Relationship Between Social Support, Quality of Life and Resilience Among Recovering Persons in Malaysia’s Private Rehabilitation Centres

Relationship Between Social Support, Quality of Life and Resilience Among Recovering Persons in Malaysia’s Private Rehabilitation Centres

Uswah Hasanah Ahmad Shakir, Mohamad Salleh Abdul Ghani

Department of Human Development and Family Studies, Faculty of Human Ecology, University Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia.

^*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90700070

Received: 24 June 2025; Accepted: 27 June 2025; Published: 30 July 2025

ABSTRACT

This study investigates the influence of social support and quality of life on resilience among individuals undergoing treatment at four private rehabilitation centres in Selangor. A total of 84 participants were assessed using the Multidimensional Scale of Perceived Social Support (MSPSS), the World Health Organisation Quality of Life-BREF (WHOQOL-BREF), and the Adult Resilience Measure-Revised (ARM-R). Employing a quantitative correlational design, the study explored the relationships among the variables studied. The results indicated no significant difference in resilience between individuals from urban and rural backgrounds, nor significant associations with age or duration of recovery. However, social support showed a moderate positive correlation with resilience, and all domains of quality of life were significantly associated with resilience. Notably, psychological and environmental quality of life emerged as significant predictors, with the latter being the strongest. These findings highlight the crucial role of both social and environmental factors in supporting resilience during recovery. The study offers valuable insights for practitioners and rehabilitation centres, suggesting the need to enhance psychological and environmental aspects of care to better support individuals in treatment. Future research should consider broader demographic representation and varied settings to further understand the dynamics of resilience in recovery contexts.

Keywords: Resilience, Social Support, Quality of Life, rehabilitation, substance use treatment, substance abuse

Background

Recovering individuals in drug addiction are those actively working to overcome substance dependence and rebuild meaningful lives. Recovery is a complex, lifelong process involving continuous physical, psychological, and social adjustments (Laudet, 2011). In Malaysia, recent surveillance of 9,606 new substance-use patients across government hospitals (2018-2021) revealed a steady rise in admissions, with 64% residing in urban areas and a large proportion unemployed- underscoring the growing demand for effective, targeted recovery support (Muhammad et al., 2024).

Resilience has emerged as a pivotal protective mechanism in addiction recovery. A recent Malaysian study found that among low-income spouses of drug-dependent individuals, higher resilience helped buffer the mental health impact of negative life events, showing that resilience is not just a personal trait but also a socially shaped capacity (Nurul et al., 2024). Qualitative findings from a self-help group in Kuantan further highlighted that individuals in early recovery often “borrow” resilience from peer leaders until they can internalize coping mechanisms on their own (Abu Hassan Shaari & Waller, 2022). These findings affirm global perspectives that resilience is dynamic and responsive to environmental inputs and supportive structures (American Psychological Association, 2016).

Social support also plays a critical role in sustaining abstinence and psychological stability. A Malaysian cross-sectional study of methadone-maintenance patients demonstrated that every unit increase in perceived social support halved the likelihood of major depression, underscoring its protective value in local treatment settings (Wahab et al., 2021). International work on sober active communities further clarifies that mentors and peers in recovery provide the most consistent day-to-day support, especially for individuals with longer engagement in recovery networks (Patterson et al., 2025).

Quality of life (QoL), once overlooked in addiction treatment, is now recognised as a central indicator of recovery. Among methadone-maintained patients in Malaysian hospitals, higher levels of positive emotions were significantly associated with better QoL across physical, psychological and social domains (Ganesh et al., 2024). These results suggest that psychosocial strategies that promote meaning, hope and emotional resilience may enhance overall life satisfaction and reduce likelihood of relapse.

Despite these important insights, there is a noticeable research gap in Malaysia: most existing studies examine resilience, QoL, or social support individually and often within government clinics or compulsory drug detention settings. Very little is known about how these psychosocial factors interact simultaneously in private rehabilitation centres, which are becoming more prominent in urban Malaysia but may operate under different therapeutic models and resource constraints. Thus, this study aims to address the gap by examining the relationships between resilience, social support and quality of life among individuals undergoing treatment at four private rehabilitation centres in Selangor. Understanding how these variables intersect in this localized context is essential for informing more responsive, person-centred interventions in Malaysia’s evolving rehabilitation landscape.

LITERATURE REVIEW

Recent Malaysian and regional studies and underscore resilience as both a personal asset and a socially cultivated capacity. Mohamad Yasin, Shafie, and Baharuddin (2024) examined spirituality and resilience among individuals in Malaysian drug rehabilitation, finding strong positive correlations– suggesting spiritual engagement may bolster adaptive coping and reduce relapse risk. Their correlational study in private Malaysian centres (n=104) emphasizes resilience’s malleability and its dependence on environmental and cultural supports. Similarly, Yamashita, Yoshioka and Yajima (2021), in a Japanese sample demonstrated that higher resilience predicted lower relapse risk via improved self-regulation. This underscores resilience as a dynamic, measurable construct with direct implications for intervention design (Yamashita, Yoshioka & Yajima, 2021).

The protective role of social support has also received fresh empirical backing in Southeast Asian settings.  Notably, qualitative insights from a self-help group in Pahang revealed that ongoing engagement fosters empowerment and peer accountability– key to sustained recovery (Abu Hassan Shaari & Waler, 2022). Furthermore, Fauziah Ibrahim et al. (2022) reported a modest but meaningful inverse relationship between perceived social support and high-risk relapse among 407 Malaysian drug offenders (r = -.258, p < .01), emphasizing the importance of community and familial ties in relapse prevention.

Contemporary studies suggest these factors do not operate in isolation but synergistically for instance topping strategies such as spiritual practices and peer connection simultaneously promote resilience and perceived social support (Mohamad Yasin et al., 2024; Abu Hassan Shaari & Waller, 2022). Meanwhile, resilience may mediate the relationship between social support and relapse; individuals with stronger networks report greater adaptive coping and lower relapse risk (Ibrahim et al. 2022; Yamashita et al., 2021). However, regional research has not fully tested these pathways within private Malaysian rehabilitation settings.

While global literature emphasizes the interplay of resilience, support, and quality of life, recent Malaysian research remains fragmented– treating each construct separately and typically focusing on public or compulsory care. There is a lack of integrative studies examining how these factors interact to shape recovery trajectories, especially in private centres where after-care services and therapeutic models differ. This presents both and empirical gap and an opportunity: a holistic study in Selangor’s private rehabilitation environment can clarify these interrelations and guide targeted interventions.

RESEARCH METHOD

Study design 

The investigation employed a cross-sectional correlational survey because it allows several psychosocial variables to be measured simultaneously in a time- and cost- efficient manner– an approach widely used in Malaysian addiction studies to generate baseline evidence before investing in longitudinal follow-up (Hasani et al., 2023). Cross-sectional data are also practical in private rehabilitation settings where clients’ length of stay is short and unpredictable. Nevertheless, we acknowledge inherent limitations:  temporal sequencing cannot be established, self- report measures may inflate associations through common-method variance, and current findings may not reflect changes at other recovery stages.

Because no public roaster exists for clients in private drug-rehab centres, purposive (criterion-based) sampling was adopted. This technique intentionally selects “information-rich” cases that meet clear inclusion criteria (≥ 18 years, ≥ 30 days post-detox), thereby matching the sample to the study’s aims and improving methodological rigour (Campbell et al. 2020). Such sampling is recommended when working with hard-to-reach or vulnerable groups whose privacy is protected by ethics regulations. Recognised biases include selection effects (more motivated or stable clients may volunteer) and limited generalizability. To minimise these risks, recruitment spanned four centres with different fee structures, demographic quotas (age, gender, primary substance) were tracked, and comparisons with national treatment statistics will be reported.

Population and sample 

The study employed a purposive sampling to recruit participants undergoing rehabilitation for at least one month, aged 18 to 70 years, without diagnosed mental disorders, and voluntarily refraining from substance use. Exclusion criteria included less than one month in rehabilitation, severe mental health conditions, and involuntary abstinence. Sample size was determined using G*Power 3.1 for a bivariate normal model correlation test with an a priori analysis. Parameters included a two-tailed test, effect size (correlation) of 0.3, alpha of 0.05, and power of 0.80, resulting in a required sample size of 84 participants to detect a true correlation while controlling Type 1 error (Faul et al., 2009). This approach ensures sufficient statistical power for the study’s objectives, though purposive sampling of social support, quality of life and resilience among individuals in recovery (Franz et al., 2009)

Instrument

Social support, quality of life and resilience were measured using validated instruments with strong psychometric properties and demonstrated cultural appropriateness for the Malaysian context. Social support was assessed using the 12-item Multidimensional Scale of Perceived Social Support (MSPSS), which evaluates perceived support from family, friends and significant others on a 7-point Likert scale. The Malay version of MSPSS has been validated among Malaysian populations, showing excellent internal consistency (Cronbach’s α = 0.93) and confirming its cultural suitability (Song et al., 2023).

Quality of life was measured using the WHOQOL-BREF, a 26-item questionnaire developed by the World Health Organization, which assesses physical health, psychological well-being, social relationships and environmental domains using a 5-point Likert scale. The Malay version of the WHOQOL-BREF has been tested among various Malaysian adult populations and demonstrated good reliability and construct validity (Rusyda et al., 2022), indicating its relevance and appropriateness in assessing QoL in the local context.

Resilience was evaluated using 28-item Adult Resilience Measure-Revised (ARM-R), which assesses personal strengths, social support and environmental factors using a 5-point Likert scale. Although the ARM-R has not been widely validated in Malaysia, its structure and domains align with local resilience research, and item wording was carefully reviewed to ensure cultural relevance. Minor adjustments were made during pre-testing to improve comprehension and ensure contextual fit. The scale showed excellent internal consistency in local pilot use (Cronbach’s α > 0.90), supporting its application in Malaysian rehabilitation settings.

Data analysis

Statistical analysis was conducted using IBS SPSS Statistics version 29. Descriptive statistics (frequencies, percentages, means and standard deviations) were used to summarise demographic characteristics and the main study variables.

To examine group differences in resilience between participants from urban and rural areas, independent samples t-tests were conducted. In addition to p-values, Cohen’s d effect sizes were calculated to determine the magnitude of group differences, and 95% confidence intervals (CIs) were reported to estimate the precision of these effects.

Pearson correlation coefficients (r) were computed to assess the strength and direction of relationships among resilience, social support and quality of life domains. Interpretation of correlation strength standard conventions (e.g., small: .10 -.29, moderate: .30 -.49, large: ≥ .50). Confidence intervals were included to enhance interpretative transparency.

To identify the unique contributions of social support and quality of life domains in prediction resilience, multiple linear regression analysis was employed. Standardised beta coefficients (β), 95% confidence intervals, and adjusted R² values were reported. Effect sizes (Cohen’s f²) were calculated to evaluate the practical significance of each model, with thresholds of .02 (small), .15 (medium), and .35 (large). Assumptions of linearity, multicollinearity, homoscedasticity and normality were tested to ensure the validity of regression results.

RESULTS

Demographic Background

The study’s respondents ranged in age from 19 to 69 years, with a mean age of 36.82 (SD = 11.13), predominantly falling within Middle Adulthood (30-64 years, 67.9%), followed by Early Adulthood (19-29 years, 31.0%) and a small proportion in Old Age (1.2%). Employment status showed that more than half were unemployed (54.8%), with others being employed (28.6%), self-employed (11.9%), or retired (4.8%). The average monthly salary was RM 1,358.81 (SD = 2,125.79), with the majority (95.2%) classified in the lower-income B40 group. Most respondents were single (67.9%), while 14.3% were married and 17.9% were widows. Regarding education, over half (52.4%) had completed Sijil Pelajaran Malaysia (SPM), with smaller percentages holding diplomas (11.9%), lower secondary qualifications (11.9%), or higher education degrees (4.8% bachelor’s). The recovery period varied widely (mean = 12.60 months, SD = 13.96), with most in medium-term recovery (4-12 months, 53.6%), followed by long-term (13-24 months, 22.6%), short-term (1-3 months, 16.7%), and extended recovery (7.1%). Ethnically, the majority were Malay (67.9%), followed by Chinese (31.0%) and Indian (1.2%). Most respondents resided in urban areas (63.1%) compared to rural settings (36.9%).

Table 4.1: Description of Recovering Persons’ Demographic background

Age (years) 

Early Adulthood (19-29)

Middle Age (30-64)

Old Age (65 onward)

Social Support 

Based on Table 4.2, the respondents perceived social support scores ranged from 2.17 to 7.00, with a mean score of 4.935 and a standard deviation of 1.142. The majority of respondents, 47.6% (n=40), fall under the Moderate Support category (3.0-5.0). Meanwhile, 45.2% (n=38) of the respondents experience High Support (5.1 -7.0), and a small proportion, 7.1 % (n=6), report Low Support (1.0-2.9). This distribution indicates that most respondents perceive a moderate to high level of social support, with only a small percentage experiencing low support.

Table 4.2: Level of Social Support (n=84)

Note: Sd = Standard Deviation, Min = Minimum, Max = Maximum

Quality of Life

Based on the data, respondents’ quality of life (QoL) scores across four domains show varied perceptions. For physical health, scores ranged from 25.00 to 100.00 with a mean of 66.75 (SD = 16.82), evenly split between low (50.0%, n=42) and high (50.0%, n=42) QoL. Psychological QoL scores ranged from 25.00 to 87.00, with a mean of 62.30 (SD = 15.17); 42.9% (n=36) reported low psychological QoL, while 57.1% (n=48) reported high. In social relationships, scores ranged from 0.00 to 100.00 with a mean of 59.13 (SD = 22.58), where the majority (56.0%, n=47) experienced low QoL and 44.0% (n=37) high QoL. Environmental QoL scores ranged from 25.00 to 100.00, with a mean of 62.83 (SD = 18.47); 54.8% (n=46) reported low environmental QoL and 45.2% (n=38) high. Overall, while half or more respondents perceive moderate to high QoL in physical and psychological domains, more than half report low QoL in social relationships and environmental conditions, highlighting areas needing attention.

Table 4.3: Level of Quality of Life (n=84)

Note: Sd = Standard Deviation, Min = Minimum, Max = Maximum

Resilience 

Based on Table 4.7, the respondents’ resilience scores range from 30.00 to 85.00, with a mean score of 64.5595 and a standard deviation of 13.5605. The majority of respondents, 56.0% (n=47), fall into the high resilience category (scores above 65.5595), while 44.0% (n=37) fall into the low resilience category (scores below 64.5595). This distribution suggests that more than half of the respondents demonstrate a high level of resilience, indicating better coping

Table 4.7: Level of Resilience (n=84)

Note: Sd = Standard Deviation, Min = Minimum, Max = Maximum

DISCUSSION

Our results show that stronger perceived social support and higher scores on psychological and environmental quality-of-life (QoL) domains are associated with greater resilience among clients in private Malaysian rehabilitation centres. From the lens of the broaden-and-build theory of positive emotions, environments that cultivate supportive ties and a sense of safety expand client’s thought-action repertoires, enabling them to accumulate coping resources that fortify resilience over time (Roth et al., 2024). The environmental QoL domain emerged as the strongest predictor, echoing evidence that structural factors- such as safe housing, meaningful activity options and recovery-friendly community norms- are pivotal in sustaining abstinence and motivation (Razali et al., 2023).

These findings add Malaysian specificity to recent Southeast-Asian work. A latent-class survey of 12,000 adults showed that polysubstance users cluster in socio-economically disadvantaged settings, underscoring the need to tackle environmental risk drivers in tandem with individual factors (Hasani et al., 2023). Likewise, a national Delphi panel of rehabilitation experts ranked “supportive community context” and “family engagement” as the top relapse-prevention levers (Mustapha et al., 2023), while ex-clients in Kedah identified self-development efforts that were scaffolded by peer mentors and spiritual programmes as key to their recovery progress (Noordin et al., 2023). Our finding that psychological QoL predicts resilience dovetails with a multi-site trial of the Community Reinforcement Approach, where gains in positive affect translated into significant QoL improvements and lower craving scores at three-month follow-up (Khalid et al., 2024). Collectively, the pattern supports resource-oriented frameworks: individuals invest personal and social resources to offset losses inherent in recovery, and high-resource contexts generate adaptive “gain spirals” that build resilience.

Limitation and Suggestions

Research on the relationship between social support, quality of life, and resilience among recovering individuals in private rehabilitation centres in Hulu Langat, Selangor, faces several limitations. Key challenges include limited generalizability due to geographic and contextual differences, reliance on self-reported data prone to social desirability bias, and insufficient data on peer support services, which remain underdeveloped in Malaysia (Home Team Journal, 2020; Xie et al., 2020; Molinaro et al., 2018; Sulaiman et al., 2024). These factors may affect the accuracy and applicability of findings.

To address these issues, future research should expand the geographic scope beyond Hulu Langat to include diverse urban and rural populations across Malaysia, and increase sample size and diversity to better capture variations in resilience. Additionally, studies should explore other potential predictors of resilience such as personality traits, coping strategies, spirituality, and economic stability. Employing longitudinal designs will allow for tracking resilience changes over time and understanding the dynamic impact of social support and quality of life throughout recovery. Finally, developing and evaluating resilience-building interventions in collaboration with rehabilitation centres and policymakers is essential to improve recovery outcomes and support.

CONCLUSION

The findings of this study provide valuable insights into the role of social support and quality of life in fostering resilience among individuals recovering from drug addiction. Understanding these relationships can help recovering individuals strengthen their support networks and enhance their overall well-being, contributing to a more effective recovery process. Rehabilitation centers can implement structured interventions to improve social support systems and quality of life, ultimately promoting long-term resilience and reducing the risk of relapse.

From a policy perspective, these findings have emphasised the need for stronger governmental support and intervention programs to aid individuals in recovery. The government agencies such as the Ministry of Health (MoH), the Ministry of Home Affairs (MOHA), and the Royal Malaysia Police (PDRM) play crucial roles in preventing drug abuse, supporting rehabilitation efforts, and implementing policies to reduce relapse rates.

These agencies can enhance their efforts by expanding mental health services, increasing access to rehabilitation programs and promoting social integration initiatives for recovering individuals. Furthermore, social workers, rehabilitation officers and drug enforcement agencies can use these findings to refine recovery programs by integrating peer support groups, psychological counselling, vocational training and community integration efforts. Strengthening partnerships between government agencies, NGOs, and rehabilitation centres can create a more sustainable recovery framework, ensuring that individuals overcoming substance addiction receive comprehensive and continuous support throughout their journey to resilience and long-term recovery.

ACKNOWLEDGEMENTS

The author wishes to extend sincere appreciation to the clients and staff of Rumah Sahabat, Baitul Ridwan Rehab Centre, Rumah Victory, and Peace Charis Home for their invaluable cooperation and participation in this study. Their contributions were essential to the successful completion of this research.

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