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Vol. 76 | No. 1/1 | Jan 2020
DOI: 10.21506/j.ponte.2020.1.11 International Journal of Sciences and Research
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Psychological Capital and Mental Health: Empirical Exploration in
Perspective of Gender
Sana Younas1
Ph.D Candidate, Department of Behavioral Sciences, National University of Sciences and
Technology, Pakistan (sana.phdp19s3h@s3h.nust.edu.pk)
Lecturer, Riphah International University, Pakistan
Fariha Tahir2, Dr. Fazaila Sabih3, Rabia Hussain4, Amna Hassan5*, Mona Sohail5, Saba Zer
Naz Hafa6, Asima Munawar, 6 Rubab Kanwal6, Maria Tanvir6, Mashiat Zahra6
2Lecturer, Development Studies, NUST Pakistan (fariha-tahir@s3h.nust.edu.pk)
3Associate Professor, Riphah International University, Pakistan
4Ph.D Candidate, NUST, Pakistan
5*Senior Lecturer, Riphah International University, Pakistan
5Assistant Professor, Riphah International University Pakistan
6Lecturer, Riphah International University Pakistan
ABSTRACT
The study of Positive Psychology has revealed that there exists a connection between
psychological capital (PsyCap) with better mental health but the role of gender as a moderator
and particularly the differences across gender on the aforementioned constructs have not been
explored before. Hence, our study was an endeavor to explore the differences across gender on
PsyCap (measured through Psychological Capital Questionnaire) and mental health (measured
through Strength and Difficulty Questionnaire (SDQ). The study sample included 200
university students (Age = 18-25 years) of Islamabad and Rawalpindi. Gender differences
revealed that high score was obtained by male students on the constructs of conduct and
hyperactivity in comparison to female students. Regression analysis suggested that PsyCap
negatively predicts emotional problems and positively predicts pro-social behavior. One of the
novel findings in our study was the role of gender as a moderator between PsyCap and
externalizing behavior problems among young adults; explaining 8% variance in the model (p
<.001). PsyCap among young adults leads towards better mental health as it is negatively
associated with internalizing (emotional problems) and externalizing (pro-social) behavior
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problems. These findings also highlight the importance of moderating process that explain how
gender effects mental health and psychological capital.
Key words: Psychological Capital, Gender differences, Mental Health, Moderator
INTRODUCTION
Young adults face many difficulties in behavioral and emotional life stemming from the
challenges in managing interpersonal relationships, demands of academic coursework, and a
diverse number of other stressors (Houghton, Wu, Godwin, Neck, & Manz, 2012; Nafees &
Jahan, 2017). Studies conducted in the previous decade revealed an upward trend of mental
health problems among young adults (Center for Collegiate Mental Health (CCMH), 2016;
Drum, Brownson, Denmark, & Smith, 2009; Fink, Patalay, Sharpe, Holley, Deighton, &
Wolpert, 2015). The severity and prevalence of mental-health problems for instance, suicidal
ideation, anxiety, self-injury, and depression have increased among college students (Drum et
al., 2009; Eisenberg, Hunt, & Speer, 2013; Fink etal., 2015), setting a sound ground to address
this as a severe physiological condition alongside other mental health issues (Keyes, 2006,
2014). Studies have shown that college students suffer from high level of psychological stress
as compared to general population (Abdulghani, AlKanhal, Mahmoud, Ponnamperuma, &
Alfaris, 2011; Stallman, 2010). Major changes including demographic, cultural, technological,
and societal changes are marked in college years that may lead towards development of severe
mental, developmental, psychological, and emotional problems. According to Kadison and
DiGeronimo, (2004), potential stressors for college students are interpersonal issues, poor
identity development, and onset of numerous psychological and physical disorders,
relationships, and sexuality. The theoretical frameworks of developmental psychology are used
to understand the experience of acute anxiety, uncertainty, and bewilderment (Kadison &
DiGeronimo, 2004) faced by young adults. However, these negative consequences and
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disruptions are not faced by all young adults (Riolli et al., 2012). Positive traits like optimism,
resilience, hope, emotionality, and hardiness may help individuals to remain safe from the
negative consequences aforementioned (Schulman, 1999; Tugade & Fredrickson, 2004).
Efforts are being put to shift the viewpoint of mental health from the ‘‘absence of mental
illness’’ (Keyes, 2002, p. 208) to the presence of ‘‘well-being’’ (Seligman, Steen, Park, &
Peterson, 2005; World Health Organization, 2004, p. 12), or to ‘‘something positive’’ (Sigerist,
1941, p. 100), mental health scholars and policy makers, instead of focusing on the promotion
of positive mental health (Keyes, 2014) are still principally focused on instituting risk reduction
initiatives and addressing the mental illness issues. As the positive psychology grows (Seligman
& Csikszentmihalyi, 2000; Seligmanet al., 2005), there is a burgeoning interest in the dynamic
potential for multi-disciplinary application, including the young adults. The positive approaches
that emphasize emotional wellbeing (Seligman, 2003; Seligman et al., 2005) and human
strengths have gained impetus beyond the fields of clinical psychology. The examination of
constructs included in the Positive psychology through clinical trials with individuals belonging
from diverse age groups including university students (Ouweneel, Blanc, & Schaufeli, 2014),
students in k-12 schools (Burckhardt, Manicavasagar, Batterham, & Hadzi-Pavlovic 2016;
Shoshani, Nakash, Zubida, & Harper, 2016); and the older participants (Proyer, Gander,
Wellenzohn, & Ruch 2014; Ram´ırez et al., 2015). It has been found by various studies
(Andrews, Chen, & Myers, 2014; Nikrahan et al., 2016) that positive psychological
interventions may help in treating physiological ailments. Application and understanding of
character traits studied within the domain of positive organizational behavior (POB; Luthans,
Youssef, Sweetman, & Harms, 2013; Wright, Rains, & Banas, 2010) has furthered the
understanding by discussing the conception of ‘‘psychological capital’’ (PsyCap; Luthans,
Youssef, & Avolio, 2007, p. 3).
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Psychological Capital
PsyCap has been defined by Luthans et al. (2007) as a positive psychological state of
development that is differentiated by (i) self-efficacy (having complete confidence that an
individual can take effective steps for facing with challenges of life (ii) can make an optimistic
outlook regarding present life and future success; (iii) remain directed towards following short
but consistent steps for achieving the goals of life; and (iv) when face adversities and problems,
bouncing and sustaining back beyond (resilience) to achieve success.
Higher education aims at developing human capital that is profound in competitive
abilities, skills and knowledge (Luthans et al., 2013). The long term goals of university students
includes improvement in the performance of students learning abilities, identification and
building up of resources in areas of deficiency (Mather & Seifert, 2011). Additionally, the scope
of PsyCap has tremendously increased in the educational context, that also enriches the
existing body of literature in management, health studies, psychology, educational technology,
leadership, and business studies (Clapp- Smith, Vogelgesang, & Avey, 2009; Luthans et al.,
2013; Riolli et al., 2012; Simsek & Sali, 2014). Though the growth of PsyCap in educational
context has widely been recognized, still there seems to be a small room for its application in
higher education where research as gap exists in psychological development such as optimism,
resilience, efficacy, hope, and learning abilities of students (Luthans et al., 2012; Mather &
Seifert, 2010). The study of PsyCap a higher order dependable construct throws light on its
importance to study its connection with mental health.
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Mental health
Corey Keyes (Keyes, 2002, p. 207) definition of mental health is most famous that
operationalizes mental health as ‘‘a syndrome of symptoms of positive functioning and
positive feelings in life”, where people can be differentiated on a continuum from the
dimension of flourishing in mental health to languishing in mental health (Keyes, 2002). A
valuable perspective of mental health is provided by this where a complete mental health is
indicated by absence of mental illness and presence of favorable mental health condition
(Keyes, 2002, p. 607). The model proposed by Keyes (2002) on mental health continuum not
only differentiates between flourishing and languishing mental health but also categories
individuals on three facets of well-being; psychological well-being, social well-being, and
emotional well-being (Keyes, 2009). In return, this enables us to measure both eudemonia
wellbeing (positive functioning) and hedonic wellbeing (positive feeling) (Keyes, 2002).
Subjective wellbeing that includes both feeling good about oneself as well as appropriate
functioning in life are considered to be the trademarks for a healthy mental health (Keyes et
al., 2012). An optimal functioning of subjective well being and psychological well being are
included in the “flourishing” state of mental health. Contrary to this, low level of subjective
well-being with low social and psychological well-being is regarded as a state of “languishing”
(Westerhof & Keyes, 2010). People who are languishing in life do not find aspirations in life
or fulfilling and lack positive emotions (Grant & Cavanagh, 2007). In a study by Keyes and
colleagues (Keyes et al., 2012), it was found that languishing college students were high on
depression, generalized anxiety, and panic disorder (Keyes et al., 2012). Furthermore, anxiety
and depression were found to be strong negative predictors of flourishing dimension among
college students (Schotanus, Ten Have, Lamers, de Graaf, &
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Bohlmeijer, 2016). Individuals who fall neither on languishing state nor on flourishing state
were found to have moderate mental health (Keyes, 2002, 2009). These divisions of mental
health into eudemonia (positive functioning) and hedonic (emotional well-being) are in
alignation with Seligman (2012) theory of Wellness as symptomology of mental health (Keyes,
2002). Hence, we worked on establishing the relationship of psychological capital and mental
health, particularly the predictive role of psychological capital towards positive mental health.
\
LITERATURE REVIEW
The relationship between psychological capital and wellbeing among individuals has
been established previously that implied that development of PsyCap may help in better
wellbeing (Avey, Reichard, Luthans, & Mhatre, 2011; Krasikova, Lester, & Harms, 2015;
Younas, Muqtadir, & Khan, 2018). Positive effects of psychological capiatal on individual’s
mental health has been reported by Krasikova et al. (2015). Problems related to mental health,
particularly, PTSD, substance abuse, depression and anxiety may increase with the decrease
in the levels of PsyCap. In simple words, all the previous studies mentioned earlier have shown
an inverse relation of PsyCap with mental health problems (anxiety, burnout, stress, and
workplace deviance) (Avey et al., 2011).
Studies (Diener & Seligman, 2004; Keyes, 2002; Keyes & Haidt, 2003; Lyubomirsky &
Abbe, 2003) in positive psychology focus on wellbeing and mental health; similarly the focus
of present study is in the same domain. Snyder (2000) argued that healthy, positive, and
adaptive features of human functioning by expending the familiarity to obtain insight into their
life. Moreover, (Krasikova et al., 2015) has revealed the predictive role of PsyCap in positive
mental health (e.g., prosocial bevaior); hence, the aim of our study is not only the
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predictive role evaluation of PsyCap but also to determine the role of gender across different
domains of mental health (emotional problems, conduct, prosocial, peer, and hyperactivity)
and PsyCap.
As far as gender differences are concerned (Gitay et al. 2018) found that women are
higher on stress, anxiety, and depression as compared to men. 43.6% female Iranian students
were found to be mentally as well as physically ill because of poor socio economic reasons
(Mokhtari et al. 2013).
To the best of author’s knowledge, there is no study within Pakistani context that
examined PsyCap and mental health across male and female University students. (Riolli, et al.,
2012). Hence, the present study is an effort to see if PsyCap has an equivalent significance in
academic setting improving the capability of undergraduates so they can adapt to academic
pressure successfully and productively. Moreover, it’s a first step to analyze the role of gender
as a moderator between psychological capital and mental health (assessed through internalizing
and externalizing behavior problems). Additionally, our study is novel in studying the predictive
role of psychological capital on mental health. Specifically, the current study has following
objectives.
(1)
To examine the relationship between mental health and psychological capital among
young adults.
(2)
To study the gender differences across psychological capital and mental health (emotional
problems, conduct problems, hyperactivity, prosocial behavior, and peer relations).
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(3)
To analyze the role of psychological capital in predicting mental health among young
adults.
(4)
To assess the role of gender as a moderator between psychological capital and
externalizing behavior problems.
METHODOLOGY
The present study is cross sectional survey based research that analyzed the impact of
psychological capital on mental health of students. Questionnaires were used as a research tool.
Sample and Sampling Technique
Convenient sampling technique was used to approach towards different participants. As
it allows assessing the readily available participants easily and requires least time for data
collection and also useful for survey based research so this technique was used to approach the
participants. The sample consisted of 200 University students from different Universities of
Islamabad and Rawalpindi. Average age range of students was 18-25 years. Out of 200 students,
92 were male students and 108 were female students. Data was collected individually and
informed consent was taken from each of them. Confidentiality was ensured that the
information given by students will be kept secret and will solely be used for research purpose.
Measures
The following research instruments were utilized in the present study.
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Strength and Difficulty Questionnaire (SDQ) (Measure of Mental Health). The
Strength and Difficulty Questionnaire is easy to measure problematic behavior of adults and
children. It is user friendly and short in length. In the current study, SDQ 18+ version was used
as developed by Youth in Mind Organization (Goodman, 2011). It is a part of DAWBA family
of Mental Health measures and it is freely assessed through its website. It is a 25 items
questionnaire, including five subscales with five items in each subscale. Items are anchored on
a likert scale that ranges from 0 to 3. Zero denotes “not true”, 1 denotes “somewhat true” and
2 denotes “Certainly true”. The total difficulty score is the sum of all scores on all subscales
except the prosocial subscale. Hyperactivity and conduct problem form one subscale i.e.,
externalizing problems. Their score ranges from 0 to 20. On the other hand, prosocial
relationship problems and emotional problems form the other subscale i.e., internalizing
behavior problems whose score also ranges from 0 to 20.
Psychological Capital Questionnaire (PsyCap). The short form of PsyCap (originally
developed by Luthans et al. 2007) is a self-reported questionnaire that consists of four subscales
including optimism, resilience, hope, and efficacy. It has been adapted from previous studies
(Scheier & Carver 1985; Synder & Wilson, 1997) that worked on these constructs. It is a 12
items scale whose responses range on a 6 point likert scale (where 1 = Strongly Disagree to 6
= Strongly Agree). The higher the score on a particular subscale, the higher that trait will be
present in an individual. For instance, higher score on self-efficacy represents more self-
efficacy trait and same for other variables. The chronbach alpha for PsyCap across various
occupations and organizations has been found to be satisfactory as well as the internal
consistency of all subscales is also reported to be in optimum range
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(Optimism = .78, Resilience = .83, Hope = .87, Efficacy = .92) (Avey, Luthans, & Youssef,
2010).
Data Collection
Institutional review Board (IRB) of the institute approved the study for the data
collection. In order to obtain permission from Head/Dean of departments, an explanation about
the research purpose and implications had been provided by the researcher. Before the data
collection, complete ethical protocol was followed. Participants were informed that they have
the right to quit anytime if they feel uncomfortable, however, completion of research tools
would be highly appreciated. Informed consent was taken prior to data collection and complete
anonymity was ensured. Only those Participants were included who showed their voluntary
participation. Total average time span taken by participants was 20 minutes to fill out the
questionnaires. The total distribution of questionnaire booklets among students was 235 on
which response rate was assessed. Total 200 booklets were returned back by the participants
that were completely filled.
RESULTS
We used both descriptive and inferential statistics to analyze the results of our study.
Descriptive statistics, T-test, and regression were calculated using SPSS 22. Descriptive
statistics were calculated for PsyCap and mental health (strengths and difficulties) prior to
studying their relationship. The overall SDQ scores (M = 26.51, SD = 5.89) is the sum of
strengths and difficulties score is measured within the range of 25–75. Total PsyCap score (M
= 52.75, SD = 7.12) is the sum of hope, optimism, efficacy, and resilience. PsyCap has
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significant positive relation with prosocial behavior (r = .32, p < .001) and negative relationship
with emotional problems (r = -.17, p <.05). It means that more the prosocial behavior more will
be the positive attributes (optimism, resilience, efficacy, and hope) in a person. Non-significant
differences are found on all other domains of SDQ with PsyCap. The reason can be attributed
to the reverse scored items and small sample size.
Pearson Correlation analysis was conducted in order to test the first objective
(relationship between predictor i.e., PsyCap and outcome variable i.e., mental health). Statistical
significant correlation was found between mental health variables (emotional problems and
prosocial behavior) and PsyCap variables (df = 336, p < 0.01). Prosocial behavior (strengths)
and emotional problems (difficulties) correlated well with PsyCap. There exists a strong
relationship between PsyCap and Prosocial behavior (r = .32, p < 0.01), compared to other
domains of strengths. Additionally, as compared to other domains of SDQ, the most strong
relationship exists with emotional problems (r = .72, p < 0.01). In conclusion, we can write that
there exists moderate to high correlation between PsyCap and mental health.
Differences Across Gender
To analyze the gender differences across psychological capital and mental health, t-test
was conducted. Levene test for homogeneity of variance was conducted prior to analysis in
order to find if there is any violation in the assumptions of homogeneity of variance across the
two groups. Few violations of homogeneity were observed that could be related to
heteroscedasticity, but we conducted analysis across two groups with the help of independent
sample t test because heterocedasticity did not affect results of t test (Warner, 1981).
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Table 1
Gender differences on PsyCap and SDQ (N = 200).
Variables
Men
(n = 92)
Women
(n=108)
T
p
LL
UL
Cohen’s
d
M
SD
M
SD
PsyCap
53.73
7.81
52.03
6.52
1.61
.10
.25
3.65
NS
SDQ
27.64
5.78
25.69
5.85
2.27
.02
-.37
3.77
.33
Emotional
4.04
2.57
4.12
2.46
-.23
.81
-.82
.64
NS
Conduct
4.10
1.63
3.32
2.13
2.80
.00
.20
1.34
.41
Hyperactivity
5.95
1.62
5.37
1.70
2.35
.02
.08
1.06
.34
Peer
5.37
1.59
5.19
1.74
.72
.46
-.31
.67
NS
Prosocial
8.14
1.62
7.74
1.77
1.56
.11
-1.02
.89
NS
TDQ
19.47
5.59
18.03
5.76
1.71
.08
-.21
3.10
NS
Int
9.42
3.32
9.32
3.44
.18
.85
-.89
1.08
NS
Ext
10.05
2.84
8.70
3.19
3.04
.00
.45
2.24
.44
Note. SDQ = Strength and Difficulty Questionnaire, PsyCap = Psychological capital, TDQ = Total Difficulty
Questionnaire, Int =Internalizing problems , Ext = Externalizing Problems; NS = Non-Significant
Table 2 shows the mean differences across PsyCap scores and the mental health
categories. It is revealed that on domain of SDQ, there exists a significant difference among
male and female students. Men are high on strengths and difficulties as compared to women.
Moreover, significant difference is found on the subscales of conduct and hyperactivity where
again high score is obtained by male students. It means that in comparison to women, men are
more prone towards externalizing problems i.e., conduct and hyperactivity.
Results of Regression
Another objective of the research focused on determining if PsyCap cause significant
variation in the model. In the regression equation, PsyCap acted as predictor variable and facets
of mental health were the dependent variable. Linear regression was used as the most suitable
method to predict mental health (dependent variable) of young adults. In order to
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detect violations of test assumptions, outliers, and multicollinearity, standard diagnostic
procedures were conducted that revealed absence of any problem. Two regression models are
yielded by analysis of regression (see Table 2), of which a linear combination of PsyCap exists
in negatively predicting emotional problems (R2 = .02, F = 5.5, p < .00). The value for adjusted
R2 was .02 which suggests 20 % variance in the individual’s mental health. Moreover, PsyCap
also predicts pro-social behavior (R2 = .10, F = 21.98, p < .00). This shows that 10 % variance
in the mental health is accounted by pro-social behavior. Moderate effect size has been
observed. Results reveal that PsyCap among young adults leads to better their mental health as
it is negatively associated with internalizing (emotional problems) and externalizing (pro-social)
behavior problems. Results are shown in table 2.
Table 2
Summary of Analysis of Regression for PsyCap Predicting Emotional Problems and Pro- Social
Behavior Problems (N = 200).
PsyCap Predicting Emotional Problems
Variables
B
R2 adjusted
95% CI
β
T
p
Constant
7.26
(4.58, 9.93)
5.35
.00
PsyCap
-.06
.02
(-.11, -.01)
-.17
-2.35
.00
PsyCap Predicting Pro-Social Behavior
Variables
B
R2 adjusted
95% CI
β
T
p
Constant
3.76
(2, 5.5)
4.21
.00
PsyCap
.07
.01
(.04, .11)
.32
4.68
.00
Note. PsyCap = Psychological capital; CI = Confidence interval for B
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Moderation by Gender
The last but not the least objective of the study was the exploration of the gender role as
a moderator between the relationship of psychological capital and externalizing behavior
problems. Our findings reveal significant effect of gender as moderator between PsyCap and
externalizing behavior problems among young adults by explaining 8% variance in the model (p
<.001). It has been observed that interaction term i.e., gender × PsyCap significantly predict (B
= 1.12; p <.001) by explaining additional 2% variance in the model (see Table 3). The
relationship becomes clearer with the help of graphic representation given below.
Table 3
Moderating Effect of Gender in the Relationship Between Psychological Capital and
Externalizing Behavior Problems (N = 200).
Variables
Externalizing Problems
B
95% CI
Constant
3.10
[-7.29, 13.50]
Gender
5.10***
[-1.44, 11.64]
PsyCap
.16***
[-.02, .33]
Int_1
-.12***
[-.24, -.00]
R²
.08
∆R²
.02
F
5.45***
Note. B = Standardized coefficient; S.E. = Standard Error; Sig = significant, LL = Lower limit; UP = Upper limit
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Fig 1. Mod Graph explaining gender as a moderating variable between PsyCap and externalizing behavior
Problems
The graph shows relationship between psychological capital and externalizing behavior
problems that is moderated by the gender. The graph clearly shows men (showed by single
straight line) high on externalizing problems as compared to women (shown by dotted line).
Graph is clear depiction of inverse relationship between psychological capital and externalizing
behavior problems.
DISCUSSION
The present study was conducted with the aim to determine the effect of psychological
capital on mental health of students. It also aimed to investigate the difference between the
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groups with reference to study variables. Survey design was used in which cross sectional data
was collected with the help of standardized self-report measures. The instruments used for this
purpose were Strength and Difficulty Questionnaire (SDQ) which is the measure for Mental
Health (Goodman, 1997) and another scale, named as Psychological Capital Questionnaire
(PCQ) (Luthans et al., 2007) that measures optimism, resiliency, hope, and efficacy. The
reliabilities of both measures came in acceptable range i.e. greater than .70
Results of correlation analysis that PsyCap had no significant relationship with SDQ).
The reason can be attributed to the sample size. As sample was relatively small so it was
expected that relationship may become obvious and clear with increase in sample size.
Furthermore, negative score items were included in SDQ (internalizing and externalizing
behavior problems) that may result in lessening the relationship between variables. However,
our study found emotional problems having significant negative relation with PsyCap while
prosocial behavior has significant positive relation with PsyCap. These results were in line with
the literature. Positive states have been linked with better psychological health as revealed by
past studies (for instance, happiness— Krasikova, Lester, & Harms, 2015; positive emotions--
(Tugade, Fredrickson, & Feldman Barrett, 2004). Additionally, it has also been found in theory
and empirical studies that negative components like stress has inverse relation with PsyCap
(Anwer, Masood, & Younas, 2019; Bandura, 2008; Chang, Rand, & Strunk, 2000).
Additionally, the study also found a significant difference among male and female
students (see Table 1). Men were high on strengths and difficulties as compared to women.
Moreover, significant difference was found on the subscales of conduct and hyperactivity where
again in comparison to female students, male students scored high significantly high.
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These results are supported by literature as studies have found the manifestation of externalizing
behavior problems, like drinking, substance abuse (Huselid & Cooper, 1994) delinquency, and
antisocial behavior problems, such as conduct disorders and aggression (Stein et al., 2013) in
male adolescents. Moreover, males having traditional gender roles correlated highly with
externalizing problems but not with internalizing behavior problem (Huselid & Cooper, 1994).
Results of regression analysis revealed that PsyCap negatively predicts mental health
problems. Significant association of PsyCap was found for pro-social problems and emotional
problems. The study shows that one can effectively deal with hardships of life and can flourish
in a healthier way just by having an awareness of one’s strengths (Park & Grant, 2005). PsyCap
(optimism, resilience, hope, and self-efficacy) can be strengthened and build up in individuals
with conscious awareness, increasing age, life experiences, and lessons directed towards
improvement. As sample of our study also consisted of young adults between ages 18-25 years.
Hence this assumption has significant importance for explaining PsyCap. As young adults are
in process of maturation and development both physically and psychologically, so they can
develop positive traits with lifelong experiences and learning. Moreover, reverse score items
were also included in the subscales of resiliency and optimism which are the domains of
PsyCap. Internal consistency of these two domains was also found to be low as compared to
other domains (hope, self-efficacy (Dawkins, Martin, Scott, & Sanderson, 2013). Inverse
scoring might have contributed in lowering the scale reliability (Schmitt & Stults, 1985). This
could be the reason that all domains of PsyCap did not predict mental health problems, rather,
overall combined effect of PsyCap predicted mental health, particularly, emotional problems
and peer relations. Moreover, the discrepancies seen in the
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167
separate domains of PsyCap are also justified by this. Increase in mental health problems may
contribute to decrease in subjective wellbeing (Keyes, 2002); this may explain substantial
psychological impairment, lack of positive emotions and thinking, and inability to form
fulfilling life goals.
Results of moderation analysis revealed gender acting as a moderator in the relationship
between PsyCap and externalizing problems. Gender did not moderate in the relationship
between internalizing problems and PsyCap, it is of no surprise as the conservative nature of
interactions in correlational designs should be kept in mind (McClelland, 1997). We also found
some evidence that gender plays a significant role in bolstering the effects of externalizing
behavior problems among boys but not in girls and also that gender plays a moderator role in
relation between emotional and behavior problems and text reading among boys (Mano,
Denton, Epstein, & Tamm, 2017). It is worthy to mention that it may be difficult to draw
conclusions based on this preliminary result. Further research does seem warranted on the role
of gender in the pathways to positive attributes.
Limitations and Suggestions
Though the results of the study were supported by the extensive body of research
findings yet there were few limitations of the study. First and foremost limitation is the small
sample size (taken from twin cities of Rawalpindi and Islamabad) that limited the
generalizability of the research findings. In order to generalize the results on a larger group,
future studies should focus on taking the data from whole country that could help in
generalizability. Furthermore, experimental studies could be conducted to assess the cause
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168
and effect relationship between the selected variables controlling the effect of confounding
variables. This could also help in designing of intervention based studies. Self-reported data has
always the danger of subjectivity and biases findings from the participants. Future researchers
should work with both qualitative and quantitative methods to get insight on selected topic and
for getting more reliable findings. Future researchers should also focus on other variables as the
potential predictors of mental health; like altruism, compassion, gratitude, forgiveness etc.
Conclusion
The purpose of the study was to explore the impact of psychological capital on mental
health of students. Results revealed that, emotional problems had significant negative relation
with PsyCap while prosocial behavior has significant positive relation with PsyCap. Men were
high on strengths and difficulties as compared to women. Moreover, significant difference was
found on the subscales of conduct and hyperactivity where again in comparison to female
students, male students scored significantly high.
In past few decades, positive mental health and well-being has gained much momentum
against prevention strategies of mental health problems. Sustainable mental health can be
propelled among young adults by focusing on building positive resources. Findings of the study
have widespread implications for the development of strategies for the promotion of better
mental health among young adults and also draws attention towards more examination into
positive psychological constructs as crucial features of mental health of young adults’.
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