research on self esteem over the lifespan indicates the following

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The Developmental Trajectory of Self-Esteem Across the Life Span in Japan: Age Differences in Scores on the Rosenberg Self-Esteem Scale From Adolescence to Old Age

Yuji ogihara.

1 Division of Cognitive Psychology in Education, Graduate School of Education, Kyoto University, Kyoto, Japan

2 Faculty of Science Division II, Tokyo University of Science, Tokyo, Japan

Takashi Kusumi

Associated data.

The datasets presented in this article are not readily available because participants were not asked to provide permission to disclose individual data at the time of data collection. Requests to access the minimal datasets (aggregate level) should be directed to Yuji Ogihara ( pj.ca.sut.sr@arahigoy ).

We examined age differences in global self-esteem in Japan from adolescents aged 16 to the elderly aged 88. Previous research has shown that levels of self-liking (one component of self-esteem) are high for elementary school students, low among middle and high school students, but then continues to become higher among adults by the 60s. However, it did not measure both aspects of self-esteem (self-competence and self-liking) or examine the elderly over the age of 70. To fully understand the developmental trajectory of self-esteem in Japan, we analyzed six independent cross-sectional surveys. These surveys administered the Rosenberg Self-Esteem Scale, which measured both self-competence and self-liking, on a large and diverse sample ( N = 6,113) that included the elderly in the 70s and 80s. Results indicated that, consistent with previous research, for both self-competence and self-liking, the average level of self-esteem was low in adolescence, but continued to become higher from adulthood to old age. However, a drop of self-esteem was not found over the age of 50, which was inconsistent with prior research in European American cultures. Our research demonstrated that the developmental trajectory of self-esteem may differ across cultures.

Introduction

Self-esteem, which is the positivity of a person's global evaluations of the self [e.g., Baumeister et al. ( 1 )], is one of the most famous indicators of mental health. To maintain good mental health, it is important to have a positive view of the self to some extent.

The average level of self-esteem changes across the life span along with changes in one's capacities (e.g., social, cognitive) and surrounding environments (e.g., social, economic). Uncovering the developmental trajectory of self-esteem across the life span is important at least for two reasons. First, it is crucial to reveal the effects of basic demographic variable on self-esteem. Age is one of the most frequently examined demographic variables. Thus, how age influences self-esteem should be investigated. Furthermore, when researchers are interested in the effects of other variables (e.g., socio-economic status, interpersonal relationships) on self-esteem, they should control for basic demographic variables that might confound these effects (e.g., age, gender). To statistically control for the effect of age, it is imperative to know in advance how age is associated with self-esteem. Second, investigating the developmental pattern across the lifetime contributes to understanding how self-esteem is formed, maintained, and influenced by changes in one's capacities and surrounding environments. For instance, finding two periods when self-esteem declines can estimate that a consistent factor common to the two periods might decrease self-esteem.

Revealing the developmental trajectory of self-esteem is also important for public health at least for two reasons. Such knowledge contributes to promoting public mental health by providing empirical evidence about the developmental pattern of self-esteem. First, knowing when self-evaluation tends to become negative over the life span facilitate effective prevention and provision. For example, parents and teachers can pay more attention to and provide more resource to people in the periods at higher risk. Second, knowing the period when self-evaluation is at high risk for turning negative can facilitate effective interventions and responses. Interventions and responses that are necessary depend on age categories (e.g., adolescence, old age). Moreover, people that are in the periods of lower self-esteem might feel relieved if they understand that they are not special and it is rather natural to have relatively low self-esteem during specific developmental stages.

Previous research especially in European American cultures has provided empirical evidence about the developmental trajectory of self-esteem over the life course. However, is this developmental pattern of self-esteem consistent across cultures?

Age Differences in Self-Esteem in European American Cultures

A large amount of research has investigated the developmental trajectory of self-esteem in European American cultures (especially in the U.S.; for reviews, see Orth and Robins ( 2 ); Robins and Trzensniewski ( 3 ). Robins et al. ( 4 ) investigated age differences in self-esteem from a broad range of population aged 9 to 90 years old in the U.S. They found that self-esteem is high in childhood, low in adolescence, but then continues to become higher in adulthood. Then, self-esteem peaks around the mid-60s, and shows a drop afterward. Moreover, Orth et al. ( 5 ) explored the developmental trajectory of self-esteem from young adults aged 25 to the elderly aged 104 by analyzing longitudinal data in the U.S. They showed that self-esteem increases from young adulthood through middle age, but then decreases from around the age of 60. In addition, Orth et al. ( 6 ) investigated the life-span development of self-esteem from adolescents aged 16 to the elderly aged 97 by examining other longitudinal data in the U.S. They demonstrated that self-esteem rises from adolescence to middle adulthood, peaks at about age 50, and declines in old age. This pattern of developmental change has been found not only in the U.S., but also in Germany. Orth et al. ( 7 ) examined the development of self-esteem from adolescents aged 14 to the elderly aged 89 by analyzing a longitudinal study. Results indicated that self-esteem increases from adolescence to middle adulthood, reaches a peak at about age 60 years, and decreases in old age in Germany.

Studies have shown that self-esteem reaches a peak in one's 50s or 60s, and then sharply drops in old age ( 4 – 7 ). This is a characteristic change, so it is important to reveal about when self-esteem peaks across the life span. This drop is thought to occur mainly for two reasons [e.g., Robins et al. ( 4 ); Robins and Tresniewski ( 3 )]. The first is the loss of things that are important to one's evaluation of oneself. These include the loss of socioeconomic positions or roles due to retirement, loss of close others (e.g., spouse, romantic partner), and a reduction in one's abilities (e.g., physical, cognitive). The second is a change in attitudes toward oneself. The elderly come to accept their limitations and faults, leading them to have more humble, modest, and balanced perspectives toward themselves.

Age Differences in Self-Esteem in Japan

Previous research has shown that self-esteem is profoundly affected by culture [e.g., Heine et al. ( 8 ); Schmitt and Allik ( 9 )], leading to the possibility that the developmental trajectory of self-esteem may differ across cultures. Thus, it is important to investigate the developmental change in self-esteem in cultures other than America and Europe 1 .

Prior research examined age differences in self-esteem from elementary school students aged 10 to the elderly in their 60s by analyzing cross-sectional data from a large, representative and diverse sample in Japan ( 12 ). It showed that levels of self-esteem were high for elementary school students, low among middle and high school students, but then gradually continued to become higher among adults, consistent with the pattern obtained in European American cultures ( 2 , 3 ). Moreover, previous research has indicated the same pattern of age differences in self-esteem from middle school students to the elderly in their 60s by analyzing another independent and large-sample survey ( 13 ).

However, previous research had two limitations. First, it did not directly examine age differences in global self-esteem in Japan. Prior research investigated age differences in self-esteem by focusing on one component of self-esteem: self-liking [“our affective judgment of ourselves, our approval or disapproval of ourselves, in line with internalized social values” (( 14 ), p. 325); also see, Tafarodi and Milne ( 15 ); Tafarodi and Swann ( 16 )]. It has been shown that self-esteem consists of self-liking and self-competence (“the overall sense of oneself as capable, effective, and in control”; ( 14 ), p. 325), which are strongly correlated with each other and construct self-esteem. Thus, it is strongly predicted that age differences in self-esteem would be consistent with those in self-liking. However, this has not been examined empirically. Although we do not have strong evidence, it is possible that patterns of age differences in self-competence are different from patterns of age differences in self-liking. To reveal the developmental trajectory of global self-esteem, it is desirable to directly investigate age differences in self-esteem by capturing both of its aspects simultaneously.

Second, previous research did not sufficiently investigate age differences in self-esteem in the elderly over the age of 70, leaving the developmental trajectory of self-esteem after the age of 70 in Japan unclear. Previous research in European American cultures has indicated that the average level of self-esteem drops sharply in the elderly period ( 2 , 3 ). To capture the whole picture of the developmental trajectory of self-esteem in Japan, it is necessary to investigate whether this sharp drop is also found among the elderly in Japan. Many studies have shown that people in Japan have more humble, modest and balanced attitudes toward themselves compared to people in European American cultures [e.g., Heine et al. ( 8 ); Heine and Hamamura ( 17 )]. Given that the sharp decline in self-esteem observed in European American cultures may be caused by increases in such attitudes in old age, it is possible that a decline may be absent or less sharp in Japanese older adults. Indeed, one prior study did not find a drop in self-liking between the ages of 50 and 69, which implies that a decline may be absent or found later in old age in Japan ( 18 ). Thus, the developmental pattern of self-esteem may differ across cultures, which should be investigated empirically.

Present Research

To overcome the first limitation of previous research, we measured global self-esteem by administering the Rosenberg Self-Esteem Scale [RSES; ( 11 )]. This scale is one of the most frequently used measures of global self-esteem. We predicted that the developmental trajectory of self-esteem would be consistent with that of self-liking: levels of self-esteem were low in adolescence, but then continued to become higher among adults. Here, we also empirically examined whether self-competence and self-liking were closely related to each other. We expected that self-competence and self-liking would be highly correlated with each other, and the developmental pattern of self-competence would be consistent with that of self-liking. To overcome the second limitation, we collected data covering a more diverse sample that included the elderly over the age of 70. We predicted that a drop of self-esteem would be absent or less sharp in Japanese older adults. In sum, in the current research, we investigated age differences in global self-esteem among a broader range of the population in Japan by using the RSES.

Prior research has shown that the pattern of age differences in self-esteem is similar between males and females in the U.S. [for a review see, Orth and Robins ( 2 )] and Germany ( 7 ). Although the patterns are consistent between gender, in some cases, small differences were found with females showing larger age differences than males ( 4 , 5 ). This was also the case in Japan ( 19 ). Thus, we also investigated whether age differences in self-esteem are moderated by gender. We predicted an absence of the moderating effect of gender, but if there were any differences, they would be small differences, which would be larger in females than in males.

We analyzed six independent web surveys administered to a large and diverse sample in Japan.

Each survey was conducted independently in 2009, 2011, 2012, 2013, 2017, and 2018. The data in 2009 was collected by Kyoto University Global COE Program (Revitalizing Education for Dynamic Hearts and Minds). The data for this secondary analysis, “International Comparative Research on Sense of Happiness, 2009–2011” was provided by the Social Science Japan Data Archive (Center for Social Research and Data Archives, Institute of Social Science, The University of Tokyo). The data from 2011, 2012, 2013, 2017, and 2018 were collected by us [e.g., Ogihara et al. ( 20 )]. We recruited participants from every prefecture in Japan on the internet via research firms. The research firms had their own large pools of participants. In each survey, a designated number of participants were assigned to each cell by age category and gender. Participants were rewarded after answering the survey. The summary of each survey is shown in Table 1 .

Summary of surveys.

A: the Japanese translation of the Rosenberg Self-Esteem Scale used in previous research [e.g., Heine et al. ( 8 ); Uchida et al. ( 21 )], B: Yamamoto et al. ( 22 ) .

Sample sizes by gender and generation are indicated in Table 2 . The sample sizes ranged from 763 to 1,331 and the total sample size was 6,113.

Sample sizes by gender and generation.

Self-Esteem

The Rosenberg Self-Esteem Scale, a 10-item measure of global self-esteem [e.g., “I feel that I have a number of good qualities,” “On the whole, I am satisfied with myself.”; ( 11 )], was administered.

In the 2017 and 2018 surveys, the Japanese translation of the RSES from Yamamoto et al. ( 22 ) was used (5-point scale; 1: Not applicable−5: Applicable). In the other surveys, a different translation of the RSES that has been used in previous research [e.g., Heine et al. ( 8 ); Uchida et al. ( 21 )] was administered (7-point scale; 1: Strongly disagree−7: Strongly agree) 2 . Reliabilities of the RSES in the six surveys were sufficiently high (αs > 0.86; Table 1 ).

The average scores for self-competence (e.g., “I feel that I have a number of good qualities”; SC1 3 ) and self-liking (e.g., “On the whole, I am satisfied with myself.”; SL1 4 ) were calculated by averaging the five items of the RSES, as was done in previous research ( 15 ). The reliabilities for self-competence (αs > 0.77; Table 1 ) and self-liking (αs > 0.69; Table 1 ) were sufficiently high.

First, we confirmed whether the Self-Esteem Scale measured the same concepts between genders and age-groups (i.e., measurement invariance/equivalence). We divided the participants into subgroups and conducted multi-group confirmatory factor analysis (CFA). For this analysis, we split the participants into three age groups: younger adults (10s 5 , 20s, 30s), middle-aged adults (40s, 50s), and older adults (60s, 70s, 80s) 6 . Following previous research ( 14 , 15 ), we made a two-factor model in which self-competence (measured by five items) and self-liking (measured by five items) constituted self-esteem ( Figure 1 ) 7 . For the multi-group CFA, we used IBM SPSS Amos (ver. 26).

A two-factor model in which self-competence and self-liking constitute self-esteem.

Then, to check whether self-competence and self-liking are closely related to each other, we calculated their correlation coefficients at the individual level and at the age level.

Next, we conducted hierarchical multiple linear regression analyses on each dataset for predicting self-esteem from age and gender 8 . The independent variables we entered in Step 1 were gender (male = 0, female = 1), the age, and their interaction (age × gender), and in Step 2, the age squared and its interaction with gender (age 2 × gender), and in Step 3 the age cubed and its interaction with gender (age 3 × gender). If the interaction effect was significant, we conducted hierarchical multiple linear regression analyses separately by gender for predicting self-esteem from the age (Step 1), the age squared (Step 2), and the age cubed (Step 3). In these analyses, we centered each age variable and weighted sample sizes to estimate the developmental trajectory of self-esteem more precisely.

Finally, we looked at whether these developmental patterns were found in each component (i.e., self-competence and self-liking) by conducting a series of hierarchical multiple linear regression analyses. The dependent variable was the average score for each component (self-competence or self-liking; not global self-esteem). In Step 1, the independent variables were age, the age-squared, and the type of component (categorical variable: self-competence = 0, self-liking = 1). In Step 2, the interaction terms were added (i.e., the age × the component, the age-squared × the component). We used IBM SPSS (ver. 25) for the analyses.

Measurement Invariance

We tested measurement invariance in two steps. First, we conducted a confirmatory factor analysis for each subgroup separately (single-group CFA) in each dataset. Second, we conducted confirmatory factor analysis by including the subgroups (multi-group CFA) at four successive levels in each dataset. These results are summarized in Table 3 .

Fit indices for the confirmatory factor analyses.

df, degree of freedom; SRMR, standardized root mean square residual; RMSEA, root mean square error of approximation; CI, confidence interval; CFI, comparative fit index .

Single-Group CFA

The model fits were acceptable to adequate in all the datasets ( Table 3 ), showing that the two-factor model successfully described the construction of self-esteem in each subgroup.

Multi-Group CFA

To evaluate the fitness of the model at four hierarchical levels, we used changes in CFI (ΔCFI) index. Specifically, if ΔCFI was smaller than 0.010, the successive model that constrained more equality was accepted ( 27 ). We did not use Δχ 2 for this evaluation because χ 2 is sensitive to sample size ( 27 ).

First, configural invariance was tested. Configural invariance indicates that structure of latent factors and observed variables (e.g., number of latent factors, same associations between each factor and observed items) are consistent across groups. Second, metric invariance (weak factorial invariance) was investigated. Metric invariance means that factor loadings are comparable across groups, indicating that participants in different groups respond to each item in a similar way. We constrained each factor loading to be equal across groups. Third, scalar invariance (strong factorial invariance) was tested. Scalar invariance indicates that factor loadings and intercepts of items are comparable across groups, showing that latent factor scores lead to observed scores in the same way across groups. We constrained each factor loading and intercept of each observed variable to be equal across groups. Finally, structural invariance (factor variance/covariance invariance) was examined. Structural invariance means that latent factors are distributed and associated similarly across groups. We constrained the variance of each factor and covariance of the two factors across groups.

Regarding gender, five out of the six datasets (2009, 2011, 2012, 2017, 2018 datasets) demonstrated scalar and structural invariance, and one (2013 dataset) showed partial scalar 9 and structural invariance. In the 2013 dataset, ΔCFI between the metric invariance model and the scalar invariance model was 0.011, which was slightly above the conventional criterion of 0.010 ( 27 ). This criterion is not a golden rule, and excluding only one constraint of item intercept cleared the criterion (partial scalar invariance). In all of the datasets, at least partial scalar and structural invariance were supported.

Regarding age-group, one out of the six datasets (2011 dataset) showed scalar and structural invariance, four (2009, 2012, 2013, 2018 datasets) showed partial scalar 10 and structural invariance, one (2017 dataset) showed metric and factorial invariance 11 . In the 2017 dataset, ΔCFI between the metric invariance model and the partial scalar invariance model was 0.012, which was slightly above the conventional criterion of 0.010 ( 27 ). Overall, in the most datasets, at least partial scalar and structural invariance were supported.

The Relationship Between Self-Competence and Self-Liking

We calculated correlation coefficients between self-competence and self-liking at the individual level and at the age level in each of the six studies ( Table 4 ). At the individual level, they were highly correlated for the total population ( r s > 0.72, p s < 0.001), for males ( r s > 0.68, p s < 0.001), and for females ( r s > 0.72, p s < 0.001). These strong relationships were also found within sub-populations (each age group for both males and females). Relatively lower coefficients for some sub-populations ( r = 0.42 for males in their 70s in 2018, r = 0.27 for females in their teens in 2018) were due to the small sample sizes ( n = 44 for males in their 70s in 2018, n = 5 for females in their teens in 2018; see Table 2 ). Similarly, at the age level, the correlations were large both for males ( r s > 0.71, p s < 0.001) and females ( r s > 0.79, p s < 0.001).

Correlation coefficients between self-competence and self-liking.

Age Differences in Global Self-Esteem

A summary of the regression models predicting self-esteem from age and gender is indicated in Table 5 .

Summary of regression models predicting self-esteem from age and gender.

Gender was coded as male = 0, female = 1 .

The model in Step 1 was significant, and the addition of the age squared and its interaction with gender significantly increased the coefficient of determination (Step 2; Table 5 ). The addition of the age cubed and its interaction with gender did not significantly increase the coefficient of determination (Step 3). Thus, the quadratic model (Step 2) was accepted. We conducted a consistent analysis separately by gender because the interaction between the age squared and gender was significant.

The age significantly predicted self-esteem (Step 1), and the addition of the age squared term significantly increased the coefficient of determination (Step 2; Table 6 ). The addition of the age cubed term did not significantly increase the coefficient of determination (Step 3). Thus, the quadratic model (Step 2) was accepted ( Figure 2 ). Self-esteem showed a slight downward trend from the teens to the mid-30s (the lowest predicted score was the age of 32 12 ), but then it continued to become higher to the 80s 13 .

Summary of regression models predicting self-esteem from age by gender (in the 2009, 2011, and 2013 surveys).

Average and predicted self-esteem scores across ages in Japan (2009 survey). Note. Error bars represent 95% confidence intervals.

The model in Step 1 was significant, and the addition of the age squared term did not significantly increase the coefficient of determination (Step 2; Table 6 ). Thus, the linear model (Step 1) was accepted ( Figure 2 ). Self-esteem continued to become higher from the teens to the 80s ( d = 0.97 14 ) 15 .

The model in Step 1 was significant, and the addition of the age squared and its interaction with gender did not significantly increase the coefficient of determination (Step 2; Table 5 ). Thus, the linear model (Step 1) was accepted. We conducted a consistent analysis separately by gender because the interaction between the age and gender was significant.

The model in Step 1 was significant, and the addition of the age squared term did not significantly increase the coefficient of determination (Step 2; Table 6 ). Thus, the linear model (Step 1) was accepted ( Figure 3 ). Self-esteem continued to become higher from the 20s to the 50s ( d = 0.51).

Average and predicted self-esteem scores across ages in Japan (2011 survey). Note. Error bars represent 95% confidence intervals.

The model in Step 1 was significant, and the addition of the age squared term did not significantly increase the coefficient of determination (Step 2; Table 6 ). Thus, the linear model (Step 1) was accepted ( Figure 3 ). Self-esteem continued to become higher from the 20s to the 50s ( d = 1.05). The slope for females ( B = 0.03, p < 0.001) was larger than that for males ( B = 0.01, p < 0.05).

The model in Step 1 was significant, and the addition of the age squared and its interaction with gender did not significantly increase the coefficient of determination (Step 2; Table 5 ). Thus, the linear model (Step 1) was accepted. The interaction between the age and gender was not significant, showing that self-esteem continued to become higher from the 20s to the 50s both for males and females ( Figure 4 ) 16 .

Predicted self-esteem scores across ages in Japan (2012 survey). Note. Error bars represent 95% confidence intervals.

The model in Step 1 was significant, and the addition of the age squared term did not significantly increase the coefficient of determination (Step 2; Table 6 ). Thus, the linear model (Step 1) was accepted ( Figure 5 ). Self-esteem continued to become higher from the teens to the 60s ( d = 1.00).

Average and predicted self-esteem scores across ages in Japan (2013 survey). Note. Error bars represent 95% confidence intervals.

The model in Step 1 was significant, and the addition of the age squared term did not significantly increase the coefficient of determination (Step 2; Table 6 ). Thus, the linear model (Step 1) was accepted ( Figure 5 ). Self-esteem continued to become higher from the teens to the 60s ( d = 1.42). The slope for females ( B = 0.02, p < 0.001) was larger than that for males ( B = 0.01, p < 0.001).

The model in Step 1 was significant, and the addition of the age squared and its interaction with gender significantly increased the coefficient of determination (Step 2; Table 5 ). The addition of the age cubed and its interaction with gender did not significantly increase the coefficient of determination (Step 3). Thus, the quadratic model (Step 2) was accepted. The interaction between the age squared and gender was not significant. Self-esteem continued to become higher from the 20s to the 50s both for males and females ( Figure 6 ) 17 .

Predicted self-esteem scores across ages in Japan (2017 survey). Error bars represent 95% confidence intervals.

The model in Step 1 was significant, and the addition of the age squared and its interaction with gender did not significantly increase the coefficient of determination (Step 2; Table 5 ). Thus, the linear model (Step 1) was accepted. The interaction between the age and gender was not significant, showing that self-esteem continued to become higher from the 20s to the 50s both for males and females ( Figure 7 ) 18 .

Predicted self-esteem scores across ages in Japan (2018 survey). Note. Error bars represent 95% confidence intervals.

Age Differences in Self-Competence and Self-Liking (The Two Components of Global Self-Esteem)

The results of the hierarchical multiple regression analyses are summarized in Table 7 . Except for females in 2009, the additions of their interaction terms did not significantly increase the coefficient of determination. Neither of the interaction terms significantly predicted the scores. These results consistently suggest that the developmental patterns for self-competence and self-liking were not different.

Hierarchical multiple linear regression predicting components of self-esteem from age, component type and their interactions.

For females in 2009, Step 2 significantly increased the coefficient of determination. The interaction term between age and the component significantly predicted the score. Thus, we conducted the same hierarchical multiple regression analyses on each component as we did for the global self-esteem ( Table 8 ). Although in both components age significantly explained the scores, the slope of the increase was higher for self-liking ( B = 0.02, p < 0.001) than for self-competence ( B = 0.01, p < 0.001; Figure 8 ). Yet, both patterns consistently indicated a continuous upward trend in self-esteem.

Regression models predicting each sub-component of self-esteem from age for females in the 2009 study.

Average and predicted self-esteem scores by component across ages among females in Japan (2009 survey). Note. Error bars represent 95% confidence intervals.

Due to the consistent relationship between self-competence and self-liking, the age patterns for each component were same as those for global self-esteem. Specifically, the quadratic increases were found among males in 2009 and both genders in 2017, and the linear increases were found in the other subgroups.

Summary of the Results and Implications

We investigated age differences in self-esteem in Japan from adolescents aged 16 to the elderly aged 88 by using the RSES. Previous cross-sectional research has investigated age differences in self-esteem in Japan ( 12 , 13 , 17 ). However, it had two limitations: (1) it did not directly examine age differences in global self-esteem and (2) it did not investigate self-esteem among the elderly over the age of 70. These limitations had to be overcome to fully understand the developmental trajectory in self-esteem across the life span in Japan. Therefore, we examined age differences in self-esteem by conducting the RSES on more diverse sample that included the elderly over the age of 70.

First, as predicted, we found a pattern to the developmental trajectory of global self-esteem that is consistent with previous research on self-liking ( 12 , 13 , 18 ). We had predicted that the developmental pattern of self-esteem would be consistent with that of self-liking, but we had not had empirical evidence to support it. In this research, we empirically confirmed that self-competence and self-liking are closely associated with each other and have a consistent developmental pattern in Japan. Specifically, across the six cross-sectional surveys, the average level of self-esteem was low in adolescence, but then gradually continued to become higher from young adulthood to late adulthood. This trajectory was consistent with findings in previous research in European American cultures ( 2 , 3 ).

Second, as expected, analyses showed that the average level of self-esteem continued to indicate an upward trend beyond the age of 50 in Japan. All of the six independent cross-sectional datasets consistently showed that self-esteem continued to become higher from adulthood to old age both for males and females. This finding was inconsistent with previous research that showed a drop in self-esteem over the age of 50 in European American cultures ( 2 , 3 ). With old age comes a more humble, modest, and balanced perspective toward oneself, which leads to a decline in self-esteem in old age in European American cultures [e.g., Robins et al. ( 4 ); Robins and Tresniewski ( 3 )]. Previous research has indicated that, compared to people in European American cultures, people in Japan have more humble and balanced attitudes toward themselves, not just in old age [e.g., Heine et al. ( 8 ); Heine and Hamamura ( 17 )], which may account for the absence of a drop of self-esteem among the Japanese people over the age of 50. Thus, this research demonstrates that different developmental patterns can emerge in different social/cultural environments.

One may wonder whether the absence of a sharp drop in self-esteem in Japan is caused by the fact that participants answered the questionnaire on the internet. Elderly people who use the internet may differ from the elderly population in general (e.g., they may be wealthier and healthier). However, this was also the case in previous research that observed a clear drop in self-esteem among the elderly in the U.S. (e.g., ( 4 )). Thus, this explanation is insufficient to account for the cultural difference in the developmental trajectory of self-esteem among the elderly. Still, it is desirable to collect more representative data especially from the elderly and see if the result is consistent with the present research.

Three datasets showed that gender differences in the pattern of age differences were absent. The other three datasets indicated that there were slight differences between gender: slopes for females were a little larger than those for males. In sum, the pattern of age differences in self-esteem was similar between gender, if any small differences. These results were consistent with previous research ( 2 , 7 , 19 ).

We also confirmed the measurement invariance of the Rosenberg's Self-Esteem Scale ( 11 ) across gender and age-groups in Japan. Regarding gender, five out of the six datasets demonstrated scalar and structural invariance, and one showed partial scalar and structural invariance. Thus, in all of the datasets, at least partial scalar and structural invariance were supported. Regarding age-group, one out of the six datasets showed scalar and structural invariance, four showed partial scalar and structural invariance, and one showed metric and structural invariance. Overall, in the most datasets, at least partial scalar and structural invariance were supported. These results showed that the model structure and the adequacy of the measure were invariant across gender and age-groups.

Limitations and Future Directions

This research investigated age differences in self-esteem from adolescents in their teens to the elderly in their 80s by analyzing six cross-sectional datasets from a large and diverse sample. But, in cross-sectional data, age differences involve cohort differences. This research is a reasonable first step to understand the developmental trajectory of self-esteem across the life span in Japan. In fact, the absence of a drop in self-esteem in Japan might be caused by the cohort effect. Specifically, older cohorts might have higher self-esteem and younger cohorts might have lower self-esteem ( 23 – 26 ), which might obscure the drop of self-esteem in Japan. Thus, in the future, it is necessary to analyze longitudinal data which can distinguish between age differences and cohort differences.

Another limitation is that, although the sample sizes were relatively large for teens ( n = 211), adults ( n 20s = 1,161, n 30s = 970, n 40s = 1,382, n 50s = 1,056), and the elderly in their 60s ( n = 1,031) and 70s ( n = 253), the sample size for the elderly in their 80s was small ( n = 49). Thus, the results for this age group may be unreliable. It would be desirable to examine this point further by collecting more representative data.

Data Availability Statement

Ethics statement.

This study was carried out in accordance with the recommendations of the Declaration of Helsinki and the Japanese Psychological Association with written informed consent from all subjects. Ethical approval was not required for this study in accordance with the local legislation and institutional requirements. This study asked participants to answer one of the most frequently used questionnaires (Rosenberg Self-Esteem Scale) and this questionnaire did not include any items that may harm participants. Thus, the protocol was not submitted to an ethics committee. Both individual researchers in charge of each survey and their respective research firms confirmed that all surveys were without any ethical concerns. All subjects gave written informed consent via the online questionnaire in accordance with the Declaration of Helsinki.

Author Contributions

YO contributed conception and design of the study, performed the statistical analysis, and wrote the first draft of the manuscript. TK collected the data and provided the critical comments on the manuscript. All authors contributed to manuscript revision and approved the final manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer ST declared a shared affiliation, with no collaboration, with the authors to the handling editor at the time of review.

Acknowledgments

We thank Pamela Taylor for her helpful comments on our previous versions of the manuscript.

1 Bleidorn et al. ( 10 ) examined cultural variation in age and gender differences in self-esteem across 48 nations including Japan. However, with regards to cultural differences in the developmental trajectory of self-esteem, it had at least three limitations. First, it investigated age differences in self-esteem between the ages of 16 and 45, leaving it unclear how average levels of self-esteem change after early middle age. Second, it indicated that self-esteem in females showed an upward trend from early adolescence to middle adulthood in Japan whereas self-esteem in males showed a downward trend during this period. Among 48 nations, this age pattern in males was found only in Japan, but the reason for this was not discussed. Third, as mentioned as a limitation by the authors, it used only one item “I see myself as someone who has high self-esteem” (a 5-point scale ranging from 1: disagree strongly to 5: agree strongly) instead of adequately constituted scale [e.g., Rosenberg Self-Esteem Scale; Rosenberg ( 11 )]. Although it was stated that the validity and reliability had been confirmed in the U.S. (although the item and its anchors differed from the original research), it is unclear whether the validity and reliability were confirmed in other nations including Japan. The word “self-esteem” is abstract and conceptual, so it may be interpreted differently across cultures and/or within each culture. This may have contributed to the exceptional pattern found in Japan (i.e., the continuous downward trend in males and the continuous upward trend in females).

2 The translations differed between years is because these studies were conducted as an omnibus survey with other researchers.

3 The other four items assessing self-competence were “I am able to do things as well as most other people.” (SC2), “I feel that I'm a person of worth, at least on an equal plane with others.” (SC3), “I feel I do not have much to be proud of.” (SC4), and “All in all, I am inclined to feel that I am a failure.” (SC5).

4 The other four items assessing self-liking were “I take a positive attitude toward myself.” (SL2), “I certainly feel useless at times.” (SL3), “At times I think I am no good at all.” (SL4), and “I wish I could have more respect for myself.” (SL5).

5 Although teenagers are usually not regarded as younger adults, because the size of this sample was relatively small, teenagers were conventionally included in the younger adults group in this analysis.

6 Because the datasets in 2011 and 2012 did not include participants aged over 60 years, we split the participants into two age groups: younger adults (20s, 30s) and middle-aged adults (40s, 50s).

7 Because the covariances between error terms of SC1, SC2, SC3, and error terms of SL1 and SL2 were large, we included them in the model (Model 1). These high associations may be due to the nature of the items: the items were affirmative, and the remaining (i.e., SC4, SC5, SL3, SL4, SL5) were reversed items. Even if we did not include these covariances in the model, the patterns of the results of multi-group CFA were consistent.

8 We did not examine whether the developmental pattern of self-esteem (e.g., the shape of changes, the magnitude of the slope) differed among the six datasets. Naturally, the developmental pattern is different because the time periods covered in the surveys are significantly different ( Tables 1 , ​ ,2). 2 ). Moreover, previous research has shown that the average levels of self-esteem decreased over time in Japan [( 23 – 25 ); for a review of historical changes in self-esteem in Japan see Ogihara ( 26 )]. Thus, the self-esteem score should not be simply averaged across the surveys that were conducted over nine years. Even if the self-esteem scores are z-transformed in each survey, the periods covered by the surveys are significantly different, and they should not be aggregated.

9 In the partial scalar invariance model, item intercepts that were constrained did not include SL5 (i.e., excluding the constraint of SL5's item intercept from the full scalar model).

10 In the partial scalar invariance models, item intercepts that were constrained were as follows. 2009: SC1, SC2, SC3, SL2; 2012: other than SL3; 2013: SC1, SC3, SL2, SL5; 2017: SC4, SL5; 2018: SC2, SL5.

11 The reason for these differences in the levels of measurement invariance could be due to differences in factors such as total sample sizes, proportions of age-group sample size, and type of scale translations. However, we do not have sufficient data to empirically detect the reason(s). Thus, in the future, it would be important to investigate the possibility that people across a broad range of age might respond to RSES items differently.

12 The lowest predicted score was at the age of 32 when raw data were unavailable. Thus, effect sizes were not calculated.

13 We describe developmental patterns of self-esteem based on age differences in self-esteem. However, it should be noted that our data were cross-sectional and not cross-temporal. Age differences include not only developmental changes that an individual experiences over the life course, but also cohort differences. Thus, these age differences do not necessarily mean developmental changes. Although findings obtained from cross-sectional research on self-esteem are consistent with those obtained from cross-temporal research [for a review, see Orth and Robins ( 2 ), this should be kept in mind (also see, the Limitations and Future Directions section of the Discussion below).

14 Effect sizes were calculated by using predicted average scores, standard deviations and sample sizes in three years (a given age, and 1 year before and after the age) to secure larger sample sizes and avoid unstable results.

15 Comparing the slopes in linear models (Step 1) between gender, the slope for females ( B = 0.011, p < 0.001) was slightly larger than that for males ( B = 0.009, p < 0.001).

16 We have also shown the results of the analysis conducted separately by gender to facilitate comparisons with other surveys ( Supplementary Material ; Table S1 ; Figure S1 ).

17 We have also shown the results of the analysis conducted separately by gender to facilitate comparisons with other surveys ( Supplementary Material ; Table S1 ; Figure S2 ).

18 We have also showed the results of the analysis conducted separately by gender to facilitate comparisons with other surveys ( Supplementary Material ; Table S1 ; Figure S3 ).

Funding. This work was supported by the Japanese Group Dynamics Association.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2020.00132/full#supplementary-material

The Elusive Quantification of Self-Esteem: Current Challenges and Future Directions

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• First Online: 14 April 2022

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• Stefano De Dominicis 3 &
• Erica Molinario 4  

Part of the book series: Health Informatics ((HI))

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Self-esteem, a person’s overall evaluation that she is valued and accepted vs. devalued and rejected by others, is crucial for people quality of life. As such, self-esteem has been central in the social-psychological literature since the late eighteenth century. However, its relevance is coupled with lack of agreement on how self-esteem is best conceived and assessed. Here we review definitions and measures of self-esteem in relation to quality of life in order (a) to understand how self-esteem has been defined, operationalized and assessed, and (b) to clarify which facets of self-esteem have been overlooked and need further study. Although we found multiple definitions of self-esteem, which led to a series of measures ranging from single item to multi-dimensional measures of state, trait and contingent self-esteem, the motivational component of self-esteem and its in-context behavioral correlates have yet to be operationalized. What follows, is that whether people think, feel, or behave in particular ways is caused by, concomitant with, or causes self-esteem, is still not understood. Because self-esteem is an emotionally laden system monitoring one’s relational value to others, we suggest that future research could use new technology-based research methods and eventually grasp real-time self-report and behavioral assessment of self-esteem. This appears a promising approach to overcome the limitations of self-esteem’s current theorizations and operationalizations. Thus, a new line of research considering the momentary experience of self-esteem, its behavioral components and its social context, could potentially unveil novel processes and mechanisms linking self-esteem and quality of life that have yet to be discovered and understood.

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Introduction

The concept of self-esteem has been central in the social-psychological literature since the late eighteenth century and it can be arguably considered one of the most important constructs in psychology. A quick database search of PsychINFO reveals a striking 52,126 results in March 2020, and 53,248 results in October 2020, showing how central this topic was and still is (with an estimate increase of 2000 hits per year) for scientists and practitioners alike. William James introduced this topic more than one hundred years ago, and more recently Rhodewalt and Tragakis [ 1 , p. 66] stated that self-esteem is one of the “top three covariates in personality and social psychology research”. Perhaps, the relevance of self-esteem can be easily understood if we consider that this construct is linked to all levels of human existence, from mental illness to mental wellbeing: indeed, on the one hand, low self-esteem is related to various mental disorders, such as depression and anxiety (e.g., [ 2 , 3 , 4 , 5 ]); on the other hand, high self-esteem is related to various proxies of mental wellbeing, such as success, happiness, agency, and motivation (e.g., [ 6 , 7 , 8 ]). It is therefore fundamental to understand what self-esteem is, how it is assessed, and why it is so important for people’s quality of life.

Definition of Self-Esteem

In a way, we all know what self-esteem “really is”: indeed, we can have a fairly good understanding of what is meant by self-esteem through introspection and observation of the behavior of others [ 9 ]. After all, self-esteem is a human phenomenon; yet, it is hard to put that understanding into precise words. In fact, as soon as we begin to examine self-esteem more closely, the understanding of this construct becomes quite problematic. The issue of defining self-esteem is crucial because definitions help shape what to focus on, which methods to choose and use, and what standards should be adopted to accept or reject evidence or conclusions [ 10 ]. Nevertheless, to find a concise and overarching definition of self-esteem is challenging because it encompasses different aspects and levels of analysis related to the context and its time stability or fluctuation. Self-esteem can be understood in terms of values (such as self-enhancement and openness to change values; [ 11 ]), feelings or affective dimensions (such as pride and shame; [ 12 ]), motivational (such as the desire to protect, maintain, and enhance feelings of self-worth; [ 13 ]), cognitive (such as evaluative components of self; [ 14 ]) and behavioral factors (such as being more independent or assertive, or more willing to exercise to gain fitness instead of reducing dissatisfaction with one’s body image; [ 6 , 15 , 16 ]).

Historically, self-esteem has been conceptualized in terms of (a) self-competence, or the ratio of a person’s successes over her failures in areas of life that are relevant to personal identity (dating back to William James work 1890/1983; James, Burkhardt, Bowers, Skrupskelis, and James, 1981; [ 17 ]) and (b) self-worth, or the affect concerning the degree to which one feels good about oneself [ 18 ]. Therefore, self-esteem is considered an evaluative psychological process that reflects both the extent to which people accept and like themselves, and believe they are competent (e.g., [ 19 , 20 ]). Such evaluation can occur in relation of a specific point on time (state self-esteem) or as an overall and more stable evaluation of the self (global self-esteem). Scholars have suggested that this evaluation may involve the assessment of several dimensions of the self. For instance, Tafarodi and Swann [ 20 , 21 ] suggested that self-esteem involves perceptions of self-worth (i.e., self-liking) and personal efficacy and self-regard of one’s capabilities (i.e., self-competence); or as suggested by O’Brien and Epstein [ 22 ], it encompasses several dimensions related to worthiness, competence, and global self-esteem.

Favorable views of the self, vs. evaluations of the self that are either uncertain or negative would then be the manifestations of high vs. low self-esteem, respectively [ 23 ]. It is relevant to note that self-esteem reflects subjective perceptions rather than objective reality, and therefore could be either accurate or not [ 24 ]. We suggest that, to fully understand self-esteem, it should be conceptualized in its social-psychological context. Therefore, we define self-esteem as the extent to which one person accepts and likes herself (in a specific point on time or overall) according to socially and personally defined standards, as well as believes of being competent in specific areas of life which are relevant to her personal and social identity .

To further corroborate this perspective, we should highlight that our definition is in line with sociometer theory [ 25 ], which basically consider self-esteem as the output of a psychological meter, or instrument, that monitors the quality of people’s relationships with others [ 26 ]. This psychological instrument is used by the self to monitor and respond to threats to the basic need to belong—i.e., that innate human need to form and maintain at least a minimum quantity of interpersonal relationships [ 25 ]. What follows, is that the degree to which a person perceives others to regard their relationship with herself as valuable, important, or close—i.e., her own relational evaluation—might change in specific situations or through the lifespan. Accordingly, when a person’s relational evaluation is changing, the sociometer puts her attention to the related social acceptance threat or reward and motivates her to deal with it. Thus, the sociometer output is the affectively-charged self-appraisal that we typically perceive as self-esteem [ 27 ]:

At its core, self-esteem is one’s subjective appraisal of how one is faring with regard to being a valuable, viable, and sought-after member of the groups and relationships to which one belongs and aspires to belong. [ 26 , p. 2]

This understanding of self-esteem appears coherent and comprehensive, as it can indeed explain why self-esteem is a relatively stable, but by no means immutable, psychological trait, as well as why it appears that self-esteem trait might have a specific trajectory across the individual’s lifespan [ 28 ].

In light of the above-mentioned arguments, the assessment of self-esteem becomes a critical issue because it lies at the heart of empirical research. Accordingly, the focus of this chapter is to synthetize previous work detailing the assessment of self-esteem and to link this work with future possibilities, especially those arising from the beginning of the digital age.

Assessing Self-Esteem

With more than 200 different scales that ostensibly assess self-esteem [ 29 ], the critical issue of assessing self-esteem is far from simple. One of the reasons of this enormous effort lies in a critical element of self-esteem, namely the fact that self-esteem is, by definition, a subjective construct which is not tied to objective standards [ 30 ]. Indeed, because its subjective nature, self-esteem has been assessed mostly by self-report scales [ 31 ], and to a smaller extent by implicit measures [ 32 ]. It is based on subjective, affective-laden evaluations of one’s own self, which however can occur with respect to specific domains (such as work, athletics or physical appearance) or to more broad and general level (such as overarching evaluation of the self as a whole).

A time specific self-evaluations represent the state self-esteem, which refers to the “feeling” aspect of self-esteem, that is an individual’s affectively loaded self-evaluation in a given, specific situation [ 26 ]. Whereas, evaluation of the self as a whole refers to global, general or trait self-esteem [ 31 ]: it is one’s long-term, characteristic and somewhat stable affectively charged self-evaluation. Because of trait self-esteem is a person’s “summary” self-evaluation, it may or may not reflect her state self-esteem in a particular situation.

Finally, self-esteem may capture self-evaluations in specific domains: fluctuations of state self-esteem around a person’s self-esteem typical level can be understood in terms of contingencies of self-worth [ 33 ]. Central to this model is the controversy that the way events and circumstances impact self-esteem lies on the perceived relevance of those events and circumstances to one’s contingencies of self-worth: in other words, contingency self-worth represents a self-evaluation particularly vulnerable in which a failure or rejection is devastating to our sense of self-esteem [ 13 , 34 ].

Historically, scholars involved in self-esteem research have focused mainly on individual differences in dispositional self-esteem [ 26 ]. However, from a practitioner’s perspective, it is worth studying both stable self-esteem and its fluctuations, not only for the obvious advantage of better defining the construct itself, but also due to its possible applications. From the clinical perspective, measuring fluctuation of self-esteem allows to assess the efficacy of clinical interventions quantifying changes in self-esteem. Additionally, it can be used as a valid manipulation check in experimental design in which self-esteem is enhanced or diminished in a specific point in time. Finally, it can be used to understand confounded relations with other constructs. In the subsections below we discuss the assessment of both trait and state self-esteem (2.1), as well as situational self-esteem (2.2). In Table 11.1 we report the main characteristics of the reviewed scales measuring self-esteem.

Trait, Global, and State Self-Esteem Measures

As James [ 37 ] argues self-esteem is open to momentary changes, thus it raises and falls as a function of one’s aspirations and success experiences. Within this framework—developed from the wide body of research that supports self-esteem as an enduring yet flexible concept [ 18 , 38 , 39 , 40 ]— state self-esteem refers to how we evaluate or feel about ourselves in a given situation or at a given point in time. State self-esteem is therefore considered as a series of transitory states, momentary fluctuations, short-lived changes in one’s own global self-esteem [ 36 ]. However, although momentary self-evaluations may be context dependent, there is a self-feelings people have the tendency to maintain and a level of self-esteem that derives by averaging feelings about themselves at one time across a number of different social situations: trait or global self-esteem .

Trait and Global Self-Esteem Measures

To assess trait self-esteem, scholars have developed several measures which differ in number of items and latent dimensionality. Here we discuss the Single-Item Self-Esteem Scale (SISE; [ 35 ]), the Rosenberg Self-Esteem Scale (RSE; [ 18 ]), and the Self-Liking/Self-Competence Scale-Revised (SLSC-R; [ 20 , 21 ]) which are among the most common tools used to assess trait self-esteem.

Single-Item Self-Esteem Scale (SISE) . The simplest way to assess trait self-esteem is to ask individuals whether they have high self-esteem. In fact, this is the core of the Single Single-Item Self-Esteem Scale, which aims to assess the global self-worth or the overall attitude that one holds about oneself (SISE; [ 35 ]). The SISE was developed from the Rosenberg Self-Esteem Scale (described in the next section of this chapter) to assess self-esteem in contexts where time or other constraints severely limit the possibility of using or administering more complex or comprehensive measures of self-esteem. The SISE, as suggested by its name, consists of a single item and assesses a person’s explicit knowledge about her global self-evaluation. This very brief, standardized measure of global self-esteem is valid and reliable [ 31 ] and asks participants to rate whether to have high self-esteem (“ I have high self-esteem ”) is true for them (on a 5-point Likert scale, ranging from ‘not very true of me’ to ‘very true of me.’). Although very simple to use, single-items measures are often less reliable than other multi-items measures, especially when constructs are heterogeneous [ 41 ]. Specifically within the realm of self-esteem and compared to multi-item measures, single-item measures are more susceptible to a person’s biased knowledge of her own explicit feelings of specific or global self-worth, and are also more vulnerable to acquiescence and social desirability [ 31 , 35 ]. Yet, SISE demonstrated to have a high convergent validity with other measures of self-esteem [ 31 , 36 ] and therefore can be used without reservations in situations and research contexts that would require a single-item measure of self-esteem.

Rosenberg Self-Esteem Scale (RSE) . Perhaps the most commonly used scale to assess trait self-esteem is the Rosenberg Self-Esteem Scale (RSE; [ 18 ]). The global self-esteem measured by the RSE is defined as the overall attitude one holds about oneself. This mono-dimensional definition of self-esteem implies the assumption that one might believe to be ‘good enough’ (high self-esteem) or not—meaning, to occur in self-rejection and to lack self-respect. This 10-item, easy-to-administer, self-esteem scale (example question: “ I feel that I have a number of good qualities ”), is originally designed as a 4-point Guttman scale but is often measured on a 5-point Likert-type scale, ranging from (1) Strongly disagree to (5) Strongly agree. It quickly became the “gold standard” for self-esteem research [ 20 ]. Although RSE is the most widely used assessment of self-esteem in research with a high reliability and validity [ 31 ], there has been discussions about its mono-factorial or multi-factorial structure [ 42 ]. However, it seems that a prominent global self-esteem factor consistently explains a considerable amount of variance in the RSE items [ 43 , 44 , 45 ], supporting the hypothesis of the mono-dimensionality of the RSE items [ 46 ].

Self-Liking/Self-Competence Scale-Revised (SLSC-R) . To solve the single- vs. multiple-factor composition of the measures of self-esteem, a specific scale measuring two distinct components of global self-esteem was developed. Specifically, the Self-Liking/Self-Competence Scale (SLSC; and its Revised version SLSC-R) measures the two dimensions of self-esteem corresponding to a personal sense of worth (i.e., self-liking) and to a sense of personal efficacy (i.e., self-competence; [ 20 , 21 ]). More specifically, the authors define self-liking as feeling positive towards one’s own self, while self-competence refers to feeling capable and in control, and to believe that one will be successful in the future. The SLSC is a 16-item self-report scale, measured on a 5-point Likert-type response scale, which encompasses two 8-item subscales measuring each of the two components of self-esteem. The two dimensions (self-liking and self-competence) are related, but substantially distinct [ 31 ]. This scale has shown high reliability and convergent, discriminant and construct validity.

State Self-Esteem Measures

As mentioned, a momentary self-evaluation is represented by the state self-esteem, also called self-esteem feeling, which indicates a person’s affectively laden self-assessment in a given situation [ 26 ]. The development of a measure of state self-esteem stemmed by the need for an instrument designed exclusively for assessing the momentary self-evaluations and self-esteem fluctuation [ 36 , 47 ]. Here we discuss the State Self-Esteem Scale (SSES, [ 36 ]) and the Multidimensional Self-Esteem Inventory (MSEI; [ 22 ]).

State Self-Esteem Scale (SSES) . The State Self-Esteem Scale (SSES) is a 20-item Likert-type scale designed for measuring temporary changes in individual self-esteem and is composed by three subscales including performance, social, and appearance self-esteem [ 36 ]: the performance component measures the extent to which subjects feel their performance is worthy (example question: “ I feel confident about my abilities ”); the social factor assesses the extent to which people feel self-conscious, foolish, or embarrassed about their public image (example question: “ I feel self-conscious ” [reversed item]); finally, the appearance element is instead related to physical appearance (example question: “ I feel good about myself ”).

The Multidimensional Self-Esteem Inventory (MSEI ; [ 22 ]) is an extensive self-report inventory which aims to define a respondent’s profile across eight categories: four categories related to worthiness (lovability, likability, moral self-approval, and body appearance) and four related to competence (competence, personal power, self-control, and body functioning)—which are understood to impact self-esteem. Additionally, the MSEI includes three dimensions related to global measures of self-esteem, sense of identity, and defensiveness—which are understood as overall characteristics of or related to self-esteem. This inventory, initially developed as a clinical test for measuring and treating self-esteem and self-esteem related issues [ 24 ], has been widely used and validated across a great variety of domains both in research and clinical work (e.g., abuse, substance abuse and harassment; positive psychology, adjustment and emotional intelligence; academic, work and sport performance; goal attainment; childhood and adolescence wellbeing; emotional awareness, expression, reactivity and regulation; health psychology and physical wellbeing; mood, eating and personality disorders; stress and coping, trauma, anxiety; treatment, prevention, psychotherapy, self-help; for a complete list see [ 48 ]).

The MSEI consists of 116-item rated on a 5-point Likert scale: (‘strongly agree’ to ‘strongly disagree’; or, ‘hardly ever’ to ‘very often’) which profiles the respondent’s self-esteem on the following 11 scales: lovability (ability to express and receive affection), likeability (feeling accepted and liked by others) moral self-approval (satisfaction with one’s moral values and acting accordingly), body appearance/physical attractiveness (being satisfied with one’s body image), competence (ability to master new tasks), personal power (being assertive and able to influence others), self-control (being disciplined, persistent, able to set, and reach one’s goals), body functioning/vitality (motor coordination and the feeling of being fit), global self-esteem (satisfaction with the self and confidence), identity integration (the self’s internal integrity), and defensive self-esteem (defensive reaction of increasing one’s self-esteem). This instrument was developed by gathering and categorizing thousands of incidents that participants reported as impacting on their self-esteem [ 24 ]. Accordingly, the emerged eight areas of life impacting self-esteem can be considered the components of self-esteem. In addition, the global measures of self-esteem and of secure sense of identity provide information about the overall feelings of worthiness and sense of security in one’s identity; and the assessment of defensive self-enhancement differentiates between secure vs insecure self-esteem: high scores express a biased self-presentation which denies weaknesses and claims strengths and which may not correspond to genuine self-evaluations [ 24 ].

The MSEI can be compared to other measures of self-esteem (especially with the SLSC-R) because the eight components can be construed as corresponding to the realms of worthiness or competence. Specifically, the categories of lovability, likability, moral self-approval, and body appearance imply that the source of self-esteem is more dependent on acceptance and worth, and in fact they are based in part on a judgment of acceptance and value (worthiness). Instead, the categories of competence, personal power, self-control, and body functioning imply that the source of self-esteem is more dependent on one’s own ability to proactively impact the world, and are in fact based in part of one’s own agency and efficacy (competence)—namely, the pillars of perceived self-efficacy [ 49 ]. However, despite the validity, applicability and the comprehensiveness of the MSEI [ 10 , 24 , 48 , 50 ], it is not always possible to use such instrument out of clinical settings where time constrains or other impediments might hinder the likelihood of its usage [ 22 ].

Nevertheless, it is worth noting that MSEI is able to provide important insights that other instruments cannot grasp. First, global measures of self-esteem may not provide sufficient information specificity on which facet or dimension of self-esteem is particularly problematic (or functional) for a given person. Measures that are too specific or contingent are also problematic since a particular domain (e.g., athletic performance) may be relevant for someone but not for others [ 26 ]. Therefore, the mid-level components of self-esteem identified by the MSEI represent a level of analysis useful for effective applied interventions: on the one hand, these components are general enough to be related to a general trait measure of self-esteem (to which they have strong correlations; [ 24 ]) and thus changes in these component can have an impact on overall self-esteem; on the other hand, they are specific enough to provide a deeper, idiosyncratic understanding about how to build on one’s own strengths and overcome weaknesses in the likelihood of an intervention for increasing self-esteem [ 24 ].

Second, the dimension of defensiveness assessed by the MSEI is a critical element in assessing self-esteem: it represents a person’s social desirability bias, namely a bias in self-appraisal, in which she claims rare virtues and denies common human weaknesses (e.g., gladly accepting criticism vs. never trying to avoid unpleasant responsibilities). Evaluating defensiveness scores on the MSEI allows insight into self-presentation and projection to others of an overly positive image of themselves, or in other words of a false self-esteem.

Contingency of Self-Esteem

Expanding upon James’ [ 37 ] idea that individuals differ in the domains on which they base their self-esteem, scholars have proposed several measures that capture domain-specific self-worth. The domains represent the context in which we are not only most likely to pursue self-esteem, but also are most vulnerable—in which a failure or rejection is devastating to our sense of self-worth [ 34 ]. Based on the work carried out by Crocker, Luhtanen, Cooper, and Bouvrette [ 51 ], which we discuss next, researchers have developed measures of contingent self-worth in several domains, such as friendships [ 52 ], romantic relationships [ 53 , 54 ], and body weight [ 55 ].

Contingency of Self-Worth scale (CSWs) . According to Crocker and Wolfe [ 33 ], individuals differ in the areas on which they base their self-worth and they proposed a model that examined self-worth in specific domains. CSWs is a 35-item measure divided into seven domains of contingent self-worth: academic competence, physical appearance, virtue, having God’s love, having love and support from family, outdoing others in competition, and obtaining others’ approval [ 51 ]. A key prediction of the CSWs model is that the impact of life events on self-esteem and affect is proportionate to the relevance of such events to one’s contingency of self-worth. In other words, our self-esteem is more affected (positively or negatively) by events that occur in areas of life that are relevant for us—and for our identity. For example, students who strongly based their self-worth on academic competence experienced lower state self-esteem when they performed poorly on academic tasks, received lower-than-expected grades, or were rejected from graduate schools, compared to those whose self-worth was less based on this domain or did not experience self-threat [ 56 , 57 ].

The Motivational Force of Self-Esteem

It is clear, at this point, that self-esteem is a complex psychological variable and thus there is not a unique way to assess it. In order to effectively operationalize self-esteem, it is important to have clear what aspect of self-esteem is important to a given research question and be aware of the objective limits of the measures available in the literature.

Perhaps, one of the most worrisome issues related to the abovementioned measures is their self-report nature, which is also a wider issue in psychological research. Self-report measures entangle several advantages but limitations too, such as memory limitations, recall biases, and social desirability sensitiveness, as in the case of the SISE which was found susceptible to acquiescence and social desirability [ 31 , 35 ]. To overcome these measurement problems, some researchers have assessed implicit self-esteem (Implicit Association Test-IAT; [ 58 ]) by assessing automatic associations of self (through reaction times) with positive or negative valence [ 59 ]. However, the studies revealed unclear results, as construct divergence between implicit and explicit measures of self-esteem emerged. This result might seem contradictory, yet it highlights that the self-report measures of self-esteem developed to this point, although reliable, valid and all somehow different from each other, have all a common limitation. The operationalization of self-esteem so far developed takes into consideration its cognitive (evaluation of oneself, e.g., RSE), affective (emotional responses, e.g., SSES), behavioral (competence, e.g., SLSC-R), and value components (domain important to the individual, e.g. CSWs), yet they neglect an important aspect of self-esteem: namely, its motivational component. Understanding self-esteem as a fundamental psychological need implies that people are motivated to gain and maintain high levels of self-esteem: in other words, self-esteem is a goal in and of itself [ 60 ]. According to this conceptualization, self-esteem is a self-motive: it provides both a standard and a direction for behavior.

However, although the idea that this motive underlies human behavior has been a central theme in psychological theorizing (e.g., [ 33 , 37 , 61 , 62 , 63 , 64 , 65 ]), self-esteem has been traditionally assessed as a status (situational or stable) that characterizes the individual and does not capture the desire for a high self-esteem. In defining self-esteem, Crocker and Wolfe [ 33 ] recognize the motivational component of such psychological construct; yet, their operationalization of self-esteem does not capture whether the individual is striving to increase the level of self-esteem. Indeed, this operationalization of self-esteem as a motivational concept is, perhaps, the missing link to understand the behavioral strategies with which the individual might decide to engage to pursue or regain optimal levels of self-esteem.

As mentioned, many scholars have indeed assumed that people possess a motive or need to maintain self-esteem (e.g., [ 27 ]). The abovementioned sociometer theory grasps very well this idea, by conceptualizing the motivational force of self-esteem (namely, the self-esteem motive) as the human impulse of minimizing the likelihood of relational devaluation, or in other words, of rejection [ 25 , 26 ]. This, in turn, leads to the pursue and preservation of high self-esteem. In fact, people typically act in ways that they believe will be of help in increasing their social acceptance by increasing their relational value: when this process is achieved, the individual’s self-esteem will be enhanced. On the contrary, when a given situation, a behavior, or even an anticipated, potential, or irrational consequence of a behavior, might hinder the social or relational value of a person, her self-esteem is reduced or, at least, perceived to be threatened. Indeed, events that are known (or potentially known) to be “public”, and therefore are more socially laden, have great effects on self-esteem; rather, “private” events, that are lived (or perceived to be lived) only by the individual, are usually less influential on self-esteem: if self-esteem was determined exclusively by private self-judgments, socially laden events should have no greater impact on self-esteem than private ones [ 27 ].

The Dark Side of Self-Esteem

Perhaps, one of the most significant and influential consequence of this conceptualization lies in the understanding of the crucial role of self-esteem in undesirable behaviors. Indeed, although self-esteem has been historically associated with desirable outcomes (e.g., better performance; [ 6 ]), it also recognized that high self-esteem can be associated with certain dysfunctional psychological processes and undesirable behaviors, such as egotism, narcissism, and violence: the dark side of self-esteem [ 66 ].

Within this conceptualization, the defensive aspect of self-enhancement grasped by the MSEI gains significant relevance. As mentioned, this inventory differentiates between secure vs insecure self-esteem, with high scores expressing a biased self-presentation which tends to always denies weaknesses and claims strengths. This biased self-presentation may correspond to a non-genuine self-evaluation [ 24 ]. Therefore, this non-authentic self-assessment (being conscious or not) might cover other negative patterns of self-evaluations, such as those related to negative, instable, contingent or narcissistic self-appraisals. In this conceptualization, the definition of self-esteem as a motive potentially could explain the heterogeneity of individuals with high self-esteem, encompassing people who honestly acknowledge their good (and bad) qualities along with narcissistic, defensive, and arrogant individuals [ 6 ]. Simply put, the definition of self-esteem as a motive would presuppose that people would strive for high self-esteem, no matter if it is non-genuine or authentic.

Indeed, high scores in overall self-esteem coupled with high variability in the worthiness dimensions of the MSEI are often associated with high scores of narcissism and aggression [ 67 ]. What follows, is that high and optimal self-esteem actually are two distinct constructs: the former can be fragile or secure, while the latter is characterized by genuine, true, stable, and congruent (with implicit self-esteem) high self-esteem [ 67 , 68 ]. Likewise, contingent self-esteem studies (e.g., [ 13 , 69 ]) have also argued for the existence of the dark side of positive self-appraisal, in which individuals become psychologically vulnerable due to their dependence on external validation for their self-esteem.

General principles from this work may be useful for clinical and non-clinical consideration alike. Yet, no specific implications have been developed or tested for assessing or intervening to address contingent self-esteem in a way that could consider positive authentic and dark self-esteem simultaneously, as well as its motivational component.

Future Directions in Assessing Self-Esteem

As we described beforehand, researchers have developed several kinds of measures targeting different features of self-esteem. To sum up, the literature provides measures to assess the state self-esteem, trait self-esteem, and domain-specific self-esteem. However, the quantitative psychological studies carried out to develop such measures relied heavily on surveys and laboratory experiments, which have well-known and long-endured limitations. In fact, on the one hand, surveys require people to make retrospective and often generalized judgments, which tend to be affected by memory limitations and recall biases [ 70 , 71 ]. On the other hand, laboratory experiments do not take into account the context of a person’s daily life which can influence her states and responses [ 72 , 73 ]. Taken together, these considerations raise questions about the ecological validity of theoretical and methodological conclusions if not coupled with field data [ 74 ].

Furthermore, it seems that among several possible theorizations and measures of self-esteem, there is still a lack of consensus upon the most adequate ones. Obviously, it would be too simplistic and trivial to presuppose a priori which theoretical model and measure should be considered the finest to grasp the most precise definition and operationalization of self-esteem. We suggest that the best possible way to overcome such limitations—at least in part—and therefore to select the most efficient and accurate measure of self-esteem, is threefold: (a) to consider carefully the aspects of the psychological process under scrutiny; (b) to understand which facets of self-esteem would be relevant to the main research question; and (c) to take into account which scientific method (e.g., correlational, experimental, etc.) will be most suitable and effective in a given setting.

Nevertheless, as Baumeister et al. [ 75 ] argued, more attention should be given to how individuals actually behave in various situations rather than rely on what they claim, recall having done, or believe they would do in hypothetical situations. In addition, more attention should be given to the interaction between individual and social idiosyncrasies of self-esteem [ 26 ], as a growing amount of evidence shows that different constructs related to the self should indeed incorporate individual, social and cultural components (e.g., [ 76 ]).

Within this perspective, the widespread use of mobile technologies opens up new opportunities of collecting (social-) psychological data in specific contexts and situations. For example, mobile technology is already widely used to optimize health behavior change interventions (e.g., [ 77 ]). More specifically, the use of new digital technologies can help to overcome the limitations of the existing measures of self-esteem, giving the opportunity of looking at changes in self-esteem that occur in a field setting and therefore within the daily life moments. Such new data could not only be relevant to the understanding of self-esteem per sè, but could be coupled with other types of data collected through various types of sensors (e.g., global positioning systems-GPS, microphones, cameras, activity and sleep monitors, heart rate monitors, etc.) or software (e.g., social networks activity, mobile apps, etc.). Therefore, thanks to the means provided by new digital and wearables technologies, for the first time self-reported measures of self-esteem can be combined (above and beyond other psychological measures) to physiological and behavioral measures.

Along this line of research, Quantified Self-enabled data collection procedures could be advantageous. The quantification of the self (Quantified Self—QS) is a form of self-tracking an one’s own daily life activities and behaviors, which eventually allow for the analysis of behavioral trends and patterns across a variety of life domains (e.g., physical activity, nutrition, weight; [ 78 ]). Generally, QS helps the individual to reflect upon such patterns and trends, and potentially leads to the application of behavior change strategies built upon these data. Theoretically, the process of self-monitoring and self-tracking one’s own data could be useful to kick-start a process of behavior change across different life domains by enabling the person to change her relation to her own body and health, and to better control health-related decisions [ 79 ]. However, although some evidence seems to corroborate these hypotheses (e.g., [ 80 , 81 ]), caution should be used in implementing interventions based on QS. First, recent research shows that an excessive quantification of one’s own actions and behaviors could lead to psychological distress [ 82 , 83 ]. Second, and perhaps most importantly, an enormous amount of research shows that in order to promote long-lasting behavior change one will need to detach from the monitoring of external objects and data, and rather should “monitor” his/her own internal physiological and psychological states and processes: in fact, by focusing on internal rather than external rewards and therefore by increasing intrinsic motivation in the new behavior (e.g., [ 84 ]), the person will in turn develop to greater self-awareness, presence in the moment, values and meanings, and perhaps identity change in the long term [ 85 , 86 , 87 ].

New Technologies and Social-Psychological Processes and Constructs

However, as mentioned before, the opportunities arising from the digital era should not be overlooked. In the last couple of decades, plenty of research has shown the link between various technological tools (both hardware and software) and a plethora of psychological processes and characteristics. Since the spread of mobile phones and smartphone, one track of research aimed to study the relationship between the (mis)use of technology and psychological processes (e.g., [ 88 , 89 , 90 ]). For instance, Andreassen et al. [ 88 ] examined the effect of personality traits such as narcissism, socio-demographic characteristics, and self-esteem on addictive social media. Among the others, and accordingly to previous research [ 91 , 92 , 93 ], they found that positive self-concept (i.e., high self-esteem) was negatively related to social media addiction, indicating that the Internet may provide a different social arena from the in the face-to-face life to enhance self-esteem. This track of research is extremely useful and much needed, since it helps clarifying (and will continue to do so) the psychological processes which can cause, be related, or be caused by the functional or dysfunctional use of different technology-based tools. For example, personality traits can predict Facebook use [ 94 ], while technology-based self-help therapies—which relies on minimal contact with an actual therapist—have proven effective, low-cost interventions at least for anxiety and mood disorders [ 95 ].

Furthermore , together with the development of social media, wearable devices, machine learning, big data, data mining technologies, internet of things, etc., another track of research has been consistently growing and aims to leverage these new technologies and related digital tools in various healthcare-related domains [ 96 , 97 ]. More specifically within the social-psychological domain, this track of research is extremely interesting since it could unveil a totally new research filed which will transform the way we measure social-psychological constructs and processes: it is indeed possible to leverage new technologies to measure such constructs and processes—which have been historically assessed by self-reported measures exclusively—through behavioral data collected in a unobtrusively and longitudinally manner (via wearables, smartphone use, smart home and smart office, smart meters, etc.; e.g., [ 98 ]). Some research has already succeeded in this goal. For example, aggregated smartphone usage features can predict the Big-Five personality traits [ 99 ]; Facebook likes can predict, among other sensitive personal attributes, personality traits, intelligence, happiness and addictions [ 100 ]; and, the combination of mobile phone usage and sensor data can predict with 75% accuracy low and high perceived stress [ 101 ]. It is therefore clear that the relationship between automatically extracted physiological and behavioral characteristics derived from rich data, and self-reported measures of social-psychological constructs and processes, could be disentangled eventually, and could potentially lead to new, behavior-based, ecologically valid measures of such facets. For example, Sun et al. [ 102 ], correlated gait patterns with self-reported self-esteem measured via the RSS: first, all participants completed the RSS; then they walked for 2 min on a rectangular carpet, while their gait data were recorded using a Kinect sensor. Based on machine learning, the authors were able to build predicting models to recognize self-esteem, with significant results ( r  = 0.45 for males; r  = 0.59 for females; both p  < 0.001.)

Toward New Methods of Quantifying and Conceptualizing Self-Esteem

Based on the abovementioned considerations, and specifically in relation to self-esteem, we propose a new approach to measuring such construct which could shed light, on the one side, on its theoretical understanding and definition and, on the other side, on its applied implications and applications to promote greater psychological wellbeing and to enhance quality of life. Drawing upon recent developments in applied social psychology (e.g., [ 98 ]) the suggested approach would combine both self-reported and digital technology-based tools. Specifically in the context of Quality of Life Technologies (QoLT)—technologies for assessment or improvement of a person’s quality of life [ 103 ]—we believe that the contingent measurement of self-esteem via self-report and digital technology-based tools, could potentially shed light on its facets and processes above and beyond what has been understood so far through the standalone implementation of self-report measures. In turn, this could potentially expand the goals of QoLT above and beyond its already defined aims [ 103 ]: QoLT could aim at clarifying and expanding the theoretical understating of latent variables included in the WHO definition of QoL, such as self-esteem.

In our view, the combination of self-reported and digital technology-based tools would allow researchers and practitioners to take into account the two missing factors that seem important to assess self-esteem, namely, the momentary experience and the social context . With reference to the former, we suggest that future research should investigate via digital tools the momentary experience of self-esteem , namely its daily fluctuations. Indeed, past research has shown that self-esteem: (a) is most closely connected to a specific class of emotions—rather than to the whole spectrum of emotions—that relate to how people feel about themselves in a specific moment [ 12 ]; (b) that self-esteem indeed is open to momentary changes, raising and falling as a function of one’s aspirations and failure/success experiences [ 36 ]; and that (c) one of the simplest way to measure state self-esteem is directly to ask individuals how they feel about themselves at that given moment via a single-item, valid and reliable measure [ 26 ]. In this vein, new technologies may be used to monitor the momentary experience of self-esteem , through collecting visual data (e.g., posture, clothes worn, facial expression and or posture in ‘selfies’ etc.), audio data (e.g., voice volume/pitch, etc.), text data for content analysis (e.g., text, social media posts, etc.), emoticon usage for sentimental analysis (e.g., number/type/of emoticon).

With reference to the latter, the social context, we believe that longitudinal information derived from new technologies usage (such as behavior shown on social media—likes, comments, selfies posted, etc.; data gathered from GPS enabled devices; physiological data such as heart rate variability, etc.), if combined with validated measures of self-esteem, can be indeed used to indirectly measure both the affective (e.g., self-liking) and behavioral (e.g., competence) components of self-esteem and to couple such components to the specific social context in which self-esteem components are assessed. In fact, previous research shows that: (a) self-esteem can be considered a monitor of social acceptance and therefore it motivates people to behave in ways that would make them valuable in specific social context which is perceived to be relevant by the individual [ 26 , 27 ]; (b) the self-esteem motive, functioning as a tool to avoid social devaluation and rejection, should be measured in-context by contingent measures of such construct [ 51 ]; and (c) in-context measures of self-esteem can shed light on how self-esteem is implicated in affect, cognition, self-regulation of behavior and social processes, and can possibly unveil solutions to debates about the nature and functioning of self-esteem [ 34 , 69 ]—and, in turn, suggest how self-esteem is causally related to mental health, wellbeing, performance and quality of life [ 6 ].

According to the abovementioned evidence, we believe that it would be possible to leverage new technologies specifically in two (or, arguably, one) methods of research: the Experience-Sampling Method [ 104 ] also known as the Ecological Momentary Assessment [ 74 , 105 ]. Certain technology-based applications of such methods are already in use and show important mechanisms and processes that are relevant to the assessment and treatment of mental health—e.g., PsyMate™ [ 106 , 107 ]—, such as the use of machine learning in predicting therapeutic outcomes in depression [ 108 ]. Along the same line of research, initial evidence reveals the efficacy of passive sensors for predicting self-esteem: by using machine learning techniques, it has been possible to relate performance, social and appearance self-esteem to several mobile-based digital behavior categories (such as calls, texts, conversations, and physical activity; [ 109 ]); furthermore, preliminary data indicate that is could be possible to correlate gait data to self-esteem with a fairly good criterion validity [ 102 ], suggesting that posture and perhaps other body-language characteristics could be taken as a good supplementary method to measure self-esteem.

In conclusion, the present chapter shows that far more research is needed to really uncover the potential of a variety of digital and technological tools in the broader field of applied psychology—such as mobile and wearable technologies used in different contexts of applications for the promotion of better quality of life [ 110 , 111 , 112 ]. Within this realm, new measures and conceptualizations of self-esteem should likely depend on both intrapersonal and interpersonal/social factors. We suggest that academics and practitioners alike should try to take advantage of the opportunities provided by the digital age in trying to further understand and measure the concept of self-esteem, by specifically capturing the level of self-esteem in context and anchoring such level to specific behaviors. Such new methods might make both the intrapersonal and social influence of self-esteem salient and decipherable.

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De Dominicis, S., Molinario, E. (2022). The Elusive Quantification of Self-Esteem: Current Challenges and Future Directions. In: Wac, K., Wulfovich, S. (eds) Quantifying Quality of Life. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-94212-0_11

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Self-Esteem

How self-esteem changes over the lifespan, self-esteem builds over the lifespan and peaks at age 60..

Posted September 6, 2018 | Reviewed by Lybi Ma

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Positive self-regard varies from person to person, but research shows that this psychological resource rises and falls in systematic ways across the lifespan.

Scientists recently combed through numerous studies of self-esteem to chart the average changes that occur from childhood to old age. The trajectory they observed challenges ideas about how self-esteem develops and deepens our understanding of a trait thought to influence relationships, health, education , and professional success.

“This is the first time researchers have charted out, across studies, the trajectory of self-esteem,” says Brent Donnellan , a professor of psychology at Michigan State University who was not involved with the research. “It’s a massive contribution to understanding self-esteem across the lifespan.”

The team analyzed 331 studies that assessed self-esteem, collectively covering more than 164,000 people between 4 and 94 years old. Self-esteem is measured with questionnaires in which respondents state to what extent they agree with statements such as “I feel that I'm a person of worth, at least on an equal basis with others” or “I wish I could have more respect for myself.”

The investigators discovered that self-esteem tended to rise slightly from ages 4 to 11, remain stagnant from 11 to 15, increase markedly from 15 to 30, and subtly improve until peaking at 60. It stayed constant from 60 to 70 years old, declined slightly from ages 70 to 90, and dropped sharply from 90 to 94. (Fewer studies addressed the oldest and youngest age groups—just a couple each for the 4 to 6 range and 90 to 94 range—so the evidence is weaker for the tail ends of the spectrum.) The results were published in the journal Psychological Bulletin .

“The trajectory is much more positive than previously thought,” says Ulrich Orth , the lead author of the study and a developmental psychologist at the University of Bern. “Most people experience positive changes in self-esteem as they go through life, and only in very old age does the trend reverse.”

Every individual has a unique set of experiences; the trends observed only chart the average changes that occur. Still, the overall growth in self-esteem between ages 4 and 60 represents substantial change. “The cumulative increase in self-esteem going from childhood to young adulthood to midlife was much larger than I expected,” says Richard Robins , a psychology professor at the University of California, Davis, who was not involved in the research but has worked closely with Orth in the past. For example, the jump in self-esteem was greater in magnitude than the difference between men and women in body weight, Robins explains.

The findings challenge assumptions scientists previously held about certain age groups, Orth says. Past evidence suggested that children experience a decrease in self-esteem between 7 and 9 years old. It was thought that youngsters initially develop an inflated sense of self, which they revise when cognitive advancements allow them to distinguish between the real and ideal self—leading to a dip in self-esteem. However, self-worth turned out to increase slightly during this time window.

Another previous assumption was that adolescents experience a sharp drop in self-esteem thanks to factors such as challenging academic environments, social comparison, and the physiological changes brought on by puberty. Nevertheless, the review demonstrates that on average, self-esteem held steady. The finding doesn’t necessarily imply that everyone maintains the status quo, Robins notes. Changes that take place in adolescence likely lead some to grow and others to struggle, combining to display no overall change.

Past studies also suggested that older folks experience a notable drop in self-esteem, Orth says. The review demonstrated a more benign decrease through age 70 and a stark change only at age 90. Despite the challenges of aging, such as retirement , physical health problems, reduced social mobility, and loss of family and friends, the elderly can maintain relatively high levels of self-esteem. “It’s important to take care of the elderly and help them maintain high self-esteem,” Orth says. “It would be desirable for everyone to be satisfied with themselves when they look back on their life.” Evidence suggests that low self-esteem is a risk factor for developing depression , he adds, so addressing self-esteem could potentially help improve health and well-being for seniors.

Robins has observed the relationship between age and self-esteem firsthand. His father, Al, had worked for the government for years as a psychologist in human resources. When he was in his 80s, he moved to an assisted living home. Al struggled with feeling helpless, useless, and unable to leverage his professional skills, Robins says. He was also extremely frustrated by the institution’s inefficiencies. So Robins suggested that his father meet with the director and share a few ideas about how to improve operations and employee management . The two ended up meeting regularly. “It feels great to use all the knowledge I’ve acquired over the course of my life,” Robins recalls his father saying. “And, secondly, I’m finally getting this place into shape.”

Abigail Fagan is a Senior Associate Editor at Psychology Today .

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The Lifespan Self-Esteem Scale: Initial Validation of a New Measure of Global Self-Esteem

Affiliations.

• 1 a Department of Human Ecology , University of California , Davis.
• 2 b Department of Psychology , Texas A&M University.
• PMID: 28631973
• DOI: 10.1080/00223891.2016.1278380

This article introduces the Lifespan Self-Esteem Scale (LSE), a short measure of global self-esteem suitable for populations drawn from across the lifespan. Many existing measures of global self-esteem cannot be used across multiple developmental periods due to changes in item content, response formats, and other scale characteristics. This creates a need for a new lifespan scale so that changes in global self-esteem over time can be studied without confounding maturational changes with alterations in the measure. The LSE is a 4-item measure with a 5-point response format using items inspired by established self-esteem scales. The scale is essentially unidimensional and internally consistent, and it converges with existing self-esteem measures across ages 5 to 93 (N = 2,714). Thus, the LSE appears to be a useful measure of global self-esteem suitable for use across the lifespan as well as contexts where a short measure is desirable, such as populations with short attention spans or large projects assessing multiple constructs. Moreover, the LSE is one of the first global self-esteem scales to be validated for children younger than age 8, which provides the opportunity to broaden the field to include research on early formation and development of global self-esteem, an area that has previously been limited.

Publication types

• Validation Study
• Aged, 80 and over
• Middle Aged
• Personality Inventory / standards*
• Psychometrics
• Reproducibility of Results
• Self Concept*
• Surveys and Questionnaires / standards*
• Young Adult