Barriers to physical activity among pharmacy undergraduates at Universiti Malaya, Malaysia: profiles and associated factors from a cross-sectional study

Abstract

Background

Despite its significant implications for student well-being, nationally representative data on physical activity among pharmacy students in Malaysia remain limited. Accordingly, this study aimed to assess the frequency of physical activity and the factors associated with barriers to physical activity among pharmacy undergraduates at Universiti Malaya, Kuala Lumpur, Malaysia.

Methods

This cross-sectional, questionnaire-based study utilised the Barriers to Being Active Quiz. All undergraduate students enrolled in the pharmacy programme at the University of Malaya were invited to participate. Differences in barrier scores across demographic groups were evaluated using Mann–Whitney U tests for two-group comparisons and Kruskal–Wallis tests for variables with three or more categories. Binary logistic regression analysis was further performed to identify factors associated with physical activity. A p-value of < 0.05 was considered statistically significant for all analyses.

Results

Two hundred and sixty-three pharmacy undergraduates participated in the study, yielding a response rate of 92.2%. More than half of the respondents (56.3%) were physically inactive. Several demographic characteristics, including gender, ethnicity, and residence status, were significantly associated with selected physical activity barrier domains. The most reported barriers were lack of energy, lack of willpower, and lack of time. In binary logistic regression analysis, lack of willpower was the only factor significantly associated with physical inactivity (AOR = 3.816, 95% CI: 1.91–7.64, p = 0.001).

Conclusion

This study demonstrates a high prevalence of physical inactivity among pharmacy undergraduates in this setting. Lack of willpower emerged as the only factor independently associated with physical inactivity, while lack of energy and lack of time were also commonly reported barriers. These findings suggest that individual-level behavioural constraints may play a more prominent role than environmental factors in shaping physical activity behaviours. They highlight the need for targeted, behaviour-focused strategies to promote physical activity within academically demanding university settings.

Introduction

In 1978, Tomas Strasser argued that disease prevention should extend beyond conventional approaches, laying the foundation for the concept of primordial prevention [1]. Among the strategies underpinning primordial prevention, physical activity is a cornerstone of health promotion and the prevention of non-communicable diseases across the lifespan. As a result, the World Health Organization (WHO) emphasizes that any amount of physical activity is better than none, as well as highlighting the benefits for all age groups [2]. Regular physical activity is associated not only with reduced risk of non-communicable diseases but also with improved psychological well-being, better mental health, and enhanced cognitive functioning [3–6]. Consequently, regular physical activities are widely promoted by healthcare professionals at all levels of care [7]. Despite these well-established benefits, physical inactivity remains a major global concern. A global pooled analysis of more than 5.7 million participants from 163 countries showed an increase in physical inactivity from 23.4% in 2000 to 26.4% in 2010, with further growth projected beyond 2022 [8]. Another report by the WHO indicated that 31% of adults were physically inactive, with the highest prevalence observed in lower-middle-income countries [9]. This rising prevalence is particularly troubling given the strong association between physical inactivity and adverse cardiometabolic outcomes, chronic diseases, and premature death [10].

Within this global context, university students represent a particularly vulnerable group. Evidence consistently indicates that many university students fail to meet recommended physical activity levels, underscoring the importance of understanding the barriers that impede their participation in such activities [11, 12]. Long hours of sitting, increased screen time, and irregular eating patterns can also exacerbate weight gain, fatigue, and metabolic dysfunction. From this perspective, pharmacy undergraduates constitute a particularly relevant subgroup, as the intensity of their academic training may exacerbate barriers to physical activity [13–15]. Furthermore, as future pharmacists, their personal engagement with physical activity is especially significant because healthcare professionals’ own lifestyle behaviours can influence both their willingness and confidence to counsel patients about physical activity [16]. This is particularly important given the growing recognition that community pharmacists can play a key role in improving the management of diseases, including both infectious and non-infectious diseases, with their role growing among low- and middle-income countries [17–19]. This includes promoting lifestyle modification [20], with community pharmacists often the first healthcare professional that patients visit with their medical problems [21, 22].

In Malaysia, assessing physical activity among university students is progressively important in view of the country’s substantial burden of obesity and diabetes [23, 24]. Whilst public health messaging on active lifestyles has intensified, regular participation in physical activity among Malaysian young adults remains suboptimal, suggesting that awareness alone may not translate into sustained behaviour change [25]. This is a concern as bad habits learnt as students may be difficult to address later in life [26]. Such habits tend to persist in adulthood, thereby underscoring adolescence as a critical period for promoting sustained engagement in physical activities later in life. Previous research has shown that once formed, unhealthy habits are likely to persist into adulthood [27]. Consequently, it is recommended that physical activity-based interventions should be initiated from adolescence through young adulthood to address rising rates of diabetes and obesity in the country. While existing studies have analysed physical activity levels and related factors among Malaysian university students in general [28, 29], these findings may not be directly transferable to pharmacy undergraduates. This is because, as mentioned, pharmacy undergraduates represent a distinct and underexplored subgroup within higher education. Pharmacy training is characterized by a uniquely intensive academic structure, including demanding coursework, laboratory sessions, clinical placements, and continuous assessments. These combined activities impose substantial constraints on students’ time, energy, and psychological resources [30, 31]. These context-specific demands may shape both the nature and intensity of barriers to physical activity in ways that meaningfully differ from the broader student population.

Alongside this, pharmacy students are future healthcare professionals, whose personal health behaviours are not only important for their own well-being but may also influence their professional practice, including the impact of public health advice to patients. Evidence suggests that healthcare professionals who engage in healthy lifestyle behaviours, including regular physical activity, are more likely to counsel patients effectively and promote behaviour change [16]. Consequently, insufficient physical activity among pharmacy undergraduates may have implications that extend beyond individual health, potentially affecting future patient education, counselling practices, and public health outcomes.

Notwithstanding these factors, there is a notable lack of empirical data concerning the drivers of and obstacles to physical activity among Malaysian pharmacy students. This needs to be urgently addressed, especially as high tuition fees and the additional expenses associated with pharmacy education can further exacerbate the ongoing stress and anxiety of labour-intensive courses, thereby adversely affecting students’ mental health [31]. One way to manage these academic and financial pressures is through engagement in physical activity, a proven strategy for reducing stress and promoting healthier behaviours and lifestyles [32]. In this context, identifying the barriers that hinder physical activity among pharmacy students is crucial for informing future targeted, feasible, and sustainable campus-based strategies, which, as mentioned, have important implications not only during university but also post-qualification.

Accordingly, this study aimed to assess the frequency of physical activity and the perceived barriers to physical activity among pharmacy undergraduates at Universiti Malaya, Malaysia. Specifically, the study sought to: (1) determine the frequency of physical inactivity among students, (2) identify potential barriers to physical activity, and (3) examine the association between these perceived barriers and physical activity. Given the limited discipline-specific evidence, this study adopted an exploratory analytical design. Initially, an exploratory approach was used to describe patterns of physical activity and perceived barriers within this under-researched population. Subsequently, an analytical approach was applied through inferential statistical techniques, including non-parametric tests and binary logistic regression, to examine associations between variables and identify factors independently associated with physical inactivity.

Methods

Study design and settings

This questionnaire-based cross-sectional study was conducted at the Faculty of Pharmacy, Universiti Malaya, Kuala Lumpur, Malaysia, where pharmacy students were approached for data collection. The pharmacy curriculum is intensive, and students are continuously engaged in academic and co-curricular commitments. In addition, the faculty provides a range of student exchange programmes, community engagement initiatives, and research-based activities that further increase demands on students’ time. In line with the study objectives, this cohort was particularly appropriate, as the intensive academic and co-curricular commitments associated with pharmacy training impose significant time and energy constraints, which may directly reduce students’ ability to initiate and sustain participation in physical activity.

Sampling procedure, recruitment, and criteria

The study employed a universal sampling strategy, whereby all undergraduate pharmacy students at the Faculty of Pharmacy, Universiti Malaya were invited to participate [33]. A universal sampling approach was adopted as the target population was relatively small, well-defined, and easily accessible within a single institutional setting. This approach minimized selection bias and enhanced the representativeness of the sample, thereby improving the internal validity of the findings. Additionally, including the entire cohort increased statistical power and allowed for more reliable subgroup comparisons across demographic characteristics [33, 34].

Eligible participants were undergraduates currently enrolled in the Faculty of Pharmacy, Universiti Malaya who were willing to participate and able to provide written informed consent. Students who declined participation or did not provide consent were excluded.

Assessment of physical activity among pharmacy undergraduates

Physical activity was assessed using self-reported measures of frequency and duration of moderate- and vigorous-intensity activities performed during a typical week. Participants were asked to report the number of days and the average time spent engaging in such activities. Based on these responses, total weekly physical activity was calculated. In accordance with WHO’s recommendations [2], participants were classified as physically active if they engaged in ≥ 150 min of moderate-intensity activity or ≥ 75 min of vigorous-intensity activity per week (or an equivalent combination). Participants who did not meet these criteria were classified as physically inactive.

Research tool: reliability and validity

In addition to demographic information, this study employed the Barriers to Being Active Quiz (BBAQ), developed by the Centers for Disease Control and Prevention, to assess perceived barriers to physical activity [35]. The BBAQ is a 21-item instrument administered using a 4-point Likert-type response format. It categorizes barriers to physical activity into seven domains. Each domain comprises three items, and in accordance with the instrument developers’ scoring guidelines, a subscale mean score of ≥ 5 was interpreted as indicating a salient or important barrier [35].

Cultural validity was ensured through expert review (n = 12) and pilot testing (n = 30), confirming the clarity and contextual suitability of the BBAQ within the Malaysian student population. This process involved six pharmacy undergraduates and six certified fitness experts, who independently reviewed the instrument to assess clarity, relevance, and comprehensiveness of the items. Reviewers evaluated whether the items were appropriate, clearly worded, and aligned with the study objectives and target population. Feedback from both groups was collated, and no revisions were required. As the BBAQ is an established and previously validated instrument, a formal Content Validity Index was not calculated. Instead, expert consensus was used to confirm content adequacy and cultural appropriateness for the study context.

Subsequently, the instrument was pilot tested with 30 pharmacy students to assess reliability and clarity. Participant feedback confirmed that the items were clear and comprehensible, with no modifications required. The instrument demonstrated excellent internal consistency (Cronbach’s alpha = 0.946), indicating high reliability for use in the main study. Subscale reliability across the seven domains was also high: lack of time (α = 0.902), social influence (α = 0.900), lack of energy (α = 0.915), lack of willpower (α = 0.947), fear of injury (α = 0.922), lack of skill (α = 0.932), and lack of resources (α = 0.939). Pilot data were excluded from the final analysis.

Data collection

A two-month data collection period (1 October – 30 November 2025) employed a structured, self-administered instrument developed on the Google Forms platform. To ensure a high response rate, the second author recruited participants in person following compulsory academic commitments, including laboratory shifts and Objective Structured Pharmacy Examinations, as well as during general on-campus hours. At the time of recruitment, students were provided with a brief explanation of the study objectives, procedures, expected time commitment, and assurances of confidentiality and voluntary participation. A secure link to the online questionnaire was then shared with participants, including via the official WhatsApp group of pharmacy students at Universiti Malaya, to ensure accessibility to all eligible participants. This approach ensured that most enrolled students were reached at the time of recruitment. Participation was entirely voluntary, and students who did not respond were those who chose not to complete the questionnaire.

Data coding and analysis

Data coding and statistical analyses were performed using Statistical Package for the Social Sciences version 31 [36]. The Kolmogorov-Smirnov test was applied to identify the nature and distribution of the data. All items generated highly significant values, and accordingly, the analysis proceeded with descriptive statistics followed by appropriate non-parametric tests [37].

Responses to the BBAQ were recorded on a 4-point Likert scale. For each domain, item scores were summed and averaged to generate composite domain scores. Whilst Likert-scale data are ordinal, the use of mean scores is considered acceptable when multiple items are combined into a composite scale with demonstrated internal consistency [38, 39]. Importantly, the internal consistency of the instrument in our study was excellent (Cronbach’s alpha = 0.946), supporting the reliability of aggregating items into domain scores [40, 41].

The Mann–Whitney U test was used to compare barrier domain scores between two groups (age group and gender), while the Kruskal–Wallis test was used for comparisons involving three or more than three groups (ethnicity, year of study, and residence status). These analyses were conducted for each of the seven barrier domains derived from the BBAQ. Effect sizes were calculated to assess the magnitude of differences (r for Mann–Whitney U and eta-squared for Kruskal–Wallis tests).

Physical activity status was treated as the dependent variable and categorized as a binary outcome (physically active vs. physically inactive) based on WHO’s recommendations. Participants were classified as physically active if they reported engaging in ≥ 150 min of moderate-intensity activity or ≥ 75 min of vigorous-intensity activity per week (or an equivalent combination), and as physically inactive otherwise [2]. A binary logistic regression analysis was conducted to examine factors associated with physical inactivity. The independent variables included the seven barrier domains derived from the BBAQ, namely lack of time, social influence, lack of energy, lack of willpower, fear of injury, lack of skill, and lack of resources. To control for potential confounding, the model was adjusted for key demographic variables, including gender, age group, ethnicity, year of study, and residence status. All variables were entered simultaneously into the model to assess their independent associations with physical inactivity. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported.

Results

Demographic profile of the study respondents

Out of the 285 eligible students, 263 participated in the study, yielding a response rate of 92.2%. Table 1 summarizes the demographic characteristics of the respondents. Most participants were aged between 19 and 21 years (71.5%), with females constituting a larger proportion of the sample (n = 177, 67.3%). In terms of ethnicity, nearly half of the respondents were Malay (49.0%), followed by Chinese (44.1%) and Indian (3.8%) ethnicity. The distribution across academic years was relatively balanced, with 28.9% in Year 1, 24.7% in Year 2, 23.2% in Year 3, and 23.2% in Year 4. Additionally, most respondents (63.9%) were residing in university-provided hostels.

Table 1.

Demographic profile of the study respondents

Variables		Frequency (N)	Percentage (%)
Age group	19–21 22–24	188 75	71.5 28.5
Gender	Male Female	86 177	32.7 67.3
Ethnicity	Malay Chinese Indian Others	129 116 10 8	49.0 44.1 3.8 3.0
Year of study	Year1 Year2 Year3 Year4	76 65 61 61	28.9 24.7 23.2 23.2
Residence status	Hostel Home Rental	168 25 70	63.9 9.5 26.6

Participation in physical activity

Respondents were asked about their current participation in physical activity and were classified as either active or inactive. Nearly 56% of the respondents reported being physically inactive. Across age categories, non-active students constituted the larger proportion, while males were more likely to be active (58.1%) than females. Comparable patterns were seen across ethnic groups. Whilst no clear trend emerged by year of study, fourth-year students showed slightly higher inactivity rates, as shown in Table 2.

Table 2.

Respondents’ participation in physical activity

Variables		Physically active* (115, 43.7%)		Physically non active (148, 56.3%)
		N	%	N	%
Age group	19–21 22–24	91 24	48.4% 32.0%	97 51	51.6% 68.0%
Gender	Male Female	50 65	58.1% 36.7%	36 112	41.9% 63.3%
Ethnicity	Malay Chinese Indian Others	65 44 4 2	50.4% 37.9% 40.0% 25.0%	64 72 6 6	49.6% 62.1% 60.0% 75.0%
Year of study	Year 1 Year 2 Year 3 Year 4	35 32 26 22	46.1% 49.2% 42.6% 36.1%	41 33 35 39	53.9% 50.8% 57.4% 63.9%
Residence status	Hostel Home Rental	75 11 29	44.6% 44.0% 41.4%	93 14 41	55.4% 56.0% 58.6%

“*As per World Health Organization guidelines, students were classified as ‘sufficiently active’ if they accumulated ≥ 150 min per week of moderate-intensity activity or ≥ 75 min per week of vigorous-intensity activity (or an equivalent combination), preferably distributed across the week”

Assessment of barriers to physical activity

The first domain, lack of time, received strong endorsement, with most respondents moderately agreeing that busy schedules and limited free time restricted their ability to exercise. In terms of social influences, participants reported minimal encouragement from family and friends. Fear of injury was comparatively less prominent than other barriers. Responses for lack of skill and lack of resources were more mixed, with many indicating limited access to suitable facilities or exercise equipment.

Based on the recommended scoring approach, lack of willpower emerged as the most prevalent barrier to physical activity, reported by 65.4% of respondents, followed by lack of energy (60.8%) and lack of time (57.0%). Overall, internal and motivational barriers were more prominent than external or environmental constraints (Table 3).

Table 3.

Assessment of barriers to physical activity

Items in questionnaire	VU*	SU*	SL*	VL*
Lack of time (N = 150, 57% reporting barrier ≥ 5)
My day is so busy now, I just don’t think I can make the time to include physical activity in my regular schedule.	11% (n = 29)	23.2% (n = 61)	43.3% (n = 114)	22.4% (n = 59)
Physical activity takes too much time away from other commitments - time, work, family, etc.	15.6% (n = 41)	32.7% (n = 86)	29.3% (n = 77)	22.4% (n = 59)
My free time during the day is too short to include exercise.	16.7% (n = 44)	28.5% (n = 75)	30.8% (n = 81)	24% (n = 63)
Social influences (N = 119, 45.2% reporting barrier ≥ 5)
None of my family members or friends like to do any activity, so I do not have a chance to exercise.	28.5% (n = 75)	32.3% (n = 85)	21.7% (n = 57)	17.5% (n = 46)
I’m embarrassed about how I will look when I exercise with others.	25.9% (n = 68)	28.1% (n = 74)	26.6% (n = 70)	19.4% (n = 51)
My usual social activities with family or friends do not include physical activity.	21.7% (n = 57)	25.5% (n = 67)	28.1% (n = 74)	24.7% (n = 65)
Lack of energy (N = 160, 60.8%% reporting barrier ≥ 5)
I am just too tired after work to get any exercise.	10.3% (n = 27)	23.2% (n = 61)	44.1% (n = 116)	22.4% (n = 59)
I don’t get enough sleep as it is.  I just couldn’t get up early or stay up late to get some exercise.	17.1% (n = 45)	24.7% (n = 65)	29.7% (n = 78)	28.5% (n = 75)
I’m too tired during the week and I need the weekend to catch up on my rest.	13.7% (n = 36)	20.5% (n = 54)	38.4% (n = 101)	27.4% (n = 72)
Lack of willpower (N = 172, 65.4% reporting barrier ≥ 5)
I’ve been thinking about getting more exercise, but I just can’t seem to get started.	13.3% (n = 35)	23.2% (n = 61)	36.1% (n = 95)	27.4% (n = 72)
It’s easier for me to find excuses not to exercise than to go out to do something.	17.1% (n = 45)	30.0% (n = 79)	30.8% (n = 81)	22.1% (n = 58)
I want to get more exercise, but I just can’t seem to make myself stick to anything.	14.8% (n = 39)	23.2% (n = 61)	36.9% (n = 97)	25.1% (n = 66)
Fear of Injury (N = 91, 34.6% reporting barrier ≥ 5)
I’m getting older so exercise can be risky.	40.7% (n = 107)	24.7% (n = 65)	17.9% (n = 47)	16.7% (n = 44)
I know of too many people who have hurt themselves by overdoing it with exercise.	25.5% (n = 67)	32.3% (n = 85)	27.0% (n = 71)	15.2% (n = 40)
I’m afraid I might injure myself or have a heart attack.	35.7% (n = 94)	25.5% (n = 67)	21.7% (n = 57)	17.1% (n = 45)
Lack of skills (N = 117, 44.5% reporting barrier ≥ 5)
I don’t get enough exercise because I have never learned the skills for any sport.	24.0% (n = 63)	29.7% (n = 78)	26.6% (n = 70)	19.8% (n = 52)
I really can’t see learning a new sport at my age.	29.3% (n = 77)	29.7% (n = 78)	22.1% (n = 58)	19.0% (n = 50)
I’m not good enough at any physical activity to make it fun.	28.1% (n = 74)	25.5% (n = 67)	25.5% (n = 67)	20.9% (n = 55)
Lack of resources (N = 78, 29.7% reporting barrier ≥ 5)
I don’t have access to jogging trails, swimming pools, bike paths, etc.	42.6% (n = 112)	29.7% (n = 78)	16.0% (n = 42)	11.8% (n = 31)
It’s just too expensive.  I must take a class or join a club or buy the right equipment.	41.4% (n = 109)	25.1% (n = 66)	20.2% (n = 53)	13.3% (n = 35)
If we had exercise facilities and showers at work, then I would be more likely to exercise.	27.0% (n = 71)	25.5% (n = 67)	29.7% (n = 78)	17.9% (n = 47)

Responses are presented as percentages with corresponding frequencies (n). Each barrier domain consists of three items derived from the Barriers to Being Active Quiz. A total domain score ≥ 5 indicates the presence of a salient barrier, and N represents the number and proportion of respondents meeting this threshold for each domain. Higher proportions in the “SL” and “VL” categories reflect greater perceived likelihood of the respective barrier

* VU Very unlikely, SU Slightly unlikely, SL Slightly likely VL Very likely

Comparison of barrier domain scores across demographic characteristics

Table 4 presents the comparison of perceived physical activity barrier domains across demographic characteristics using non-parametric tests with corresponding effect sizes. Overall, gender differences were statistically significant across all barrier domains, indicating that males and females differed in their perceptions of barriers to physical activity. The most prominent difference was observed for lack of willpower (U = 5244.0, p < 0.001, r = 0.26), representing a moderate effect size, suggesting meaningful practical differences between genderes. Other domains, such as lack of skill (r = 0.20), lack of resources (r = 0.20), social influence (r = 0.19), and lack of energy (r = 0.19), demonstrated small to moderate effects, while fear of injury (r = 0.13) showed a smaller effect. These findings indicate that gender plays a consistent role in shaping perceived barriers.

Table 4.

Comparison of barrier domain scores across demographic characteristics

Variable	Barrier Domain	Test Statistic	p-value	Effect Size
Gender	Lack of time	U = 6069.0	0.007	r = 0.17
	Social influence	U = 5847.5	0.002	r = 0.19
	Lack of energy	U = 5879.0	0.003	r = 0.19
	Lack of willpower	U = 5244.0	< 0.001	r = 0.26
	Fear of injury	U = 6370.5	0.031	r = 0.13
	Lack of skill	U = 5783.5	0.001	r = 0.20
	Lack of resources	U = 5766.0	0.001	r = 0.20
Age group	Lack of time	U = 5875.5	0.033	r = 0.13
	Social influence	U = 5784.0	0.022	r = 0.14
	Lack of energy	U = 6154.0	0.105	r = 0.10
	Lack of willpower	U = 6069.0	0.075	r = 0.11
	Fear of injury	U = 4908.0	< 0.001	r = 0.14
	Lack of skill	U = 6289.5	0.169	r = 0.08
	Lack of resources	U = 6624.5	0.440	r = 0.05
Ethnicity	Lack of time	H = 11.819	0.008	η² = 0.034
	Social influence	H = 3.853	0.278	η² = 0.003
	Lack of energy	H = 16.542	0.001	η² = 0.052
	Lack of willpower	H = 7.354	0.061	η² = 0.017
	Fear of injury	H = 11.810	0.008	η² = 0.034
	Lack of skill	H = 4.947	0.176	η² = 0.007
	Lack of resources	H = 11.727	0.008	η² = 0.034
Year of Study	Lack of time	H = 7.249	0.064	η² = 0.016
	Social influence	H = 4.717	0.194	η² = 0.006
	Lack of energy	H = 4.666	0.198	η² = 0.006
	Lack of willpower	H = 5.012	0.171	η² = 0.008
	Fear of injury	H = 14.716	0.002	η² = 0.045
	Lack of skill	H = 2.954	0.399	η² = 0.000
	Lack of resources	H = 3.790	0.285	η² = 0.003
Residence status	Lack of time	H = 5.646	0.059	η² = 0.014
	Social influence	H = 8.711	0.013	η² = 0.026
	Lack of energy	H = 5.279	0.071	η² = 0.013
	Lack of willpower	H = 4.943	0.084	η² = 0.011
	Fear of injury	H = 0.437	0.804	η² = 0.000
	Lack of skill	H = 1.467	0.480	η² = 0.002
	Lack of resources	H = 6.999	0.030	η² = 0.019

U = Mann–Whitney U test statistic, H = Kruskal–Wallis test statistic; p values below 0.05 indicate statistically significant differences between groups; r represents effect size for Mann–Whitney U tests, and η² represents effect size for Kruskal–Wallis tests

Among the age groups, statistically significant differences were observed for lack of time (U = 5875.5, p = 0.033, r = 0.13), social influence (U = 5784.0, p = 0.022, r = 0.14), and fear of injury (U = 4908.0, p < 0.001, r = 0.14). The effect sizes were small, suggesting minimal practical or clinical relevance. Other domains were not significantly associated with age.

Regarding ethnicity, significant differences were identified for lack of time (η² = 0.034), lack of energy (η² = 0.052), fear of injury (η² = 0.034), and lack of resources (η² = 0.034) (p < 0.05), indicating that cultural or contextual factors may influence these barriers. Notably, a lack of energy demonstrated the largest effect (η² = 0.052), although still within the small-to-moderate range. For the year of study, only fear of injury (p = 0.002, η² = 0.045) was statistically significant, suggesting that perceptions of injury risk may vary with academic progression. However, the effect size remained small. Similarly, residence status showed significant differences in social influence (p = 0.013, η² = 0.026) and lack of resources (p = 0.030, η² = 0.019). This indicates that the living environment may influence access-related and social barriers, although effect sizes were small.

Summarizing, while several statistically significant differences were observed across demographic variables, most effect sizes were small. As a result, this indicates that the practical magnitude of these differences is limited, except for gender differences, particularly regarding a lack of willpower, which demonstrated relatively stronger effects.

Factors associated with barriers to physical activity

A binary logistic regression analysis was performed to identify which perceived barriers were significantly associated with physical activity participation among pharmacy undergraduates. The overall model was statistically significant (χ²(7) = 41.34, p < 0.001), indicating that it reliably distinguished between physically active and inactive students. The Cox & Snell R² = 0.145 and Nagelkerke R² = 0.195 showed that the model explained roughly 15–20% of the variance in physical activity status, a moderate effect typical for behavioral research. The Hosmer–Lemeshow test (p = 0.850) confirmed that the model fit the data well, and the classification accuracy of 69.6% indicated satisfactory predictive power for this sample.

Binary logistic regression analysis showed that lack of willpower was the only factor significantly associated with physical inactivity after adjusting for demographic variables (AOR = 3.816, 95% CI: 1.91–7.64, p = 0.001). The corresponding odds ratio (Exp B) = 3.816 meant that for each one-unit increase in lack of willpower, the odds of being physically inactive are approximately 3.816 times higher, holding other factors constant. Other barriers did not reach statistical significance (p > 0.05), suggesting their effects on physical activity status were comparatively weaker or indirect in this sample (Table 5).

Table 5.

Factors associated with barriers to physical activity

Variables in the equation
Step 1a	Variable	B	SE	p-value	AOR (Exp B)	95% CI
	Lack of time	0.019	0.386	0.961	1.019	0.48–2.17
	Social influences	0.194	0.334	0.562	1.214	0.63–2.33
	Lack of energy	0.003	0.426	0.994	1.003	0.44–2.31
	Lack of willpower	1.339	0.354	0.001	3.816	1.91–7.64
	Fear of injury	0.406	0.364	0.264	1.501	0.73–3.05
	Lack of skills	0.152	0.378	0.688	1.164	0.55–2.44
	Lack of resources	-0.145	0.336	0.666	0.865	0.45–1.67

Statistical significance was set at p < 0.05. The model was adjusted for gender, age group, ethnicity, year of study, and residence status. Higher barrier scores indicate greater perceived barriers, and odds ratios reflect the change in odds of being physically inactive per one-unit increase in score

B Regression coefficient, SE Standard error, AOR Adjusted odds ratio, CI Confidence interval

^aVariable(s) entered on step 1; Dependent variable: Physical activity status (0 = active, 1 = inactive)

Discussion

This study aimed to describe patterns of physical activity and the associated barriers among pharmacy undergraduates. Overall, more than half (56.3%) of respondents in the current study were physically inactive, indicating a substantial frequency of inactivity among pharmacy undergraduates. These findings are consistent with previous literature highlighting high levels of physical inactivity among university students globally [8, 9, 28, 29]. Similar patterns have been reported in other Malaysian studies, where nearly half of the students at the Health Campus of Universiti Sains Malaysia were not regularly engaged in physical activity [42]. Likewise, Anuar et al. (2022) reported that 50.1% of their participants enrolled at Universiti Teknologi Mara Malaysia, were physically inactive [43]. Within this context, Yuan et al., in their systematic review and meta-analysis also highlighted inadequate physical activity among university students as a growing apprehension [44]. Similarly, studies from other countries have also reported that university students are not adequately engaged in physical activity, and that insufficient activity has become a global concern among professionals, including HCPs, policymakers, dietitians, and sports experts [29, 45].

The lack of physical activity reported in this study was consistent with the Malaysian National data on physical activity. In its latest publication, the Ministry of Health Malaysia (2023) reported that approximately one-third of Malaysian adults are insufficiently active and that participation in physical activity is showing a declining trend [46]. This needs to be urgently addressed to reverse the rising rates of diabetes and obesity in the country.

Descriptive analyses indicated that physical inactivity appeared more prevalent among female students, those of Chinese ethnicity, and final-year students. However, these observations were based on unadjusted distributions and should not be interpreted as independent predictors. Findings from the non-parametric analyses further demonstrated that demographic characteristics were primarily associated with differences in perceived barrier domain scores rather than physical inactivity itself. Importantly, when examined using logistic regression, only a lack of willpower was independently associated with physical inactivity, indicating that behavioural factors may play a more direct role than demographic characteristics in determining activity status. Nevertheless, existing literature provides possible contextual explanations. For example, previous studies have suggested that sociocultural expectations, perceived safety, and body image concerns may influence physical activity participation among female students [47]. Similarly, cultural emphasis on academic achievement has been reported to shape lifestyle behaviours in some student populations, which may potentially affect engagement in physical activity [48, 49]. Final-year students may also experience increased academic demands, which could limit available time and motivation for exercise [50].

According to the scale developers, scores ≥ 5 indicated the most prominent barriers to undertaking physical activities [35]. In our study, lack of energy and lack of willpower, followed by lack of time, were identified as the most prominent barriers to engaging in physical activity. However, binary logistic regression analysis revealed that lack of willpower was the variable most strongly associated with physical inactivity (OR = 3.816, p < 0.001), indicating that willpower plays a critical role in determining participation in such activities. This construct, however, should be interpreted with caution. In the context of the present study, “lack of willpower” does not represent a fixed personal trait but rather reflects a broader set of modifiable behavioural and psychological processes, including motivation, self-regulation, habit strength, and the intention–behaviour gap. Consequently, we believe it is more appropriate to understand this finding as indicating challenges in translating intention into sustained physical activity, rather than an inherent deficiency in individuals. This interpretation is consistent with behavioural literature suggesting that individuals may intend to be active but struggle to maintain consistent engagement due to competing demands and limited self-regulatory capacity [51, 52].

To better understand the correlation between perceived barriers and physical activity behaviour, it is important to intellectualise these barriers within established behavioural frameworks. Contemporary evidence highlights that barriers operate through multiple behavioural mechanisms, influencing individuals’ capability, opportunity, and motivation to engage in physical activity [53]. This aligns with recent literature on the intention–behaviour gap, which demonstrates that even when individuals intend to engage in physical activity, perceived barriers significantly hinder actual participation [54]. Consequently, perceived barriers should be understood not merely as descriptive factors but as key determinants that dynamically shape physical activity behaviour through interconnected psychological, social, and environmental pathways, warranting further investigation in future research.

Beyond individuals, the findings of this study have important implications for public health at the institutional level. Structural and environmental conditions also shape physical activity behaviour among university students. Academic timetables, intensive coursework, and competing academic demands may limit opportunities for regular engagement in physical activity. In addition, campus environments, including the availability, accessibility, and affordability of recreational facilities, as well as safe and supportive spaces for exercise, play a critical role in facilitating or constraining active lifestyles [55, 56]. Programme-level initiatives, such as embedding physical activity into curricula, offering flexible scheduling, and promoting active breaks during academic sessions, may further support student engagement [57]. Moreover, integrating physical activity promotion into university health systems through awareness campaigns, behavioural support programmes, and interdisciplinary collaboration can contribute to a more comprehensive and sustainable approach [58]. Taken together, these findings highlight the need for multi-level strategies that address not only individual behavioural factors but also the broader institutional context in which physical activity occurs.

Conclusion

This study offers valuable insights into physical activity patterns and perceived barriers among pharmacy undergraduates at Universiti Malaya, highlighting a notably high prevalence of physical inactivity within this academically demanding cohort. Binary logistic regression analysis identified a lack of willpower as the factor most strongly associated with physical inactivity. These findings suggest that perceived individual-level constraints may play a significant role in shaping physical activity behaviours in this population. However, this interpretation should be approached with caution, given the reliance on self-reported measures and the study’s cross-sectional design.

Recommendations

Future research should employ longitudinal designs to examine how barriers influence physical activity behaviour over time and to allow for clearer causal interpretations. Broadening the sampling frame to include students from multiple universities across Malaysia engaged in similar academic pressures would provide a more diverse perspective and enhance comparability across settings.

Policy implications

The high prevalence of physical inactivity among pharmacy undergraduates, with a lack of willpower emerging as the factor most strongly associated with inactivity, highlights the need for policy approaches that move beyond awareness and access. University and higher-education policies among healthcare students should embed physical activity and wellness within academically intensive programs, emphasizing behavioral self-regulation, habit formation, and intrinsic motivation in line with primordial prevention. Such activities will also be beneficial both to the students and the public post-qualification.

Limitations

This study has several limitations that should be acknowledged. First, the cross-sectional design precludes any inference of causality, and the observed associations should therefore be interpreted as correlational rather than causal. Second, physical activity and perceived barriers were assessed using self-reported measures, which are subject to recall bias and may also be influenced by social desirability bias, potentially leading to over- or under-reporting of behaviours. Third, the study was conducted within a single institution, which may limit the generalisability of the findings to other universities or student populations with different academic structures, cultural contexts, or resource availability.

In addition, the classification of participants as physically active or inactive was based on self-reported activity levels aligned with guideline thresholds, which may introduce measurement limitations and potential misclassification. While widely used, such categorisation may not fully capture the complexity, variability, and context of physical activity behaviours. Finally, although the study adjusted for key demographic variables, there remains the possibility of residual confounding from unmeasured factors such as psychological stress, academic workload intensity, or environmental influences. Taken together, these limitations highlight the need for cautious interpretation of the findings and underscore the importance of future longitudinal and multi-centre studies using objective measures of physical activity among pharmacy and other healthcare students to provide more robust evidence.

Authors’ contributions

FS and MB conceived and designed the study. LLT and FHS contributed to instrument validation and data acquisition. BI and IUR provided methodological support and assisted with statistical analysis. BG contributed to data interpretation and critically revised the manuscript for important intellectual content. FS and MB supervised the study and contributed to manuscript preparation and finalization. All authors contributed to drafting or revising the manuscript, read and approved the final manuscript, and agreed to be accountable for all aspects of the work.

Funding

This study was conducted without any financial support from public, commercial, or not-for-profit funding agencies.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

All participants were informed about the purpose and procedures of the study prior to their involvement. Participation was entirely voluntary, and participants had the right to withdraw from the study at any time without penalty. Written informed consent for both participation and publication were obtained from all participants included in this study. Participants were assured that their responses would remain confidential and that all data would be anonymized and used solely for research purposes.

This study was conducted in accordance with the Declaration of Helsinki. The study protocol was reviewed and approved by the Universiti Malaya Research Ethics Committee, under approval number UM.TNC(P&I)/UMREC_4914, confirming that all study procedures met the required ethical standards for research involving human participants.

Competing interests

The authors declare no competing interests.