Perceived Wellbeing, Happiness, and Related Challenges among Indian College Students

Abstract

The present study aimed to examine the conceptualisation and determinants of happiness among Indian college students and identify areas in which they require help. The sample consisted of 362 students in the age group of 18 to 30 years (M_age = 20.9, SD_age = 2.25) from two locations in North and South India. Online forms, including the Satisfaction with Life Scale (Diener et al., 1985), Positive and Negative Affect Schedule (Watson et al. in J Pers Soc Psychol 54:1063–1070, 1998) and a qualitative survey, were used to collect the data. Results indicated that participants from institutions that offered mental health initiatives reported higher well-being than those who did not. Findings from the qualitative survey suggest that most participants conceptualised happiness in terms of need for satisfaction and well-being. The responses also indicated that leisure activities and time spent with the family determined the participants’ happiness. Concerns related to interpersonal relationships made the participants unhappy, and most of them were willing to seek help in this regard. Factors beyond immediate self and interpersonal networks had a limited role in participants’ perceived happiness and unhappiness. Study findings could guide the development of customised mental health and well-being promotion initiatives to meet the needs of Indian college students.

Introduction

It has been estimated that over 40% of the global population is below 24 years of age (United Nations, 2019). Global estimates issued by the World Health Organization (WHO, 2001) suggest that 20% of young people confront mental disorders. The significant majority of these young people reside in low- and middle-income countries (LMIC) and have low access to mental health care (Lu et al., 2018). According to the decennial Census of India (2011), every fifth person in India is an adolescent (10–19 years), and every third person falls in the category of youth (10–24 years). This underlines the dominant representation of young people in the Indian population. Further, the WHO (2013) Mental Health Action Plan for 2013–2020 advocates the delivery of holistic and inclusive mental health and social care encompassing community-based initiatives. Nevertheless, there is evidence to suggest the tremendous lag between the burden of mental disorders and accessible services in LMICs in general (Kohrt et al., 2018) and India in particular (e.g. Gururaj et al., 2016; Sagar et al., 2017). According to the National Institute of Mental Health and Neuro-Sciences (Gururaj et al., 2016), the proportion of mental health services to India’s population is less than two per lakh people in every state. Moreover, Sagar et al. (2020) reported that mental disorders impacted as many as one in seven Indians in 2017. Sagar et al. (2020) further affirmed the gravity of the situation, stating that mental illness accounts for one of India’s main causes of non-fatal disease burden. Shifting the focus to happiness at the other end of the spectrum, India was ranked at 144 (out of 156 countries) in the annual United Nations’ World Happiness Report for 2020 (Helliwell et al., 2020).

Need to Focus on Mental Health and Well-Being Among Youth

Mental health is defined as ‘a state of wellbeing in which an individual realises his or her own abilities, can cope with the normal stresses of life, can work productively and is able to make a contribution to his or her community’ (WHO, 2018). The closely related construct of subjective well-being (Diener, 2000) is understood as an overall cognitive and affective evaluation of how satisfied individuals are with their life and their experience of both positive and negative states. While these constructs are important for all, they assume greater significance in youth, especially in LMICs like India, in light of the status and services mentioned previously. It is widely understood that the age of 10–24 years is crucial in preventing and remedying mental health issues (WHO, 2014). Chen and Page (2016) identified that students’ transition from adolescence to young adulthood could be unstable, leading to decreased well-being. Ogorchukwu et al. (2016) explored the knowledge of late adolescents towards mental health and found that most of them lacked a practical understanding of mental illness. The disruption caused by the recent pandemic has forced students to adapt to a completely new mode of learning leading them to face a number of issues (Govindarajan & Srivastava, 2020). There is a great feeling of fear and uncertainty among affected college students, wherein the pandemic has caused panic, anxiety, and depression (Chaturvedi et al., 2022; Xu & Huang, 2022). Uhlhaas et al. (2020) commented on the lacunae in youth mental health care, mentioning how existing systems have emphasised younger or older demographic groups, thereby neglecting young people. Within this context, the present study is focused on young people in higher education settings.

Understanding Well-Being Among Young People in College

Mental health problems are common among college students, and it is important to understand these problems’ patterns (Bruffaerts et al., 2018). A study among college students in the USA found that forty per cent of participants developed mental health issues for the first time during college (Gibbons et al., 2018). Attending college is stressful for most college students (Jaisoorya et al., 2017). Coping with academic stress, changes in their environment, and living away from the family for the first time all present various prominent challenges (Chadda, 2018). Recent times have seen an emerging global emphasis on psychological well-being in the higher education space (e.g. Lambert et al., 2019; Orygen, The National Centre of Excellence in Youth Mental Health, 2017), with a growing understanding of the association between student well-being and academic achievements (Hoare et al., 2017; Oades et al., 2011). Young et al. (2020) affirm the benefits of investing resources towards the well-being of university students.

As a step in this direction, many studies have looked at the determinants and correlates of student happiness and well-being (Antaramian, 2017; Brannan et al., 2013; Chakraborty et al., 2018; Chan et al., 2005; Mangeloja & Hirvonen, 2007). Some prominent research from diverse locations over the past two decades has been presented here. Chan et al. (2005) investigated the determinants of happiness among students in an Australian university. They identified that schoolwork, time management, and relationships formed in the university led to high life satisfaction levels. Mangeloja and Hirvonen (2007) replicated the study by Chan et al. (2005) in Finland and found that social relationships, resources, educational environment, personal goals, and extra-curricular activities influenced student satisfaction. Brannan et al. (2013) explored cross-cultural differences in well-being among college students from Iran, Jordan, and the USA. They found that while perceived social support from family predicted students’ well-being in all three countries, support from friends predicted well-being only among students from Jordan and the USA. Antaramian (2017) asserted that students from a mid-Atlantic university who reported very high life satisfaction had a significant advantage over others in better academic performance, greater engagement, self-efficacy, and lower stress levels. Working with Indian college students, Chakraborty et al. (2018) identified that time spent with family and friends and job prospects significantly enhanced students’ happiness. They also found that dwelling on memories and substance addiction hampered participants’ happiness.

Examining the Situation with an Indian Focus

The inadequacy of mental health services in LMICs like India (Gururaj et al., 2016; Hanlon et al., 2014) is exacerbated by the absence of a robust policy to promote mental health among young people in India (Hossain & Purohit, 2019). Gaur and Ram (2016) noted that as many as 11–31 million Indian youths suffered from various mental health conditions. Given the massive load of untreated mental health concerns among Indian youth, Gaiha et al. (2020) discuss apprehensions about their social and economic future. The growing focus on youth mental health in India has led to the development and implementation of interventions to prevent mental illness (e.g. Mehrotra et al., 2017) and promote well-being (e.g., Michelson, et al., 2020; Toussaint et al., 2020) among students. Some others (e.g. Ahuja et al., 2017; Maulik et al., 2017; Mehrotra et al., 2017) have focused on reducing stigma associated with mental health issues among college students in India.

Nevertheless, Gaiha et al. (2020) assert the limited understanding of the level of mental-health-related stigma among young Indians. Parikh et al. (2019) emphasise the importance of understanding contextual aspects to provide relevant and feasible solutions in such a setting. To sum up, there is a need to build the conversation around how mental health promotion among Indian youth and educational settings offers a good milieu for this. Mehrotra et al. (2013) recommend using everyday language and emphasis on mental well-being to improve outreach, accessibility, and uptake of interventions among Indian youth. Furthermore, there is evidence for a greater success of mental health initiatives if they account for people’s understandings and issues (Armstrong et al., 2000). The current study was designed in light of all these factors. The researcher briefly explains the focus and rationale of this study in the next section.

Current Study

This research examined well-being among Indian college students. It also gathered insight into how they conceptualise happiness and identify the determinants of their happiness and unhappiness and areas in which they need help. Besides gathering a better understanding of how this significant demographic group conceives their happiness and unhappiness, it is also vital to get information regarding the challenges they face and areas in which they require support. Platt et al. (2020) recommend seeking students’ opinions of mental health and allied services available to them to modify these offerings for greater benefit and utility. Wasil et al. (2020) further emphasise the relevance of such research in LMICs such as India, characterised by a high burden of mental health concerns and limited treatment access. The knowledge of a cohort-specific understanding of well-being may facilitate the development of nuanced and contextualised positive psychological interventions and the selection of relevant interventions from those already available (Hamling et al., 2020). Therefore, current findings could enhance mental health awareness efforts and initiate culturally and contextually relevant interventions among college students in India.

Methodology

Participants

Participants were an opportunity sample of college and university students aged between 18 and 30 years (M_age = 20.9 and SD_age = 2.25). The sample was collected mainly from two locations—North India (National Capital Region—NCR, Delhi) and South India (Chennai). Participants were recruited through personal networks by sharing the study link among potential respondents via email and other social media platforms. The data for the study were collected between May 2019 and April 2020. The study’s inclusion criteria were participants between 18 and 30 years enrolled in Indian educational institutes. Participants outside the age range (1.5%) and those from different locations apart from NCR and Chennai (0.8%) were excluded from the study. Thus, of 462 responses received, the data for 362 students (78.36%) were complete and therefore considered for the present study. Although there is no specific recommendation for determining sample size for qualitative surveys like this study, a larger sample size is preferable for such a medium of data collection than in-person data collection strategies (Braun & Clarke, 2013; Braun et al., 2020). Keeping in mind the commonly accepted upper range of 400 respondents (Fugard & Potts, 2015), the present sample size was deemed appropriate. Table 1 shows the demographic details of the sample.

Table 1.

Demographic details of the study sample

Variable	Category	n (Percentage)
Gender	Male	127 (35%)
	Female	235 (65%)
Type of Institution	Government	89 (25%)
	Private	273 (75%)
Qualification	Undergraduate	286 (79%)
	Postgraduate	76 (21%)
Location	North India	298 (82.3%)
	South India	64 (17.7%)

n denotes the number of participants in each group

Measures Used

The online form circulated among participants was divided into three sections, as explained next.

Section A included a note about the study background, consent form, and demographic information sheet. Respondents confirmed their informed consent before proceeding with the rest of the form. The form offered information about data confidentiality and the right to withdraw from participation.

Section B contained the following scales to assess subjective well-being.

1. Satisfaction with Life Scale (SWLS; Diener et al., 1985): SWLS is a 5-item scale that measures an individual’s overall cognitive judgment of their satisfaction with life. Participants rate their responses on a 7-point Likert scale, ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). For the present study, the Cronbach alpha for this scale was 0.74. Dahiya and Rangnekar (2020) have previously standardised this scale in the Indian context.

2. Positive and Negative Affect Schedule (PANAS; Watson et al., 1988): PANAS is a 20-item scale to measure whether the individual is experiencing more positive or negative emotions. The scale has 10 items to measure positive affect and 10 items to measure negative affect, rated on a 5-point Likert scale ranging from 1 (very slightly or not at all) to 5 (extremely). Cronbach alpha was 0.85 in the present study. The scale has proven reliable and valid in the Indian context (Dahiya & Rangnekar, 2019).

Section C consisted of a qualitative survey anchored on the topic of student well-being. The researcher crafted four open-ended questions for this purpose. Research questions revolved around students’ ideas of happiness, factors causing them happiness and unhappiness, areas in which they would like to receive help, and whether their institution offered mental health initiatives. A sample question is ‘What does happiness mean to you?’.

Data Analysis Procedures

All responses collected via the online survey were coded in an excel sheet to ensure confidentiality. Using Statistical Package for the Social Sciences (SPSS 25), independent sample t tests were conducted to compare participants’ scores on SWLS and PANAS based on demographic variables and institutional access to mental health initiatives.

The researcher used content analysis to analyse the open-ended textual responses received for Section C of the online form. The responses varied from a single word to multiple sentences. Several readings of the responses ensured sufficient immersion in the data. The preparation phase started with deciding to analyse only the manifest content. After making sense of the data set as a whole, the researcher followed an inductive approach to content analysis. Following an inductive or bottom-up approach (Elo & Kyngas, 2008), the researcher coded the data and looked for meaningful patterns in the entire data set. Responses in the form of sentences were translated to single word responses based on textual meaning to help with the coding process. Emergent response categories were identified and formulated for each research question. The researcher sent out the responses to professionals in the field and engaged in frequent dialogue, often revising the codes and categories as required (Elliott et al., 1999; Graneheim & Lundman, 2004). The professionals and the researcher developed guidelines based on existing theories and past experiences to help make inferences to the research questions (White & Marsh, 2006). The investigator thereafter reviewed all categories thus identified to ensure consistency of the process. Grouping similar categories into broader higher-order categories followed this initial coding process (Burnard, 1991; Dey, 1993). Three such higher-order categories were formulated and used across all the research questions in the present study. Next, the researcher computed each higher-order category and sub-category frequency, along with the corresponding percentages. In cases where a participant shared multiple responses to a single question, these were counted under various sub-categories wherever appropriate. Thus, the calculation of percentage used the number of responses and not respondents for every question. Findings obtained through these analyses are available in the next section.

Results

Findings from the t tests revealed a significant difference in life satisfaction for variables—gender, type of institution, qualification, location, and mental health initiative. Table 2 represents the results of the t tests, along with the levels of significance. To elaborate, students from government institutes reported higher life satisfaction than those from private institutes.

Table 2.

Comparison of groups on variables of interest

Variable	Group (n)	SWLS		t value	PANAS		t value
		Mean	SD		Mean	SD
Gender	Male (127)	16.22	6.2	1.83	57.7	9.5	0.008
	Female (235)	17.51	6.3		57.8	10.04
Type of institution	Government (89)	18.57	7.4	2.52*	57.82	11.22	0.01
	Private (273)	16.57	5.9		57.84	9.4
Qualification	Undergraduate (286)	16.34	6.01	3.2**	58.2	9.28	0.74
	Postgraduate (76)	19.5	7.06		57.2	11.61
Location	North India (297)	15.73	5.31	8.09**	57.65	10.09	0.38
	South India (64)	23.38	7.2		58.75	8.85
Mental health initiative	Yes (169)	18.49	6.73	4.93**	58.41	9.61	1.35
	No (168)	15.24	5.28		56.98	9.88

n denotes the number of participants; SWLS—Satisfaction With Life Scale; PANAS—Positive And Negative Affect

^*p < 0.05; **p < 0.01

Similarly, participants enrolled in postgraduate programs reported better satisfaction with life than participants enrolled in undergraduate programs. It was found that participants from South India reported better satisfaction with life than participants from North India. Further, participants from institutes offering mental health initiatives scored significantly higher on life satisfaction than their counterparts from colleges without mental health initiatives. No significant difference was found between males and females for life satisfaction and between all groups for positive affect and negative affect.

Next, the findings for the open-ended questions are presented from section C. The researcher consolidated the categories that emerged from the content analysis under three higher-order categories—self-oriented, interpersonal relationship-oriented, and beyond self. Figure 1 represents an overview of the categories that emerged from participant responses to questions in the qualitative survey.

1. Self-Oriented: This category included all responses focused on self-related aspects, wherein respondents’ entire emphasis was on themselves only and did not include other people.

2. Interpersonal relationship oriented: This category included all responses focused on the respondent’s relationship with significant others, such as family and friends. The responses were related to how the association, interaction, and behaviour of the significant other impacted the respondent’s happiness or unhappiness.

3. Beyond the self: This category included all responses where respondents attributed their happiness or unhappiness to factors beyond their immediate self and social network. These responses included larger social, political, and environmental issues. Across all research questions, the least number of responses emerged under this category.

Fig. 1.

Overview of the categories identified Note. n denotes the total number of responses for the research question ^aSocial gathering is only

Responses that were unique and did not fit into any of the categories mentioned earlier were clubbed under the label ‘Miscellaneous’. Table 3 represents the frequency and percentage of the responses under each category, along with corresponding sample responses.

Table 3.

Frequency, percentage, and exemplar responses under each category

Research question, N	Self-Oriented n (%), ER	Interpersonal relationship Oriented n (%), ER	Beyond the Self n (%), ER	Miscellaneous n (%), ER
What does happiness mean to you? 369 responses	Satisfied needs 106 (21.7), being content with what you have	Family 41 (11.1), making parents proud	Ability to help 11 (2.9), helping poor people	19 (5.1), a few simple things, everything
	Well-being 60 (16.2), peace of mind	Interpersonal Others 34 (9.2), good social circle	Environment 3 (0.8), watching nature
	Leisure activities 44 (11.9), exciting adventures	Friends 18 (4.8), having relatable friends	Spiritual activities 2 (0.5), practice humanity
	Work 23 (6.2), achieving my goals	Romantic (1), my boyfriend
	Food 20 (5.4), having my morning coffee
	Material goods 12 (3.2), having lots of money
What makes you happy? 717 responses	Leisure activities 155 (22.1), a trip to the mountains	Family 99 (13.8), time spent with family	Environment 19 (2.6), bird watching on the terrace	16 (2.2), being open-minded, puppies
	Food 75 (10.4), good food	Friends 79 (11), meeting my friends	Ability to help 16 (2.2), doing something that makes others happy
	Well-being 51 (7.1), taking things positively	Romantic relations 24 (3.3), talking to my boyfriend	Spiritual activities 6 (0.8), spiritual connections
	Work 51 (7.1), satisfaction with work	Social gathering 22 (3), attending festivals
	Satisfied needs 49 (6.8), having my personal space	Interpersonal others 12 (1.6), people I love
	Material goods 43 (5.9), good clothes
What makes you unhappy? 459 responses	Work-related pressure 82 (17.9), unable to complete assignments	People’s behaviour 132 (28.7), people arguing	Social and political issues 28 (6.1), lack of safety	46 (10), staying at home and doing nothing, depends on the condition
	Poor self-regulation 54 (11.8), lack of control over emotions	Dysfunctional relations 50 (10.9), being with my family	Environment 12 (2.6), messy or disorganised places
	Unsatisfied needs 44 (9.6), unmet expectations
	Fears 11 (2.3), stage fear
Area of your life in which you wish you had some help? 256 responses	Work 53 (20.7), future career options	Relationships 78 (30.5), my relationship with my parents	Nil	11 (4.2), change the system, all areas of life
	Self-regulation 38 (14.8), healthy lifestyle
				No help 76 (29.7)

N indicates the total number of responses to each question; n indicates the total number of responses under each sub-category; and ER stands for exemplar response

The following section describes the response categories that emerged for each research question. The researcher presented the responses organised across the higher-order categories and briefly explained what they entailed to facilitate understanding. For each research question, the responses categorised as ‘miscellaneous’ are mentioned in Table 3 but not explained separately.

Participants’ Conceptualisation of Happiness

Self-Oriented: Within this category, maximum responses conveyed that satisfied needs in terms of fulfilment of expectations, demands, and desires represented participants’ idea of happiness. Further, participants also conceptualised happiness in terms of well-being (aspects related to thoughts, feelings, and behaviours accounting for physical and mental well-being), leisure activities (voluntary activities for enjoyment and relaxation), work (engagement or achievements in work-related tasks), food (equating happiness with food in general or specific food items), and material goods (possession or pursuit of tangible items).

Interpersonal Relationship Oriented: In this category, the maximum number of responses indicated that participants defined happiness in terms of behaviour, thoughts, and feelings related to the family. Other responses focused on interpersonal relations (relationships in general without specifying the nature of relation) and friends (aspects related to friendship). In relatively few responses, participants conceptualised happiness as romantic relationships (behaviour, thoughts, and feelings towards a significant other).

Beyond the Self: The maximum number of responses conceptualised happiness as the ability to help (activities or services performed for the community’s welfare or society). Fewer responses described happiness as the environment (features or aspects of the surroundings) and spiritual activities (performing spiritual activities or seeking meaning in something).

Perceived Determinants of Happiness

Self-Oriented: Under this category, most of the responses indicated that engaging in leisure activities (voluntary activities for enjoyment and relaxation) was the source of the participant’s happiness. The next most frequent sub-categories were food (equating happiness with food in general or specific food items), well-being (aspects related to thoughts, feelings, and behaviours accounting for physical and mental well-being), work (engagement or achievements in work-related tasks), satisfying needs (fulfilment of expectations, demands and desires), and material goods (possession or pursuit of tangible items).

Interpersonal Relationship Oriented: Within this category, the maximum number of responses indicated family as a source of happiness which included thoughts, feelings, and behaviour related to them. The responses also revealed other determinants such as friends (aspects related to friendship), romantic relations (behaviour, thoughts, and feelings towards a significant other), social gathering (interacting or engaging with people in small or large groups), and interpersonal others (relationships in general without specifying nature of relation).

Beyond the self: Most responses under this category indicated environment (features or aspects of the surroundings) and ability to help (activities or services performed for the welfare of the community or society) as determinants of happiness. The least frequently occurring category was spiritual activities (performing spiritual activities or seeking meaning in something).

Perceived Determinants of Unhappiness

Self-oriented: Maximum number of responses revealed that work-related pressure (stress and pressure from work/academics) was a determinant of the participant’s unhappiness. Other unhappiness determinants were poor self-regulation (inability to control or monitor one’s own emotions, behaviour, and thoughts) and unsatisfied needs (unsatisfied desires, expectations, needs, or demands). Fear (of situations or things perceived to be painful, dangerous, and harmful) also emerged as a reason for unhappiness.

Interpersonal relationship oriented: Within this category, most responses indicated people’s behaviour (certain behaviours that society or the respondent disfavour) as a determinant of unhappiness. Dysfunctional relations (disturbed or broken relationships) was another source of unhappiness for the participants.

Beyond the self: In this category, the maximum number of responses revealed social and political issues (injustice towards others or conflicting ideologies) that made the participants unhappy. Aspects from the environment (features of the surroundings) emerged as another determinant of unhappiness.

Areas Identified for Seeking Support

Self-oriented: The majority of the responses indicated work (improving performance or achievements in work-related tasks) as an area requiring support. It included support in making career decisions, improving their concentration, etc. Responses also revealed self-regulation (managing and controlling one’s thoughts, feelings, and behaviour) as an equally important area where participants required help with their mental health, improving their self-esteem, managing their emotions, and so on.

Interpersonal relationship-oriented: All responses under this category revealed a broad area—relationships (included responses such as relationships and issues with parents and family). The maximum number of responses revealed relationships as an area without indicating the nature or type of relationship that require help or support.

Beyond the self: Only one response was received under this category and therefore this was not considered a separate category.

Discussion

Young adults are highly susceptible to developing mental health problems and tend not to seek help (Gulliver et al., 2010). India, in particular, reports a substantial treatment gap along with numerous barriers that prevent young adults from seeking help (Gururaj et al., 2016). This emphasises the need for mental health interventions that are culturally based and account for the needs of Indian youth (Mehrotra, 2020). To this end, the researcher aimed to examine the conceptualisation and determinants of happiness among Indian college students and identify potential areas requiring help.

The findings suggest a significant difference among participants’ life satisfaction based on demographic variables. Students studying in government institutions reported higher life satisfaction than those in private institutions. Contrary to the findings, previous studies (e.g. Moghnie & Kazarian, 2012; Singh & Junnarkar, 2014) have reported that students studying in private institutions had better life satisfaction and quality of life than government institutions. Results also indicated that students enrolled in undergraduate programs reported lower life satisfaction than students in postgraduate programs. This finding aligns with previous findings suggesting that life satisfaction increases with age (Bibi et al., 2015). Also, students residing in North India reported lower perceived life satisfaction than students from South India, which indicates the role of cultural difference in predicting life satisfaction (Bibi et al., 2015). Like Deb et al. (2020), and no significant difference was found between genders in life satisfaction. Students enrolled in institutions that provide mental health initiatives reported higher life satisfaction than those without institutional provision of mental health services. Previous studies (e.g. Mehrotra, 2013; Young et al., 2020) have emphasised the importance of including well-being programs in educational institutes to improve college students’ well-being. This reinforces the importance of mental health initiatives in educational institutions.

Wasil et al. (2022) in their study illustrated, through 3 questions, how open-ended surveys can be a useful and feasible way to gather input from students in low- and middle-income countries. The present study incorporated a similar strategy of asking 4 open-ended questions related to happiness. Three categories emerged based on the content analysis, namely self-oriented, interpersonal relationship oriented, and beyond self. It was found that participants’ idea of happiness and perceived determinants of happiness and unhappiness were predominantly self-focused. Previous studies have shown that persons from collectivistic countries evaluate their happiness based on relationships with others (Lu & Gilmour, 2004; Ye et al., 2015). The respondents’ individualistic focus seems to suggest otherwise. A plausible explanation for this could be cultural fusion, where people from collectivistic countries adopt individualistic countries’ attitudes and behaviour (Lu & Gilmour, 2004). The majority of the participants defined happiness as their need satisfaction and well-being, while the determinants of their happiness were leisure activities and their family. These findings are aligned with previous studies (e.g. Brannan et al., 2013; Chakraborty et al., 2018; Chan et al., 2005; Mangeloja & Hirvonen, 2007), highlighting the role of extra-curricular activities, relationships, and personal goals in student’s well-being. The present paper also revealed relationships, self-regulation, and work as primary areas with which college students need help. These findings emphasise the importance of involving young people when designing paradigms and practices for youth mental health, as suggested by Platt et al. (2020) and Uhlhaas et al. (2020). The data from the qualitative questions augmented our understanding of areas of happiness in college students. These perceived areas of happiness and well-being could help stakeholders and other individuals strengthen training modules and other initiatives to revamp the mental health. This discovery helps us identify core areas in a student’s life which could help researchers and other stakeholders such as policymakers, educational institutes, and communities to work towards enhancing the self-development of young adults and help tackle their areas of concerns and prominent challenges.

Study Limitations and Future Implications

It is imperative to acknowledge the limitations of the study to gain an insight into the findings and plan for future research in this area. Study participants included English-speaking students with internet access from two predominantly urban sites. This sample cannot represent Indian college students at large, encompassing students from diverse social, cultural, and linguistic backgrounds. The study only focused on students at large; an analysis of differences in the responses for participants from North and South India could be performed to understand the subcultural differences among students. Next, the survey used in this study consisted of a few open-ended questions. However, it did not allow further probing or in-depth responses, limiting the researcher’s knowledge of the participants. Finally, this study took only students’ perceptions into account without any triangulation by considering other important stakeholders’ inputs.

The present study indicates broad areas in which the participants are happy and unhappy or require help and presents an inadequacy of mental health initiatives by Indian educational institutions. These results could help understand the concerns of young adults in an LMIC (Platt et al., 2020) and how this could prove vital in understanding the population’s needs while designing relevant interventions. Recognising the cultural variations that exist, previous studies have reported different determinants of happiness and unhappiness among college-going youth across various cultures (Chakraborty et al., 2018; Chan et al., 2005; Mangeloja & Hirvonen, 2007). Therefore, the present study also highlights the importance of understanding how demographics influence happiness. Understanding the needs of young adults and knowing what makes them happy and unhappy could help take relevant steps to foster well-being and mitigate distress. Instead of a top-down approach to offering mental health interventions, educational institutions and mental health professionals could first understand the students’ needs and design more suitable mental health interventions.

In the midst of the COVID-19 outbreak, the lockdown was bound to have adverse effects on the public’s mental health (Xu & Huang, 2021). As a result of the virus’ widespread, more than a third of the world’s population has been placed under lockdown with restricted movement (Kaplan et al., 2020). The uncertain circumstances surrounding school and college examinations, as well as job availability, have caused distress to students around the world (Rehman et al., 2020). The coronavirus has raised copious concerns about the psychological distress around the globe, and Xiang et al. (2020) have argued for proactive actions regarding mental health. Existing literature indicates the lack of mental health services and professionals in LMIC’s like India (Gururaj et al., 2016; Kohrt et al., 2018; Sagar et al., 2017). Given the lack of resources, the emphasis for improvement in mental health is mostly given to children and older adults while neglecting the young adults’ needs. The well-being of college students is of great concern since they constitute a large part of the Indian and global population (United Nations, 2019). Thus, the study reported various factors of happiness, unhappiness, and areas of improvement, such that the results may guide the design of suitable mental health interventions for Indian college students. Institutes and other stakeholders can use the findings of the present study and other scientifically proven initiatives (Herbert & Manjula, 2022; Mehrotra, 2013; Toussaint et al., 2020) as a guide to further understand what area (self, interpersonal, or beyond) should they focus on while designing the initiative.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of Data and Material

The datasets generated during and/or analysed during the current study are available from the author on reasonable request.

Declarations

Conflict of Interests

The author declares no conflict of interests.

Consent to Participate

Consent was taken from the participants to use their responses for academic purposes.

Ethical Approval

The researcher used guidelines from the Helsinki declaration of ethics for human behavioural studies. Participants were approached randomly through online networks to elicit interest in participation. Those who agreed had filled in an informed consent before proceeding with data collection. The informed consent clearly stated the right to voluntary participation, confidentiality, and the option to exit the study at any point.