792 © 2025 Conscientia Beam. All Rights Reserved. Predicting Instagram usage, online incivility, and online political engagement among Malaysian youth: An extension of UTAUT2 Tak Jie Chan1+ Hin Ying Chua2 Sheh Chin Foo3 Miew Luan Ng4 Miza Izwanis Mangsor5 1,5Faculty of Applied Communication, Multimedia University, Cyberjaya, Selangor, Malaysia. 1Email: tjchan@mmu.edu.my 5Email: miza.izwanis@mmu.edu.my 2School of Communication and Creative Design, SEGi University, Petaling Jaya, Selangor, Malaysia. 2Email: ying20000724@gmail.com 3School of Marketing and Management, Asia Pacific University of Technology and Innovation, Taman Teknologi Malaysia, Kuala Lumpur, Malaysia. 3Email: eugene.foo@apu.edu.my 4Faculty of Education and Liberal Arts, INTI International University, Nilai, Negeri Sembilan, Malaysia. 4Email: miewluan.ng@newinti.edu.my (+ Corresponding author) ABSTRACT Article History Received: 3 February 2025 Revised: 27 May 2025 Accepted: 30 June 2025 Published: 18 July 2025 Keywords Instagram Online incivility Online political engagement Online violence prevention UTAUT2. Political activities have gone on online means through virtual applications. Past research has been done on social media and online political engagement across several countries, including Malaysia. However, limited literature has investigated online political engagement on Instagram. This study examines Instagram usage attributes that impact Malaysian youths’ online political engagement. This research was driven by the Unified Theory of Acceptance and Use of Technology (UTAUT2) theory with the expansion of online incivility to fill the academic gap. A quantitative approach (online survey) and purposive sampling were used by distributing online questionnaires to Malaysian youths between 18 and 30 years old who are Instagram users. 170 valid respondents were gathered through Google Forms and were analyze through Structural Equation Modelling (PLS-SEM). The findings showed that social influence, habit, and online incivility are the predictors of online political engagements which support online incivility as a crucial construct that further extends the UTAUT2 theory. However, the effort expectancy, performance expectancy, and facilitating conditions were not the predictors. The study contributed to the political communication scholarship and urged government agencies such as the Malaysian Communications and Multimedia Commission (MCMC) to provide guidelines on handling online incivility and uncivil behavior. Contribution/Originality: This research extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) theory by including online incivility to predict political engagement. 1. INTRODUCTION Many studies have been done to probe the impact of social media use and youths’ political engagement due to the great importance of youth political participation, involvement, and engagement (Alodat, Al-Qora’n, & Abu Hamoud, 2023; Wahyuningroem, Sirait, Uljanatunnisa, & Heryadi, 2024). However, there is still room for further research as the dominance of social media platforms, the political landscape, and government policies change (Kasmani, 2024; Xie, 2024). Numerous scholars have identified that the dominance of social media platforms has a Humanities and Social Sciences Letters 2025 Vol. 13, No. 3, pp. 792-807 ISSN(e): 2312-4318 ISSN(p): 2312-5659 DOI: 10.18488/ © 2025 Conscientia Beam. All Rights Reserved. https://orcid.org/0000-0001-8655-0924 https://orcid.org/0000-0003-0949-5858 https://orcid.org/0000-0001-9684-9428 mailto:tjchan@mmu.edu.my mailto:ying20000724@gmail.com https://www.doi.org/10.18488/73.v13i2.4298 Humanities and Social Sciences Letters, 2025, 13(3): 792-807 793 © 2025 Conscientia Beam. All Rights Reserved. causal relationship to the rise of political rallies, showing that with the change in social media platform dominance, political engagement can be affected (Kim, 2023; Matthes, 2022; Yilmaz, Akbarzadeh, Abbasov, & Bashirov, 2024). However, since the amendment of enactment in 2013 which abolished the restrictions of political activities given to students (Mohd Zain et al., 2023) as a result of Malaysian students’ demand for political freedom (Tain & Vivian, 2022) and reduced the minimum legal voting age from 21 to 18 years old (Nazaruddin & Yusoff, 2024). A recent article by Fadzil, Ismail, and Krauss (2022) showed that Malaysian youths are now more actively participating in Malaysian politics. For instance, numerous scholars (e.g., Audrey & Arnold, 2024; Kasmani, 2023; Nazaruddin & Yusoff, 2024) mentioned the acceleration of social movements like Undi18, which demonstrates how keen young people are to be involved in political decision-making. In this age of technology, social media, such as Instagram has been utilized and expanded for many purposes, including political purposes (Alodat et al., 2023; Kim, 2023). Information and communications technologies (ICTs) have offered more information accessibility, openness, and improvements for learning (Intyaswati, Maryani, Sugiana, & Venus, 2021). Since the onset of the COVID-19 pandemic, it was reported by Booth, Tombaugh, Kiesa, Lundberg, and Cohen (2020) that young people are increasingly engaging in political activism online. Since the citizens seem to have become accustomed to the new normal, whereby most things have to be done through online platforms or social media. It is believed that the pandemic has become a driving force to promote more online political engagement in the future. This study extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) theory to determine Instagram usage and attributes and Klang Valley youths’ political engagement. A lot of literature has been done on identifying social media or electronic technologies’ attributes and use of UTAUT2 theory. However, there are still inconsistencies in the findings obtained. Mensah, Zeng, and Luo's (2020) study on electronic government adoption services by extending the UTAUT theory showed that facilitating conditions and effort expectancy positively impact the intention to use e-government service while performance expectancy, social influence proved to be insignificant determinants of attitude and intention of e-government adoption. Besides, the study by Naranjo- Zolotov, Oliveira, and Casteleyn (2018) revealed that performance expectancy and facilitating conditions drive citizens to use e-participation while effort expectancy and social influence do not significantly drive citizens’ e- participation adoption. In addition, performance expectancy, habit, social influence, and price value as proposed by UTAUT2 theory are all significant in attracting Lebanese citizens to adopt e-government services (Fakhoury & Chebaro, 2021). Agbesi (2020) also identified performance expectancy and effort expectancy have positive correlations with the intention of adopting the Internet voting system while facilitating conditions and social influence have no significant correlations with the use of the Internet voting system. These show a need to further re-examine the UTAUT2 theory. An additional variable which is online incivility is included in this study. In life, people communicate and interact with others with proper, polite, and non-offensive words to maintain a good relationship with people that they meet in person regularly. However, since social media users are not meeting other online users in person, it is easier and carefree to exert dehumanization (Aji & Sapto, 2020; Oz, 2023).On the other hand, other online users use words or take certain online actions to attack others aggressively due to some reasons, such as when they disagree with the opinions of others (Lu & Liang, 2024). For instance, Javeed, Khan, Alomair, and Al Naim (2024) discovered that the uncivil comments initiated by other virtual users spark online incivility. Thus, uncivil discussion demonstrated a greater inclination to engage in online political discussion (Rega & Marchetti, 2021). Gondwe (2020) who investigated incivility and online participation in the Hong Kong protests in 2019 found that incivility had a great impact on promoting online participation. Nevertheless, Van’t Riet and Van Stekelenburg (2022) concluded political incivility reduces the effect of political trust and participation. Therefore, the inclusion of the online incivility dimension is to fill the gap of the previous studies by testing whether online incivility relates significantly to online political engagement due to the inconsistency that occurs in the previous literature. Humanities and Social Sciences Letters, 2025, 13(3): 792-807 794 © 2025 Conscientia Beam. All Rights Reserved. Based on the gaps highlighted, this study would like to test the relationship between Instagram usage attributes from the UTAUT2 (effort expectancy, performance expectancy, social influence, facilitating conditions and habit) and online incivility on online political engagement among Malaysian youths. 2. LITERATURE REVIEW 2.1. Theoretical Underpinning This study utilized the UTAUT2 theory which was established by Venkatesh, Thong, and Xu (2012) and it forecasted technology adoption, acceptance, and utilization. UTAUT2 is deemed to be among the popular technology acceptance theories and has been widely adopted in studies related to ICT (Ayas & Yanartaş, 2020; Nordhoff, Madigan, Van Arem, Merat, & Happee, 2021; Quinones, Romero, Schmitz, & Díaz-Martín, 2024). Four dimensions of the UTAUT comprise performance expectancy, effort expectancy, social influence, and facilitating conditions. Despite this, UTAUT theory was then further extended to UTAUT2 with three additional dimensions which are hedonic motivation, price value, and habit. For this study, another two dimensions of UTAUT2 theory, namely hedonic motivation and price value were excluded in the current study. The hedonic motivation was found to relate more with entertainment-oriented content and it has a distraction effect or reduces the likelihood of engaging with political participation (Matthes, Heiss, & van Scharrel, 2023) while price value does not apply to this study because Instagram was introduced to be free to install and free to use (Han et al., 2020). 2.2. Hypothesis Development Numerous literatures have found a favorable outcome between effort expectancy and political engagement. For instance, it was discovered a positive and significant relationship between perceived ease of use of social media usage and youths’ political engagement (Omotayo & Folorunso, 2020) which is in line with many other studies focusing on the perceived ease of use/ effort expectancy of system and various users’ outcomes (Adnan, Ghazali, & Othman, 2022; Nordhoff et al., 2021; Ting et al., 2024; Wa & Zhang, 2023). Besides, Li (2021) has also identified that effort expectancy positively influences the adoption of e-government services among citizens. Hence, this study was formulated. H1: Effort expectancy positively impacts online political engagement. Venkatesh et al. (2012) defined performance expectancy as a person’s expectation that adopting a certain technology will allow the opportunity to make a profit in terms of performance. Mensah et al. (2020) found that performance expectancy was significantly impacting the e-voting system adoption in Ghana. This also synchronized with the study of Adnan et al. (2022) to have more research to examine the performance expectancy and satisfaction with e-government services. In addition, Ting et al. (2024) asserted that performance expectancy (usefulness) positively impacts government political social media usage and foster youth civic engagement in political movements (Borrero & Borrero-Domínguez, 2024). Hence, the study assumed that H2: Performance expectancy positively influences online political engagement. According to Ahmad and Mohd Zain (2021) youths do not directly get involved actively in politics. They prefer to discuss and talk about political topics with people around them, such as friends, peers, and family. This indicates that discussions on political issues are more favorable to be done with close people around youths which includes the mass and social media (Alodat et al., 2023; Kasmani, 2024; Yaakub, Kamil, & Nordin, 2023). These close people may still influence them to engage actively in politics in the future. Social influence/ subjective norms were also a significant indicator of positive relationships with the e-government system and online political participation (Ayas & Yanartaş, 2020; Zhao & Cao, 2024). Hence, the hypothesis is formed as H3: Social influence positively impacts online political engagement. Humanities and Social Sciences Letters, 2025, 13(3): 792-807 795 © 2025 Conscientia Beam. All Rights Reserved. Social media adoption among youths have facilitated more political and civic involvement (Alodat et al., 2023) notably for those who believe that they have a constrained ability to engage in and comprehend political issues. Matthes (2022) indicates that using social media facilitates young people participating in politics. Furthermore, Nurul Huda and Amin (2023) found that facilitating conditions positively influence the user satisfaction of e- democracy applications in Indonesia. This also aligned with the study of Alkhazali and Albattat (2022) where they found that facilitating conditions positively impact the perceived value and e-voting use intention. Thus, the study postulated that H4: Facilitating conditions positively influence online political engagement. Abubakar and Al-Mamary's (2025) study has exhibited that habit has the strongest positive influence on intentions of using social media among students and lecturers. Similarly, Mahmood et al. (2023) showed that user habit (frequency of visiting) had a major impact on user behavior. The habit has a positive impact on mobile Internet usage intention among teachers and students (Nikolopoulou, Gialamas, & Lavidas, 2021). While habit promotes social media use, it exposes individuals to political information and knowledge, thereby positively affecting political engagement (Intyaswati et al., 2021; Tan, 2024). Thus, this study is formulated as H5: The habit of using Instagram positively impacts online political engagement. Javeed et al. (2024) indicated that political news posts on social media positively impact online uncivil behavior, as the uncivilized behavior can increase political engagement (Van’t Riet & Van Stekelenburg, 2022) because it draws attention and deepens impression (Lu, Liang, & Masullo, 2023) thereby enhancing their political interest (Kasmani, 2024). Rega and Marchetti (2021) expected that incivility is more likely to arouse people’s strong desire to engage politically only when uncivil disputes occur, trigger uncivilized reactions and eventually lead to hostile behavior. Hence, it is indicated that H6: Online incivility positively impacts online political engagement. The research framework is illustrated in Figure 1. Figure 1. Research framework. 3. METHODOLOGY 3.1. Research Design A quantitative research design is adopted because hypothesis testing allows a researcher to test the cause-and- effect connections (Ghanad, 2023). According to Regmi, Waithaka, Paudyal, Simkhada, and Van Teijlingen (2016) data collection through online questionnaires can gather massive amounts of data effectively and time-saving. Humanities and Social Sciences Letters, 2025, 13(3): 792-807 796 © 2025 Conscientia Beam. All Rights Reserved. 3.2. Sampling Procedure Purposive sampling is a sampling technique to select the respondents based on the attributes they possess (Etikan, Musa, & Alkassim, 2016). The researchers determine the criteria required and seek individuals who can share their information, knowledge, and experience by using purposive sampling. Hence, for this study, the respondent must be an Instagram user, as argued by Ching Velasco et al. (2024) that platforms such as Instagram and TikTok encourage more people to participate in online political discourse. Besides, other criteria such as respondents being aware of online petitions, having seen politicians’ social media accounts, and having been exposed to politics-related online content were embedded as the screening questions to facilitate valid responses. Researchers utilized G-power analysis to determine the sample size. Hence, the minimum sample size required is 146 (predictors: 6, effect size: 0.15 and power: 0.95). A total of 302 responses were gathered after screening out the invalid respondents who did not meet the purposeful sampling criteria, this study has 170 valid responses. 3.3. Measurement Section A includes the respondents’ demographic attributes which are age, gender, nationality, race, education level, and employment. Section B generally contains Instagram attributes derived from the UTAUT2 theory. Items for effort expectancy were adapted from Venkatesh, Morris, Davis, and Davis (2003). Performance expectancy items were modified (Chao, 2019; Chauhan, Jaiswal, & Kar, 2018; Venkatesh et al., 2003) social influence items were adapted from (Thomas, Singh, & Gaffar, 2013; Venkatesh et al., 2012). Besides, items for facilitating conditions were adapted from (Thomas et al., 2013; Venkatesh et al., 2003; Venkatesh et al., 2012) items for habit were modified from (Venkatesh et al., 2012; Verplanken & Orbell, 2003) and items for online incivility were adapted from (Aljawarneh, Alomari, Alomari, & Taha, 2022 and Yuin, 2006). 13 items on online political engagement (Section C) were adapted from (Abdulrauf, Abdul Hamid, & Ishak, 2017; De la Garza Montemayor, Peña-Ramos, & López, 2019; Gil de Zúñiga, Jung, & Valenzuela, 2012; Kim & Chen, 2016; Yamamoto, Kushin, & Dalisay, 2015). Sections B and C are in interval scale and measured using a four-point Likert scale, (1= strongly disagree and 4= strongly agree). 3.4. Common Method Variance Common method variance (CMV) is a single- source of data to measure each variable and is commonly happens in cross-sectional design (Jordan & Troth, 2020). Hence, to test the CMV, the researchers used a regression-based marker technique (Kock, Berbekova, & Assaf, 2021; Siemsen, Roth, & Oliveira, 2010) to produce a variance inflation factor (VIF). Table 1 presents the values for all the variables that are less than 3.3 as suggested by Hair and Alamer (2022). Thus, there is no severe CMV issue. Table 1. CMV using the regression-based marker technique. Variables VIF (Marker) EE 2.119 FC 1.884 HT 1.754 OI 1.604 OPE 1.736 PE 2.342 SI 2.165 3.5. Procedures for Data Collection The data were collected using an online survey where the instrument was distributed through social media platforms (Facebook, WhatsApp and email). The consent form to participate appears on the cover page of the online Humanities and Social Sciences Letters, 2025, 13(3): 792-807 797 © 2025 Conscientia Beam. All Rights Reserved. survey where the respondents voluntarily participate in the study. The researchers ensured the respondents of the anonymity and confidentiality of their data and only be used for research purposes. 4. RESULTS Based on Table 2, the majorities is between the ages of 20 and 25 years old (78.2%) and are mostly female (69.4%). For the race, the respondents’ majority was Chinese (72.4%) and had bachelor’s degrees (75.3%), and they always use Instagram which comprised 74.4%. Table 2. Respondents’ profile attributes (N=170). Variables Frequency % Age (Years old) <20 (Teens) 5 3.0 20-25 (Young adults) 133 78.2 26-30 (Adults) 32 18.8 Gender Male 52 30.6 Female 118 69.4 Race Malay 30 17.6 Chinese 123 72.4 Indian 11 6.5 Others 6 3.5 Highest education level SPM/O-Level/A-Level/Foundations/STPM 11 6.5 Diploma 10 5.9 Bachelor degree 128 75.3 Master degree 17 10.0 Ph.D. 1 0.6 Professional certificate 3 1.8 Employment Employed 29 17.1 Self-employed 8 4.7 Not employed 133 78.2 Frequency of use of Instagram Always 127 74.4 Sometimes 31 18.2 Rarely 12 7.1 4.1. Measurement Model Assessment Cheung, Cooper-Thomas, Lau, and Wang (2024) highlighted that reliability can be ascertained using factor loading and composite reliability (CR). As depicted in Table 3, the loading of the items is more than 0.60 (Afthanorhan, Awang, & Aimran, 2020) and Cronbach’s alpha also exceeded 0.7 (Hair, Sarstedt, Ringle, & Gudergan, 2024). Discriminant validity was utilized to test the validity of constructs. Hair et al. (2024) highlighted that the CR should exceed 0.70, while the Average Variance Extracted (AVE) should be more than 0.50. Thus, the convergent validity is confirmed. Humanities and Social Sciences Letters, 2025, 13(3): 792-807 798 © 2025 Conscientia Beam. All Rights Reserved. Table 3. Convergent validity. Variables Items Loadings Cronbach's alpha CR AVE Effort expectancy EE1 0.614 0.831 0.816 0.536 EE2 0.649 EE3 0.642 EE5 0.966 Facilitating conditions FC1 0.740 0.841 0.875 0.584 FC2 0.757 FC3 0.788 FC4 0.830 FC5 0.701 Habit HT1 0.869 0.919 0.939 0.754 HT2 0.870 HT3 0.899 HT4 0.897 HT5 0.804 Online incivility OI1 0.926 0.950 0.961 0.803 OI2 0.902 OI3 0.933 OI4 0.832 OI5 0.915 OI6 0.862 Online political engagement OPE1 0.749 0.944 0.951 0.600 OPE2 0.693 OPE3 0.820 OPE4 0.807 OPE5 0.857 OPE6 0.803 OPE7 0.785 OPE8 0.821 OPE9 0.683 OPE10 0.780 OPE11 0.777 OPE12 0.770 OPE13 0.706 Performance expectancy PE1 0.686 0.863 0.907 0.712 PE2 0.890 PE3 0.881 PE4 0.899 Social influence SI1 0.829 0.857 0.892 0.626 SI2 0.843 SI3 0.783 SI4 0.824 SI5 0.661 Heterotrait-Monotrait Ratio of Correlations (HTMT) was applied to check the discriminant validity (Ringle, Sarstedt, Sinkovics, & Sinkovics, 2023). Based on Cheung et al. (2024) the HTMT value should not exceed 0.85. As indicated in Table 4, all HTMT values did not surpass 0.85 which ascertained the discriminant validity. The researchers used the VIF to detect the collinearity issue. Kock (2015) mentioned that the VIF value should not be more than 3.3. Thus, there is no severe collinearity issue. Table 4. HTMT ratio. Variables EE FC HT OI OPE PE SI EE FC 0.768 HT 0.587 0.458 OI 0.172 0.072 0.408 OPE 0.136 0.112 0.414 0.589 PE 0.555 0.506 0.573 0.359 0.455 SI 0.388 0.443 0.495 0.423 0.468 0.803 Humanities and Social Sciences Letters, 2025, 13(3): 792-807 799 © 2025 Conscientia Beam. All Rights Reserved. 4.2. Structural Model Assessment Researchers used the bootstrapping technique with 10,000 resamples (Kostanek, Karolczak, Kuliczkowski, & Watala, 2024) to test the structural model. The results in Table 5 showed that social influence has a positive impact on online political engagement (β = 0.205, t-value = 2.115 and p < 0.05). Thus, H3 is supported. Similarly, habit significantly and positively impacts online political engagement (β = 0.152, t-value = 1.977 and p < 0.05), thus, sustaining H5. In addition, online incivility was also positively impacted by the online political engagement (β = 0.388, t-value = 4.880 and p<0.05). Accordingly, H3, H5, and H6 are retained. However, effort expectancy, performance expectancy, and facilitating conditions were not the predictors. All the 6 exogenous variables can explain online political engagement by 43.3%. Figure 2 illustrates the assessment of the structural model. Table 5. Hypothesis testing for direct effects. Paths Std. beta Std. error T P LLCI (5%) ULCI (95%) D R2 f2 VIF H1: EE -> OPE -0.038 0.103 0.375 0.354 -0.201 0.137 NS 0.433 0.002 1.517 H2: PE -> OPE 0.159 0.099 1.606 0.054 0.020 0.346 NS 0.018 2.424 H3: SI -> OPE 0.205 0.097 2.115 0.017 0.053 0.376 S 0.033 2.249 H4: FC -> OPE -0.140 0.074 1.885 0.030 -0.313 -0.070 NS (-Ve) 0.022 1.584 H5: HT -> OPE 0.152 0.077 1.977 0.024 0.021 0.273 S 0.026 1.563 H6: OI -> OPE 0.388 0.080 4.880 0.000 0.240 0.504 S 0.198 1.343 Note: ULCI = Upper level confidence interval, LLCI = Lower level confidence interval; D= Decision; S= Supported and NS = Not supported 1- tailed test. Figure 2. Assessment of structural model. 4.3. PLS-Predict Analysis PLS-predict was used to solve the apparent dichotomy between explanation and prediction (Hair Jr, 2020; Shmueli et al., 2019). Since the results of Q2 predict values were all more than zero, the Q2 predict indicates the Humanities and Social Sciences Letters, 2025, 13(3): 792-807 800 © 2025 Conscientia Beam. All Rights Reserved. model has sufficient predictive relevancy. Table 6 denoted that online political engagement has a high predictive power. Table 6. PLS predict. Items Q²predict PLS-SEM_RMSE LM_RMSE PLS-SEM – LM Interpretation OPE1 0.261 0.873 1.032 -0.159 High OPE2 0.236 0.929 1.067 -0.138 OPE3 0.403 0.770 0.781 -0.011 OPE4 0.287 0.860 0.949 -0.089 OPE5 0.304 0.862 0.926 -0.064 OPE6 0.217 0.973 1.014 -0.041 OPE7 0.256 0.871 0.869 0.002 OPE8 0.219 0.932 0.974 -0.042 OPE9 0.040 0.975 1.032 -0.057 OPE10 0.215 0.928 0.992 -0.064 OPE11 0.164 0.958 1.009 -0.051 OPE12 0.187 0.918 0.954 -0.036 OPE13 0.171 0.915 0.948 -0.033 5. DISCUSSION The findings revealed that effort expectancy does not impact online political engagement which contrasted with past studies that have demonstrated that effort expectancy is a factor that can positively increase online political engagement or electronic services related to politics (Li, 2021; Omotayo & Folorunso, 2020). This can be further explained by Alam and Yousuf (2021) who say that social media is user-friendly and requires little effort. This also aligned with the current demographic attributes of the respondents who are young adults and are very technology savvy. Besides, performance expectancy was found insignificant impact on online political engagement, which contradicted the findings of Mensah et al. (2020); Adnan et al. (2022) and Ting et al. (2024). The facilitating conditions and online political engagement have a significant relationship. However, it has a negative impact which also contradicted the study (Alkhazali & Albattat, 2022; Nurul Huda & Amin, 2023). The contradicted results are possibly explained by the demographic attributes which make up largely youth aged between 20 and 25 years old where this group is well-versed with technology and might use technology/systems for other purposes rather than engage with e-political content in social media. The study ascertained social influence and positive impact on online political engagement, which is congruent with (Ayas & Yanartaş, 2020; Zhao & Cao, 2024). In addition, it also best explained that youths are more likely to discuss political matters with peers, friends, and family, including in social media settings (Alodat et al., 2023; Kasmani, 2024; Yaakub et al., 2023). Habit has also been found to significantly lead to social media usage and expose youth to political information (Intyaswati et al., 2021; Tan, 2024) and engage with political matters. The findings proposed that people with a frequent habit of using Instagram will tend to have a higher likelihood of engaging politically online. Online incivility has a positive impact on online political engagement, which aligns with the findings of Van’t Riet and Van Stekelenburg (2022) and Kasmani (2024). The positive outcome also supported the statements emphasizing uncivil discussions draw attention deepen impressions and enhance political interest (Rega & Marchetti, 2021). From another perspective, people who are highly involved in political engagement may be more likely to behave uncivilly when engaging in political discussions. This emotion could arise when they get agitated in emphasizing their ideas and opinions or strongly disagreeing with the opinion of others. The researcher proposed that even in such emotionally charged situations, people will not stop participating in politics, and instead, they will Humanities and Social Sciences Letters, 2025, 13(3): 792-807 801 © 2025 Conscientia Beam. All Rights Reserved. feel more motivated to politically engage because they are more likely to eagerly express their logical ideas or influence others to agree with their ideas when they are provoked by other online users. 6. CONCLUSION The empirical findings indicated that social influence, habit, and online incivility have a positive and notable influence on online political engagement with online incivility being the most prominent predictor of online political engagement while effort expectancy, performance expectancy, and facilitating conditions were not the predictors. 6.1. Academic Implications This study contributes to the media and communication scholarship on the aspect of online political engagement by demonstrating the applicability of the UTAUT2 developed by Venkatesh et al. (2012). It also creates a great contribution to the habit dimension of UTAUT2 theory since very few literatures have attempted to view online political engagement from the dimension of habit. Most importantly, this study extended the UTAUT2 with online incivility and it was found to have a positive relationship with online political engagement, which contributes to the corpus of political communication and communication technology scholarships. 6.2. Practical Implications First and foremost, online incivility can contribute to a greater involvement of online political engagement. The government and app developers may not need to solve the problem of online incivility. However, future researchers may suggest a necessity to tackle the problem of online incivility when it slowly evolves into a disadvantageous situation, such as when it becomes a negative determinant of online political engagement, decreasing society’s involvement in online political engagement. Besides, the Malaysian government and experts may revise or improve the current efforts to increase online political engagement to make Malaysia a better land for Malaysians to enjoy stable and satisfying political, economic, and social conditions. For instance, openly respond to hot topics of political discussions, comments or concerns about the recent political, economic, and social situations through a specific forum to bring awareness to the citizens that their voices can be heard, thereby enhancing political trust and efficacy, and creating a way to connect government and citizens, rather than enforcing rules and regulations to limit the society to express their political views to a certain extent. Thirdly, the trend of online political engagement is absent on Instagram. It might be great if social media users who play an important role in society, such as key opinion leaders (KOLs) and non-government organizations (NGOs) could bring this trend to Instagram. Everyone has their own preferred social media platform. They might spend more time on that particular or several social media platforms that they prefer. Instagram fans could have been exposed to more activities about online political engagement, but since this trend has not yet been popularized or caught on Instagram, they may be less likely to engage in online political engagement unless they are politically motivated. In this era, it has been common for everyone, including elders, children, and even politicians to have at least one social media account. Online political engagement enables more political communication among the netizens and more viewpoints about the current country’s situation to be known. Being active in online political engagement could increase the possibility of bringing an issue to the attention of government and politicians, especially when netizens tend to tag the relevant authorities in postings or comments, thereby allowing public opinions to be heard. Humanities and Social Sciences Letters, 2025, 13(3): 792-807 802 © 2025 Conscientia Beam. All Rights Reserved. 6.3. Limitations and Future Research Directions First, the current study only looks from the positivist perspective and uses a cross-sectional design. Thus, deeper understanding of the phenomenon can be obtained by combining qualitative and quantitative or mixed- methods approaches in the future. Second, the study was only done in a country, Malaysia specifically, solely in the areas of Klang Valley. Future studies could involve more regions in the survey to better understand and have an overview of online political engagement. The study only focused on Instagram as a platform. Thus, a future comparative study that focuses on the various social media platforms to investigate the type of social media platforms that are much favorite for the portrayal of political content (Ching Velasco et al., 2024). In addition, the existing study merely discussed the general aspect of online incivility without viewing the uncivil behaviors of netizens in-depth or from different dimensions. Thus, interrelated dimensions of perceived political incivility, such as disrespectful statements, deceit, and behaviors attempting to stifle ongoing and democratic conversations (Stryker, Conway, Bauldry, & Kaul, 2024) were suggested as the multidimensional construct of online political incivility. Future research could revise the current construct by investigating different dimensions of online incivility to obtain a more precise and insightful finding. The current study only tested the direct effects and can explain the endogenous variable by 43.3%. Thereof, future studies can incorporate digital media literacy (Hasrullah, Arya, & Hidayatullah, 2023; Zhao & Cao, 2024), political efficacy (Lai & Beh, 2025) political fake news sharing (Roshdi, Lyn, & Jie, 2025), perceived risk (Liew, Tan, Sung, Gan, & Lee, 2023) and also can test the generation cohorts (Alfred & Wong, 2022; Boulianne & Shehata, 2022) through the mediating and moderating effects to expand the current framework and significantly contribute to the media and political communication scholarship. Funding: This study received no specific financial support. Institutional Review Board Statement: The Ethical Committee of the Multimedia University, Malaysia has granted approval for this study on 15 July 2024 (Ref. No. RMC/REC/EA/024/2024). Transparency: The authors state that the manuscript is honest, truthful, and transparent, that no key aspects of the investigation have been omitted, and that any differences from the study as planned have been clarified. 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