Does Quality of Life Influence Pro-Environmental Intention? An Extension of Theory of Planned Behaviour

Abstract

In light of escalating global environmental deterioration, studies on pro-environmental intention and behaviour with the ultimate goal of identifying contributing factors to minimise environmental issues are common. Theory of Planned Behaviour (TPB) is widely used to study environmental intentions and behaviours. However, how quality of life (QoL) influences these intentions and interactions among TPB’s own variables within a single research framework has not been thoroughly explored. Therefore, this study extends TPB by incorporating the four dimensions of QoL, as measured by the Control, Autonomy, Self-Realisation, and Pleasure (CASP-19) scale, to understand pro-environmental intentions from Malaysian viewpoints. In this study, quantitative approach was applied, and the data were collected from Malaysians aged 18 and above (N = 182) in Klang Valley, Malaysia. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), a two-step approach was employed to assess the measurement and structural models. The findings confirmed Theory of Planned Behaviour (TPB) is a robust model for environmental studies showing that subjective norm and perceived behavioural control significantly influence attitudes toward pro-environmental behaviour, ultimately leading to pro-environmental intention. Interestingly, this study found no relationship between QoL dimensions and pro-environmental intention. Lastly, both theoretical and managerial implications were discussed, and research limitations and suggestions for future research directions were put forward.

1. Introduction

Globally, modern consumption patterns are putting a significant strain on sustainable development [1,2]. The environmental issues such as overconsumption of natural resources, widespread deforestation, and increasing carbon emissions are alarming as they lead to environmental degradation, which in turn harms the ecosystem and accelerates climate change [3]. To tackle the environmental and climate challenges, the United Nations established the Sustainable Development Goals and provides general guidance to raise awareness and encourage collective action towards greater sustainability [4]. Ultimately, shifting human behaviours towards more environmentally protective actions is crucial for achieving a sustainable future.

In Malaysia, rapid industrialisation has certainly boosted its economy, but has also led to significant environmental deterioration that demands immediate attention. These significant environmental consequences, including air and water pollution, soil degradation and contamination, deforestation and habitat loss, resource depletion, and massive waste generation threaten not only natural ecosystems but also human health and long-term economic sustainability. To counter this, individual consciousness and everyday environmentally friendly actions, often referred to as pro-environmental behaviour, can collectively help minimise these impacts. Given the alarming rate of environmental deterioration, it remains crucial for researchers across industries, government, and academia to continue studying the factors that influence pro-environmental behaviour. The reported findings are still inconclusive over the years.

The concept of QoL focuses on an individual’s overall well-being and life satisfaction, which enhance happiness and contentment. The World Health Organisation (WHO) defines QoL as “an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns.” Nguyen et al. [5] reveal that individuals who demonstrate strong happiness and life satisfaction are always concerned for the well-being of others and the environment, thus having a strong tendency to undertake pro-environmental behaviour. However, this crucial link largely remains underexplored, especially when integrating QoL dimensions into behavioural intention theories like the Theory of Planned Behaviour (TPB) within an environmental context.

In this regard, the CASP-19 scale was selected to operationalise QoL, as it captures four psychological dimensions—control, autonomy, self-realisation, and pleasure—that are theoretically relevant to individual motivation and may shape pro-environmental intention. According to Ajzen [6], the TPB model exhibits three key variables: attitude toward the behaviour, subjective norm, and perceived behavioural control. Despite its popularity, past studies report that the interactions among these three variables within the environmental domain are far from conclusive. For example, Tonder et al. [7] reveal that subjective norm explains pro-environmental attitudes and pro-environmental customer–citizenship behaviours. It further raises important considerations, such as whether an individual’s belief in their control over a behaviour influences his or her attitude towards it, subsequently impacting intention. Therefore, extending the TPB, this study aims to investigate the interactive influence of subjective norm and perceived behavioural control on attitudes and pro-environmental intentions alongside the impact of QoL dimensions on such intentions. It is important to note that unpacking this dynamic is critical for crafting effective interventions and policies, because fostering pro-environmental behaviour is not just about awareness; it is also about ensuring people have the foundational well-being and supportive environments that empower them to make sustainable choices.

2. Literature Review

2.1. Theory of Planned Behaviour and Pro-Environmental Behaviour

Kollmuss et al. [8] define pro-environmental behaviour as the behaviour that minimises the negative impact of one’s action on the environment. It is the type of human behaviour that consciously and altruistically protects the environment and improves sustainability [9]. It focuses on minimising the negative impact on the environment and minimising harm as much as possible, while ensuring preservation and sustainability of the environment. As there is an increase in the environmental issues attributable to human behaviours, the topic of pro-environmental behaviour has been greatly investigated by the researchers. It has been identified by past researchers that pro-environmental behaviour is influenced by distinctive factors, including environmental attitude [10], environmental commitments [11], environmental knowledge [12], and environmental education [13].

Theory of Planned Behaviour (TPB) has been widely applied to examine human behaviours in different contexts, such as pro-environmental behavioural intention [14], forest conservation [15], organic food [16], e-wallet system [17], eco-friendly home appliances [18], and use of public transport [19]. According to Ajzen [6], behaviour is determined by behavioural intention, which is affected by attitude, subjective norm, and perceived behavioural control.

2.2. Subjective Norm

Subjective norm is the perceived social pressure to determine whether or not to perform a particular behaviour [6]. In other words, it is the individual’s perception that people who are important to him, such as family and friends, think he should or should not perform a behaviour. Although past studies revealed that subjective norm has a positive and significant effect on intention, refs. [20,21] demonstrated that subjective norm did not significantly affect intention, especially when individuals’ lack of environmental awareness and social pressure from others does not motivate them to comply with those people’s views to perform a particular behaviour.

In addition, Arli et al. [22] suggested that subjective norm is conceptually independent of attitudes and has a direct relationship with behavioural intention. For instance, when an individual has social pressure to engage in a particular behaviour, regardless of his attitude towards the behaviour, will choose to perform the behaviour. In consideration of the empirical evidence, this study hypothesised that

H1: 

There is a positive relationship between subjective norm and attitude towards pro-environmental behaviours.

H2: 

There is a positive relationship between subjective norm and pro-environmental intention.

2.3. Perceived Behavioural Control

Perceived behavioural control (PBC) refers to how an individual perceives the difficulty of performing a particular behaviour [22]. Generally, an individual tends to perceive the behaviour as easy to perform when he has had good and positive experiences in performing the behaviour. When the individual thinks performing the behaviour is easy and under his control, he is likely to perform the particular behaviour. According to Ajzen [6], human behaviours generally depend on resources, such as time, money, and knowledge, which affect whether one performs a particular behaviour [6]. If one has the resources and a high degree of control over his behaviour, he tends to have high perceived behavioural control and is more likely to adopt pro-environmental behaviours.

Past studies suggested that perceived behavioural control is a strong factor to account for behavioural intention [21,22,23,24,25]. For example, Budovska et al. [26] confirmed that PBC, subjective norm, and attitude have positive and significant effects on the pro-environmental behaviour of hotel guests. Therefore, the following hypotheses were formed to test the relationship:

H3: 

There is a positive relationship between perceived behavioural control and attitude towards pro-environmental behaviours.

H4: 

There is a positive relationship between perceived behavioural control and pro-environmental intention.

2.4. Attitude

Attitude can be defined as the assessment of a specific behaviour, either a positive or negative assessment [27]. Attitude plays an important role in shaping individuals’ responses, social interactions, and behaviours. Existing studies have conducted significant explorations of the relationship between attitudes and intentions, as well as confirmed the significant relationship in different contexts, such as pro-environmental behaviours [25,26,28] and technology use [21]. Although past studies have confirmed the positive relationship between attitude and intention, Arli et al. [22] examined the factors influencing intention to recycle and found that attitude did not predict intention. Nonetheless, it is anticipated in this study that people who have favourable attitudes towards pro-environmental behaviours will more likely have a higher degree of intention to engage in pro-environmental behaviours. Hence, the study hypothesised that

H5: 

There is a positive relationship between attitude towards pro-environmental behaviours and pro-environmental intention.

2.5. Quality of Life

QoL is defined as how a person perceives his life in terms of the culture and value system in which he lives and in relation to his goals, expectations, standards, and concerns [29]. As defined in Encyclopaedia Britannica, QoL refers to the degree to which a person is healthy, comfortable, and able to participate in life events [30]. In other words, if a person is able to experience his own life and have good living conditions, then he would perceive himself as having good QoL.

QoL is a multidimensional concept that has been used as an endpoint in the evaluation of multisector policies, including environmental policy actions [31]. QoL has been studied vastly in the past to understand human behaviour better, especially in the contexts of anxiety and depression in older adults [32,33], mental health and well-being of older adults [34], social isolation in older adults [35], healthcare [36], and occupation classes [37]. Ramkissoon [38,39] proposed a conceptual model that links the perceived social impacts of tourism to residents’ QoL. Although the study focused on tourism, its insights into how QoL is influenced by social factors can be extrapolated to understand pro-environmental behaviour. Past studies [38,39] stated that adoption of a healthy lifestyle is directly related to the environment, which is subsequently related to QoL.

The Control, Autonomy, Self-Realisation, and Pleasure scale (CASP-19) developed by Hyde et al. [40], is a widely recognised instrument for assessing QoL, particularly among older adults. Originally introduced as a 22-item scale, it was later refined to 19-item scale based on statistical validation [41,42]. The CASP-19 has been extensively applied across various populations and cultural contexts, including Asia [43,44], and performed well with cross-sectional samples [31]. Although initially designed for individuals aged 65 to 75 years, subsequent research has shown that it possesses robust dimensionality across broader demographic groups [45].

The CASP-19 consists of four dimensions: control, autonomy, self-realisation, and pleasure. Control refers to the ability of a person to influence their environment and life circumstances through their actions [46,47]. Autonomy represents self-determination and freedom from unwanted interference [46]. Borrat-Besson et al. [46] define self-realisation as the process of fulfilling one’s potential, whereas pleasure refers to the pursuit of activities that bring enjoyment. McCarthy et al. [47] offer a similar interpretation, describing pleasure as the sense of happiness or satisfaction derived from actively engaging in life. According to Higgs et al. [48], when individuals achieve control and autonomy, they are able to pursue self-realisation through meaningful activities that contribute to personal fulfilment and overall well-being.

While CASP-19 was originally developed to assess QoL in older adults [40], subsequent research supports its relevance across life stages. Notably, Oros and Păun [49] demonstrate that emotional autonomy and identity commitment are significant predictors of psychological well-being in adolescents, supporting the scale’s applicability to younger populations who are undergoing identity formation and autonomy development.

The CASP-19 scale was chosen for this study because it provides a multidimensional perspective on QoL, capturing psychological and social aspects rather than focusing solely on health status. Its four dimensions—control, autonomy, self-realisation, and pleasure—are conceptually aligned with motivational factors that can influence pro-social and pro-environmental actions [31,40]. Specifically, individuals with a greater sense of control over life circumstances may feel more capable of carrying out sustainable practices. Higher autonomy reflects the freedom to make choices, which can facilitate independent decisions to engage in environmentally friendly behaviours. Self-realisation, which concerns pursuing meaning and personal growth, resonates with value-driven motivations to protect the environment. Lastly, pleasure reflects enjoyment and satisfaction with life, which may nurture greater concern for collective well-being, including ecological sustainability. By incorporating CASP-19 into the TPB framework, this study extends behavioural intention research by examining whether these broader aspects of QoL shape pro-environmental intention.

Empirical and theoretical work suggest that each CASP-19 dimension may provide psychological resources relevant to environmental behaviour. For instance, control has parallels with perceived behavioural control in TPB, as individuals who feel capable of managing life circumstances are more likely to believe they can perform sustainable actions [50]. Autonomy aligns with self-determination theory, which emphasises that freely chosen actions—such as adopting eco-friendly practices—are more likely to be sustained over time [51]. Self-realisation, reflecting fulfilment of personal values and meaning, resonates with research showing that pro-environmental behaviour often stems from value-expression and identity motives [52]. Finally, pleasure and life satisfaction are linked with pro-social orientations, as individuals experiencing higher well-being may extend their concern to collective goods such as environmental quality [53,54]. Thus, the CASP-19 dimensions provide a theoretically grounded basis for investigating QoL as a predictor of pro-environmental intention.

While CASP-19 was originally designed for older adults, its four dimensions—control, autonomy, self-realisation, and pleasure—represent universal aspects of psychosocial well-being that are also meaningful for younger populations. For this reason, it has been applied in this study, with the recognition that future work should further validate or adapt QoL measures for younger respondents.

Building on these theoretical linkages between CASP-19 dimensions and pro-environmental behaviour, the following hypotheses (H6–H9) are proposed to test whether QoL factors significantly predict pro-environmental intention. The complete research framework for this study is presented in Figure 1.

H6: 

There is a positive relationship between QoL in control and pro-environmental intention.

H7: 

There is a positive relationship between QoL in autonomy and pro-environmental intention.

H8: 

There is a positive relationship between QoL in self-realisation and pro-environmental intention.

H9: 

There is a positive relationship between QoL in pleasure and pro-environmental intention.

3. Methodology

3.1. Measures

This study is quantitative in nature. The validated scales to measure the variables in this study were adapted from past studies to suit the context of this study. Subjective norm (four items), perceived behavioural control (four items), and attitude (three items) were adapted from Wang [55]. The QoL variables were assessed and measured using the CASP-19 scale, which consists of four items on control and five items each on autonomy, self-realisation, and pleasure. The QoL items were adapted from Hyde [40] and Borrat-Besson et al. [46]. Although CASP-19 was originally developed for older adults [40], prior research has confirmed its applicability across different age groups. Recent findings, for example, demonstrate that autonomy and identity-related dimensions of well-being are also central to younger populations [49]. This supports the suitability of using CASP-19 with the present sample of young adults in Malaysia. All constructs were assessed using a five-point Likert scale.

3.2. Sample and Procedures

The target population for this study comprised adults aged 18 years and above residing in Klang Valley, Malaysia. Data were collected through an online questionnaire, yielding a total of 182 responses. Participation was voluntary and informed consent was obtained from all respondents. The study was conducted in accordance with established ethical guidelines to ensure participant confidentiality and anonymity. Data were analysed using the Statistical Package for the Social Sciences (SPSS) version 29 and Partial Least Squares Structural Equation Modelling (PLS-SEM) version 4. A two-step approach was employed to assess the measurement and structural models.

4. Results and Discussion

4.1. Demographic Profile of Respondents

Table 1. Demographic profiles of respondents (N = 182).

Categories		Frequency	Percentage (%)
Gender	Male	82	45.1
	Female	100	54.9
Age group	18–25	153	84.1
	26–35	19	10.4
	36–45	4	2.2
	46–55	6	3.3
	56 and above	0	0
Ethnicity	Malay	111	61.0
	Chinese	40	22.0
	Indian	19	10.4
	Others	12	6.6
Education level	Primary school	0	0
	High school	2	1.1
	Certificate/Diploma	62	34.1
	Bachelor’s Degree	113	62.1
	Postgraduate Degree	5	2.7
	Others	0	0
Marital status	Single	170	93.4
	Married	11	6.0
	Others	1	0.5
Occupation	Government	0	0
	Private companies	35	19.2
	Self-employed	7	3.8
	Retired	0	0
	Not working/Unemployed	140	76.9
	Others	0	0
Monthly household income (MYR)	Less than MYR 2500	89	48.9
	MYR 2500–MYR 4849	35	19.2
	MYR 4850–MYR 10,959	34	18.7
	MYR 10,960 and above	24	13.2

presents the demographic profile of respondents. Out of the 182 respondents, 100 (54.9%) were female. The majority (84.1%) were aged between 18 and 25 years and most identified as Malay (61.0%). A total of 12 respondents represented a diverse range of other ethnic backgrounds, including Arab, Bangladeshi, Indonesian, Iraqi, Portuguese, Punjabi, Sundanese, and Zimbabwean. In terms of education, 62.1% had completed a Bachelor’s degree. Most respondents (93.4%) reported being single with only one respondent indicating divorced status. Additionally, 76.9% of the sample were currently enrolled as university students.

4.2. Measurement Model Assessment

As shown in

Table 2. Correlations.

Correlations		SN	PBC	AT	INT	QC	QA	QS	QP
SN	P.C	1	0.566 **	0.423 **	0.430 **	0.252 **	0.309 **	0.302 **	0.282 **
PBC	P.C	0.566 **	1	0.415 **	0.447 **	0.362 **	0.388 **	0.277 **	0.268 **
AT	P.C	0.423 **	0.415 **	1	0.558 **	0.310 **	0.325 **	0.440 **	0.394 **
INT	P.C	0.430 **	0.447 **	0.558 **	1	0.322 **	0.376 **	0.443 **	0.434 **
QC	P.C	0.252 **	0.362 **	0.310 **	0.322 **	1	0.514 **	0.527 **	0.541 **
QA	P.C	0.309 **	0.388 **	0.325 **	0.376 **	0.514 **	1	0.644 **	0.587 **
QS	P.C	0.302 **	0.277 **	0.440 **	0.443 **	0.527 **	0.644 **	1	0.776 **
QP	P.C	0.282 **	0.268 **	0.394 **	0.434 **	0.541 **	0.587 **	0.776 **	1

** P.C: Pearson Correlation. Correlation is significant at the 0.01 level (two-tailed). Legend: SN = Subjective norm, PBC = Perceived behavioural control, QC = QoL control, QA = QoL autonomy, QS = QoL self-realisation, QP = QoL pleasure, AT = Attitude, INT = Pro-environmental behavioural intention.

, the Pearson correlation analysis revealed several statistically significant relationships among the variables at the 0.01 significance level. Attitude demonstrated the strongest positive correlation with pro-environmental intention (r = 0.558, p < 0.01), consistent with the theoretical expectation that a favourable attitude significantly influences behavioural intention. Behavioural intention was also correlated with all other variables, with notable associations observed with QoL self-realisation (r = 0.443, p < 0.01) and QoL pleasure (r = 0.434, p < 0.01). These findings suggest that higher levels of self-realisation and pleasure are positively associated with stronger intentions to engage in pro-environmental behaviour.

Table 3. Multicollinearity test.

Dependent Variable	Independent Variables	Tolerance	VIF
Pro-environmental behavioural intention	Subjective norm	0.629	1.589
	Perceived behavioural control	0.581	1.721
	QoL control	0.614	1.628
	QoL autonomy	0.505	1.979
	QoL self-realisation	0.325	3.079
	QoL pleasure	0.366	2.732
	Attitude	0.680	1.470

presents the Tolerance and Variance Inflation Factor (VIF) values used to assess potential multicollinearity among the independent variables. Following the guidelines by Awang [56], tolerance values greater than 0.1 and VIF values of less than 5 indicates the absence of multicollinearity. In this study, all tolerance values exceed 0.1 and all VIF values were below 5, suggesting that multicollinearity is not a significant concern. Therefore, the independent variables can be reliably retained in the regression analysis without compromising the validity of the model.

Cronbach’s alpha coefficients were calculated to assess the internal consistency of the measurement constructs. As shown in

Table 4. Cronbach’s Alpha.

Variables	Items	Cronbach’s Alpha
Subjective norm	4	0.871
Perceived behavioural control	4	0.759
QoL control	4	0.601
QoL autonomy	5	0.744
QoL self-realisation	5	0.832
QoL pleasure	5	0.892
Attitude	3	0.796
Pro-environmental behavioural intention	4	0.850

, the reliability values ranged from 0.601 to 0.892. Consistent with Nunnally’s [57] recommendation, alpha values above 0.7 were generally considered acceptable. While most constructs demonstrated good-to-excellent internal consistency, those slightly below the threshold still fell within a tolerable range for exploratory research, indicating that the measurement instruments used in this study are generally reliable. It is noted that the Cronbach’s alpha for QoL Control (α = 0.601) fell slightly below the conventional 0.70 threshold. However, this value can still be considered acceptable in the context of exploratory research, especially given that the construct was measured with only a small number of items. In addition, the composite reliability for all constructs, including QoL Control, exceeded the recommended level of 0.70, suggesting that the construct demonstrates satisfactory internal consistency within the PLS-SEM framework.

Discriminant validity was assessed using the heterotrait–monotrait (HTMT) ratio of correlations. According to Franke and Sarstedt [58], HTMT values below the threshold of 0.90 indicate adequate discriminant validity. As presented in

Table 5. Heterotrait–monotrait ratio (HTMT).

HTMT	AT	INT	PBC	QA	QC	QP	QS	SN
AT
INT	0.681
PBC	0.530	0.558
QA	0.433	0.505	0.492
QC	0.454	0.469	0.526	0.780
QP	0.467	0.498	0.327	0.705	0.751
QS	0.540	0.527	0.349	0.784	0.749	0.896
SN	0.506	0.501	0.689	0.363	0.341	0.322	0.356

, all the HTMT values in this study were below 0.90, confirming that discriminant validity was established across all constructs.

4.3. Structural Model Assessment

As illustrated in Figure 2, subjective norm (t = 3.045, p < 0.05) and perceived behavioural control (t = 2.722, p < 0.05) were found to be significant predictors of attitude. Additionally, attitude (t = 4.545, p < 0.05) emerged as the only significant predictor of pro-behavioural intention. These results provide empirical support for hypotheses H1, H3, and H9. In contrast, subjective norm (t = 1.576, p > 0.05), perceived behavioural control (t = 1.553, p > 0.05), QoL control (t = 1.204, p > 0.05), QoL autonomy (t = 0.995 p > 0.05), QoL self-realisation (t = 0.466, p > 0.05), and QoL pleasure (t = 0.803, p > 0.05) did not exhibit statistically significant relationships with behavioural intention. Consequently, hypotheses H2, H4, H5, H6, H7, and H8 were not supported.

As presented in

Table 6. Results of the hypotheses testing.

Hypothesis		Path Coefficient	Sample Mean (M)	Standard Error	t-Value	p-Value	Results
H1	SN → AT	0.264	0.270	0.087	3.045	0.002	Supported
H2	SN → INT	0.132	0.135	0.084	1.576	0.115	Not supported
H3	PBC → AT	0.282	0.291	0.104	2.722	0.007	Supported
H4	PBC → INT	0.140	0.138	0.090	1.553	0.120	Not supported
H5	AT → INT	0.331	0.331	0.073	4.545	0.000	Supported
H6	QC → INT	0.100	0.114	0.083	1.204	0.229	Not supported
H7	QA → INT	0.074	0.080	0.074	0.995	0.320	Not supported
H8	QS → INT	0.050	0.049	0.108	0.466	0.641	Not supported
H9	QP → INT	0.086	0.076	0.108	0.803	0.422	Not supported

Note: t > 1.96, p < 0.05. Legend: SN = Subjective norm, PBC = Perceived behavioural control, QC = QoL control, QA = QoL autonomy, QS = QoL self-realisation, QP = QoL pleasure, AT = Attitude, INT = Pro-environmental behavioural intention.

, attitude exerted the strongest influence on behavioural intention (AT = 0.331), indicating its central role in predicting pro-environmental behaviour. In turn, perceived behavioural control demonstrated the strongest effect on attitude (PBC = 0.282), followed by subjective norm (SN = 0.264), suggesting that both perceived ease of performing the behaviour and social pressures are important determinants in shaping an individual’s environmental attitudes.

5. Discussion

This study explored how constructs from the Theory of Planned Behaviour (TPB)—attitude, subjective norm, and perceived behavioural control—as well as QoL dimensions relate to pro-environmental behavioural intention among younger adults residing in Klang Valley, Malaysia. The structural model confirms that attitude is the strongest and most significant predictor of pro-environmental behavioural intention, supporting the core TPB idea that people are more inclined to act when they perceive the behaviour as favourable, meaningful, and personally valuable [59,60]. This outcome aligns with earlier studies which also found attitude to be a more dominant predictor than other TPB variables such as subjective norm and perceived behavioural control [61,62].

The analysis also revealed that both subjective norm and perceived behavioural control have a significant impact on attitude, in line with Hypotheses 1 and 3. These results lend further support to TPB by showing that people are more likely to form positive views about environmental behaviour when they feel encouraged by others or believe they are capable of carrying out such actions [22,63]. In this context, it appears that individuals tend to adopt more favourable environmental attitudes when they believe those around them expect such behaviour. Similarly, those who feel confident in their ability to engage in green practices are more likely to hold positive attitudes towards doing so [50].

However, subjective norm and perceived behavioural control did not have a direct effect on behavioural intention, meaning that H2 and H4 were not supported. Although this contrasts with some TPB studies, it is not entirely unexpected. A number of recent works suggest that these constructs may influence intention directly through attitude [28,51]. This implies a mediation effect whereby social pressure and control beliefs contribute to behavioural intention primarily by shaping one’s attitude.

In relation to QoL, none of the four CASP-19 dimensions—control, autonomy, self-realisation, and pleasure—were significantly associated with behavioural intention, resulting in Hypotheses 6 through 9 being unsupported. One possible explanation for this lack of significance is that QoL may play a different role for younger adults compared to older populations. For younger adults, who made up the majority of the sample, environmental choices are often shaped more strongly by social influences, perceived behavioural control, or identity expression rather than by general life satisfaction or feelings of personal pleasure. Younger individuals may also prioritise immediate concerns such as education, career development, and social belonging over broader reflections of life quality. In this context, value orientations and environmental concern could be more powerful motivators than the CASP-19 dimensions of control, autonomy, self-realisation, or pleasure. This suggests that pro-environmental intentions among younger generations may be more closely linked to identity, social expectations, and future-oriented values than to their current assessments of QoL.

This finding differs from earlier studies that connected higher life satisfaction with stronger environmental engagement [53,54]. In summary, the study confirms the significant role of attitude in influencing pro-environmental intention, while also showing that subjective norm and perceived behaviour control help shape these attitudes, even though they do not directly affect intention.

6. Implications and Future Research Directions

This study offers several contributions relating to theoretical and practical contributions. From a theoretical perspective, the study provides support to the Theory of Planned Behaviour (TPB) as a useful framework for understanding pro-environmental intention, especially in the Malaysian setting. The observation that subjective norm and perceived behavioural control shape intention indirectly by influencing attitude may offer further clarity on how the TPB constructs interrelate. This provides additional weight to the idea that developing positive attitudes is crucial in encouraging behavioural intention.

On the practical level, the results may provide insights to policy makers, educators, or even to environmental advocates. Programmes that are designed to encourage eco-friendly behaviour should prioritise fostering positive individual attitudes. These include initiatives such as campaigns that align pro-environmental actions with personally meaningful outcomes, including cost savings or community benefits. In addition, more strategies that may improve an individual’s perceived behavioural control including environmental literacy, simplifying eco-friendly actions, and better infrastructure may lead to positive attitudes towards pro-environmental behaviours and ultimately stronger intentions to act sustainably.

Interestingly, the study found that QoL, measured through the CASP-19 dimensions, did not significantly predict pro-environmental intention. This could mean that general well-being alone may not be a strong motivator for environmentally responsible behaviour, and this is observed among younger adults. In fact, the findings highlight the need for more targeted communication strategies that explicitly connect environmental actions with values and issues that younger people care about.

The study also opens the opportunity for further research on how cultural context or demographic factors might influence these relationships. For instance, culture, age, or life stage could moderate how QoL or TPB variables relate to behavioural intention. Given that CASP-19 was originally designed for older adults, its dimensions may not fully capture how younger respondents define and experience QoL. Nevertheless, the scale was employed in this study because its four dimensions—control, autonomy, self-realisation, and pleasure—represent universal aspects of psychosocial well-being that are also relevant for younger age groups. The non-significant findings observed here further highlight the importance of validating or adapting QoL measures for younger populations in future research to ensure that the constructs reflect their lived experiences more accurately.

Drawing from the literature and findings, this study proposes two main avenues for future research. Researchers should compare the predictive power of the Theory of Planned Behaviour (TPB) when adhering to its original structure versus a model that accounts for interactions between its core variables, ultimately determining the most robust framework for the environmental domain.

Another limitation relates to the demographic profile of the sample. The majority of respondents were younger adults (84% aged 18–25, mostly university students), which restricts the generalisability of the findings to other age groups. QoL considerations and pro-environmental motivations may vary significantly across lifespan, and future studies should therefore examine more age-diverse samples to capture these differences. Research involving older populations may be particularly valuable, given that QoL measurement are likely to hold greater relevance for them.

Lastly, the cross-sectional nature of the research makes it difficult to draw any conclusions about cause and effect. Future work employing longitudinal designs would allow for stronger causal inferences and a deeper understanding of how attitudes, norms, control, and QoL interact over time to shape pro-environmental intention. In addition, qualitative approaches such as interviews or focus groups could provide richer insights into how younger individuals perceive QoL in relation to environmental issues, thereby clarifying why CASP-19 dimensions did not significantly predict pro-environmental intention in this study.

7. Conclusions

This study reinforces the relevance of the TPB in explaining pro-environmental intention, particularly within the Malaysian context. The findings clarify that subjective norm and perceived behavioural control influence intention indirectly through attitude, which emerges as the most important predictor of pro-environmental intention. This provides further insights into how the TPB variables interact and confirms the central role of attitude in shaping intention. At the same time, the non-significant influence of QoL dimensions indicates that for younger adults, environmental intentions are less dependent on overall well-being and more closely associated with values, social expectations, and identity-related factors.

Theoretically, this study contributes to ongoing work on TPB by showing the mediating role of attitude and by testing the inclusion of QoL factors, even though their effects were limited in this context. From a practical perspective, the findings suggest that interventions designed for younger adults should place stronger emphasis on building favourable environmental attitudes and connecting pro-environmental behaviour to meaningful values and social identities, rather than relying on general measures of life satisfaction. Such approaches may better encourage sustained engagement in pro-environmental behaviour.