Research Journal of Psychology and Educational Sciences. Vol., 2 (1), 1-5, 2016
Available online at http://www.rjpes.com
ISSN 2149-9691©2016
Ego identity Status and Positive and Negative Affect
Seddiq Asadi1*, Hamid Soltani Zangbar2, Parvin Asadi3, Mohadese Asadi4
1
M.A in General Psychology, Tabriz Islamic Azad University, Tabriz, Iran
Ms student in Occupational Therapy, School of Rehabilitation, Iran University of Medical Sciences, Tehran,
Iran
3
M.A in Educational Psychology, Kharazmi University, Tehran, Iran
4
M.A student in Art History, Shabestar University, Shabestar, Iran
2
*
Corresponding Author Email: [email protected]
Abstract: This study aimed at examining the ego identity status and its link with positive and negative affect.
The sample consists of 280 secondary school student selected using stratified random sampling among Tabriz
education district 4’s students. The research method was survey-correlation. The measures employed included
Objective Measure of Ego Identity Status (OMEIS), made-researcher interpersonal life skills scale and canonical
correlation analysis. Data were analyzed using a canonical correlation analysis (CCA). Results of canonical
correlation analysis showed a significant positively correlation between positive and negative affect and
foreclosure and achievement identity statuses, and a significant negatively correlation between positive and
negative affect and diffusion and moratorium identity statuses. Findings indicated that first canonical root of
predictor predicted and explained 56.70% of canonical correlation from an amount of variance in canonical
criterion variable, and second root predicted and explained 48.00% of its variance. Other roots had fewer portion
in predicting and explaining canonical criterion variable of positive and negative affect.
Key words: Ego Identity Status, Exploration, Commitment, Positive and Negative Affect.
Introduction
According to psychology, the nature and development of identity and related concepts like self and selfidentity have attracted voluminous research over many decades (Ashmore & Jussim, 1997). Studies began with
Freud’s early writings and were popularized by Erikson’s theoretical expositions. Since the 1960s, Marcia’s
empirical operationalization of the concept has led other contemporary theorists like Berzonsky et al (2007) to
develop it further. The identity statuses (Adams & Fitch, 1982) originated from attempts to validate a major
construct, ego identity, drawn from Erikson’s ego psychoanalytic theory. She also proposed two dimensions,
namely, exploration and commitment, which influence identity formation. Exploration refers to a process of
actively questioning and searching for adult roles and values in the various domains of adolescent life.
Commitment refers to firm decisions regarding aspects, such as vocation, political ideology, religion, and social
roles, and includes specific strategies for achieving personal goals and a desired life path. Identity diffusion is a
status in which exploration has not occurred nor has any commitment been made. Foreclosure denotes the status
when commitment has been made but is not supported by adequate exploration. Moratorium refers to an active
exploration of identity with weak commitment, possibly trying on several different masks at the same time.
Identity achievement is the status in which the individual has explored his or her identity potential fruitfully and
can now commit to a particular identity. Diffusion is often considered the least adaptive status. While research
has revealed adolescent boys and girls to be similar in few identity statuses, such as in identity achievement and
identity foreclosure (Cramer, 2000), but they tend to differ in identity moratorium and identity diffusion
(Cramer, 2000). On the other hand, research also showed no statistical significant difference between adolescent
boys and girls in any of the four identity statuses.
Throughout the lifecycle identity status shifts will occur. When identity status change occurs (in late
adolescence and young adulthood) the change is more than twice as likely to be progressive as opposed to
1
R. J. Psych. Edu. Sci. Vol., 2 (1), 1-5, 2016
regressive. Longitudinally status change is most often a transition from moratorium to identity achievement.
Specifically, an individual’s identity profile (strengths and weaknesses across the different identity domains),
identity status (including the interplay of exploration and commitment, the magnitude of discrepancies between
real and ideal self), and the ability of that individual to effect necessary improvement to his or her identity
development, all have an impact on the immediate positive and negative aspects of the individual’s well-being.
In addition, it will affect one’s long-term development into adulthood and the future stages of one’s life span.
Positive indicators include self-esteem, life satisfaction, positive affect (Barsade & Gibson, 2007; Cohen &
Pressman, 2006), quality of life, environmental mastery, positive relations with others like parents (Berzonsky et
al., 2007), teachers, and peers, and self-acceptance. Negative indicators include internalizing pathology like
negative affect (Diener & Iran-Nejad, 1986; Diener & Emmons, 1984), stress, depression, and anxiety, as well as
externalizing pathological behavior like hostility, aggression, loss of control, and disruptive behavior. Many such
indicators are included as positive youth development constructs.
According to Erikson, the overall task of the individual is to acquire a positive ego identity. The enhancement of
positive identity development (Carver & Scheier, 1992; Russell, 1980) in young people can be achieved at both
individual and the social levels, leads to positive affect. Catalano conceptualized positive youth identity as “the
internal organization of a coherent sense of self” (Catalano et al., 2004). He found that “positive identity” was
treated as a core construct in effective positive youth development stages.
Positive and negative effects (Ortony, Clore, & Collins, 1988; Feldman, 1995) represent independent domains of
emotion in the general population, and positive affect is strongly linked to social interaction. Positive and
negative daily events show independent relationships to subjective well-being, and positive affect is strongly
linked to social activity. Recent research suggests that high functional support is related to higher levels of
positive affect.
Positive and negative affect extensive evidence demonstrates that two broad mood factors-positive affect
and negative affect-are the dominant dimensions in self-reported mood. Positive and negative affect are in fact
highly distinctive dimensions that can be meaningfully represented as orthogonal (uncorrelated) factors. Both
mood factors can be measured either as a state (i.e., transient fluctuations in mood) or as a trait (i.e., stable
individual differences in general affective tone).
In contrast, positive affectivity (PA) is a dimension reflecting one's interested, excited, strong, enthusiastic,
proud, alert, inspired, determined, attentive and active. Trait PA is a corresponding predisposition conducive to
positive emotional experience; it reflects a generalized sense of well-being and competence, and of effective
interpersonal engagement. Studies suggested negatively significant correlation between negative emotions and
positive emotion. In Iran, some secondary students are unable to regulate their affects (i.e. positive or negative)
in light of identity achievement under different circumstances (e.g. home, school and society). Evidence even
exists that a number of students have suffered from achieving ego identity statuses until they experience positive
and negative affect resulting in personal, familial and collective problems. In educational specialists have been
considered that these issues are to create sensitivity about some students. In accordance with lack of conducted
research on these issues, we decided to investigate them as a study. Then we were to examine the relationship
between ego identity status and positive and negative affect in Iranian secondary school students.
Materials and Methods
Sample
The sampling method was the stratified random sampling. The participants were 280 students (160 male
and 120 female) secondary school students of Tabriz education district 4, aged 17-19 years old (M= 18.13, SD =
0.729). 57.14% of the respondents were male and 42.86% were female. The sample included the students of
different courses in both 3th and 4th secondary school graders that were studying in the first semester of the
academic years 2014-2015. The aim of study was explained to each participant and they were assured about the
participants’ information confidentiality.
Instruments
1- Objective Measure of Ego Identity Status (OMEIS). The 24 item Objective Measure of Ego Identity
Status was used to assess the ego-identity statuses. This brief 24 item version was used due to its brevity and
frequent use in survey studies. Identity statuses are based on responses to the ideological dimensions associated
with occupation, politics, and religion. These dimensions reflect the Eriksonian focus on the power and role of
social institutions on ego-identity development. A 6-point scale from 1-strongly disagree to 6 strongly agree was
used in this study. Cronbach alpha in data from this study were as follows: diffusion (alpha = 0.63), foreclosure
(alpha = 0.67), moratorium (alpha = 0.64), and identity achievement (alpha = 0.67). The total subscales scores
for each of the identity statuses were used in this study for the primary analyses and the more familiar identity
status paradigm categorical classification was used in a secondary analysis.
2
R. J. Psych. Edu. Sci. Vol., 2 (1), 1-5, 2016
2. The Positive and Negative Affect Schedule (PANAS) Questionnaire. Participants read each item and
then list the number from the scale below next to each word. This indicates to what extent a person feels this way
right now, that is, at the present moment OR indicates the extent a person has felt this way over the past week
(they circle the instructions you followed when taking this measure) 1 2 3 4 5 Very Slightly or Not at All A
Little Moderately Quite a Bit Extremely based on the Likert scale. Positive Affect Score: Add the scores on
items 1, 3, 5, 9, 10, 12, 14, 16, 17, and 19. Scores can range from 10 – 50, with higher scores representing higher
levels of positive affect. Mean Scores: Momentary 29.7 (SD 7.9); Weekly 33.3 (SD 7.2) Negative Affect Score:
Add the scores on items 2, 4, 6, 7, 8, 11, 13, 15, 18, and 20. Scores can range from 10 – 50, with lower scores
representing lower levels of negative affect. Mean Score: Momentary 14.8 (SD 5.4); Weekly 17.4 (SD 6.2). The
PANAS scale intercorrelations and internal consistency reliabilities (Cronbach's Alpha coefficient) are reported
in Table 2. The alpha reliabilities are all acceptably high, ranging from 0.86 to 0.90 for PA and from 0.84 to 0.87
for NA. The reliability of the scales is clearly unaffected by the time instructions used. Scale validity. Within
each data set, we then correlated these estimated factor scores with the PANAS PA and NA scales. The results,
shown in Table 4, demonstrate the expected convergent/discriminant pattern: Both PANAS scales are very
highly correlated with their corresponding regression-based factor scores in each solution, with convergent
correlations ranging from .89 to .95, whereas the discriminant correlations are quite low, ranging from -0.02 to 0. 18.
3. Canonical correlation analysis (CCA). Canonical correlation analysis (CCA) (Anderson, 1984) is a
standard statistical technique for finding linear projections of two random vectors that are maximally correlated.
CCA has been used for unsupervised data analysis when multiple views are available; learning features for
multiple modalities that are then fused for prediction; learning features for a single view when another view is
available for representation learning but not at prediction time; and reducing sample complexity of prediction
problems using unlabeled data. The applications range broadly across a number of fields, including medicine,
meteorology, biology and neurology, natural language processing, speech processing (Choukri & Chollet, 1986),
computer vision, and multimodal signal processing. An appealing property of CCA for prediction tasks is that, if
there is noise in either view that is uncorrelated with the other view, the learned representations should not
contain the noise in the uncorrelated dimensions.
Results
The results of canonical correlation analysis have followed for this study as:
Table 1. Canonical Solution for ego identity statuses predicting Negative and positive affect for Function 1 and
2.
Positive Affect
Negative Affect
ex
pl
or
ati
on
3
Variable
Interested
Excited
Strong
Enthusiastic
Proud
Alert
Inspired
Determined
Attentive
Active
Distressed
Upset
Guilty
Scared
Hostile
Irritable
Ashamed
Nervous
Jittery
Afraid
RC2
Diffusion
Coef
-0.559
-0.307
-0.366
-0.306
-0.555
-0.492
-0.245
0.609
0.531
0.621
0.383
0.516
0.092
0.186
0.425
0.244
0.442
0.252
0.341
0.569
0.183
Function 1
rs
rs2 (%)
-0.902
81.36
-0.758
57.46
0.699
48.86
-0.738
54.46
-0.819
67.08
-0.718
51.55
-0.695
48.30
-0.913
83.36
-0.882
77.79
-0.826
68.23
0.683
46.65
0.938
87.98
0.382
14.59
0.677
45.83
0.860
73.96
0.684
46.79
0.722
52.13
0.577
33.29
0.629
39.56
0.856
73.27
56.70
0.772
59.59
Coef
0.284
-0.342
-0.322
-0.266
-0.463
-0.066
-0.267
0.035
-0.053
-0.321
-0.151
-0.112
-0.237
-0.191
-0.286
-0.061
-0.384
0.051
0.392
-0.224
0.701
Function 2
rs
rs2 (%)
0.718
51.55
0.664
44.09
0.623
38.81
0.553
30.58
-0.710
50.41
0.684
46.79
0.590
34.81
0.479
22.94
0.661
43.69
0.835
69.72
-0.559
31.24
-0.693
48.02
-0.606
36.72
-0.509
25.91
-0.739
54.61
-0.596
35.52
-0.786
61.78
-0.402
16.16
-0.705
49.70
-0.692
47.89
48.00
-0.609
37.09
h2 (%)
69.56
60.22
71.57
56.41
47.33
64.16
69.06
63.20
61.94
56.55
40.07
56.25
45.97
32.60
49.84
55.56
72.59
55.20
55.95
68.39
47.33
R. J. Psych. Edu. Sci. Vol., 2 (1), 1-5, 2016
commitme
nt
Foreclosure
Moratorium
Achieved
Diffusion
Foreclosure
Moratorium
Achieved
-0.067
0.561
-0.094
0.293
-0.125
0.134
-0.083
-0.689
0.894
-0.585
0.829
-0.221
0.568
-0.216
47.47
72.92
34.22
68.72
4.88
32.26
5.11
-0.288
-0.383
-0.023
0.365
-0.267
-0.710
-0.152
0.331
-0.698
-0.444
-0.564
0.453
-0.403
0.580
10.96
48.72
19.71
31.81
20.52
16.24
33.64
4.79
49.70
27.98
50.55
9.06
46.65
32.72
Note. Structure coefficients (rs) greater than |.45| are underlined. Communality coefficients (h2) greater than
45% are underlined. Coef = standardized canonical function coefficient; rs = structure coefficient; = squared
structure coefficient; h2 = communality coefficient.
A canonical correlation analysis was conducted using the 8 explorative and commitment ego identity statuses
variables as predictors of the 20 positive and negative affects variables to evaluate the multivariate shared
relationship between the two variable set (i.e., Positive Affects: Interested, Excited, Strong, Enthusiastic, Proud,
Alert, Inspired, Determined, Attentive, Active, and Negative Affect: Distressed, Upset, Guilty, Scared, Hostile,
Irritable, Ashamed, Nervous, Jittery and Afraid). The analysis yielded eight functions (Table 2, Appendix) with
squared canonical correlations (RC2) of 0.567, 0.480, 0.193, 0.153, 0.127, 0.089, 0.057 and 0.042 for each
successive function. Collectively, the full model across all functions was statistically significant using the
Wilkes’s λ = 0.110 criterion, F (160, 1896.05) = 4.075, p <0.001. Because Wilkes’s λ represents the variance
unexplained by the model, 1– λ yields the full model effect size in an r2 metric. Thus, for the set of eight
canonical functions, the r2 type effect size was 0.742, which indicates that the full model explained a substantial
portion, about 74%, of the variance shared between the variable sets.
The dimension reduction analysis (Table 4, Appendix) allows the researcher to test the hierarchal
arrangement of functions for statistical significance. As noted, the full model (Functions 1 to 8) was statistically
significant. Functions 2 to 8, 3 to 8, 4 to 8 and 5 to 8 were also statistically significant, F(133, 1682.34) =
2.91248, p < 0.002, F(108, 1462.87) = 1.79950, p = .003, F(85, 1237.13) = 1.58541, p = 0.005, and F(64,
1004.47) = 1.39479, p = 0.024,respectively. Then Functions 1, 2, 3, 4, and 5 explained a statistically significant
amount of shared variance between the variable sets. Given the effects for each function (Table 3, Appendix);
only the first two functions were considered noteworthy in the context of this study (57% and 48% of shared
variance, respectively). The last two functions only explained 19.3%, 15.3%, 12.7%, 8.9%, 5.7% and 4.2%,
respectively, of the remaining variance in the variable sets after the extraction of the prior functions. Table 1
presents the standardized canonical function coefficients and structure coefficients (Table 5, 6, 7, and 8,
Appendix) for Functions 1 and 2. The squared structure coefficients are also given as well as the communalities
(h2) across the two functions for each variable. Looking at the Function 1 coefficients, one sees that relevant
criterion variables were primarily interested, excited, strong, enthusiastic, proud, alert, inspired, determined,
attentive, active, distressed, upset, guilty, scared, hostile, irritable, ashamed, nervous, jittery and afraid making
secondary contributions to the synthetic criterion variable. This conclusion was supported by the squared
structure coefficients. These positive and negative affects also tended to have the larger canonical function
coefficients. A slight exception involved the negative effects of scared and irritable, which had modest function
coefficients but large structure coefficients. This result was due to the multi-collinearity that this variable had
with the other criterion variables. Furthermore, all of the positive affect variables’ structure coefficients had the
negative sign, indicating that they were all positively related. On the other hand, all of the negative affect
variables’ structure coefficients had the positive sign, indicating that they were all negatively related.
Regarding the predictor variable set in Function 1, identity moratorium in explorative ego identity statuses
and identity diffusion in commitment ego identity statuses variables were the primary contributors to the
predictor synthetic variable, with a secondary contribution by identity diffusion in explorative ego identity status.
Because the structure coefficient for identity diffusion and identity moratorium were positive, it was negatively
related to all of the positive effects and positively related to all of the negative effects. Similarly, because the
structure coefficient for identity foreclosure and achieved identity were negative, it was positively related to all
of the positive effects and negatively related to all of the negative effects. These results were generally
supportive of the theoretically expected relationships between achieved and unachieved adult identity and
positive and negative effects, and we labeled Function 1 as “positive achieved affects”. Moving to Function 2,
the coefficients in Table 1 suggest that the only criterion variables of relevance were interested, excited, strong,
enthusiastic, proud, alert, inspired, determined, attentive, active, distressed, upset, guilty, scared, hostile,
irritable, ashamed, jittery and afraid, exception with nervous. The positive and negative effects were inversely
related on this function. As for explorative ego identity statuses, identity moratorium and identity diffusion were
now the dominant predictors, along with achieved identity in commitment ego identity statuses. These
explorative ego identity statuses variables were also inversely related. Looking at the structure coefficients for
the entire function, we see that identity diffusion and identity moratorium were negatively related to distressed,
4
R. J. Psych. Edu. Sci. Vol., 2 (1), 1-5, 2016
upset, guilty, scared, hostile, irritable, ashamed, jittery and afraid, exception with nervous and positively related
to interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive, active. Identity
foreclosure and achieved identity had the opposite pattern. Given the nature of these variables, we labeled this
function as “negative achieved affects”.
Discussion and Conclusion
The purpose of this study was to examine the link between different types of ego identity statuses ((identity
diffusion, foreclosure, moratorium, and identity achievement) with positive effects (interested, excited, strong,
enthusiastic, proud, alert, inspired, determined, attentive, active) and negative effects (distressed, upset, guilty,
scared, hostile, irritable, ashamed, nervous, jittery and afraid) in secondary school students. According to
canonical correlation analysis, the first function demonstrated theoretically consistent relationships among all of
the variables that contributed to the function. The Function 1 results also pointed to a need for further study
regarding the strong variable. For example, it may be important to examine the various ego identity statuses used
in the presentation of the positive effects versus negative effects. Perhaps the strong positive affects is so
dominated by ego identity statuses. The second function also yielded theoretically expected relationships;
however, this function capitalized on variance in the identity achievement predictor that was not useful in the
first function. Therefore, not only do we learn about relationships between ego identities and positive effects and
negative effects, we also learn that identity achievement status is something of a different person than the other
variables of ego identity statuses. Additional work is needed to further explicate this possibility.
The foreclosure predictor only made a marginal contribution as a predictor (see the foreclosure h2 in Table
1), thereby suggesting that it may not have been strongly related to positive effects and negative effects.
Furthermore, the negative effects of guilty did not appear to be related to ego identity statuses (see the h2
statistics in Table 1). This is informative, particularly given the general disregard for some emotions that these
affects typify and the general sense of positive emotions that characterizes the other affects (again, with the
exception of strong, which represents something of the opposite of positive emotions).
Conflict of interest
The authors declare no conflict of interest
References
Adams GR, Fitch SA, 1982. Ego stage and identity status development: A crosssequential analysis.J. Personal. Social
Psychol. 43: 574–583.
Anderson TW, 1984. An Introduction to Multivariate Statistical Analysis (2nd edition). John Wiley and Sons.
Ashmore RD, Jussim L, 1997. Self and Identity : Fundamental Issues. Cary, NC, USA: Oxford University Press.
Barsade SG, Gibson DE, 2007. Why does affect matter in organizations?. Academy of Management Perspectives. Pp.
36-59.
Berzonsky MD, Branje S JT, Meeus W, 2007. Identity-processing style, psychosocial resources, and adolescents'
perceptions of parent-adolescent relations. Journal of Early Adolescence. 27(3): 324-345.
Carver CS, Scheier MF, 1992. Perspectives on personality (2nd ed.). Boston: Allyn & Bacon.
Catalano RF, Berglund ML, Ryan JAM, Lonczak HS, Hawkins JD, 2004. Positive youth development in the United
States: research findings on evaluations of positive youth development programs. Annals of the American
Academy of Political and Social Science. 591: 98–124.
Choukri K, Chollet G, 1986. Adaptation of automatic speech recognizers to new speakers using canonical correlation
analysis techniques. Speech Comm. 1: 95-107.
Cohen S, Pressman SD, 2006. Positive Affect and Health. Current Directions in Psychological Science. 15 (3): 122.
Cramer P, 2000. The development of identity: Gender makes a difference. Journal of Research in Personality. 34: 4272.
Diener E, Emmons RA, 1984. The independence of positive and negative affect. Journal of Personality and Social
Psychology. 47: 1105-1117.
Diener E, Iran-Nejad A, 1986. The relationship in experience between various types of affect. Journal of Personality
and Social Psychology. 50: 1031-1038.
Feldman LA, 1995. Variations in the circumplex structure of mood. Personality and Social Psychology Bulletin. 21:
806-817.
5