times. On the other hand, respondents who did not feel overwhelmed disclosed that they found online teaching manageable, flexible, and convenient.

Figure 5. Online teaching and stress levels.

Apart from this, the study sought to assess whether online teaching increased academic staff stress levels. Interestingly, 60% of the respondents suggested that online teaching did not increase their stress levels (see Figure 5). However, 40% claimed that delivering instructions online was increasingly causing them stress. The reasons that these individuals made this negative observation were that online teaching increased their workload, challenged dealing with passive students, constant student emails and messages, and increased the time that they spent on troubleshooting technical issues. The positive responses suggested that some professionals found it easier to adjust to the demands of online teaching and that the approach was flexible and rewarding in the long run.

Figure 6. Challenges involving students’ interactions on online platforms.

Moreover, 46.7% of these respondents found it difficult to manage student interactions online, while 53.3% did not (see Figure 6). Some of the reasons for ease were that lecturers found it easy to promote interactions and presentations online. However, the reasons for difficulty included challenges maintaining engagement, difficulties maintaining discipline in virtual classrooms, unstable internet connections that resulted in frequent disruptions, and students’ failure to participate during meetings.

Figure 7. Workload and mental well-being.

Apart from this, it was crucial to understand how the workload impacted the mental well-being of academic staff in academic establishments. As Figure 7 shows, 66.7% of the respondents confirmed that the increased workload continued to affect their mental wellness. Some of the reasons that these individuals cited were pressure to meet deadlines, issues managing large classes, difficulties adapting to online platforms, and overwhelming workloads that left them mentally drained and constantly anxious. The 33.3% of respondents who did not feel overwhelmed indicated that they were managing online teaching well.

Figure 8. Online learning and burnout.

Remarkably, 66.7% of the respondents confirmed that they had experienced burnout due to excessive academic responsibilities (see Figure 8). Besides, only 33% disclosed that they did not face the same challenge. Some of the responses that these respondents offered included working long hours with limited breaks, more personal responsibilities and administrative burdens that led to exhaustion, lack of clear separation between personal time and work, challenging balancing administrative duties, research, and responding to students at all times. Lecturers shared that there were infrastructure issues that affected online teaching and caused stress.

Figure 9.Online teaching and the ability to fulfill personal obligations.

Essentially, 57.1% of respondents felt that they did not have enough time to fulfill their professional obligations effectively (see Figure 9). One of the major reasons that they faced was long working hours that encroached on leisure and family time. The other reasons that were cited included feeling constantly rushed, unrealistic workload demands, extra work that made it challenging to manage teaching and research, and endless grading, lesson planning, and other administrative activities that left academic staff with limited time for research and personal development or rest. The many obligations that these individuals have affect their ability to engage in personal development activities.

Figure 10. Online teaching and work commitments.

Fundamentally, 76.9% of the respondents disclosed that work commitments often affected and interfered with their personal lives (see Figure 10). The respondents suggested that they had to remain alert and have laptops at all times to ensure that they could respond to work-related issues. Besides, frequent late-night work and the need to respond to students and attend virtual meetings disrupted family time. Some of the respondents shared that they had to work late into the night or during weekends. Academic staff were also expected to respond to students late into the night, leaving them with little or no time for their personal life. 23.1% of the respondents did not agree with this statement and affirmed that they had found mechanisms to balance online teaching and their personal lives.

Figure 11. Online teaching and work-life imbalance.

Besides, the results showed that 64.3% of respondents felt mentally exhausted due to work-life imbalances (see Figure 11). At the same time, 35.7% did not agree with this statement. The respondents who agreed suggested that teaching online blurred the work-life boundaries. Moreover, there was constant pressure from work and the lack of time for self-care that could lead to significant mental exhaustion and fatigue. The lack of clear distinction between personal time and work hours could also lead to chronic exhaustion.

Figure 12. University policies to support work-life balance.

The research study also revealed that there was inadequate institutional support to help academic staff teach online. Based on this, 71.4% confirmed that there were no formal institutional mechanisms or guidelines to help academic staff (see Figure 12).

Figure 13. Age impact on online learning.

Figure 14. Gender and its role in work-related stress.

The other factors that the study investigated were the impact of gender and age and how these two independent variables affected online teaching. The outcomes revealed that older faculty members are likely to register more challenges (Figure 13). Besides, the respondents also disclosed that gender played a role in how work-related stress affects them (Figure 14). Female respondents complained that they often feel pressure to meet both professional and familial expectations, which adds an additional layer of stress to their work. Moreover, female faculty members often juggle family responsibilities along with increased online teaching stress.

DISCUSSION

The results of this qualitative study reflect the various challenges and insights into the experience of academic staff working in higher education in Kenya, especially in relation to online learning. Specifically, a notable finding was the challenges in engaging with university academic staff due to the lack of a centralised communication platform. Remarkably, the respondents were split in their feelings regarding being overwhelmed by online teaching, with 53.3% affirming that the demands of online teaching were overwhelming. The challenges that respondents cited included slow internet, long hours spent online, and the constant need to adapt to new online teaching methods. In contrast, individuals who did not feel overwhelmed disclosed the convenience and flexibility that online teaching provided. The explained division reveals that the experience of online teaching is not universal, and it depends on personal adaptability and the available resources to academic staff.

The workload that is connected to online teaching was another vital area that considerably impacted respondents’ mental health. A majority of 66.7% disclosed that increased workloads negatively affected their mental well-being, citing multiple stressors, including technical issues, tight deadlines, and large class sizes. Besides, a significant portion of these respondents (80%) indicated that they experienced burnout due to excessive academic responsibilities, including administrative tasks and the pressure to be available to students continuously. The highlighted findings stress the mental toll of online teaching, particularly when coupled with other administrative and academic duties. The outcomes suggest a need to implement better support systems and effective workload management to mitigate these stressors.

Furthermore, work-life balance also emerged as a crucial concern, with 76.9% of these respondents reporting that their work commitments often affected their personal lives. The highlighted shift to online teaching blurred the lines between personal and professional time, with many academic staff working late into the night and during weekends. The research study also revealed that age and gender were significant factors that influenced stress levels (Figure 13-14). Older faculty members and females who participated in this study reported heightened challenges, with women disclosing that they faced additional pressures to balance both familial and professional obligations. The outcomes suggest that age- and gender-specific support systems could be necessary to deal with the distinct issues faced by various groups of academic staff members within Kenyan universities.

RECOMMENDATIONS

Based on the findings of this research study, the following recommendations can be made to improve the experiences of academic staff engaged in online teaching and help improve their mental well-being. The recommendations seek to address the problems that have been identified in this research study, including work-life imbalance, mental health, workload, and institutional support.

1. Implement Comprehensive Support Systems for Online Teaching – The study has disclosed the challenges faced by Kenyan academic staff in managing the technical demands of online teaching. Based on this, universities must establish comprehensive technical support systems. The explained moves should include creating a dedicated helpdesk for faculty, where workers can receive real-time assistance for troubleshooting online teaching platforms. Apart from this, Kenyan universities need to offer tailored professional development opportunities for academic staff to improve their digital fluency, especially for staff members who are less familiar with emerging online teaching tools. Partnerships with technology companies in Kenya could also be explored to offer affordable learning management systems and other digital resources. Universities can mitigate the challenges of large class sizes by offering additional teaching assistants and encouraging faculty collaboration in course delivery. Besides, universities must improve infrastructure like stable internet connectivity and access to reliable teaching equipment, particularly in regions that are away from the city.
2. Introduce Mental Health and Well-being Programs for Academic Staff – Kenyan universities must introduce mental well-being and health for their staff members. The explained recommendation is crucial in the Kenyan context, where such issues are often overlooked. Kenyan universities should develop appropriate institutional structures that concentrate on mental health support, including offering peer support groups, counselling services, and stress management programs. Specifically, due to the stigma and cultural issues surrounding mental health in Kenya, the explained services should be marketed in a manner that lowers stigma and encourages staff members to seek help. Universities could also collaborate with local non-governmental organisations (NGOs) and health organisations to offer affordable and personalised counselling services. Universities could also create online workshops focusing on mental health awareness, resilience-building, and progressive stress management tactics and policies. Academic staff mental well-being should also be embedded in overall university policies, with clear and personalised strategies to support staff who experience exhaustion and burnout. Specifically, reducing workloads during stressful periods, such as end-of-semester grading and organising mental health days, could help mitigate the effect of online teaching and associated stress on academic staff.
3. Create Clear Work-Life Balance Policies and Encourage Their Implementation – The research study found that academic staff in Kenyan universities struggle to strike a balance between work and personal life, mainly due to unrealistic workload expectations and long working hours. Based on this, Kenyan universities must implement a clear and flexible work-life balance that enables faculty members to set boundaries between personal time and academic responsibilities. The highlighted policies should also encourage staff members to take time off when this is needed, provide opportunities for family-friendly benefits such as flexible work options, and reduce administrative burdens. Besides, it would be crucial and beneficial for Kenyan universities to engage labour unions in the higher education segment to ensure that the outlined policies align with the national labour policies. Moreover, the explained policies should deal with the realities of Kenyan academic staff, primarily in terms of family responsibilities and the cultural importance of family time. Overall, universities should promote a positive culture where taking time off and breaks is encouraged and should not be seen as a sign of weakness or incompetence.
4. Universities should provide targeted support for different demographic groups. The research study has disclosed older faculty members and female academic staff members experience unique problems in online teaching, which is especially relevant in the Kenyan context. In this area, gender roles and age-related expectations can affect work dynamics. Based on this, Kenyan universities must consider offering targeted interventions for these groups to ascertain that these persons are not disproportionally affected by online teaching. Moreover, there should be specific training forums where universities should use digital tools and promote online course delivery, which should be made available to help older staff members become more comfortable with online teaching platforms. Moreover, for female faculty members, who typically juggle between professional and personal responsibilities at home, organisations should create and introduce gender-sensitive policies that highlight and deal with specific challenges that these individuals face when balancing between work and family-related events. Some interventions could include subsidised childcare, the option for workers to reduce teaching loads when having family-related events, and access to family-friendly work environments.
5. Adoption of the Mwanzia Framework – The Mwanzia Framework, which is an original and creative holistic approach to this problem, is a structured model designed to identify, assess, and mitigate the stressors that academic staff experience due to remote teaching in Kenya. Fundamentally, this framework integrates the stressors (red flags) symptoms of stress (yellow flags) and proactive solutions (greenlights) to empower lecturers in managing their well-being while improving institutional support mechanisms. Indeed, the model is particularly tailored to the unique challenges faced by Kenyan university lecturers, considering the digital divide, workload pressures, and institutional constraints. The figure below illustrates the Mwanzia Framework:

CONCLUSION

The current research study is on the effect of online teaching on the mental well-being of diverse academic staff members in Kenyan universities. The outcomes have shed light on the considerable changes that these professions have faced as they adapt to the demands of rapidly changing learning environments. Despite the highlighted changes in online teaching, many academic staff in Kenya have reported considerable stress due to technological issues, difficulties in maintaining work-life balance, and increased workload. The findings reveal that while some faculty members have adapted well to online teaching activities, others continue to struggle with overwhelming demands for their roles, resulting in burnout, mental exhaustion, and strained personal lives. Moreover, the lack of institutional support structures and centralised communication platforms further exacerbate these issues, underlining the essence of targeted interventions and structural transformations within universities.

The research study has shown that a majority of academic staff members are dealing with an increased workload, long working hours, and the continued blurring of personal and professional boundaries, which ultimately leads to considerable stress and mental health concerns. Specifically, female faculty members and older professionals appear to face unique problems, which are also influenced by the cultural and societal expectations related to gender roles and age. Indeed, the explained findings also underscore the essence of dealing with these particular issues through tailored policies and support systems that recognise the unique and diverse need for faculty members within the Kenyan higher education landscape.

The outcomes have compelled the researchers to make multiple practical recommendations for Kenyan universities. Some of these measures include developing comprehensive support systems for online teaching and implementing mental health and well-being programs. Besides, learning institutions should prioritise creating clear work-life balance policies that should take into account the personal and professional needs of staff members. Essentially, offering targeted support to older staff and female faculty members could be vital in ascertaining that all professionals have the opportunity to thrive and succeed in the online teaching environment. This research study emphasises the need for Kenyan universities to recognise the mental health and wellness of their academic staff and understand how this plays a role in their long-term success.

Limitations of this Study

While the current study has offered invaluable insights into online teaching and the mental well-being of academic staff offering remote learning in Kenya, it has multiple limitations that should be considered when interpreting the outcomes. First, the researchers utilised a relatively small sample size of 15 respondents. Although this sample size was deemed adequate for this qualitative research study, it might not fully represent the diverse work experiences of academic staff members working in the whole Kenyan higher education segment. Second, the research study was predominantly comprised of lecturers and senior lecturers, with fewer participants from higher academic ranks, such as professors and associate professors. Specifically, this limitation in the representation of senior academic staff means that the study may not capture the unique challenges faced by these higher-ranking faculty members. Third, there is the risk of inaccurate data since this was self-reported data. Participants may have been influenced by social desirability or may not have fully disclosed the extent of their stress and mental health challenges.

Conflict of Interest

The authors declare that there is no conflict of interest in relation to this research study. The research was conducted impartially, and no financial or personal relationships influenced the outcomes or interpretation of the results. All findings and conclusions presented in this study are based solely on the data collected and the analysis conducted during the research process.

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APPENDIX 1 – THE QUESTIONNAIRE