Fesanmie Amarillo*, Marjorie Alivio, Manal Junaid, Asmaliah Macabantog
College of Health Sciences, Mindanao State University – Iligan Institute of Technology, Andres Bonifacio Avenue, Tibanga, Iligan City, 9200 Philippines
*Corresponding Author’s Email: fesanmie.amarillo@g.msuiit.edu.ph
ABSTRACT
Background: Balancing academic coursework and clinical training places significant stress on nursing students. Recent literature reports that over half of nursing students experience moderate stress and a quarter experience high stress, mainly due to clinical demands and fear of errors. Additionally, moderate to high stress levels are common across various nursing student populations, with poor time management frequently linked to increased stress. Objectives: This study examines the relationship between time management strategies and academic stress among nursing students at Iligan Institute of Technology, Mindanao State University, to guide interventions that promote academic success and well-being. Methods: This descriptive correlational study involved 212 nursing students selected through stratified random sampling to ensure representation across year levels. Standardised instruments—the Time Management Questionnaire and the Academic Stress Scale- were utilised. Data were analysed using SPSS version 25, employing descriptive statistics and ordinal regression analysis. Results: Findings revealed that many respondents struggled with consistent application of effective time management strategies. Overall academic stress was moderate (M = 3.26; SD = 0.74). A significant association was found between ineffective time management and higher levels of academic stress, particularly among students from low-income households (p = 0.018). The pseudo-R² value of 0.028 indicated that a small but meaningful variance in academic stress was explained by time management strategies and socio-demographic factors. Conclusions: The results highlight that poor time management skills contribute to increased academic stress among nursing students, especially those from financially disadvantaged backgrounds. These findings suggest the need for targeted interventions focused on strengthening time management skills and providing support programmes aimed at reducing academic stress and promoting mental well-being in nursing education.
INTRODUCTION
Effective time management is a vital skill for nursing students, who often face overwhelming academic demands, clinical responsibilities, and personal obligations. The rigorous nature of nursing education requires students to assimilate large volumes of information, perform practical competencies, and meet tight deadlines, all of which can contribute to heightened academic stress (Jadoon et al., 2023). While some students naturally adopt effective time management strategies, others struggle to develop these skills, often resulting in poor academic performance and psychological distress.
Nursing students face unique challenges that contribute to high levels of academic stress. The rigorous nature of nursing education requires students to balance academic coursework with clinical training, which places significant demands on their time and energy. According to recent studies, over half of nursing students experience moderate stress, and a quarter experience high stress, primarily due to clinical demands and fear of making errors (Mohamed et al., 2024). Additionally, 56.3% of students reported moderate stress levels, and 81.4% experienced high academic stress (Dogham et al., 2024; Mohammed et al., 2024). Poor time management has also been linked to higher stress levels among nursing students (Chacko et al., 2023).
Academic stress affects not only the cognitive functioning and motivation of nursing students but also their physical and emotional well-being. Stress can manifest in various forms, including fatigue, anxiety, sleep disturbances, and feelings of being overwhelmed. Ineffective time management is a significant contributor to such stress, particularly when students find themselves unable to keep pace with academic and clinical requirements. The importance of time management as a buffer against academic stress has been supported by numerous studies. Effective time management strategies enhance productivity, reduce procrastination, and foster a sense of control—key factors in minimising academic stress.
Moreover, Cao et al. (2025) found that students who lack structured time management are more susceptible to stress-induced academic fatigue and reduced motivation, which negatively impacts learning outcomes. Nursing students, in particular, are vulnerable to these effects due to the dual demands of didactic coursework and hands-on clinical experience. These stressors can be further amplified by socioeconomic constraints, as students from lower-income households may experience greater pressure to perform well academically while also managing external responsibilities.
Despite the growing body of evidence linking time management to academic performance and well-being, there remains a scarcity of research that specifically explores this relationship among nursing students in various educational settings. As such, this study aims to investigate the correlation between time management strategies and academic stress levels among nursing students at a selected institution. The research questions guiding this study are: (1) What is the relationship between time management strategies and academic stress levels among nursing students? (2) How do effective time management strategies impact academic performance and psychological well-being? The findings of this research may inform targeted interventions that strengthen time management skills, promote mental health, and enhance academic outcomes in nursing education.
METHODOLOGY
Design and Procedure
In this study, several demographic variables were examined to understand their potential impact on the results. These variables included age, gender, year level, and socio-economic status. Each of these variables can influence the levels of academic stress experienced by nursing students and their time management strategies.
Age
Younger students may experience higher levels of stress due to less experience in managing academic and clinical demands. Conversely, older students might have better coping mechanisms but could face additional stress from balancing studies with family or work responsibilities (Jadoon et al., 2023).
Gender
Gender differences can play a role in stress perception and management. For instance, some studies suggest that female students may experience higher levels of academic stress compared to their male counterparts (Müller et al., 2022).
Academic Year of Study
The academic year of study is an important determinant of stress among nursing students, as it reflects their stage of academic development and clinical exposure. Students in the early years of their program often experience stress associated with adjusting to university life, managing new academic demands, and adapting to a professional learning environment. Conversely, those in the later years, particularly final-year students, tend to experience increased stress due to intensified clinical responsibilities, preparation for licensure examinations, and concerns regarding future professional roles and employment (Dogham et al., 2024).
Socio-Economic Status
Students from lower socio-economic backgrounds may experience higher stress levels due to financial constraints, which can affect their ability to focus on studies and manage time effectively (Gary et al., 2024; Lykke et al., 2023). These demographic variables can introduce selection biases that affect the generalisability of the results. For instance, if the sample is not representative of the broader student population in terms of these variables, the findings may not be applicable to all nursing students. The study employs a descriptive correlational research design to investigate the relationship between time management strategies and academic stress levels among nursing students. This design is well-suited for exploring associations between variables without manipulating them, offering a realistic snapshot of the phenomena being studied (Adom et al., 2020; Ahmady et al., 2021).
Correlational studies are widely used in nursing education to understand behavioural and psychological trends among students, especially under stress or when adapting to time constraints (Sekizler et al., 2022). This method allowed for a systematic examination of variables in their natural settings, enhancing ecological validity. The study involves the administration of a survey questionnaire to the respondents, focusing on gathering data related to their time management strategies, socio-demographic profile, and academic stress levels. The questionnaire is designed to capture detailed information about the respondents’ attitudes toward time management, their family dynamics, and their perceived stress levels. The systematic administration of the survey questionnaire contributes to the reliability and validity of the study’s findings, enabling a comprehensive analysis of the relationship between time management strategies and academic stress among nursing students.
Sample
Participants were chosen using a stratified random sampling method. This approach involved dividing the nursing student population into subpopulations based on year levels (first-year, second-year, third-year, and fourth-year students). From each subpopulation, a random sample was selected to ensure that each year level was well-represented in the study. This method helps in achieving a comprehensive representation of students across different academic years, thereby enhancing the validity of the findings (Adom et al., 2020; Ahmady et al., 2021).
The study involves a total of 212 adolescent respondents, categorised as 58 first-year nursing students, 54 second-year nursing students, 36 third-year nursing students, and 64 fourth-year nursing students at Mindanao State University-Iligan Institute of Technology. The sample size was determined by considering a 95% confidence interval, a 5% margin of error, a standard deviation of 4.4, and a corresponding z-score of 1.96. The researchers employed a stratified random sampling method, ensuring that each year level was well-represented in the sample. This approach involved dividing the nursing student population into subpopulations based on year levels, thereby ensuring a comprehensive representation of students across different academic years.
Measurement Tools
The Time Management Questionnaire by Britton and Tesser (1991) was used to assess short-range planning, long-range planning, and time attitudes. This tool has shown strong reliability and validity in educational and nursing contexts (Giri & Natekar, 2019; Sadeghi et al., 2024; Alshutwi et al., 2022). To measure academic stress, the Academic Stress Scale (ASS) was employed (Bedewy & Gabriel, 2015). This scale evaluates five stress dimensions and is validated for use among healthcare students (Mhaske & Pandit, 2018; Lalramdini et al., 2024).
Academic stress was measured with the Academic Stress Scale (ASS). The ASS comprises 40 items rated on a 5-point scale (0 = no stress to 4 = extreme stress) across five domains: personal inadequacy, fear of failure, interpersonal difficulties with teachers, teacher–student relationship/teaching methods, and inadequate study facilities. Recent peer-reviewed applications describe and use this same 40-item, five-domain structure and provide current scoring and reliability guidance in health professions and university samples (Wahid et al., 2023; Aziz & Khan, 2022).
Statistical Analysis
The statistical analysis was conducted using SPSS (Statistical Package for the Social Sciences) version 25. Descriptive statistics such as frequency distribution and weighted mean were used to summarise the data. Inferential statistics, particularly ordinal regression analysis, were applied to examine the relationships between time management strategies, socio-demographic variables, and academic stress. The level of significance was set at p < 0.05 to determine statistical relevance.
The overall goodness-of-fit of the model was found to be not significant (p=0.391), suggesting that the model does not significantly explain the variance in academic stress. The pseudo-R2 value of indicates that only a small proportion of the difference in academic stress is made sense of by the model. The study used appropriate statistical tools, including the percentage, frequency distribution method, the weighted mean formula, and ordinal regression analysis to analyse and interpret the data. The coefficient estimate was used to determine the direction and strength of the association between the independent variable(s) and the ordinal dependent variable.
These statistical analyses provided valuable insights into the factors influencing academic stress among nursing students and the effectiveness of their time management strategies.
Ethical Consideration
The researchers obtained ethical clearance from the Ethics Review Committee of the College of Health Sciences, Iligan Institute of Technology- Mindanao State University, Philippines, with reference number CHS-2023-05; CHS-ERC Code: E-2023-05, on February 14th, 2023.
Informed consent was obtained from all participants, clearly outlining the study’s purpose, the voluntary nature of participation, and the confidentiality of responses. Participants were assured that their identities would remain anonymous and that all information provided would be used solely for research purposes. They were also informed of their right to withdraw from the study at any point without penalty. These measures reflect the researchers’ strong commitment to upholding ethical standards and protecting the rights and well-being of all participants throughout the research process.
RESULTS
The study revealed several significant findings, underlying patterns, and unexpected results.
In Table 1, the respondents engaged in short-range planning only occasionally (M = 3.48), pointing to an inconsistent application of daily planning practices. While structured approaches such as scheduling school activities and preparing the day before were fairly common, other essential habits—like setting daily goals, allocating time for reflection, and maintaining consistent planning routines—were less frequent. This uneven pattern suggests that although students recognise the importance of planning, their ability to sustain these practices is limited, reflecting a gap between intention and consistent behavioural follow-through.
SL No. | Short-Range Planning | Mean | SD | Description |
1. | “I make a list of the things that I have to do each day”. | 3.49 | 1.05 | Sometimes |
2. | “I make a schedule of the activities that I have to do on school days”. | 3.68 | 1.04 | Often |
3. | “I plan the day before I start it”. | 3.58 | 1.06 | Often |
4. | “I write a set of goals for myself for each day”. | 3.15 | 1.11 | Sometimes |
5. | “I have a clear idea of what I want to accomplish during the next week”. | 3.50 | 1.03 | Often |
6. | “I spend time each day planning”. | 3.10 | 1.06 | Sometimes |
7. | “I set and honour priorities”. | 3.86 | 0.96 | Often |
Total Measure | 3.48 | 0.82 | Sometimes |
SD= Standard Deviation
Table 2 showed that overall, students demonstrated a moderately positive orientation toward time management (M = 3.58). They acknowledged the need to improve their time use and generally felt responsible for managing their schedules. However, lingering unproductive routines and difficulty declining commitments revealed an ongoing struggle to assert boundaries. This highlights the tension between students’ awareness of effective time management and the persistence of habits that undermine their academic focus.
Sl. No. | Time Attitudes | Mean | SD | Description |
1. | “I continue unprofitable routines or activities”. | 3.44 | 0.78 | Sometimes |
2. | “I believe that there is room for improvement in the way I manage my time”. | 4.50 | 0.69 | Always |
3. | “I find myself doing things which interfere with my college work simply because I hate to say “No” to people”. | 3.35 | 1.13 | Sometimes |
4. | “I feel I am in charge of my own time, by large”. | 3.92 | 0.86 | Often |
5. | “On an average class day, I spend more time with personal grooming than doing college work”. | 2.83 | 0.98 | Sometimes |
6. | “I make constructive use of time”. | 3.44 | 0.80 | Sometimes |
Total Measure | 3.58 | 0.45 | Often |
Table 3 shows that engagement in long-range planning was inconsistent (M = 3.43). Students often resorted to last-minute work before deadlines, reflecting a reactive approach that risks elevating stress and reducing performance. While some organizational practices, such as maintaining a tidy workspace and alternating between tasks, were evident, proactive strategies like reviewing notes outside of exam preparation or setting quarter-long goals were far less common. This indicates that while students employ some tools for productivity, they have yet to fully embrace anticipatory planning that supports long-term academic success.
Sl. No. | Long-Range Planning | Mean | SD | Description |
1. | “The night before a major assignment is due, I am still working on it”. | 3.78 | 0.85 | Often |
2. | “I have a set of goals for the entire quarter”. | 3.31 | 1.05 | Sometimes |
3. | “I keep my desk clear of everything other than what I am currently working on”. | 3.72 | 1.03 | Often |
4. | “When I have several things to do, I think it is best to do a little bit of work on each one”. | 3.58 | 0.99 | Often |
5. | “I review my class notes, even when a test is not imminent”. | 2.75 | 0.90 | Sometimes |
Total Measure | 3.43 | 0.56 | Sometimes |
SD= Standard Deviation
Table 4 displays that respondents reported moderate stress overall (M = 3.26). Among the five dimensions, personal inadequacy emerged as the most significant stressor (M = 3.50), indicating that students’ self-perceptions of their academic ability weighed heavily on their stress levels. Fear of failure, strained teacher–student relationships, and inadequate study facilities also contributed to stress, though to a lesser extent. Together, these findings underscore that academic stress among nursing students is not rooted in a single factor but reflects a complex interplay of internal doubts and external learning conditions.
Notably, several students identified challenges linked to the abrupt transition to online learning during the COVID-19 pandemic, pointing to the importance of strengthening coping strategies and reinforcing effective time-management habits in flexible learning environments.
Academic Stress | Mean | SD | Description |
Personal Inadequacy | 3.50 | 0.68 | Highly Stress |
Fear of Failure | 3.23 | 0.85 | Moderately Stress |
Interpersonal Difficulties with Teachers | 3.15 | 0.86 | Moderately Stress |
Teacher-Student Relationship/Teaching Method | 3.27 | 0.87 | Moderately Stress |
Inadequate Study Facilities | 3.18 | 0.85 | Moderately Stress |
Total Measure | 3.26 | 0.74 | Moderately Stress |
SD= Standard Deviation
Table 5 presents an ordinal regression analysis, which revealed that household income was the only significant predictor of academic stress. Students from families earning less than ₱10,000 per month were more vulnerable to higher stress levels (p = 0.018), underscoring the role of financial strain in shaping academic well-being. Other demographic factors—including age, gender, residence type, family size, and previous academic load—were not significantly associated with stress.
Although income predicted stress levels, the model explained only a small portion of variance (pseudo-R² = 0.028), suggesting that stress is influenced by a broader set of factors beyond socio- demographic profiles. Nevertheless, the finding emphasises the need to consider economic hardship when designing student support initiatives, as financial pressures compound the academic and emotional challenges faced by nursing students.
Variables | Estimate | S.E. | Wald | P-value | 95% C. I. |
Age (years) | -0.029 | 0.111 | 0.068 | 0.794 | (-0.247, 0.189) |
Previous Academic Load | 0.041 | 0.055 | 0.560 | 0.454 | (-0.067, 0.149) |
Number of Family Members | 0.044 | 0.056 | 0.610 | 0.435 | (-0.066, 0.153) |
Gender: Male vs Female (Reference) | -0.381 | 0.314 | 1.473 | 0.225 | (-0.996, 0.234) |
Type of Residence | |||||
Apartment vs Others (reference) | -0.268 | 0.728 | 0.136 | 0.713 | (-1.696, 1.159) |
Own House vs Others (reference) | -0.473 | 0.596 | 0.630 | 0.427 | (-1.642, 0.695) |
Boarding House vs Others (reference) | -0.520 | 0.600 | 0.750 | 0.387 | (-1.697, 0.657) |
Others (reference) | - | - | - | - | - |
Co-resident | |||||
Alone vs Others (reference) | -0.426 | 0.748 | 0.324 | 0.569 | (-1.893, 1.041) |
Family vs Others (reference) | -0.132 | 0.651 | 0.041 | 0.839 | -1.408, 1.143) |
Relative vs Others (reference) | -0.279 | 0.782 | 0.127 | 0.721 | (-1.812, 1.254) |
Friends vs Others (reference) | -0.470 | 0.751 | 0.392 | 0.531 | (-1.941, 1.001) |
Others (reference) | - | - | - | - | - |
Monthly Income (Php) | |||||
Less than 10,000 vs 125,001+ (reference) | 1.764* | 0.746 | 5.585 | 0.018 | (0.301, 3.226) |
10,001-20,000 vs 125,001+ (reference) | 0.947 | 0.591 | 2.572 | 0.109 | (-0.211, 2.105) |
20,001-40,000 vs 125,001+ (reference) | 0.908 | 0.572 | 2.521 | 0.112 | (-0.213, 2.028) |
40,001-75,000 vs 125,001+ (reference) | 0.655 | 0.588 | 1.241 | 0.265 | (-0.497, 1.807) |
75,001-125,000 vs 125,001+ (reference) | 0.231 | 0.694 | 0.111 | 0.739 | (-1.128, 1.591) |
Monthly Income = 125,001+ (reference) | - | - | - | - | - |
Note: Ordinal logistic regression with proportional odds. Reference (baseline) categories: Gender = Female; Type of residence = Others; Co-resident = Others; Monthly income = ₱125,001+. Model Fit: Goodness-of-Fit (X2=391.063, p=0.391); Pseudo R2 (based on McFadden) =0 .028; Test of Parallel Lines (X2=13.250, p=0.654) p<0 .05 is denoted with *; Php ₱= Philippine Pesos; S.E.= Standard Error; Wald: The Wald statistic is used to test the null hypothesis; C.I.= Confidence Interval)
DISCUSSION
This study highlights the joint influence of financial strain and time-management behaviours on academic stress among nursing students. In our cohort, respondents from lower-income households reported higher stress levels, a finding consistent with recent evidence that financial hardship exacerbates psychological distress in student populations. Anaman-Torgbor et al. (2021) found that 73% of Ghanaian nursing students experienced stress, with gender and programme type influencing outcomes. Similarly, Mohamed et al. (2024) reported moderate to high stress among Egyptian nursing students, with fear of mistakes emerging as a primary stressor. These studies confirm that academic stress is widespread yet unevenly distributed, shaped by financial, cultural, and institutional contexts.
Our analysis revealed inconsistencies in students’ time-management practices. While some engaged in daily or weekly planning, many failed to sustain these habits. This variability aligns with evidence linking poor time management to procrastination, disengagement, and heightened stress. Sadeghi et al. (2024) showed that time-management skills explained nearly 10% of the variance in self-directed learning readiness among nursing students, while Fu et al. (2025) demonstrated that time management positively predicted study engagement in Chinese college students both directly and indirectly through self-control and reduced mobile phone dependence.
The findings are well framed by Self-Regulated Learning (SRL) theory, which views learning as the interplay of metacognition, motivation, and strategic behaviours. Within this framework, time management is part of resource regulation, enabling learners to allocate effort and prioritise tasks (Brady & Wolters, 2022). Weaknesses in this area undermine motivation and contribute to inefficiency.
In addition, our results resonate with Conservation of Resources (COR) theory, which emphasises that stress arises when valued resources are threatened or depleted. Recent higher-education work has applied COR to student burnout, showing that resource threats predict burnout over time (Thi & Duong, 2024). Meanwhile, Sarwer et al. (2025) demonstrated that academic burnout among undergraduates stems from resource depletion under competing demands. These findings parallel our data, suggesting that students with fewer resources (e.g., time, financial security, study space) may be especially vulnerable to stress when they cannot sustain consistent planning behaviours.
Overall, respondents reported moderate stress (M = 3.26), with personal inadequacy the most prominent stressor. This pattern mirrors higher education globally. Hoyt et al. (2021) found that stress became “the new normal” among U.S. students, with women and gender-diverse students reporting heightened distress. Rutkowska et al. (2022) similarly documented that 58% of e‑learning students experienced elevated stress and 56% exhibited depressive symptoms; stress and isolation explained about two‑thirds of the variance in depression. These findings suggest that our participants’ experiences of stress, particularly regarding remote learning and inadequate study facilities, are part of a broader internal pattern.
Institutional and contextual stressors were also evident. Inadequate facilities, shifting modalities, and strained teacher–student interactions echoed challenges reported internationally. In the Philippines, Estrellado (2021) described how the return to face-to-face classes after pandemic restrictions required major pedagogical adjustments. Jamaludin et al. (2022) concluded that rapid adoption of online learning globally strained resources and disrupted clinical training. Zhao and Xue (2023) noted that international students experienced uncertainty regarding assessment standards and support services during this transition. Similarly, Day et al. (2021) and Rathnayake et al. (2022) highlighted that resource shortages and disrupted pedagogies amplified inequalities, compounding academic stress.
A notable finding was the significant association between low household income and higher academic stress (p = 0.018). This suggests that financial disadvantage not only heightens stress directly but also limits the ability to engage in effective time management. Students from lower- income backgrounds may face competing obligations, limited study environments, and lack of access to learning resources, all of which hinder consistent planning. Recent COR-based research reinforces this dynamic: Guo et al. (2025) found that limited resources under stress constrained students’ ability to protect their mental health, while Kumyoung and Kumyoung (2025) demonstrated that COR processes interact with academic demands to predict student burnout. Together, these findings highlight that time management must be understood within broader socio- economic realities, not just as an individual skill deficit.
Beyond identifying stressors, recent research emphasises the value of structured interventions. Wahid et al. (2023) showed that supportive educational environments improved performance and well-being, while Wang and Syafiq (2023) reported that time-management workshops significantly enhanced academic self-efficacy. Jadoon et al. (2023) further identified heavy workloads and unpredictable schedules as major stressors among nursing students, underscoring the urgency of systematic support.
Based on these insights, effective interventions should address both structural and behavioural dimensions:
Embedding time-management and Self-Regulated Learning (SRL)-based training into nursing curricula.
Providing financial aid, mentoring, and counselling services for disadvantaged students.
Ensuring adequate infrastructure and clear pedagogical structures to minimise preventable stressors.
Promoting peer networks and resilience training to reduce perceived inadequacy.
This study contributes to theory by demonstrating that Self-Regulated Learning (SRL) and Conservation of Resources (COR) frameworks together offer a comprehensive lens for explaining stress. SRL highlights the role of individual time-management strategies in regulating learning, while COR shows how external financial strain undermines these processes by depleting resources. Recent applications of COR in higher education (Thi & Duong, 2024; Sarwer et al., 2025; Guo et al., 2025) confirm its relevance for understanding why resource-deprived students struggle disproportionately with time management and stress.
CONCLUSION
This study demonstrates that academic stress among nursing students is shaped by both individual behaviours and socio-economic contexts. While students recognise the value of time management, inconsistent use of short-, medium-, and long-range planning contributes to moderate stress, particularly feelings of personal inadequacy. Institutional stressors such as strained teacher– student interactions, limited facilities, and abrupt learning transitions further exacerbate these pressures.
Household income was a significant predictor of stress, showing how financial disadvantage amplifies academic strain and limits the consistent application of effective time-management practices. This underscores the need for interventions that address not only individual skill development but also systemic barriers.
Framed within self-regulated learning and conservation of resources theories, the findings extend theoretical understanding by illustrating how behavioural regulation interacts with resource constraints to shape student outcomes. Educational institutions can reduce stress and foster resilience by embedding time-management training in curricula while strengthening financial, infrastructural, and psychosocial support.
Limitations
This study offers meaningful insights into the relationship between time management strategies and academic stress among nursing students; however, several limitations must be acknowledged. First, the reliance on self‑reported data for assessing time management behaviours and perceived academic stress introduces potential bias. Participants may unintentionally overestimate or underestimate their abilities or stress levels, and responses may be influenced by social desirability bias. Second, the cross‑sectional design of the study limits the ability to establish causality among the variables. While associations can be observed, longitudinal studies are needed to determine the directionality and long‑term effects of time management practices and socio‑demographic factors on academic stress. Third, the sample size of 212 nursing students, although adequate for preliminary analysis, may not be representative of the broader nursing student population. A larger and more diverse sample would enhance the generalisability of the findings to different academic contexts and cultural backgrounds. Lastly, the study did not control other potentially significant variables, such as mental health status, academic discipline, and family or social support systems. These factors may have influenced the levels of academic stress experienced by students and should be considered in future research to provide a more comprehensive understanding of the phenomenon. Addressing these limitations in future research will contribute to more robust and generalisable conclusions, helping educators and institutions develop more effective interventions to support students’ academic well-being.
Conflict of Interest
The authors declare that there is no conflict of interest.
ACKNOWLEDGEMENT
The authors gratefully acknowledge the invaluable support of their colleagues from the Mindanao State University – Iligan Institute of Technology, College of Health Sciences, Philippines. Special appreciation is extended to Dr Mae-Lanie O. Poblete for her steadfast mentorship, expert guidance, and constant encouragement, which were instrumental in shaping the direction and rigour of this study.
The authors also extend their sincere gratitude to Dr Gloria Shiela E. Coyoca for her constructive critique, insightful feedback, and motivation to pursue publication, all of which significantly enhanced the quality of this work. Finally, the authors acknowledge the valuable contributions of Associate Professor Elvie A. Paler, whose thoughtful suggestions and scholarly input further strengthened the refinement and depth of this research.
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