The Role of Social Support Systems in Enhancing Mental Health Resilience among Young Adults

The Role of Social Support Systems in Enhancing Mental Health Resilience among Young Adults

Siti Sarah Omar¹, Lai Jia Cheng², Nur Nasriah Mohd Nazri³, Nabilah Mohd Razi⁴, Nur Syazwina Seth⁵, Ainaa’ Elisya Mohd Zulkepli⁶, Ainnurbasyirah Kamaruddin⁷ and Nomahaza Mahadi⁸

^{1,2,3,4,5,6,7}Faculty of Technology Management and Business, University Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, MALAYSIA

⁸Azman Hashim International Business School, Universiti Teknologi Malaysia, Kuala Lumpur MALAYSIA

DOI: https://dx.doi.org/10.47772/IJRISS.2025.907000267

Received: 13 June 2025; Accepted: 09 July 2025; Published: 12 August 2025

ABSTRACT

Most young adults face severe stress and other mental health challenges in their transition to adulthood; hence, the need for social support to nurture resilience. This study investigates the role of social support systems in promoting mental health resilience among young adults, focusing on the identification of effective types of support- emotional, informational, and tangible-and influential family, friends, and mentors. A quantitative approach was used, and the questionnaire was administered using Google Forms to 100 students of the University Tun Hussein Onn Malaysia. This study collects and analyzes data through a questionnaire using SPSS Statistics version 27 software. The demographic profile, social support, perceived stress, physical health status, and emotional states were assessed in the questionnaire. The Spearman’s rho correlation test therefore indicates no significant relationship between social support and perceived stress with mental health resilience. However, physical health in this case showed a fair negative correlation with mental health status, hence a need to keep the physical health going. These results thus point out that determinants of mental health are multi-faceted and need further, more extensive investigation into other influencing elements. This research is important for developing focused interventions and strengthening resilience strategies for improving mental health in young adults.

Keywords: social support, perceived stress, physical health status, mental health.

INTRODUCTION

The topic of mental health is very important for the 18 to 30 age group. This is because this age group is often in the process of transition in their lives, such as in academic, professional, and personal areas. Therefore, this period is thickly sown with thorns, which requires social support. However, some people can effectively deal with these challenges through the support of family, friends, and mentors, but others struggle. Without social support, young adults may experience psychological distress due to the immense pressures they face. Therefore, social support is crucial for the mental health of adolescents. Research by Munyan (2021) defines social support as a network of people who are typically known and interact with an individual or organization. In addition, social support is defined as the function and quality of social relationships that one receives from other people such as help and ort (Schwarzer, Knoll, & Rieckmann, 2004). By understanding the meaning of social support, we can understand its importance. With social support, adolescents can improve their resilience to stress. Resilience is one of the constructs more often linked to social support and satisfaction with life. One of the definitions of resilience is “the ability to adapt to stress and adversity” (Liu, Reed & Girard, 2017). This highlights the need to understand the mechanisms that promote resilience. This study focuses on the role of social support systems in enhancing mental health resilience in young people, an increasingly important theme in contemporary mental health research.

Research Background

People have long recognized social support as a critical factor in enhancing resilience, especially among young adults. Different forms of social support, such as emotional, informational, tangible, and companionship, play a significant role in helping young adults when facing challenges. For instance, consistent family narratives, positive parenting practices, cohesion, flexibility, open communication, and problem-solving abilities contribute to high levels of family resilience, making it an effective resource for promoting individual mental health.

Healthy social determinants of health (SDOH)—the environmental conditions in which people are born, grow, live, work, and age—are foundational to mental well-being. During adolescence, a critical developmental stage when the brain undergoes significant maturation, individuals are particularly vulnerable to mental health challenges such as anxiety and depression. Therefore, adolescents must build resilience to be able to cope with stress effectively. As social relationships are essential to human development, reproduction, and survival, identifying effective social support is the first step in building resilience in young adults.

Despite the recognized benefits of social support, unresolved questions remain. What types of social support are most beneficial for mental health resilience? Can both online and offline support systems provide effective assistance? Research indicates that interpersonal relationships can shield individuals from anxiety and depression, but the mechanisms through which social and community factors shape thought processes and emotions, especially during crises, require further exploration.

This study aims to address these gaps by exploring the interactions between social support systems and mental health resilience in young people. By focusing on these adolescents, this study can provide actionable insights into how social support can enhance young adults’ resilience to combat stress. This will not only contribute to the academic discussion but also bring practical solutions to a prevalent societal challenge.

Problem Statement

Young adults often face intense stress and mental health challenges as they transition into adulthood, and many struggle to find the support they need to cope. While social support is known to help build resilience, more research is needed to understand how it works and what types of support are most helpful for young people.

Moreover, the existing research underscores the protective role of family and social support in buffering mental health challenges. For example, Wong et al. (2021) found that satisfaction with family relationships is strongly associated with reduced negative affect and improved mental health outcomes during crises, especially for individuals with low resilience. Similarly, Liu et al. (2024) emphasized that social determinants of health, particularly the quality of social and community relationships, significantly influence mental health outcomes such as anxiety and depression. However, critical gaps remain in understanding the specific mechanisms by which different types of social support, such as emotional, informational, tangible, and companionship, contribute to resilience among young adults.

Addressing these gaps is significant, as young adulthood is a formative stage where resilience-building has long-term implications for well-being. Research has enabled an understanding of the interaction between various forms of social support and mental health resilience. This study aims to provide practical insights for improving mental health resilience in youth. These findings can not only enhance theoretical understanding but also provide a reference for practical measures to cultivate mental health resilience in a rapidly evolving social environment.

Research Aims and Significance

Through this research, we aim to explore critical questions and objectives related to the interplay between social support systems and mental health resilience. Specifically, we seek to explore the relationship between social support, perceived stress, physical health status, with the mental health of young adults.

This study addresses a critical area of mental health by exploring how social support systems contribute to mental health resilience among young adults, a demographic undergoing significant personal and societal transitions. Young adulthood is a pivotal stage for developing mature personalities and forming the foundation of a nation’s future workforce. Researching this topic will enhance our understanding of how to build mental health resilience to cope with stress effectively. Besides, it provides deeper insights into how social support works to foster resilience, moving beyond the general assumption that social support is beneficial to understanding the mechanisms of its effectiveness. This research will identify the most effective types of social support for young adults, contributing to the theoretical understanding of resilience-building mechanisms and filling critical gaps in existing literature. In practical practice, schools and educational organizations can utilize findings to implement targeted interventions and improve decision-making and management strategies. Social impact extends to individuals, communities, and broader society by offering a clearer understanding of which types of social support are most effective. This avoids ineffective support practices that may add unnecessary burdens and stress. In summary, the significance of this study lies in its potential to advance academic knowledge, inform practical strategies, and create meaningful societal impact in the domain of mental health resilience for young adults.

LITERATURE REVIEW

The present literature review focuses on the social support-stress relationship, perceived stress, physical health, and mental health.  Here we will discuss established definitions for all the constructs of interest and a brief review of the most used measures for these constructs and, especially, the existing literature on their interdependence that will help to formulate hypotheses for the proposed study.

Mental Health

Mental health represents a complex system that deeply affects personal daily experiences through a combination of emotional and psychological elements and social functioning. According to experts, we need a healthy state of mental health for it enables us to succeed in our relationships as well as our work life and community participation. According to the World Health Organization (WHO), Mental health describes a condition where people both fulfil and accomplish activities both at home and work.

Mental health is a comprehensive determinant of thought, feeling, and behaviour that influences every person’s day-to-day life.  Yet, integrating Jennifer’s (2023) proposal into the notion of mental health would require considering the bipolar range from optimal functioning to severe illness. According to Jennifer, Mental health is “a dynamic process by which every human being attains optimal physical, cognitive, and psychological human potential, manages life’s inherent strains, fulfils one’s primary and secondary tasks in society effectively and constructively.” This definition is wider and includes resilience and coping climate, and social assets besides the climate devoid of mental disorder.  Mental Health is most often measured by operationalization through multi-dimensional assessment, the most common of which includes the self-completed questionnaires designed to elicit information on symptoms, functioning, and quality of life, some of which are the SF-36, the Well-being Index.  An appropriate measure depends on the research question as well as the population under consideration.

Social Support

Social support functions as a fundamental theory that interprets relationship-based well-being effects throughout stressful situations. Multiple theories examine social support as a collection of diverse forms that perform unique roles in human relationships. Emotional support gives comfort and empathy, causing people to appreciate their worth. Instrumental support helps with everyday activities. Informational support provides direction through challenges. Appraisal support helps people evaluate themselves by giving feedback. Support of different kinds aids the development of coping skills and resilience systems, which jointly produce significant mental health benefits.

Specifically, social support, which has both an instrumental and an expressive aspect proposed by Lin (1986) is gradually quantitatively analysed. Hence, today the quality and type of support are distinguished, shifting focus from the number of social contacts (Cohen & Wills, 1985). Objective data on the social structure of the network is obtained by using SNA and perceived social support by MSPSS (Zimet et al., 1988). These enable assessment of the relations of such support elements to mental health, and potential mediators exist, such as aspects of the supported person’s viewpoint and coping mechanisms. What is aimed at here is finding out which aspects of social support are most correlated with positive mental health.

Perceived Stress

People assess their daily stress subjectively through perceived stress even though it stems from various aspects of uncertainty and diminished personal influence over their environment. Perceived stress exists in two types, which is acute stress forms during sudden short-term disturbances like deadlines or arguments, and chronic stress lasts over prolonged periods from continuous matters like financial trouble or health difficulties. During economic hardships, job security uncertainty produces anxiety that results in headaches and fatigue. Knowledge about perceived stress matters considerably because it directly affects both physical and mental wellbeing, thus leading to depression and anxiety diagnosis.

According to Konstantopoulou et al. (2020) and Puerta et al. (2022), perceived stress is not a fundamental response to environmental pressures but a psychological evaluation of events and how the individual can manage them. This cognitive appraisal process is integral to the stress process and affects both physiologic and psychologic end points. The Perceived Stress Scale (PSS) is one of the most universal questionnaires, which reflects the extent to which subjects’ lives are regarded as unpredictable, uncontrollable, and overbearing. But it is noteworthy self- reported measures depend on the subject’s observations that can be distorted with various biases and factors. In future research, measures of physiological stress (for instance, cortisol) could be included to have a better picture of stress.

Physical Health Status

Physical health represents the state of the healthiest body and basic movement performance abilities. The classification divides medical conditions into sudden onset acute forms like broken bones and ongoing chronic disorders. Research shows that physical health strengthens mental health since exercise generates endorphins and simultaneously lowers stress-related disease risks. Those with poor mental health develop increased susceptibility to various physical health disorders, including heart disease. People who participate in regular physical activities discover two useful advantages: They gain better control of their stress levels, and their anxiety and experience enhanced social bonds. People who exercise routinely often notice a better mood combined with less anxiety, which leads to balanced mental and physical harmony.

Analyzing the nature of the connection between physical health and mental health, one must mention that it is reciprocal. According to Maraccini and Brier (2017), social connectedness is also related to self-mental and physical health. But this connection is not only from the social viewpoint. Physical diseases (heart disease, diabetes, etc.) are known to affect mental health and exacerbate depression and anxiety. On the other hand, the overall well-being will be unhealthy since Mental health can cause the manifestation of unhealthy behavior such as smoking and a lack of exercise, which is not good for the body. Physical health status can be defined and operationalized in several ways: biological (like blood pressure or body mass index), self-reported (like self-reported health). It should also demonstrate an ability to give a balanced result that considers a patient’s daily activities, eating habits, exercise, and even amount of sleep.

Young Adults

According to age classification, 18 to 30 marks the young adult period, after which follows adolescence through directed movements of both social and personal growth. At this point, essential life transitions occur as people finish their academic pursuits so they can join the job market. Young adults commonly finish their college education to begin their first professional position, which pushes them toward developing financial autonomy while building their career plans. The unique challenges and opportunities that engage this demographic strongly affect their mental and physical well-being, stressing the need for community support networks during this defining life period.

Singapore’s demanding work culture affects health behaviour in young adults, according to Leu et al. (2023), who show that excessive work hours drive the combination of being physically inactive and choosing unhealthy foods. The findings underline why health promotion efforts must target specific interventions that will combat the environmental and social factors shaping young adults’ wellness. These research articles indicate how social media impacts and how work demands influence young adults’ health by demanding specific integrated health promotion systems that align with their specialized wellbeing requirements.

Conceptual Framework & Hypothesis

Building on the above, this study proposes a conceptual framework and three hypotheses to be explored as illustrated below.

Figure 1: Conceptual Framework

H1: There is positive relationship between social support and mental health among young adults.

H2: There is a positive relationship between perceived stress and mental health among young adults.

H3: There is a positive relationship between physical health status and mental health among young adults.

METHODOLOGY

Research Design

In this study, the conceptual framework theory should be supported through a quantitative approach by the researcher. The researcher employed clustered sampling to collect data from the target demographic, specifically UTHM students aged 18 to 30 years old. The approach used in this research is the survey method, wherein data collection was obtained through an online Google Form assessing social support, perceived stress, and physical health status among UTHM students to determine the relationship between the dependent and independent variables.

Sources of Data

Primary data collection is done through the survey questionnaire method on a targeted sample of 18 to 30-year-old respondents who are students of UTHM. In addition, the researcher analyzes sufficient responses by using IBM SPSS Statistics 25. The researcher also uses a secondary data source; this means data collected and reported by other researchers are used to supplement the investigation. These would include articles, journals, books, theses, and public statistics.

Data Collection

Google Forms were used to gather information from UTHM students focusing on the perception towards the topic. The questionnaire developed for the study comprised a formative questionnaire divided into different sections, which are sections A, B, and C However, Section B and Section C consisted of entirely ordinal and Likert scales, respectively. These questions sought to capture the frequencies, perceptions, or agreement/disagreement of respondents on several statements about social support systems and mental health resilience. The form was made online and shared via WhatsApp and Telegram, likely to reach many people.

Construct Measurement

In general, such research data is gathered through online surveys or Google Forms to investigate the objective pointed out in this report. In addition to that, before the respondents are allowed to respond to the online surveys, the researchers give them a consent letter. The survey comprises three parts. Section A is a Demography part, including gender, age, faculty, and race. Section B delineates the independent variables, which are Social Support, Perceived Stress, and Physical Health Status. Social Support measures how much or what kind of support the students get from their close person, friends, family, teachers, neighbors, or community. Perceived Stress measures the respondents’ concerns, their academic responsibilities, and the environment that might affect them, such as their sleep quality. Physical Health Status refers to health conditions that the respondent perceives they have issues related to, such as sleep and exercise. Section C is the assessment of psychological stress and emotional states. In this section, questions concern problems like the inability to relax and experience positive emotions, trembling, and pessimistic attitudes, including worthlessness. Such questions will enable us to assess the respondents’ mental health and their ability to cope with various stresses and strains.

Data Analysis

We employed the help of the SPSS IBM Software to analyze the collected data. The analysis was initiated with data preprocessing, where the data was imported from Google Forms and formatted as required by the variables. Afterward, we conducted data cleaning to handle missing values and outliers, which might affect the credibility of the dataset. After analyzing the nature of the collected data through a normality test, the internal consistency of our Likert scale items was also confirmed with Cronbach’s alpha reliability test. Frequency analysis was used to generate quantitative descriptive details of the data. Lastly, we do the Spearman Correlation for our Non-normal data to examine the strength and direction of a monotonic relationship between two variables.

ANALYSIS AND FINDINGS

Data Collection Process and Survey Response

Prior to the data collection phase, the research instrument underwent refinement to enhance the clarity, structure, and relevance of the questions, format, and measurement scales. This process aimed to improve the instrument’s validity and was supported by preliminary analysis using IBM SPSS software. According to Krejcie and Morgan’s (1970) sampling table, the recommended sample size for a population of 365 students is 187. However, due to time and resource constraints, only 100 valid responses were obtained for analysis.

The data collection was conducted over a one-month period beginning in December 2024. Questionnaires were distributed electronically via WhatsApp and Telegram to selected UTHM students. Following data collection, a reliability analysis was conducted using IBM SPSS. The results showed that all constructs achieved Cronbach’s alpha values above 0.6, meeting the acceptable threshold as suggested by Hair et al. (2006). These findings confirmed the internal consistency of the instrument and supported both its face and content validity.

Data Cleaning

Data cleansing is vital when conducting multivariate analysis, as meticulous data editing and screening are crucial for ensuring the analysis’s effectiveness and significance. Therefore, particular attention was given to thoroughly and carefully managing outliers and missing data.

1) Detection of Missing Data

Missing data often poses a significant challenge in research. To effectively address this issue, researchers should focus on minimizing missing data through strategic study design (Papageorgiou et al., 2018). This study implemented rigorous measures during data collection to prevent missing values. By using Google Forms with mandatory questions, respondents were required to complete all sections before submitting their responses, resulting in a comprehensive dataset without missing values. This approach allowed for the collection of complete information from 100 UTHM students, including their demographics. The absence of missing data ensured a robust analysis of the relationships between social support, perceived stress, and physical health status about mental health, thereby enhancing the reliability of the study’s findings.

2) Outlier Analysis

Outliers, which are data points that significantly deviate from the rest of the dataset, can have a profound impact on statistical analyses, potentially skewing the results of hypothesis tests. Therefore, it is essential to accurately identify and properly handle any outliers in the dataset to ensure accurate results (Bhandari, 2023). In this study, no outliers were found.

Reliability Analysis

1) Pilot Study

Table 1: reliability for pilot study

Table 1 displays a pilot test conducted and a total of 36 completed questionnaires were obtained from the respondents. A pilot test was conducted to assess the validity and reliability of the questionnaires. This step is crucial as it enhances the reliability of the survey instruments, ensuring that the questions are clearly stated and that the response options are relevant, comprehensive, and mutually exclusive. According to the results of the pre-test, the survey consists of three independent variables: social support, perceived stress, and physical health status, with 5 questions for each. The dependent variable, mental health, comprises 21 questions. By combining all the items from social support, perceived stress, physical health, and mental health, the reliability test is shown in Table 1. The Cronbach’s Alpha for the variable was within in range of 0.702 to 0.968. All the variables surpass 0.6, indicating a high level of correlation among these variables.

2) Actual Study

Table 2: reliability for actual study

After the pilot study confirmed that the questionnaires were valid and reliable, the actual research was conducted. The results of the reliability test for the main study are presented in Table 2. Cronbach’s Alpha for social support is 0.702 which is acceptable, for perceived stress is 0.879 which is good, and for physical health status is 0.715 which is good and acceptable. However, for mental health is 0.968 which is excellent.

Descriptive Analysis for Demographic

Descriptive and frequency analysis aims to provide a concise summary of the data collected from the survey and to clarify the demographic profiles of the respondents in this study, including variables such as gender, age, race, and academic faculty.

Table 3: demographic information

According to Table 3, the majority of respondents were female, accounting for 60 individuals (60%), while the remaining 40 respondents (40%) were male. In terms of age distribution, the majority of respondents (72 individuals or 72%) were between 21 and 23 years old. This was followed by 18 respondents (18%) aged between 24 and 27 years, 8 respondents (8%) aged between 18 and 20 years, and 2 respondents (2%) aged between 28 and 30 years. Regarding ethnicity, 66 respondents (66%) identified as Malay, 27 respondents (27%) as Chinese, and 5 respondents (5%) as Indian. Additionally, 1 respondent (1%) was Bumiputera Sabah, and another 1 respondent (1%) identified as Japanese, categorized under “Others.”

As for faculty affiliation, 47 respondents (47%) were from the Faculty of Technology Management and Business (FPTP). This was followed by 13 respondents (13%) from the Faculty of Electrical and Electronic Engineering (FKEE), 11 respondents (11%) from the Faculty of Civil Engineering and Built Environment (FKAAB), 10 respondents (10%) from the Faculty of Mechanical and Manufacturing Engineering (FKMP), 7 respondents (7%) from the Faculty of Technical and Vocational Education (FPTV), 5 respondents (5%) from the Faculty of Computer Science and Information Technology (FSKTM), 4 respondents (4%) from the Faculty of Applied Sciences and Technology (FAST), and 3 respondents (3%) from the Faculty of Technology Engineering (FTK).

Descriptive Analysis for Independent Variables and Dependent Variable

Table 4: Descriptive analysis data

Table 5: Mean range level interpretation

Based on Table 7, the results indicate that the level for two variables is moderate (social support and mental health). Perceived stress and physical health status are high, with the dimension with the highest mean is physical health status (Mean = 3.8120, Standard Deviation = 0.67976), followed by perceived stress (Mean = 3.7660, Standard Deviation = 1.00385). Next is social support (Mean = 3.6580, Standard Deviation = 0.73046). Lastly, mental health has the lowest mean (Mean = 2.8171, Standard Deviation = 0.94027).

Normality Test

A normality test was performed to assess whether the dataset fits a non-normal distribution and to evaluate the likelihood that a random variable within the dataset follows such a distribution. Given that the sample size in this study exceeded 50, with a total dataset of 100, the Kolmogorov-Smirnov test was employed instead of the Shapiro-Wilk test. According to the data presented in Table 8, the results indicate that two variables are not normally distributed, while the others are. A value less than 0.05 indicates non-normality. To avoid bias in the data analysis, we assume our data is not normally distributed and will utilize non-parametric tests.

Table 6: Normality test

Table 6 above displays the significance values from the Shapiro-Wilk Test for each variable. Two variables, perceived stress and physical health status, are not normally distributed, as their values are less than 0.05. In contrast, social support and mental health are normally distributed. Therefore, Spearman’s rho was employed for the correlation analysis and non-parametric testing.

Correlation Analysis

Correlation analysis examines the relationship between independent variables and the dependent variable, assessing the strength of this association. Spearman’s rho was used in this study because the data did not follow a normal distribution.

Table 7: correlations between social support and mental health

The analysis reveals a correlation of -0.089 between social support and mental health, indicating no correlation between the two variables. However, the correlation analysis does show a significant negative relationship between social support and mental health. As a result, H1 is rejected.

Table 8: correlations between perceived stress and mental health

The analysis reveals a correlation of 0.028 between perceived stress and mental health, indicating has correlation between the two variables. However, the correlation analysis does show a significant positive relationship between perceived stress and mental health. As a result, H2 is rejected because of p value is more than 0.05.

Table 9: correlations between physical health and mental health

The analysis reveals a correlation of -0.242 between physical health status and mental health, indicating has correlation between the two variables. However, the correlation analysis does show a significant negative relationship between physical health status and mental health. As a result, H3 is accepted because of the p-value is less than 0.05 (0.015< 0.05).

Summary of Hypothesis Testing

Based on the three study objectives, three hypotheses were formulated for this investigation and examined in the research. Two of the proposed hypotheses were rejected. A summary of the hypothesis testing results is presented in Table 10.

Table 10: summary of hypothesis testing

These findings indicate that, within the context of this study, social support and perceived stress do not show a statistically significant relationship with mental health among young adults. In contrast, physical health status does have a significant positive relationship with mental health. Therefore, it can be concluded that while the survey was designed to explore factors influencing mental health, its results suggest that the most meaningful insights are related to physical health status. The rejection of H1 and H2 implies that broader generalizations about mental health should be approached with caution, and future research may benefit from focusing more narrowly on physical health or other specific variables supported by empirical evidence.

DISCUSSIONS AND CONCLUSION

“The Role of Social Support Systems in Enhancing Mental Health Resilience Among Young Adults,” the study’s main objective, is to investigate how social support, perceived stress, physical health, and mental health resilience interact. Strong support networks are necessary to promote mental health since young adults, especially college students, frequently deal with severe pressures. 100 UTHM students’ replies were analysed using a quantitative methodology, with a focus on factors like physical health, perceived stress, and social support.

Critical constructs identified in the literature review include the multifaceted nature of social support (emotional, informational, tangible, and companionship), which has been shown to profoundly improve coping strategies and resilience; perceived stress, which is a subjective indicator of people’s capacity to deal with life’s obstacles and affects both mental and physical health; and the reciprocal relationship between physical and mental well-being, which shows how regular physical activity not only lowers stress but also promotes mental harmony.

The study’s surprising findings, which indicated no significant correlation between mental health and perceived stress or social support, contradict accepted wisdom. A weak negative association was found between social support, which is frequently thought of as a protective factor against mental health issues (r = -0.089, p = 0.379). Cultural variations may be the cause of this, since Cohen & Wills (1985) point out that the efficiency of assistance is influenced by its quality rather than its quantity. Furthermore, as Xie et al. (2024) point out, those who are highly independent might depend less on outside networks. Support can sometimes even increase stress or strain, which lessens its beneficial effects.

In a similar vein, perceived stress did not show a significant correlation (r = 0.028, p = 0.785). The adaptive character of stress, which views mild stress as a motivation rather than a danger, may help to explain this. This is supported by research by Yıldırım & Tanrıverdi (2020), which demonstrates that stress can promote resilience when viewed in a positive light. Additionally, Huh et al. (2021) underline that individual differences in the cognitive appraisal of stress can reduce its negative effects on mental health.

However, there was a slight but significant negative correlation between physical health and mental health (r = -0.242, p = 0.015), which is consistent with Zhang et al. (2024) who emphasized the importance of physical activity in lowering stress and fostering mental health. Brummelhuis et al. (2022) pointed out that poor physical health can worsen mental health problems by limiting physical activity and increasing fatigue.

These results highlight the intricacy of factors influencing mental health, casting doubt on long-held beliefs and emphasizing the necessity for sophisticated strategies catered to certain groups and situations. They point out that elements like the importance of physical health and the perceived caliber of support might have a bigger impact than previously thought.

According to the study, social support and perceived stress did not show a significant connection with mental health outcomes, even though young people’s physical health showed a positive relationship with their mental health resilience. These findings challenge the commonly held belief that social support always protects mental health, suggesting that its effectiveness may differ depending on individual, contextual, and cultural factors. Furthermore, perceived stress appears to be more complex, with adaptive stress potentially helping some individuals develop greater resilience.

This study is important because it explores how social support networks contribute to improving the mental health resilience of young adults aged 18 to 30. It examines the importance of different types of support—such as from family, friends, or mentors—and identifies which types (emotional, informational, tangible, or companionship) are most helpful. The findings highlight that students are in a critical phase for building resilience, especially during academic, career, or personal life transitions. To investigate variables such as resilience, perceived social support, and mental health status, the study used a quantitative approach with self-administered questionnaires. This helped capture the dynamic between social support and resilience in relation to young adults’ mental health.

Future research should consider additional factors such as resilience, mediators, and cultural context when examining the relationship between social support and mental health. Including qualitative methods and expanding the sample to include more diverse groups can improve understanding of how young adults perceive and engage with support networks. Longitudinal studies would also be useful for uncovering causal links and long-term outcomes. Lastly, an interdisciplinary approach—blending insights from mental health, physical health, and social sciences—could help create more targeted interventions tailored to young adults’ needs, ultimately enhancing our understanding of resilience.

ACKNOWLEDGMENT

The authors wish to express their gratitude to the Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, for their valuable support.

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