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The prevalence of depression in a high school population.

An increasing number of articles, books, and conferences attest to the growing attention being paid to depression in children and adolescents. While few authors question its existence (Chartier & Ranieri, 1984), there is a general lack of empirical data on affective disorders in nonclinical adolescent populations (Teri, 1982; Puig-Antich, 1985; Faulstich et al., 1986; Sullivan & Engin, 1986). Studies in the area of adolescent depression have involved different populations, methodologies, and instruments, resulting in widely discrepant results (Hodgman, 1985; see Table 1). Consequently, a confusing picture emerges of the mental health of North American youth.

In spite of the difficulties posed by empirical research, prevalence studies are essential for professionals in this field. Clinically we are likely to respond differently if we see depression in adolescence as ubiquitous as opposed to a phenomenon that is rare or does not exist at all during that stage of development. Prevalence studies provide an idea of the proportion of adolescents who experience depressive symptomatology at a given time.


Another clinical consideration is that, as professionals, we are expected to represent fairly and accurately the people with whom we work. Whether this occurs through the presentation of papers, published articles, or simply in conversation, it is incumbent upon us to reflect the "current state" of adolescent mental health.

Prevalence studies provide important data for further explorations. The accumulation of knowledge in this area facilitates understanding of this group over time, and allows comparison with other groups. In addition, data obtained from these investigations can play a part in determining types and amounts of clinical services. In short, the allocation of (scarce) clinical resources can be affected by the prevalence rates of mental illnesses afflicting adolescents.



The present study was undertaken in the metropolitan Toronto area. Parents and students of three representative secondary schools were informed that, on a specified day, a mental health questionnaire would be distributed for completion by the students. Both parents and students had the opportunity to decline participation. The completed questionnaires were then collected and tabulated by a research team not connected with the schools involved.

Each school offered a combination of general and advanced academic courses, as well as business and technical subjects. Data were obtained from 2,909 students. An additional 430 students were absent from school on the day data were collected, and another 272 chose not to participate.

Of the 2,909 students who completed the form, 141 did not indicate their gender and 70 were aged 20 or older. Data from these students were not included in the overall analysis. Thus, the final number of students in this study was 2,698, of which 49% were male and 51% were female.


Kovacs (1985) points out that it is important to quantify clinical phenomena such as depression in order to understand them from a scientific perspective. However, one reason for the lack of empirical information on adolescent depression may be that there is no widely accepted instrument specifically designed for evaluation of this population, although there is for children (Children's Depression Inventory; Kovacs, 1985) and adults (Beck Depression Inventory; Beck & Beamesderfer, 1974). Nevertheless, Table 1 demonstrates that the Beck Depression Inventory (BDI) has been used successfully with an adolescent population. It has also been used effectively as a screening instrument with both adults and adolescents.

The BDI is a 21-item self-report measure assessing four relevant aspects of depression: cognition, behavior, affect, and somatic concerns. Each item consists of four statements reflecting increasing depressive symptomatology. Statements are ranked from 0 to 3, with 0 being the least serious and 3 representing the most serious. This results in a total score ranging from 0 to 63. In terms of readability, Teri (1982) classified the BDI as requiring a fifth-grade reading level, making it readily comprehensible to the average high school student.


The results of a three-way analysis of variance (Age X Gender X School) are shown in Table 2. There was no significant difference in depression scores among the three schools. However, there was a significant main effect of age (F = 3.91, p |is less than~ .001) and gender (F = 38.31, p |is less than~ .001). There was one interaction effect, School X Gender (F = 5.51, p |is less than~ .004).




Further analysis was conducted to obtain descriptive statistics. Table 3 shows the mean scores on the BDI by age and gender.

Table 4 presents the distribution of students scoring in the four categories, ranging from none to severe symptomatology. The cutoff points for these groups, taken from Kendall et al. (1987), were: none (0-9), mild (10-19), moderate (20-29), and severe (30-63).

Table 5 shows the percentage of subjects by age and gender with scores in the collapsed categories of either none to mild depression or moderate to severe depression. The categories used for this breakdown were based on Beck's cutoff points of 19 or under constituting none to mild and 20 and above indicating moderate to severe depression (Kendall et al., 1987).

Tables 3 and 5 indicate that, with greater age, there was an increase in depression scores for both males and females. Table 3 provides this information in terms of mean BDI scores, while Table 5 shows that, with an increase in age, there was a gradual shift in frequencies away from the none to mild category and toward the moderate to severe category. However, this trend was not monotonic. Rather, there was a peak for both female and males at age 16, followed by a decrease and then another rise at age 19.

The data also reveal that for males there was (a) a somewhat steady increase in the frequency of scores in the mildly depressed range as TABULAR DATA OMITTED age increases, (b) a slight increase in the frequency of scores in the moderate range, and (c) virtually no change in the frequency of scores in the severe range. For females, there was virtually no age trend in the frequency of scores in the mildly depressed range, but clear age-related increases for both moderate and severe depression.

While there was a significant gender difference, it is important to note that the overall mean scores for both males (6.93) and females (9.58) were below the cutoff point for mild depression. In fact only 81 students from the entire population (2,698) scored in the severely depressed range, and 182 students scored in the moderately depressed range.


With reference to other studies, there are clear similarities and differences. The overall mean score on the BDI for this population was 8.29. This is lower than the mean in three studies and higher than in one other, using the same instrument. It approximates more closely the 8.45 average obtained by Ehrenberg et al. (1990) and the 8.47 average of Teri (1982) than the 10.30 of Baron and Perron (1986) or the 6.23 of Kaplan et al. (1980). The results of the present investigation lend substantial confirmation to the moderate mean scores of those other studies, especially when the large sample size is taken into consideration.

The gender difference, although similar to that of Baron and Perron (1986), stands in contrast to the findings of Teri (1982) and Sullivan and Engin (1986), who found no gender differences in their studies using the BDI and the BDI Short Form, respectively. We believe that our finding should be interpreted with caution because of the possibility that it reflects response bias rather than any real difference in the rate of depression.

While the results show an increase in measured depression over the age range sampled, there was an interesting and unexpected finding, namely the peak in the depression scores at age 16. When gathering demographic data, one is not surprised by occasional deviations from smooth or monotonic functions. There are several reasons, however, for arguing that this peak in the data may not be spurious. First, the peak itself was fairly pronounced. Second, the sample size for this study was large. Third, the effect was consistent for both males and females. While this finding needs to be confirmed through further study, one might speculate about its meaning. Around age 16, adolescents may experience more stress and anxiety as a result of the increasing demands of school life, or as a reaction to social adjustment to peers and dating or to tensions arising from emerging independence from the family. Whatever the causes, this is a time when some adolescents need to be approached with heightened sensitivity.

Finally, substantial differences are apparent in the percentage of students scoring in the moderate to severe range. Other studies, using a variety of instruments, have reported findings such as: (a) 33% of seventh- and eighth-grade students fell into the moderate to severe range (Albert & Beck, 1975); (b) over 30% of students reported moderate to severe levels of depressive symptomatology (Sullivan & Engin, 1986); (c) 48.5% of students evidenced depressive symptoms (Kashani et al., 1987); (d) nearly one half of 14- and 15-year-olds reported "appreciable misery" or depression (Rutter et al., 1976); (e) 32% of adolescents fell into the moderate or severely depressed categories (Teri, 1982); and (f) 35% of adolescents reported symptoms sufficient for "high depressed" labels and an additional 38% for "medium depressed," for a total of 73% classified as medium or highly depressed (Paton & Kandel, 1978).

The findings of this investigation are more similar to those of Adams (1986), who reported only 18.1% of the adolescents scoring above 16 on the BDI, and the results of Kaplan et al. (1980), who found only 60% of 80 students scoring over 16 on the BDI. Clearly our finding of only 7% of males and 12% of females scoring in the moderate to severe range (20 + on the BDI) lends considerable credence to a more positive view of adolescent mental health.

This study was not without its limitations. The population consisted of students present on a specific day in three schools in a large urban center. Students not enrolled at this level of secondary school, adolescents no longer attending school, students absent on the day the study was completed, and those who refused to participate were excluded. It may be argued that, in this excluded group, there may be a subgroup at greater risk for depression. That is, depressed adolescents may be more likely to drop out or have school attendance problems.

The setting for this study, and others like it, also may have affected the results. It is known that administering self-report measures in nonclinical populations can result in inflated scores (Baron & Perron, 1986). One may question whether this inflation would be more or less likely to occur when questionnaires are completed confidentially in large groups in classroom settings.

One final comment relates to the usefulness of the BDI with an adolescent population. As mentioned earlier, this instrument was selected due to the absence of an "industry standard" for this age group. Strengths of the BDI are the clarity of its language and ease of administration. In terms of the psychometric properties of this instrument, our findings were consistent with other reports (Kendall et al., 1987) which have confirmed a positive skew in the distribution of scores.


Dramatic and extreme rhetoric punctuates many articles and discussions involving adolescents. Two problems that arise as a consequence are: (a) all adolescents are viewed as experiencing psychological distress, and (b) adolescents who need help are not taken seriously because their behavior and feelings are considered part of a normal phase of adolescence. This investigation, with its substantial sample size, lends support to the view of Offer and Sabshin (1984), who suggest that most adolescents pass through this time period with little psychological disruption. The relatively low rates of moderate and severe depression in this population indicate that the large majority of teenagers do not experience difficulty in this area. The corollary is that those who evidence symptomatology need to be identified and helped.


Adams, R. M. (1986). Adolescent depression study. Unpublished manuscript, Phi Delta Kappa (Dallas Chapter).

Albert, N., & Beck, A. T. (1975). Incidence of depression in early adolescence: A preliminary study. Journal of Youth and Adolescence, 4 (4), 301-307.

Baron, P., & Perron, L. M. (1986). Sex differences in the Beck Depression Inventory scores of adolescents. Journal of Youth and Adolescence, 15 (2), 165-171.

Beck, A. T., & Beamesderfer, A. (1974). Assessment of depression: The Depression Inventory. In P. Pichet (Ed.), Psychological measurements in psychopharmacology: Vol. 7 (pp. 151-169). Paris: Karger, Basel.

Chartier, G. M., & Ranieri, D. J. (1984). Adolescent depression: Concepts, treatments, prevention. In P. Karoly & J. J. Steffen (Eds.), Advances in child behavioral analysis and therapy: Vol. 3 (pp. 153-193). Lexington, MA: D. C. Heath and Co.

Ehrenberg, M. F., Cox, D. N., & Koopman, R. F. (1990). The prevalence of depression in high school students. Adolescence, 25(100), 905-912.

Faulstich, M. E., Carey, M. P., Ruggiero, C., Enyart, P., & Gresham, F. (1986). Assessment of depression in children and adolescents: An evaluation of the Center for Epidemiological Studies Depression Scale for Children (CES-DC). American Journal of Psychiatry, 143(8), 1024-1027.

Hodgman, C. H. (1985). Recent findings in adolescent depression and suicide. Developmental and Behavioral Pediatrics, 6(3), 162-170.

Kaplan, S. L., Nussbaum, M., Skomorowsky, P., Shenker, I. R., & Ramsey, P. (1980). Health habits and depression in adolescence. Journal of Youth and Adolescence, 9(4), 299-304.

Kashani, J. H., Carlsen, G. A., Beck, N. C., Hoeper, E. W., Corcoran, C. M., McAllister, J. A., Fallahi, C., Rosenberg, T. K., & Reid, J. C. (1987). Depressive symptoms and depressed mood among a community sample of adolescents. American Journal of Psychiatry, 144(7), 931-934.

Kendall, P. C., Hollon, S. D., Beck, A. T., Hammen, C. L., & Ingram, R.E. (1987). Issues and recommendations regarding use of the Beck Depression Inventory. Cognitive Therapy and Research, 11(3), 289-299.

Kovacs, M. (1985). The Children's Depression Inventory (Revised July 1985). Unpublished manuscript.

Offer, D., & Sabshin, M. (1984). Adolescence: Empirical perspectives. In D. Offer & M. Sabshin (Eds.), Normality and the life cycle (pp. 76-107). New York: Basic Books.

Paton, S. M., & Kandel, D. B. (1978). Psychological factors and adolescent illicit drug use: Ethnicity and sex differences. Adolescence, 13(50), 187-200.

Puig-Antich, J. (1985). Affective disorders. In H. I. Kaplan & B. J. Sadock (Eds.), Comprehensive textbook of psychiatry: Vol. 2 (4th ed.). Baltimore: Williams and Wilkins.

Rutter, M., Graham, P., Chadwick, P. F. D., & Yule, W. (1976). Adolescent turmoil: Fact or fiction? Journal of Child Psychology and Psychiatry, 17, 35-56.

Sullivan, W. O., & Engin, A. W. (1986). Adolescent depression: Its prevalence in high school students. Journal of School Psychology, 24, 103-109.

Teri, L. (1982). The use of the Beck Depression Inventory with adolescents. Journal of Abnormal Child Psychology, 10, 277-284.

Brian Connelly, Ph.D., David Johnston, M.S.W., Ian D. R. Brown, Ph.D., and Steve Mackay, M.Sc., Scarborough Board of Education.

Edward G. Blackstock, Ph.D., Peel Board of Education.
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Author:Connelly, Brian; Johnston, David; Brown, Ian D.R.; Mackay, steve; Blackstock, Edward G.
Date:Mar 22, 1993
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