Abstract
Background
The age of onset for most mental disorders is typically young adulthood, and the university setting is an important one for addressing mental health. The University Personality Inventory (UPI), which was developed to detect mental health problems in university students, is widely used for screening in Japan. However, there have been limited reports on the factor structure of the UPI based on a statistical test for binary indicators. The objective of this study was to assess the factor structure of the UPI in Japanese medical students.
Methods
This study examined the factor structure of the UPI in a sample of 1185 Japanese medical students at the time of university admission. The students were divided into subgroup A (n = 589) and subgroup B (n = 596) according to their year of university admission. Based on tetrachoric correlation coefficients, exploratory factor analysis (EFA) with promax rotation was applied to explore the dimensions of the inventory in subgroup A. Confirmatory factor analysis (CFA) was then conducted to verify the dimensions in subgroup B.
Results
The EFA with categorical variables yielded four factors in subgroup A. These factors, accounting for 48.9% of the variance, were labeled “Depression and Irritability”, “Anxiety and Persecutory Belief”, “Physical Symptoms”, and “Dependence”. The new four-factor structure showed good fit, and traditional factor structures previously reported were replicated via CFA. The internal consistency reliability was good for the overall UPI scale (alpha = 0.97) and for its four new factors (alpha = 0.83–0.91).
Conclusions
The UPI is a valid and reliable measure that can be used to assess symptoms across four dimensions of mental health in university settings. These findings offer a starting point for the detection of individuals with mental health problems.
Keywords: University personality inventory, Medical students, Exploratory factor analysis, Confirmatory factor analysis
Background
The age of onset for most mental disorders is typically young adulthood [1]. In Japan, more than half of young adults receive postsecondary education [2], and universities are an important setting for addressing mental health. Approximately half of university students are living away from home for the first time and face academic pressure as they study for a degree [3]. Surveys of student life indicate that in addition to academic pressure, university students encounter a multitude of stressors related to financial strains, career choice, and friendship [3]. Compared to the general population, university students might have poorer health-related quality of life [4], and their mental health is more of a problem than their physical health [5]. Although mental illness is prevalent in university students [6, 7], a nonnegligible number of students are reluctant to use mental health services [8] and do not receive adequate treatment [9]. Previous studies have shown that mental health in university students could affect not only their grades but also their intention to drop out [4, 10]. Given the relationship between academic outcomes and mental health, screening for and treating mental health problems have been proposed to promote mental health in university settings.
The University Personality Inventory (UPI), which was developed to assess the mental health status of university students in 1966, has been widely adopted in universities in Japan [11]. The UPI is a 60-item self-report questionnaire that uses a binary scale. The existing literature supports the reliability and convergent validity of this scale [12–14]. Students with a UPI total sum score above 20 or those who respond “yes” to item 25 (“Have an idea of wanting to die”) are identified and guided to arrange personal interviews with mental health professionals [11]. However, mental health problems are heterogeneous and are expressed as a combination of emotional, physical, and social complaints [15]. Traditionally, the UPI has been regarded as a multidimensional instrument for assessing symptoms across four or five domains: physical symptoms, depression, anxiety, neuroticism, persecutory beliefs, and obsessive-compulsive symptoms [11]. However, it has been half a century since the UPI was developed in Japan. Differences in social norms and the degree of westernization could cause psychological distress specific to modern life [16] and affect the factor structure of an instrument that assesses the mental health status of Japanese university students. Furthermore, there have been limited reports on the factor structure of the UPI based on a statistical test for binary indicators [11, 17]. Although a recent report from China found a new five-factor structure consisting of physical symptoms, cognitive symptoms, emotional vulnerability, social avoidance, and interpersonal sensitivity [17], social differences make it difficult to extrapolate the mental health status of Japanese students from the results of a Chinese sample. In addition, the 60-item measurement tool might be lengthy and onerous despite the UPI scale’s established reliability. Brief measurement devices can alleviate respondent burden and lower refusal rates in surveys. It is thus necessary to assess the factor structure of the UPI and suggest the brief version for use among Japanese university students.
This study focuses on medical students, who experience a stressful environment characterized by an increasing study load due to the demanding medical curriculum [18]. In Japan, increasing numbers of students are dropping out of medical school, which is an important issue [19]. A systematic review concerning mental health among medical students indicated that their levels of psychological distress are consistently higher than in the general population [20]. The objective of this study was to assess the factor structure of the UPI in first-year medical students in Japan. To our knowledge, this study is the first to examine the factor structure of the UPI based on a statistical test for binary indicators of the scale.
Methods
Participants
This study was conducted between April 2010 and April 2019. The surveys were distributed to 1188 medical students in April of their first year at Dokkyo Medical University School of Medicine. Of the 1188 distributed surveys, 1185 questionnaires (749 males and 436 females) were completed. The demographic data (age and sex) were obtained from a self-report questionnaire. The 1185 students were divided into two subgroups according to their year of university admission. Subgroup A (n = 589; 372 males and 217 females) consisted of students who entered the university in an even-numbered year, and subgroup B (n = 596; 377 males and 219 females) consisted of students who entered the university in an odd-numbered year.
Measures
The UPI is a 60-item self-report measure assessing whether an individual usually experienced the described symptom during the past year [11]. For each item, a score of 1 was given for “Yes”, and 0 was given for “No”. After excluding the lie scales (items 5, 20, 35, and 50), we analyzed the 56 items describing psychosomatic problems. Traditionally, the 56-item UPI is regarded as a multidimensional instrument with as many as four or five factors [11]. The higher the score, the poorer the mental and/or physical condition.
Statistical analysis
Based on tetrachoric correlation coefficients, an EFA for binary indicators was conducted with promax rotation to analyze the underlying structure of the UPI in subgroup A. Because previous studies showed interfactor correlations in the factor structure of the UPI, we used promax rotation, which allows the factors to be correlated. We determined the number of factors to retain based on eigenvalues, the scree test, and the interpretability of the factors; four factors were retained. Furthermore, confirmatory factor analysis (CFA) was conducted to verify the dimensions in subgroup B. Five practical fit indices were used to evaluate the model fit: the goodness of fit index (GFI), the adjusted goodness of fit index (AGFI), the root mean square error of approximation (RMSEA), and the comparative fit index (CFI). A GFI, AGFI and CFI close to 1 indicate a good fit. An RMSEA < 0.05 indicates good fit. The data analysis was performed using R for Windows, Version 3.6.3 (The R Foundation for Statistical Computing, Vienna, Austria) [21].
Results
The mean (± standard deviation) age of the study participants was 19.6 ± 1.7 years (subgroup A: 19.6 ± 1.7; subgroup B: 19.5 ± 1.6). The overall reliability of the scale was good (alpha = 0.97). Corrected item-total correlations for individual items ranged from 0.37 (item 31, “Distressed by blushing”) to 0.80 (item 13, “Pessimistic”). The EFA with categorical variables yielded four factors in subgroup A. Factors 1 through Factor 4 were tentatively labeled “Depression and Irritability”, “Anxiety and Persecutory Belief”, “Physical Symptoms”, and “Dependence”. These factors accounted for 48.9% of the variance. Table 1 presents the rotated factor loadings for the new four-factor model. Twenty-six items had low loadings: 3, 4, 7, 9, 11, 13, 14, 15, 16, 22, 27, 28, 32, 34, 36, 37, 40, 42, 44, 47, 49, 51, 53, 54, 59 and 60.
Table 1.
Item | Factor 1 | Factor 2 | Factor 3 | Factor 4 | |
---|---|---|---|---|---|
1 | Poor appetite | 0.016 | − 0.056 | 0.664 | 0.106 |
2 | Feel sick, stomachache | 0.003 | 0.013 | 0.761 | 0.019 |
3 | Easily have diarrhea or constipation | −0.145 | 0.183 | 0.388 | 0.139 |
4 | Care about palpitation and pulse | −0.129 | 0.393 | 0.404 | 0.018 |
6 | Full of dissatisfaction and complaints | 0.693 | 0.145 | −0.011 | 0.013 |
7 | High expectation from parents | 0.483 | 0.038 | 0.039 | −0.126 |
8 | My past and family is misfortune | 0.766 | 0.050 | −0.183 | −0.154 |
9 | Over-worry about my future | 0.177 | 0.214 | −0.059 | 0.406 |
10 | Do not like meeting others | 0.584 | −0.006 | 0.200 | 0.083 |
11 | Feel that I am not myself | 0.285 | 0.238 | 0.068 | 0.349 |
12 | Lack of enthusiasm and positivity | 0.470 | −0.271 | 0.538 | 0.184 |
13 | Pessimistic | 0.358 | 0.152 | 0.185 | 0.282 |
14 | Distracted | 0.164 | 0.119 | 0.224 | 0.405 |
15 | Over-uneven in emotion | 0.430 | 0.264 | 0.042 | 0.110 |
16 | Frequent insomnia | 0.245 | 0.072 | 0.230 | 0.021 |
17 | Headache | 0.098 | −0.018 | 0.691 | −0.076 |
18 | Ache in neck and shoulder | −0.043 | − 0.001 | 0.632 | − 0.096 |
19 | Chest pain or feel oppressed | 0.040 | 0.132 | 0.545 | 0.050 |
21 | Intolerance | 0.048 | 0.409 | −0.255 | 0.576 |
22 | Inclined to worry | 0.234 | 0.291 | 0.126 | 0.235 |
23 | Restless | 0.522 | 0.327 | 0.033 | −0.061 |
24 | Irritable | 0.657 | 0.329 | −0.074 | −0.112 |
25 | Have idea of wanting to die | 0.685 | 0.086 | −0.045 | 0.051 |
26 | No interest in anything | 0.523 | −0.227 | 0.178 | 0.452 |
27 | Declining memory | 0.235 | 0.141 | 0.217 | 0.172 |
28 | Lack of patience | 0.339 | −0.160 | 0.284 | 0.354 |
29 | Lack of judgment | −0.151 | −0.008 | 0.090 | 0.833 |
30 | Too dependent on others | 0.080 | 0.143 | −0.097 | 0.567 |
31 | Distressed by blushing | −0.156 | 0.516 | 0.069 | −0.029 |
32 | Stuttering, faltering voice | 0.128 | 0.309 | 0.270 | 0.083 |
33 | Feel hot and cold | −0.357 | 0.377 | 0.660 | 0.004 |
34 | Concern about urination or sexual organs | 0.352 | 0.404 | 0.107 | −0.294 |
36 | Uneasy without reason | 0.194 | 0.225 | 0.028 | 0.437 |
37 | Feel uneasy when alone | −0.046 | 0.336 | 0.026 | 0.250 |
38 | Lack of confidence | 0.007 | 0.029 | 0.155 | 0.753 |
39 | Irresolute about anything | −0.119 | 0.114 | −0.063 | 0.837 |
40 | Easily feel misunderstood | 0.450 | 0.449 | −0.079 | −0.104 |
41 | Lack faith in others | 0.560 | 0.036 | 0.063 | 0.141 |
42 | Over-suspicious | 0.047 | 0.411 | 0.007 | 0.265 |
43 | Unwilling to associate with others | 0.644 | −0.162 | 0.038 | 0.185 |
44 | Feel self-abased | 0.222 | 0.280 | −0.001 | 0.384 |
45 | Catastrophizing | 0.005 | 0.521 | 0.032 | 0.207 |
46 | Physically exhausted | 0.172 | −0.191 | 0.656 | 0.238 |
47 | In cold sweat when I hurry | −0.225 | 0.460 | 0.157 | 0.114 |
48 | Dizzy when I stand up | 0.045 | 0.031 | 0.745 | −0.215 |
49 | Have ever lost consciousness, cramp | 0.155 | 0.309 | 0.190 | −0.283 |
51 | Over-rigid | 0.167 | 0.365 | −0.039 | 0.060 |
52 | Cannot give up repeating things | −0.055 | 0.506 | −0.154 | 0.254 |
53 | Susceptible to dirtiness | 0.052 | 0.417 | 0.154 | −0.034 |
54 | Cannot get rid of meaningless idea | 0.272 | 0.382 | −0.085 | 0.286 |
55 | Sense weird smell from myself | 0.151 | 0.551 | −0.059 | 0.029 |
56 | Suspect others say something bad about me | 0.434 | 0.538 | 0.158 | −0.367 |
57 | Wary of others | 0.214 | 0.600 | −0.202 | 0.325 |
58 | Care about others’ gaze | 0.087 | 0.638 | −0.101 | 0.268 |
59 | Feel others despise me | 0.341 | 0.217 | 0.201 | 0.145 |
60 | Sensitive emotions | 0.432 | 0.401 | −0.115 | 0.104 |
Interfactor correlations | |||||
Factor 1 | 1.000 | ||||
Factor 2 | 0.567 | 1.000 | |||
Factor 3 | 0.567 | 0.567 | 1.000 | ||
Factor 4 | 0.616 | 0.533 | 0.464 | 1.000 |
The loadings of 0.50 or above are boldfaced
After excluding the 26 items with low loadings, a CFA was conducted on the new four-factor model with the remaining 30 items in subgroup B. The factor loadings for the new four-factor model are shown in Table 2. The alpha coefficients for the four new factors were 0.91 for “Depression and Irritability”, 0.83 for “Anxiety and Persecutory Belief”, 0.89 for “Physical Symptoms” and 0.90 for “Dependence”. Intercorrelations between the four factors in the new four-factor model ranged from 0.55 to 0.77. For the traditional four-factor model, CFA was conducted on the 56 items in subgroup B. The factor loadings for the traditional four-factor model are shown in Table 3. The alpha coefficients for the traditional four factors were 0.89 for “Physical Symptoms”, 0.94 for “Depression”, 0.90 for “Anxiety” and 0.89 for “Neuroticism and Persecutory Beliefs”. Intercorrelations between the four factors in the traditional four-factor model ranged from 0.69 to 0.96. For the traditional five-factor model, CFA was conducted on the 56 items in subgroup B. The factor loadings for the traditional five-factor model are shown in Table 4. The alpha coefficients for the traditional five factors were 0.89 for “Physical Symptoms”, 0.94 for “Depression”, 0.90 for “Anxiety”, 0.78 for “Obsessive-compulsive” and 0.87 for “Persecutory Beliefs”. Intercorrelations between the five factors in the traditional five-factor model ranged from 0.60 to 0.96. Table 5 shows the fit indices for the CFA models.
Table 2.
Item | New four-factor model | ||||
---|---|---|---|---|---|
Factor 1 | Factor 2 | Factor 3 | Factor 4 | ||
6 | Full of dissatisfaction and complaints | 0.585 | |||
8 | My past and family is misfortune | 0.353 | |||
10 | Do not like meeting others | 0.617 | |||
23 | Restless | 0.581 | |||
24 | Irritable | 0.565 | |||
25 | Have idea of wanting to die | 0.523 | |||
26 | No interest in anything | 0.552 | |||
41 | Lack faith in others | 0.613 | |||
43 | Unwilling to associate with others | 0.553 | |||
31 | Distressed by blushing | 0.356 | |||
45 | Catastrophizing | 0.539 | |||
52 | Cannot give up repeating things | 0.458 | |||
55 | Sense weird smell from myself | 0.398 | |||
56 | Suspect others say something bad about me | 0.462 | |||
57 | Wary of others | 0.703 | |||
58 | Care about others’ gaze | 0.644 | |||
1 | Poor appetite | 0.527 | |||
2 | Feel sick, stomachache | 0.541 | |||
12 | Lack of enthusiasm and positivity | 0.724 | |||
17 | Headache | 0.519 | |||
18 | Ache in neck and shoulder | 0.424 | |||
19 | Chest pain or feel oppressed | 0.481 | |||
33 | Feel hot and cold | 0.457 | |||
46 | Physically exhausted | 0.728 | |||
48 | Dizzy when I stand up | 0.408 | |||
21 | Intolerance | 0.584 | |||
29 | Lack of judgment | 0.629 | |||
30 | Too dependent on others | 0.585 | |||
38 | Lack of confidence | 0.774 | |||
39 | Irresolute about anything | 0.707 | |||
Interfactor correlations | |||||
Factor 1 | 1.000 | ||||
Factor 2 | 0.683 | 1.000 | |||
Factor 3 | 0.692 | 0.624 | 1.000 | ||
Factor 4 | 0.618 | 0.769 | 0.554 | 1.000 |
The factor 1 was labelled the “Depression and Ittitability” factor
The factor 2 was labelled the “Anxiety and Persecutory belief” factor
The factor 3 was labelled the “Physical symptoms” factor
The factor 4 was labelled the “Dependence” factor
Table 3.
Item | Traditional four-factor model | ||||
---|---|---|---|---|---|
Factor 1 | Factor 2 | Factor 3 | Factor 4 | ||
1 | Poor appetite | 0.544 | |||
2 | Feel sick, stomachache | 0.591 | |||
3 | Easily have diarrhea or constipation | 0.412 | |||
4 | Care about palpitation and pulse | 0.395 | |||
16 | Frequent insomnia | 0.400 | |||
17 | Headache | 0.506 | |||
18 | Ache in neck and shoulder | 0.356 | |||
19 | Chest pain or feel oppressed | 0.473 | |||
31 | Distressed by blushing | 0.270 | |||
32 | Stuttering, faltering voice | 0.465 | |||
33 | Feel hot and cold | 0.490 | |||
34 | Concern about urination or sexual organs | 0.354 | |||
46 | Physically exhausted | 0.662 | |||
47 | In cold sweat when I hurry | 0.358 | |||
48 | Dizzy when I stand up | 0.432 | |||
49 | Have ever lost consciousness, cramp | 0.102 | |||
6 | Full of dissatisfaction and complaints | 0.573 | |||
7 | High expectation from parents | 0.253 | |||
8 | My past and family is misfortune | 0.217 | |||
9 | Over-worry about my future | 0.502 | |||
10 | Do not like meeting others | 0.519 | |||
11 | Feel that I am not myself | 0.490 | |||
12 | Lack of enthusiasm and positivity | 0.621 | |||
13 | Pessimistic | 0.674 | |||
14 | Distracted | 0.622 | |||
15 | Over-uneven in emotion | 0.563 | |||
21 | Intolerance | 0.521 | |||
22 | Inclined to worry | 0.579 | |||
23 | Restless | 0.568 | |||
24 | Irritable | 0.506 | |||
25 | Have idea of wanting to die | 0.408 | |||
26 | No interest in anything | 0.529 | |||
27 | Declining memory | 0.502 | |||
28 | Lack of patience | 0.546 | |||
29 | Lack of judgment | 0.505 | |||
30 | Too dependent on others | 0.469 | |||
36 | Uneasy without reason | 0.564 | |||
37 | Feel uneasy when alone | 0.317 | |||
38 | Lack of confidence | 0.638 | |||
39 | Irresolute about anything | 0.525 | |||
40 | Easily feel misunderstood | 0.466 | |||
41 | Lack faith in others | 0.496 | |||
42 | Over-suspicious | 0.501 | |||
43 | Unwilling to associate with others | 0.419 | |||
44 | Feel self-abased | 0.627 | |||
45 | Catastrophizing | 0.527 | |||
51 | Over-rigid | 0.396 | |||
52 | Cannot give up repeating things | 0.394 | |||
53 | Susceptible to dirtiness | 0.351 | |||
54 | Cannot get rid of meaningless idea | 0.623 | |||
55 | Sense weird smell from myself | 0.429 | |||
56 | Suspect others say something bad about me | 0.416 | |||
57 | Wary of others | 0.697 | |||
58 | Care about others’ gaze | 0.639 | |||
59 | Feel others despise me | 0.475 | |||
60 | Sensitive emotions | 0.596 | |||
Interfactor correlations | |||||
Factor 1 | 1.000 | ||||
Factor 2 | 0.753 | 1.000 | |||
Factor 3 | 0.712 | 0.959 | 1.000 | ||
Factor 4 | 0.690 | 0.897 | 0.939 | 1.000 |
The factor 1 was labelled the “Physical symptoms” factor
The factor 2 was labelled the “Depression” factor
The factor 3 was labelled the “Anxiety” factor
The factor 4 was labelled the “Neuroticism and persecutory beliefs” factor
Table 4.
Item | Traditional five-factor model | |||||
---|---|---|---|---|---|---|
Factor 1 | Factor 2 | Factor 3 | Factor 4 | Factor 5 | ||
1 | Poor appetite | 0.544 | ||||
2 | Feel sick, stomachache | 0.591 | ||||
3 | Easily have diarrhea or constipation | 0.412 | ||||
4 | Care about palpitation and pulse | 0.395 | ||||
16 | Frequent insomnia | 0.400 | ||||
17 | Headache | 0.506 | ||||
18 | Ache in neck and shoulder | 0.356 | ||||
19 | Chest pain or feel oppressed | 0.473 | ||||
31 | Distressed by blushing | 0.270 | ||||
32 | Stuttering, faltering voice | 0.465 | ||||
33 | Feel hot and cold | 0.490 | ||||
34 | Concern about urination or sexual organs | 0.355 | ||||
46 | Physically exhausted | 0.662 | ||||
47 | In cold sweat when I hurry | 0.358 | ||||
48 | Dizzy when I stand up | 0.432 | ||||
49 | Have ever lost consciousness, cramp | 0.102 | ||||
6 | Full of dissatisfaction and complaints | 0.573 | ||||
7 | High expectation from parents | 0.253 | ||||
8 | My past and family is misfortune | 0.217 | ||||
9 | Over-worry about my future | 0.502 | ||||
10 | Do not like meeting others | 0.519 | ||||
11 | Feel that I am not myself | 0.490 | ||||
12 | Lack of enthusiasm and positivity | 0.621 | ||||
13 | Pessimistic | 0.674 | ||||
14 | Distracted | 0.622 | ||||
15 | Over-uneven in emotion | 0.563 | ||||
21 | Intolerance | 0.521 | ||||
22 | Inclined to worry | 0.579 | ||||
23 | Restless | 0.568 | ||||
24 | Irritable | 0.506 | ||||
25 | Have idea of wanting to die | 0.408 | ||||
26 | No interest in anything | 0.529 | ||||
27 | Declining memory | 0.502 | ||||
28 | Lack of patience | 0.546 | ||||
29 | Lack of judgment | 0.505 | ||||
30 | Too dependent on others | 0.469 | ||||
36 | Uneasy without reason | 0.564 | ||||
37 | Feel uneasy when alone | 0.317 | ||||
38 | Lack of confidence | 0.638 | ||||
39 | Irresolute about anything | 0.525 | ||||
40 | Easily feel misunderstood | 0.466 | ||||
41 | Lack faith in others | 0.496 | ||||
42 | Over-suspicious | 0.501 | ||||
43 | Unwilling to associate with others | 0.419 | ||||
44 | Feel self-abased | 0.627 | ||||
45 | Catastrophizing | 0.527 | ||||
51 | Over-rigid | 0.452 | ||||
52 | Cannot give up repeating things | 0.447 | ||||
53 | Susceptible to dirtiness | 0.400 | ||||
54 | Cannot get rid of meaningless idea | 0.710 | ||||
55 | Sense weird smell from myself | 0.436 | ||||
56 | Suspect others say something bad about me | 0.423 | ||||
57 | Wary of others | 0.709 | ||||
58 | Care about others’ gaze | 0.650 | ||||
59 | Feel others despise me | 0.483 | ||||
60 | Sensitive emotions | 0.607 | ||||
Interfactor correlations | ||||||
Factor 1 | 1.000 | |||||
Factor 2 | 0.753 | 1.000 | ||||
Factor 3 | 0.712 | 0.959 | 1.000 | |||
Factor 4 | 0.601 | 0.786 | 0.824 | 1.000 | ||
Factor 5 | 0.681 | 0.883 | 0.923 | 0.796 | 1.000 |
The factor 1 was labelled the “Physical symptoms” factor
The factor 2 was labelled the “Depression” factor
The factor 3 was labelled the “Anxiety” factor
The factor 4 was labelled the “Obsessive-compulsive” factor
The factor 5 was labelled the “Persecutory beliefs” factor
Table 5.
GFI | AGFI | RMSEA | CFI | |
---|---|---|---|---|
One factor model | 0.999 | 0.999 | 0.034 | 0.976 |
New four-factor model | 1.000 | 1.000 | 0.034 | 0.980 |
Traditional four-factor model | 0.997 | 0.996 | 0.027 | 0.985 |
Traditional five-factor model | 0.997 | 0.996 | 0.027 | 0.985 |
GFI goodness of fit index, AGFI adjusted goodness of fit index, RMSEA root mean square error of approximatin, CFI comparative fit index
Discussion
The aim of the present study was to examine the factor structure of the UPI among Japanese medical students. In our sample, the good internal consistency of the overall UPI (alpha = 0.97) indicated that a total score of this scale can be used as a global indicator of psychological distress. In subgroup A, we demonstrated that the UPI consists of four factors via EFA with categorical variables. These factors, accounting for 48.9% of the variance, were labeled “Depression and Irritability”, “Anxiety and Persecutory Belief”, “Physical Symptoms”, and “Dependence”. Furthermore, the new four-factor structure showed good fit, and traditional factor structures previously reported were replicated by CFA in subgroup B.
With regard to the EFA, a previous study based on a statistical test for binary indicators found a new five-factor structure in Chinese students [17]. The factors “Physical Symptoms” and “Cognitive Symptoms” in that study are comparable to the factors that we labeled “Physical Symptoms” and “Dependence”, respectively. However, the UPI items belonging to the “Depression and Irritability” and “Anxiety and Persecutory Belief” factors in our new four-factor model constitute different factors in the Chinese study. The different response patterns between Japanese and Chinese individuals may be due to ethnicity or the social environment. In addition, the premorbid personality of so-called “Shin-gata utsu-byo” [new-type depression (NTD)] might affect our results. In Japan, depression characterized by a premorbid personality different from the traditional melancholic temperament has been reported among young adults since approximately 2000 [22]. Initially, Tarumi called this novel depression “dysthymic-type” and advocated that the premorbid personality and symptomatologic features of NTD include avoidant narcissistic personality, extrapunitive feelings, and stress related to social rules and expectations [22, 23]. The “Depression and Irritability” and “Anxiety and Persecutory Belief” factors might be premorbid features of NTD reflecting extrapunitive feelings and stress related to social rules and expectations. Furthermore, avoidant narcissistic personality might also contribute to the “Dependence” factor. In Japanese students, subclinical symptoms of depression and anxiety could be accompanied by anger, avoidance, or dependence.
In psychological evaluation, somatic symptoms are generally considered manifestations of underlying psychological distress, such as anxiety or depression [11, 15]. Previous studies found via EFA that items of emotional and physical symptoms merged and constituted new factors in Asian or Asian-American populations [15, 24–26]. However, exploratory analysis of the UPI did not show such merging of emotional and physical symptoms in either Japanese or Chinese students [17]. Discrepant responses between the UPI and other psychological measures might be explained by differences in participants’ age. Because most studies employing the UPI focus on university students, participants in such studies are typically in their late teens or early 20s [11, 17]. Another explanation is that differences in items or expressed statements could affect the results.
The good fit of the CFA models of the UPI (Table 5) supports the use of all the models suggested in our study as indicators for psychological distress. However, both four-factor and five-factor traditional models of the UPI showed high interfactor correlations (> 0.95) between “Depression” and “Anxiety” in. In the same models, anxiety was also highly correlated with “Neuroticism and Persecutory Beliefs” (0.94) or “Persecutory Beliefs” (0.92). Although the structures of the abovementioned factors might have been distinct in Japanese students in the 1960s, they are not in students in the twenty-first century.
Limitations
The current study has some limitations. First, subject recruitment was restricted to medical students. Medical students are known to be at high risk for depression and suicidal ideation [27, 28]. In addition, students’ university major could affect the response pattern on the UPI [11]. We cannot generalize our findings to all university students. Second, due to the lack of data on clinical diagnoses or other psychological measures, we could not confirm the criterion validity of the UPI. These limitations should be addressed in future studies. Third, this research was conducted over a long 9-year period, and some underlying psychosocial factors may change over time.
Conclusion
This study found a four-factor structure of the UPI by EFA in Japanese medical students. In Japan, this is the first study on the factor structure of the UPI based on a statistical test for binary indicators. Furthermore, CFA confirmed that the new four-factor structure as well as traditional factor structures previously reported showed good fit. The good internal consistency of the overall UPI (alpha = 0.97) indicated that a total score of this scale can be used as a global indicator of psychological distress. The UPI is a valid and reliable measure that can be used to assess symptoms in multiple dimensions of mental health in university settings. The new four-factor model of the UPI consisting of 30 items is feasible and adequate psychological measure for modern university students. These findings offer a starting point for the detection of individuals with mental health problems. Future studies with a longitudinal design are needed to investigate the predictive validity of the UPI for mental or academic outcomes in university students.
Acknowledgments
The authors would like to thank all of the coworkers for their skillful contributions to the data collection and management.
Abbreviations
- AGFI
Adjusted Goodness of Fit Index
- CFA
Confirmatory Factor Analysis
- CFI
Comparative Fit Index
- EFA
Exploratory Factor Analysis
- GFI
Goodness of Fit Index
- NTD
New-Type Depression
- RMSEA
Root Mean Square Error of Approximation
- UPI
University Personality Inventory
Authors’ contributions
NS conceived, and designed, and conducted the study, with the help of MS. NYF and KS contributed to designing methodology. All authors discussed the data and results and critically revised the manuscript. The authors approved the final version of the manuscript.
Funding
The authors received no specific funding for this work.
Availability of data and materials
All data used and/or analyzed during this study are not publicly available to maintain the anonymity of the individuals concerned. The dataset supporting the conclusions is available from the corresponding author on reasonable request.
Ethics approval and consent to participate
This protocol received approval from the Ethics Committee of Dokkyo Medical University School of Medicine (Approval number: 2019–015), and it conformed to the provisions of the Declaration of Helsinki. The requirement for written informed consent was waived by the Ethics Committee since the study involved record review only. Participants were given the opportunity to opt out of participation.
Consent for publication
The requirement for written informed consent was waived by the Ethics Committee, since the study involved record review only. Participants were given the opportunity to opt out of participation.
Competing interests
The authors report no conflicts of interest in this work.
Footnotes
Publisher’s Note
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References
- 1.Ishikawa H, Tachimori H, Takeshima T, Umeda M, Miyamoto K, Shimoda H, et al. Prevalence, treatment, and the correlates of common mental disorders in the mid 2010's in Japan: the results of the world mental health Japan 2nd survey. J Affect Disord. 2018;241:554–562. doi: 10.1016/j.jad.2018.08.050. [DOI] [PubMed] [Google Scholar]
- 2.Ministry of Education, Culture, Sports, Science and Technology, Government of Japan. School Basic Survey. (in Japanese). Available from URL: https://www.mext.go.jp/b_menu/toukei/chousa01/kihon/1267995.htm. [Accessed 7 Apr 2020].
- 3.Japan Student Services Organization. Survey of Student Life 2016 (in Japanese). Available from URL: https://www.jasso.go.jp/about/statistics/gakusei_chosa/2016.html. [Accessed 11 Apr 2020].
- 4.Stewart-Brown S, Evans J, Patterson J, Petersen S, Doll H, Balding J, et al. The health of students in institutes of higher education: an important and neglected public health problem? J Public Health Med. 2000;22(4):492–499. doi: 10.1093/pubmed/22.4.492. [DOI] [PubMed] [Google Scholar]
- 5.Roberts LW, Warner TD, Lyketsos C, Frank E, Ganzini L, Carter D. Collaborative research group on medical student health. Perceptions of academic vulnerability associated with personal illness: a study of 1,027 students at nine medical schools. Compr Psychiatry. 2001;42(1):1–15. doi: 10.1053/comp.2001.19747. [DOI] [PubMed] [Google Scholar]
- 6.Storrie K, Ahern K, Tuckett A. A systematic review: students with mental health problems--a growing problem. Int J Nurs Pract. 2010;16(1):1–6. doi: 10.1111/j.1440-172X.2009.01813.x. [DOI] [PubMed] [Google Scholar]
- 7.Eisenberg D, Hunt J, Speer N. Mental health in American colleges and universities: variation across student subgroups and across campuses. J Nerv Ment Dis. 2013;201(1):60–67. doi: 10.1097/NMD.0b013e31827ab077. [DOI] [PubMed] [Google Scholar]
- 8.Sasaki M. Barriers to use of mental health services by Japanese university students. Psychol Rep. 2007;100(2):400–406. doi: 10.2466/pr0.100.2.400-406. [DOI] [PubMed] [Google Scholar]
- 9.Zivin K, Eisenberg D, Gollust SE, Golberstein E. Persistence of mental health problems and needs in a college student population. J Affect Disord. 2009;117(3):180–185. doi: 10.1016/j.jad.2009.01.001. [DOI] [PubMed] [Google Scholar]
- 10.Pritchard ME, Wilson GS. Using emotional and social factors to predict student success. J Coll Stud Dev. 2003;44(1):18–28. doi: 10.1353/csd.2003.0008. [DOI] [Google Scholar]
- 11.Hirayama K, Japanese Association for College Mental Health. User guide for the UPI. [In Japanese] Tokyo: Sozo-shuppan; 2011.
- 12.Hosokawa R. Proceedings of the Sanyo-Onoda City University. 2019. University personality inventory (UPI) survey report; pp. 89–99. [Google Scholar]
- 13.Hattori I, Fujii C, Fukuzawa A. Survey regarding mental health conditions of high school students and attitudes of students and their teachers toward students' mental health issues. Seishin Shinkeigaku Zasshi. 2013;115(8):831–846. [PubMed] [Google Scholar]
- 14.Furuhashi Y. A study on the mental health of Japanese university students by the university personality inventory. A Epidemiol Public Health. 2020;3(1):1013. [Google Scholar]
- 15.Sugawara N, Yasui-Furukori N, Takahashi I, Matsuzaka M, Nakaji S. Age and gender differences in the factor structure of the Center for Epidemiological Studies Depression Scale among Japanese working individuals. Compr Psychiatry. 2015;56:272–278. doi: 10.1016/j.comppsych.2014.09.004. [DOI] [PubMed] [Google Scholar]
- 16.Chmitorz A, Kurth K, Mey LK, Wenzel M, Lieb K, Tüscher O, et al. Assessment of microstressors in adults: questionnaire development and ecological validation of the Mainz inventory of microstressors. JMIR Ment Health. 2020;7(2):e14566. doi: 10.2196/14566. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Zhang J, Lanza S, Zhang M, Su B. Structure of the university personality inventory for chinese college students. Psychol Rep. 2015;116(3):821–839. doi: 10.2466/08.02.PR0.116k26w3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Slavin SJ. Medical student mental health: culture, environment, and the need for change. JAMA. 2016;316(21):2195–2196. doi: 10.1001/jama.2016.16396. [DOI] [PubMed] [Google Scholar]
- 19.Association of Japanese Medical colleges (AJMC). Survey on academic perfoemance of medical studetns. (in Japanese). Available from URL: https://www.ajmc.jp/pdf/180305_2.pdf. [Accessed 9 Jul 2020.].
- 20.Dyrbye LN, Thomas MR, Shanafelt TD. Systematic review of depression, anxiety, and other indicators of psychological distress among U.S. and Canadian medical students. Acad Med. 2006;81(4):354–373. doi: 10.1097/00001888-200604000-00009. [DOI] [PubMed] [Google Scholar]
- 21.Venables WN, Smith DM, The R Core Team . An introduction to R, Notes on R: A Programming Environment for Data Analysis and Graphics Version 3.6.3. 2020. [Google Scholar]
- 22.Kato TA, Katsuki R, Kubo H, Shimokawa N, Sato-Kasai M, Hayakawa K, et al. Development and validation of the 22-item Tarumi's modern-type depression trait scale: avoidance of social roles, complaint, and low self-esteem (TACS-22) Psychiatry Clin Neurosci. 2019;73(8):448–457. doi: 10.1111/pcn.12842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Tarumi S, Kanba S. Sociocultural approach toward depression: dysthymic-type depression. (in Japanese) JPN bull. Soc Psychiatry. 2005;13:129–136. [Google Scholar]
- 24.Lee SW, Stewart SM, Byrne BM, Wong JP, Ho SY, Lee PW, et al. Factor structure of the Center for Epidemiological Studies Depression Scale in Hong Kong adolescents. J Pers Assess. 2008;90(2):175–184. doi: 10.1080/00223890701845385. [DOI] [PubMed] [Google Scholar]
- 25.Yen S, Robins CJ, Lin N. A cross-cultural comparison of depressive symptom manifestation: China and the United States. J Consult Clin Psychol. 2000;68(6):993–999. doi: 10.1037//0022-006x.68.6.993. [DOI] [PubMed] [Google Scholar]
- 26.Wang M, Armour C, Wu Y, Ren F, Zhu X, Yao S. Factor structure of the CES-D and measurement invariance across gender in mainland Chinese adolescents. J Clin Psychol. 2013;69(9):966–979. doi: 10.1002/jclp.21978. [DOI] [PubMed] [Google Scholar]
- 27.Rotenstein LS, Ramos MA, Torre M, Segal JB, Peluso MJ, Guille C, et al. Prevalence of depression, depressive symptoms, and suicidal ideation among medical students: a systematic review and meta-analysis. JAMA. 2016;316(21):2214–2236. doi: 10.1001/jama.2016.17324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Maser B, Danilewitz M, Guérin E, Findlay L, Frank E. Medical student psychological distress and mental illness relative to the general population: a Canadian cross-sectional survey. Acad Med. 2019;94(11):1781–1791. doi: 10.1097/ACM.0000000000002958. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data used and/or analyzed during this study are not publicly available to maintain the anonymity of the individuals concerned. The dataset supporting the conclusions is available from the corresponding author on reasonable request.