Investigating Linguistic Abilities and its Relationship with Empathy, Emotional Intelligence and Cognitive Flexibility

Purpose. Languages play an important role in shaping our brain and personality. Numerous studies in the past have found that bilingual and trilingual individuals outperform monolinguals on certain cognitive assessments. In some studies, monolinguals have outperformed the other two groups on emotional tests. Most of the studies have reported mixed findings on this topic, making it difficult to draw conclusions. 
Procedure. For the first time, the present study attempts to examine linguistic ability, empathy, emotional intelligence and cognitive flexibility in an Indian sample of 90 participants (Mage = 26.86 years, SD = 7.45) (28 monolingual, 30 bilingual and 32 trilingual). Each of the participants completed the Interpersonal Reactivity Index Questionnaire, Trait Emotional Intelligence Questionnaire – Short Form and Colour Stroop Test on PEBL (Psychology Experiment Building Language) software. 
Results. One – Way ANOVA revealed statistically significant results for Empathy [F(2,87) = 218.84, p < 0.001], Emotional Intelligence [F(2,87) = 232.19, p < 0.001] and Cognitive Flexibility [F(2,87) = 27.05, p < 0.001]. Mean empathy score was 38.67 for monolingual group, 65.86 for bilingual group and 81.25 for trilingual group. Mean emotional intelligence score was 76.32 for monolinguals, 151.93 for bilinguals and 195.15 for trilingual group. Mean conflict score was 253.24 for monolinguals, 108.29 for bilinguals and 20.64 for trilingual group. Pairwise comparisons and Tukey’s HSD displayed differences across groups, with the trilingual group outperforming the other two groups on all three variables. Results from this study showed large effect sizes (η2): 0.84 for EI, 0.83 for empathy and 0.38 for cognitive flexibility. 
Conclusions. Findings from this study highlight the important role played by languages and the associated benefits they offer. Participants speaking more languages dominated this study as they had better empathy, emotional intelligence and cognitive flexibility when compared to their monolingual counterparts.


Introduction
India is a home to 1.4 billion people roughly where numerous languages are spoken across the country. There is supporting evidence which claims that over 50% of the people globally speak more than one language (Grosjean, 2010). Numerous studies have found that when multilinguals speak in their first language, processing from their secondary languages occur simultaneously, concluding that more than 1 language system works together to encode information (Costa, 2005;Green, 1998;Grosjean, 1989;Rodriguez-Fornells et al., 2005). Language is a cognitive component but carries a lot of cultural aspects too, as the same meaning can be conveyed differently in different languages due to the semantics and interpretation. Some of the variables which are directly affected with one's linguistic capacity are empathy, emotional intelligence and cognitive flexibility. There is some evidence, wherein multilinguals tend to outperform monolinguals but to what degree and the role played by the three variables mentioned is unknown. It becomes imperative to probe into this matter, especially in the Indian context, owing to the number of different languages spoken in the country.
What does Empathy mean and why is it important? Empathy refers to "the ability to tune into how someone else is feeling, or what they might be thinking" (Baron-Cohen & Wheelwright, 2004). According to Wheelwright (2005), empathy plays an important part in social settings by allowing us to perceive people with a deeper insight and to experience an emotion which stems from others' emotions. It is a core ingredient in social interactions as it tends to increase our prosocial behaviour (Gilet et al., 2013). Empathy is rooted to identify, acknowledge and collate the sentiments of others (Davis, 1980;De Wall, 2008;Preston & De Wall, 2002).
Many researchers stipulate that there exists a positive correlation between empathy and emotional intelligence (Schutte et al., 2001). Mayer and Salovey (1997) found that a person with an ideal level of emotional intelligence is not only good at perceiving, understanding and controlling their own emotions, they are most likely capable of extending this power to also understand and manage the emotions of those around them with the highest calibre. Many researchers have studied this relationship with great depth and have concluded that people with greater emotional intelligence also tend to possess greater empathic concern (Caruso & Salovey, 1999; Fitness & Curtis, 2005;Mayer et al., 2001). Empathy is denoted as a psychological variable that is crucial for second language or a foreign language acquisition. Second language learner having high levels of empathy tend to be more skilled at mimicking the pronunciations of someone's first language (Guiora, Beit-Hallahmi et al., 1972;.
Empathy goes hand-in-hand with emotional intelligence as together, they create greater emotional awareness in a person and are also the hallmark of trust. When one of them tends to be low, it significantly affects the other variable. Findings of the past also suggest that when one of those variables is being studied, the other variable should also be taken into account.
Understanding Emotional Intelligence (EI) Better! According to Mayer and Salovey (1997), EI is best understood as the capacity to process emotional information comprises the ability to perceive accurately, appraise, and express emotion; the ability to access and/or generate feelings when they facilitate thought; the ability to understand emotion and emotional knowledge; and the ability to regulate emotions to promote emotional and intellectual growth. Mayer and Salovey (1997) state that a person with optimal level of emotional intelligence is usually better at recognizing and acknowledging their emotions, and also possess the necessary skill-set to understand and manage the emotions of those around them. According to Barrett (2017), people having higher emotional intelligence tend to have learnt greater number of emotion words. They have also created larger and more intense experiences involving emotions. Keeping that notion in mind, it can be understood that bilinguals have a bigger pool of emotional words and its associated concepts.
The Theory of Constructed Emotions states that emotional intelligence is an art which helps an individual to replicate more emotional scenarios from the information that is reserved in an individual's brain, which fit a given emotional setting (Barrett, 2017). Based on this theory, it could then by hypothesized that bilinguals may be more emotionally intelligent, since they have encoded more number of concepts from different languages with different perspectives. Based on the above theory, since multilinguals may be more emotionally intelligent, their ability to switch between languages should also be better than monolinguals. Sometimes, they may also listen to information in one language but process it in the other language by mentally translating it. The mechanism which allows them to do this is cognitive flexibility, which is explained in the subsequent sections.

Digging deeper into Cognitive Flexibility
Executive functions are a group of mental processes which are required when one has to focus and concentrate, usually in situations where falling back on intuitions would lead to negative outcomes (Burgess & Simons, 2005;Espy, 2004;Miller & Cohen, 2001). One of the executive functions is cognitive flexibility.
According to Merian (2010), cognitive flexibility is a mechanism which involves two primary control operations when an individual switches from one task to the other. For example, when a person switches from Task 1 to Task 2, the first primary operation is to curb Task 1 which is of no formal requirement, in order to activate Task 2, which is required at the moment. Being capable to alter perspectives spatially is the simple foundation of cognitive flexibility. Almost all the time, a complex mechanism such as cognitive flexibility is assessed by implementing different types of task switching along with set shifting tasks. One of the most vintage tests which tapped into cognitive flexibility was the Wisconsin Card Sorting Task (Milner, 1964;Stuss et al., 2000). Other tasks tapping into cognitive flexibility include design fluency, verbal fluency and semantic fluency tasks.
Many researchers in the past have claimed that the experience which bilinguals usually undergo in selection and inhibition of languages can be generalized to some other tasks as well, which involve processing of attention and executive functions like cognitive flexibility (Bialystok, 2001;Bialystok et al., 2005). According to Peal and Lambert (1962), bilinguals seem to have a special advantage when it comes to cognitive flexibility and this is primarily due to their lifelong habit of constantly switching between the two languages they speak in. By studying the performance of French monolingual children and French-English bilingual children on a wide variety of different assessments, they found that bilingual children performed significantly better than monolingual children on most of the tests, especially on those components which required symbol manipulation and some reorganization.

Link between Bilingualism and Executive Functions
Research suggests that when an individual gains higher levels of proficiency in a language and increases its usage, it leads to faster switching abilities between the spoken languages, which provides better executive control in the long run. The above findings are in sync with Bialystok's (2011) explanation, that individuals who are fluent in two languages tend to dominate language control processes coupled with improved executive functions.
However, certain disparity does exist. On tasks involving executive functions, some studies have also shown that there is no bilingual advantage, thereby disagreeing with previously reported results. In a previous study, this indifference was found to be true even after carefully matching monolingual and bilingual adolescents on important variables such as gender, age, reading and mathematical skills, verbal and non-verbal IQ, income of the family along with formal education of the parents (in years) (Antón et al., 2014). Upon examining cognitive flexibility, a handful of studies reported the presence of bilingual advantages in specific age groups, like pre-schoolers (Bialystok & Martin, 2004;Bialystok et al., 2006), middle-school children (Garraffa et al., 2015), young adults (Pelham & Abrams, 2014), elderly adults (Bialystok et al., 2014;.

Skills of Cognitive Flexibility
An interesting study done in this domain was that of Prior and Macwhinney (2010). In their study, they made use of the cued-task switching test by wishing to compare monolingual and bilingual college-going students. They found that small switching costs among bilingual students when compared to monolingual students. They attributed their results to improved flexibility which helped bilinguals to shift between mental sets, owing to their lifelong bilingualism.
By using the global-local switching task in one study, Christoffels et al. (2015) were able to recognize the perks of being a bilingual among school students. Within their sample, which comprised of Dutch monolinguals (N = 29) and Dutch and English bilinguals (N = 31), they found smaller switching costs among the bilingual group. They also attributed their findings to the advanced and more efficient cognitive flexibility present among the bilinguals.
More evidence on this front comes from a study where Hungarian-Polish bilinguals and Hungarian monolinguals undertook the social category switching task, after being matched on certain demographic variables such as age, gender, formal education and intelligence levels. Marzecova et al. (2013) revealed larger switching costs by the monolinguals, which reflected a poor performance. Similarly, by using a colour-shape switching task, Wiseheart et al. (2014) have reported much higher switching costs in their monolingual sample, which also suggests a subpar performance. Although the studies mentioned above have glorified the image of bilinguals on an array of switching tasks portraying superior executive functions in them, they do come with their own limitations. The sample size in those studies has been extremely small which hampers reliability supplemented with overly simplistic research designs. Many studies (Gathercole et al., 2014;Hernandez et al., 2013;Paap et al., 2014;von Bastian et al., 2015) which have employed sample sizes as large as 384 participants and have also held different demographic variables constant have reported non-significant results, suggesting that group differences do not exist on switching assessments like the card sorting test, colour-shape task switching test etc, used in previous studies.
Therefore, to counter these disparities and to arrive at concrete results, more research is required in this domain. The evidence on this front is mixed as some studies have found better empathy, emotional intelligence and executive functions and others have not, with respect to one's linguistic abilities.

How does Emotional Intelligence (EI) make bilinguals 'feel different' while using a foreign language?
Some speakers tend to change their own body language, facial expressions and intonation as they speak in a different language. On some occasions, speakers become very loud and energetic and on the contrary, they become extremely quiet and aloof when they undergo a transition from one language to the other. Hence, based on the above observations, it was deduced that behaviour is plastic and it often changes very evidently when it is accompanied by a language switch, ultimately impacting one's empathy and emotional intelligence levels.
By administering the California Psychological Inventory twice on his 76 Chinese-English and Korean-English bilingual subjects, Hull (1987) found that his subjects obtained different scores when they completed the inventory in their L1 (Chinese/Korean) and again in their L2 (English), even though the dimensions which were being measured were the same. This important finding suggests that people can even perceive the same thing differently in a different language, which can affect their cognitive and emotional regulation drastically.
Panayiotou (2004) narrated a story to her English-Greek bilingual sample first in English and after a span of seven days, again in Greek, and recorded their reactions. She received very different reactions from her participants when the same story's narration shifted from English to Greek. Her study also confirmed the notion that bilinguals have different perceptions and expressions whenever there is an alteration in the linguistic medium even though they are presented with the same information (Panayiotou, 2004).

Rationale of the Current Study
Past researchers have focussed on the three variables (empathy, emotional intelligence and cognitive flexibility) independently. However, based on the literature review, it is evident that the three variables play an important role in linguistics and perception together. This is something which was left out in previous studies and will be covered in this paper. To the best of my knowledge, no paper on this topic has been written in the Indian context using Indian languages and sample. This paper takes that into account, making it novel and unique. The claim being made in this paper is that as people gain fluency in more languages, they will score higher across the three variables under consideration. Hence, trilingual group will score the highest, followed by bilinguals and then monolinguals on empathy, emotional intelligence and cognitive flexibility.
Research Questions RQ 1: How does empathy and emotional intelligence differ across people with different linguistic abilities?
Hypothesis: The Trilingual group would score the highest on both the above mentioned variables, followed by the Bilinguals and then, the Monolinguals.
RQ 2: How does cognitive flexibility change with people's linguistic abilities?
Hypothesis: The Trilingual group would have better cognitive flexibility, followed by the Bilinguals and lastly, the Monolinguals.

Participants
This study comprised a total of N = 90 subjects (M age = 26.86 years, SD = 7.45) and they were divided into three groups depending on the number of languages spoken fluently. They were: Monolingual (N = 28, M age = 22 years, SD = 7.57), Bilingual (N = 30, M age = 26.86, SD = 7.97) and Trilingual (N = 32, M age = 31.12, SD = 7.96). Subjects were chosen through Convenience Sampling. The monolingual sample was taken from a single University from Chennai where medium of education was Tamil. The inclusion criteria for the subjects in this study was that they must be above 18 years of age and they must be fluent in at least one language. There was almost equal representation of males and females in this study, with 55.6% of the subjects being males (N = 50) and 44.4% being females (N = 40). Educational and professional background of the participants was diverse as they were in their under-graduation, post-graduation, pursuing PhD or working in a professional organization/start-up.
The monolingual sample comprised of Tamil speaking individuals who were University students. Everyone had completed their schooling and possessed the minimum proficiency required to be included in this study. The bilingual sample primarily spoke Tamil and English. The trilingual sample were fluent in Tamil/Malayalam, Hindi and English. The power analysis of the sample using G Power 3.1 was conducted post hoc, inputting all the parameters and it came out to be 0.998, indicating that the sample size power was high.

Research Design
This was a quantitative study having a between-subject design. The independent variable was the number of languages spoken by an individual having three levels (monolingual, bilingual and trilingual). The dependent variables were empathy, emotional intelligence and cognitive flexibility.
Measures Interpersonal Reactivity Index (IRI; Davis, 1980). The IRI is a self-report measure of empathy. It is a 28-item questionnaire which is scored on a five-point Likert Scale (see Appendix V). This scale has four sub-scales which collectively measure empathy. They are: fantasy, perspective taking, empathic concern and personal distress. Each response is scored from 1 = Does not describe me well and 5 = Describes very well. Higher score is an indicator of greater empathy in an individual. The scale has reported good internal consistency with Cronbach's alpha of 0.79 (Davis, 1980). Over a 75 day period, test-retest reliability also ranged between 0.61 to 0.81 (Davis, 1980). Trait Emotional Intelligence Questionnaire -Short Form (TEIQue-SF; Petrides & Furnham, 2006). The TEIQue-SF is a self-report measure of global trait emotional intelligence. It is a 30-item questionnaire which is scored on a seven-point Likert Scale (see Appendix VI). Out of the 30 questions, 6 questions measure well-being, 6 measure self-control, 8 measure emotionality, 6 measure sociability and 4 measure both adaptability and self-motivation. Each response is scored from 1 = Completely disagree to 7 = Completely agree. Higher score is an indicator of higher emotional intelligence in an individual. The scale has a good internal consistency with Cronbach's alpha of 0.81 (Petrides & Furnham, 2001).

Colour-Stroop Test (PEBL; Mueller & Piper, 2014).
The Colour Stroop Test was administered to assess cognitive flexibility on The Psychology Experiment Building Language (PEBL) software. It comprised of 168 trials totally, out of which 24 were practice trials and 144 were test stimuli. Participants had to select the laptop key which corresponded to the font colour of the stimuli (1 = red, 2 = blue, 3 = green and 4 = yellow) (see Appendix VII). This test measures participants' cognitive flexibility by testing their inhibition and how quickly they are able to adapt to the presenting stimuli. Faster responses with minimal errors suggest a better performance on the test. Less time taken indicates a better cognitive flexibility.

Procedure
Before participation, informed consent was taken from all the subjects and highest confidentiality was maintained (see Appendix A). Their responses were secured and from the basic demographic details, mentioning their name was optional to protect their privacy and to promote honest participation. Data was collected from the participants only after they agreed with the informed consent request. Instructions for the assessments were provided to all the participants beforehand (see Appendices B, C and D).
The questionnaires were administered through a Google Form link and all the participants were required to take the Stroop Test on a laptop. Since the translated version of the two questionnaires was not readily available in Tamil, they first had to be translated from English to Tamil and then back-translated from Tamil to English. This was done with the help of a colleague, who was fluent and well-versed in both the languages. Questionnaires were directly administered to the other two groups. Once the participants filled out both the questionnaires, they performed the Stroop Test on PEBL. Total administration time per participant was roughly 20-25 minutes and responses were available only with the researcher until the end of the study.

Results
To test for parametric assumptions, we ran the Kolmogorov-Smirnov test and checked for Skewness and Kurtosis values. Results were also confirmed by checking for the Histogram and q-q plot distribution. After meeting parametric assumptions, a One-Way ANOVA was run on IBM's Statistical Package for the Social Sciences (SPSS) version 28.0.0.0. (190). Pairwise comparisons were measured using Tukey's and Bonferroni's Post-Hoc tests.
Mean scores on the TEIQue-SF was 76.32 (SD = 31.64) for the Monolingual group, 151.93 (SD = 11.93) for the Bilingual group and 195.15 (SD = 16.93) for the Trilingual group. A One-Way ANOVA showed significant differences in scores on Emotional Intelligence across the three linguistic groups: F(2,87) = 232.196, p < 0.001. Post-Hoc Test indicate that the mean scores on Emotional Intelligence was significantly different across the three groups. Scores for Monolinguals was significantly lower than Bilinguals (p < 0.001), which was significantly lower than the Trilingual group (p < 0.001) with a large effect size Eta Squared (η 2 ) of 0.842.
Mean scores on the IRI was 38.67 (SD = 10.26) for the Monolingual group, 65.86 (SD = 7.53) for the Bilingual group and 81.25 (SD = 5.58) for the Trilingual group. A One-Way ANOVA revealed significant differences in scores on Empathy across the three linguistic groups: F(2,87) = 218.840, p < 0.001. Post-Hoc Test indicate that the mean scores on Empathy was significantly different across the three groups. Scores for Monolinguals was significantly lower than Bilinguals (p < 0.001), which was significantly lower than the Trilingual group (p < 0.001) with large effect size Eta Squared (η 2 ) of 0.834.
Mean conflict score on the Stroop Test was 253.24 (SD = 199.31) for the Monolingual group, 108.29 (SD = 80.09) for the Bilingual group and 20.64 (SD = 41.87) for the Trilingual group. A One-Way ANOVA showed significant differences in conflict scores on the Stroop Test across the three linguistic groups: F(2,87) = 27.057, p < 0.001. Post-Hoc Test and pairwise comparison indicate that the mean conflict score on the Stroop Test was significantly different across the three groups. Scores for Monolinguals was significantly lower than Bilinguals and Trilingual group (p < 0.001), whereas the Bilinguals scored significantly lower than the Trilingual group (p < 0.05) with large effect size Partial Eta Squared (η 2 ) being 0.383. From the above table, it can be inferred that average empathy scores increased as the number of languages spoken in a group increased. Means from the table above suggest highest emotional intelligence by the trilingual group and the lowest by the monolingual group. Bilingual group again, lies in the middle of the two. For both Empathy and Emotional Intelligence, the interaction was significant with p < 0.001. This suggests that all the three groups differ significantly from each other on these variables. Pairwise comparisons below (Table 5 and Table 6) explain where these differences lie. Based on observed means. The error term is Mean Square(Error) = 62.754. *. The mean difference is significant at the .05 level.
The above table reveals where the difference lies within the three groups. All the groups significantly differ from each other with p < 0.001. It can also be inferred from the table that mean difference was the maximum between monolingual and trilingual group, with the latter scoring the highest and the former scoring the least. Bilinguals scored somewhere between the two groups. The table above shows where differences lie within the groups. All the groups significantly differ from each other with p < 0.001.
By looking at mean differences, it becomes evident that the trilingual group scored the highest on emotional intelligence, followed by the bilinguals and lastly, the monolinguals. Mean score of monolinguals is the highest on the Stroop Test, which means that the time taken by them to complete the test was the highest due to the occurring interference. The opposite is true for the trilingual group whereas the bilinguals have displayed an average performance. Note. η2 = 0.01 indicates a small effect; η2 = 0.06 indicates a medium effect; η2 = 0.14 indicates a large effect size The above table shows significant interactions (p < 0.001) for all Reaction Time variables, which shows how differently the groups have performed on the Stroop Test. Multiple comparisons show that all the three groups significantly differ from each other. It becomes clear that performance by the monolinguals on the Stroop Test has been the poorest and on the contrary, the trilingual group were the fastest to respond. Bilinguals displayed an average performance, falling somewhere between the two groups. This implies that the trilingual group were able to overcome the interference effects and respond accurately with the highest efficiency. The trilingual sample significantly outperformed the monolinguals (p < 0.001) and bilinguals (p < 0.05).
Measures used in this study have harvested interesting results, supporting the hypothesis of the study. From the literature cited in this paper, it becomes clear that linguistics do play a very important role in empathy, emotional intelligence and cognitive flexibility. This is reflected in the performance of the three groups as the group which outperformed the other two across the three variables was the trilingual group. This provides more clarity and also highlights the importance of the number of languages spoken as they clearly have an impact on the variables examined in this study. Results of this study can be attributed to the number of languages spoken by an individual as there is high correlation. However, to establish causality, more research is warranted.

Discussion
In this study, an attempt was made to understand how one's linguistic ability influences their empathy, emotional intelligence and cognitive flexibility. As hypothesised, the trilingual group triumphed across the three variables, followed by the bilinguals and lastly, monolinguals. Mean scores of the trilingual group was the highest on IRI and TEIQue-SF, it was the lowest for the monolinguals and bilinguals scored somewhere between the two groups. This indicated that the trilingual participants possessed the highest empathy and emotional intelligence, while monolinguals had the lowest. Mean conflict score on the Stroop Test was the lowest for the trilingual group, suggesting the better performance. On the contrary, mean scores for monolinguals was the highest, suggesting a poorer performance. The number of errors committed by monolinguals was also the highest and it was the lowest for the trilingual group. Bilinguals again, scored somewhere between the two groups in terms of mean conflict score and errors committed. This indicated better cognitive flexibility of the trilingual group to efficiently be able to switch between congruent and incongruent stimuli, which was not the case for monolinguals. One-Way ANOVA produced statistically significant results (p < 0.001), thereby confirming the hypothesis. Tukey's HSD and Pair-wise comparisons for all the variables provide greater clarity in the results.
In the recent decades, the scientific community has observed a speedy increase in different experiments which have found multilingualism extending its roots over and above cognitive levels, also having an impact on variables apart from executive control (Barac & Bialystok, 2011). Previous studies have also been able to link multilingualism with greater creativity in behaviour and divergence in thought processes, encompassing cognitive flexibility (Kharkhurin, 2008(Kharkhurin, , 2010. There is growing evidence stemming from previous research which suggest that there exists a strong correlation between multilingualism and personality profiles, as more fluent and efficient speakers having broad linguistic skill-sets consistently score more on empathy along with open-mindedness (Dewaele & Stavans, 2012;Dewaele & Van Oudenhoven, 2009;Korzilius et al., 2011). More than half of the published studies which have looked on foreign language and its relationship with multilingualism have included empathy as their predictor variable Hu et al., 2012;Ozanska-Ponikwia & Dewaele, 2012;Reiterer, 2011;Rota & Reiterer, 2009). A past study considered multilingualism as their independent variable and they reported that as individuals learn to speak more number of languages, they tend to score very high on other factors like cultural empathy, emotional intelligence, open-mindedness and prosocial behaviour (Dewaele & Stavans, 2012).
Quite often, multilinguals who use multiple foreign languages tend to be more superior on cognitive empathy as well. This reflects their ability to engage in more skilful conversations as they are able to view the world from the interlocutor's perspective. In one study, researchers arrived at an interesting result which favoured monolinguals. They found no correlation in the scores of children who were raised as bilinguals/trilinguals with high empathy levels. This indicates that even if an individual's upbringing has been in an environment where more than one language was spoken fluently, it is not sufficient by itself to increase their empathy levels (Dewaele & Wei, 2012).

Conclusions
The primary objective of this paper was to understand the role played by linguistics across three variables: empathy, emotional intelligence and cognitive flexibility. These variables tend to have an independent effect on one's linguistic ability. Past research has found that as people gain fluency in more languages, their performance and scores across different variables tends to improve, significantly outperforming monolinguals. The results stemming from this paper also support existing literature as the Trilingual group scored the highest in all the three variables under consideration, followed by the Bilinguals and lastly, the Monolingual group.
Mean scores on Emotional Intelligence for Monolinguals, Bilinguals and Trilingual group suggest that a person is more emotionally intelligent and aware when they are fluent in greater number of languages. Mean scores on Empathy for Monolinguals, Bilinguals and Trilingual group suggest that a person's ability to understand and recognize emotions is likely to increase when they are fluent in more languages. Low mean scores of the Trilingual group indicate a better performance on the Stroop Test, as individuals were able to switch between congruent, neutral and incongruent conditions faster with better accuracy. Higher mean values of Monolinguals suggest that individuals were very slow to respond to the stimuli which led to higher conflict score and errors. It can hence, be deduced that languages do have an important role to play when the above variables were tested across the three groups.
Even though preliminary conclusions can be inferred from the results presented above, more research is warranted for these results to be replicated in the future studies to come. That would deepen understanding and help us connect linguistics with emotional and cognitive regulation with empirical data, helping us to expand our current pool of knowledge.

Strengths, Limitations and Future Directions of the Current Study
There are many facets of this study which strengthen its design and results produced. First, a sample size of 90 is large enough for the data to be normally distributed and to eliminate certain biases which are otherwise present in a study with a small sample size. Second, males and females were almost equally represented in the data collection of the study, thereby eliminating gender bias. Third, greater control was established in the study by selecting a fixed number of languages for the bilingual and trilingual groups. Fourth, measures used in the study for data collection have very high internal consistency and reliability, which elevated the quality of data collected. Fifth, by incorporating a mixed approach of quantitative and experimental study and running analyses on SPSS, results are more reliable and can be generalized to the larger population as well. Since results were quantified with the help of parametric test, any form of subjectivity and researcher's bias was eliminated while interpreting results. Sixth, by having almost equal representation within the three groups which were part of the study, some forms of inequalities and biases were extinguished. Seventh, ethical clearance was also granted for this study by the University's IRB committee (IRB Approval number: 2021/11/02/FSP/EXP).
However, unlike any other study, the present study also carries a few limitations with itself. Firstly, most of the participants in the monolingual sample were males and hence, gender bias was present. Future studies can rectify this by incorporating a diverse and a mixed sample. Secondly, the two questionnaires used in the study were not readily available in any of the Indian languages. Therefore, they had to be translated in Tamil for the monolingual sample. However, their psychometric properties were not tested. In doing so, some questions may have been interpreted differently which could hinder responses as manual translation may tamper with the psychometric properties of the questionnaires used. Later studies can keep this in mind and use the existing translated versions of the questionnaires instead. Third, the study comprised of only Tamil-monolinguals. By having just one language group, it becomes difficult to generalize the results of the study to a larger population. Future studies can include monolinguals speaking different languages to include more diversity. Fourth, the time taken per participant to complete the assessments was roughly 20-25 minutes. Fatigue may have played a role while participants were entering their responses. Fifth, fluency levels in the bilingual and trilingual group could be very different. It is very unlikely that the participant would be equally fluent in the languages they speak. For example, a Tamil-Hindi-English trilingual may be using Hindi and English for their day-to-day communication and Tamil may be used rarely/occasionally. If this was the case, then that participant is closer to being a bilingual rather than a trilingual and may eventually forget/become less fluent Tamil (in this example) in the future.
Although 100% causality cannot be established with the results this study has yielded, it does provide innovative insights. Past studies have produced mixed findings and this study supplements information to the existing pool of literature. It is hoped that future studies will build on this topic and eliminate the limitations, so that more authentic and reliable results are produced which can be generalised to the wider population. bettered the quality of my research. I have absorbed immense learnings from her and hope to carry those with me in the future work I partake.
I would also like to thank my colleague who offered his help with the translation of the questionnaires from English to Tamil, during the data collection phase from the monolinguals. This research would not have been possible without his help, for which I am eternally grateful. I would also like to extend my thanks to all the participants who made this research possible. I appreciate their patience to provide the required data with which I was able to make progress.
I am thoroughly grateful to all the authors and scholars whose work has been cited in this paper. By referring to their work, I was able to develop my hypothesis and build an elaborate literature review. Their work was exceptional and I hope to add some more literature to it. Lastly, I would like to thank FLAME University for providing me with this opportunity and enriching my grasp on research and academic writing.

ADHERENCE TO ETHICAL STANDARDS
Ethics declarations. All ethical implications of this empirical research were considered beforehand and were approved by the Institutional Review Board (IRB@ flame.edu.in) at FLAME University, Pune. The research was conducted under the guidelines put forth by FLAME University. The research was also completed within the time frame (1 year) set by the university's IRB committee.
Data availability statement. All the necessary materials pertaining to this research paper can be found here: https://osf.io/fpaxz/?view_only=342fa5a6ce064a319 9fc50cf89f4f0f9