［Paper］

Eﬀects of Sub-Threshold Neurodevelopmental Traits on the
Adjustment of Female Students to High School: A Study Focused on
Premenstrual Dysphoric Mood
Takuya Miura

Tokyo University of Agriculture and Technology

Soichi Hashimoto

Tokyo Gakugei University

Abstract
The purpose of this study was to determine the impact of the adjustment to high school on
female students with sub‑threshold neurodevelopmental disabilities traits by monitoring
premenstrual discomfort. A questionnaire survey was conducted on a group of 500 high school
seniors and on ﬁrst‑ and second‑year college students, using the sub‑threshold neurodevelopmental
disabilities traits scale, the PMDD rating scale, and the school adjustment questionnaire. To test theaccuracy of each of the scales used, we analyzed them using item response theory. To determine
whether sub‑threshold ASD and ADHD traits influenced school adjustment, the analysis was
conducted by monitoring PMDD. The results of this analysis determined that female high school
students with sub‑threshold ASD traits have diﬃculties with school life and study performance. In
the case of female high school students with sub‑threshold ADHD traits, PMDD was found tointerfere with school relationships. In particular, female high school students with sub‑threshold
ASD traits were more likely than female high school students with sub‑threshold ADHD traits toexperience depressed or hopeless moods and to have higher levels of anxiety and tension. These
results suggest that there is an urgent need to develop classroom‑based support techniques thatallow for good communication between female high school students with sub‑thresholdneurodevelopmental disabilities traits and their peers.
Keywords: Female High School Students, Sub‑Threshold Neurodevelopmental Disabilities Traits,
PMDD, School Adjustment

1.

Introduction

In clinical practice, it is often observed that in women symptoms of psychiatric disorders such as
depression, panic disorder, mood dysphoria, and personality disorders, as well as physical disorders
such as asthma, allergic diseases, and epilepsy tend to worsen over time and are poorly controlled
before menstruation (Egawa, 2020). The most severe form of these disorders, in which psychiatric
symptoms are so severe that daily life and interpersonal relationships are severely impaired, is called
premenstrual dysphoric disorder (PMDD). In the Diagnostic and Statistical Manual of Mental
Disorders, Fifth Edition (DSM‑5) (American Psychiatric Association, 2013), PMDD is classiﬁed as adepressive disorder.
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Journal of Developmental Disabilities Research No. 1

In Japan, the prevalence of moderate to severe PMDD and premenstrual syndrome (PMS)
among female high school students was found to be higher than among adult females (Takeda et al.,2010). A survey of a total of 1,431 female high school students was used to determine the relationshipbetween PMDD and PMS dysmenorrhea, and found that 3.2% of the cases qualiﬁed as PMDD. In
addition, the prevalence of PMDD and moderate to severe PMS increased with the severity ofdysmenorrhea, indicating a correlation between PMS and PMDD severity and dysmenorrhea inadolescents (Kitamura et al., 2012). PMDD can interfere with the daily lives of female high school
students and can have serious consequences.
Furthermore, women with intellectual or developmental disabilities are more likely to havemenstrual abnormalities (Yada (Hashimoto) et al. 2017). To determine the prevalence of PMS inwomen with autism, we compared a group of women with autism and learning disabilities (n = 26)
with a group of women without autism and learning disabilities (n = 36). Results showed that a 30%
or greater increase in premenstrual DSM‑IV symptoms was an evidence of fulfillment of thediagnostic criteria. The prevalence of PMS was 92% in the autistic group compared to 11% in thecontrol group. This diﬀerence was highly signiﬁcant. Susceptibility to premenstrual syndrome has
been shown to be signiﬁcantly increased in women with autism (Obaydi and Puri, 2008).
Based on the above previous studies, support for women with developmental disabilities shouldtake into account the impact of womenʼs unique hormonal ﬂuctuations on their everyday lives (Nodaet al., 2021). In addition, it is assumed that providing appropriate support, especially during theadolescent period of female high school students, will lead to an improvement in mental healthduring adolescence. However, there have been no studies demonstrating an association between sub‑threshold neurodevelopmental disabilities traits and mood disturbance in PMDD and its impact onschool adjustment among female high school students.
In this study, we clarify the eﬀects of sub‑threshold neurodevelopmental disabilities traits on
school adjustment mediated by discomfort in PMDD among female high school students. The
objective of this study is to gain, through the analysis of the results, a perspective on how to bettersupport female students with sub‑threshold neurodevelopmental disabilities traits.

2.

Method

2.1

Survey subjects
A total of 500 people were surveyed: 257 high school senior students (120 males and 137 females)and 243 ﬁrst‑ and second‑year college students (138 males and 105 females).
2.2

Survey timing and means of implementation
The survey was conducted in March 2021. The survey was conducted online through theresearch contractor Rakuten Insight. The parents or guardians of the subjects and the subjects
themselves were asked to consent to the online study in advance, and only the subjects were asked
to complete the questionnaire. The study was approved by the Ethical Review Committee of Tokyo
University of Agriculture and Technology (Approval No. 210203‑0270).
2.3 Survey Items
2.3.1 Sub‑threshold neurodevelopmental disabilities traits scale
From the questionnaires developed by Takahashi et al. (2015) and Shinoda et al. (2017), seven
items were selected from the sub‑threshold Attention‑Deﬁcit/Hyperactivity Disorder (ADHD) traits─ 62 ─

Journal of Developmental Disabilities Research No. 1

questionnaire short version and the sub‑threshold autism spectrum disorder (ASD) traits
questionnaire, respectively. The representative of the questionnaire creator had conﬁrmed that thequestionnaire could be used by high school students. A ﬁve‑point scale was used, ranging from “verytroubled (5 points)” to “not troubled at all (1 point)”.
2.3.2 PMDD rating scale
The 12 items of the PMDD Rating Scale developed by Miyoka et al. (2009) were used to evaluate
PMDD, which is defined as symptoms mainly consisting of recurrent mood changes before
menstruation. A ﬁve‑point scale ranging from “very strongly (5 points)” to “no change (1 point)” wasused.
2.3.3 School adjustment questionnaire
Two items related to poor adjustment to school, “It interfered with my eﬃciency in school lifeand studies” and “It interfered with my relationships with people at school” (Miyoka et al., 2009),
were selected for female high school students who had one or more symptoms of the PMDD Rating
Scale (all applicable). A five‑point scale was used, ranging from “very strongly (5 points)” to nochange maybe “no change? Instead of just NOT (1 point).”
2.4 Method of analysis
2.4.1 Validation of scale accuracy
To verify the accuracy of the scale used in this study, we decided to analyze the results using
Item Response Theory (IRT). The IRT is a method of inferring measurable abilities from the resultsof a questionnaire using responses to items (response status) when the characteristics of the items(difficulty and discrimination) are known. In other words, it is an analytical method that allows
detailed conﬁrmation of measurement accuracy. In addition, since the nature of the population ofsurvey participants does not aﬀect the analysis process, the scale can be used in a variety of school
settings. As shown in (1) to (3) below, the analytical procedure for this study was adapted from
Eguchi (2011) and Uragami and Wakita (2016). Easy Estimation Ver. 2.1.5 by Kumagaya (2009) wasused for the analysis.
(1) Conﬁrmation of unidimensionality of the scale
For each item of the scale used in this study, a factor analysis of the inter‑item correlation
matrix using tetrachoric correlation coeﬃcients was performed. The eigenvalues are then plotted ona graph (scree plot) to conﬁrm the unidimensionality of the scale.
(2) Estimation of item parameters
Since the five‑item method was used in this study, the Graded Response Model (GRM) was
employed to estimate the item parameters. Then, the discrimination parameter ( ) and the diﬃcultyparameter ( ) for each item were calculated by the marginal maximum likelihood estimation method.
In this study, the ﬁve‑case method was used to obtain responses, so four diﬃculty parameters ( )were estimated for each item (Iwabuchi and Kato, 2018). This analysis yielded an Item Response
Category Characteristic curve (IRCCC) for each item. The IRCCC represents the probability that
respondents with a particular latent characteristic scale value (θ) will select each choice branch. The
position and slope of this curve provide a visual indication of the characteristics of the item inquestion.
The parameter ( ), which represents the itemʼs discriminative power, is an indicator of theextent to which it can identify the respondentʼs latent characteristics. A high value implies a highdegree of contribution to the estimation of latent characteristic values (θ). The item difficultyparameter ( ) is an index of item difficulty. It represents the position of the item on the latent─ 63 ─

Journal of Developmental Disabilities Research No. 1

characteristics scale. The larger this value is, the more the position of the curve is to the right, andthe smaller it is, the more it is to the left. Therefore, a large value of b expresses that the item
cannot be answered correctly unless the ability value (θ) is high, indicating that it determines thediﬃculty of the item. In this study, the level of the discrimination ability parameter ( ) was set to >0.75 (Ironson et al., 1989). The level of the diﬃculty parameter ( ) was set to 4.00 > > ‑4.00 (Kijima,
1999).
(3) Estimation of reliability
To examine measurement accuracy, Cronbachʼs alpha coeﬃcient was obtained as an estimate of
the reliability coeﬃcient. Generally, when α is 0.7 to 0.8 or higher, it is considered an indication thata certain level of reliability is ensured. The free statistical software HAD by Shimizu (2016) was used
for the analysis.
2.4.2 Characteristics of female high‑school students with sub‑threshold neurodevelopmental
disabilities traits
The sub‑threshold ASD and ADHD traits scores of female high school students were comparedwith those of male high school students and female college students using an unpaired t‑test.
2.4.3 Characteristics of PMDD among female high school students
We compared scores for premenstrual unpleasant mood in the group with high scores of sub‑threshold ASD and ADHD traits using an unpaired t‑test with female college students. In addition,
scores are compared between the group with high scores of sub‑threshold ASD and ADHD traits
and the group with overlapping sense of distress in female high school students and the group withstereotyped developmental students using a one‑way ANOVA.
2.4.4 Eﬀects of characteristics related to sub‑threshold neurodevelopmental disabilities traits on
school adjustment among female high school students
A mediation analysis was conducted to see if characteristics of sub‑threshold ASD and ADHD
traits inﬂuenced school adjustment by mediating PMDD.

3.

Results

3.1

Conﬁrmation of the accuracy of each scale
The accuracy of each scale was conﬁrmed by IRT. First, the inter‑item correlation matrix withtetrachoric correlation coefficients was factor analyzed to check its eigenvalues. The first threeeigenvalues were 4.87, 0.60, 0.41, ... for the sub‑threshold ASD traits questionnaire; the ratio of thefirst eigenvalue to the second eigenvalue was 4.27, which is large, indicating that theunidimensionality aspect of the scale was satisfied. Next, for the sub‑threshold ADHD traits
questionnaire, the scores were 3.99, 0.86, 0.58, ..., and the ratio of the ﬁrst eigenvalue to the second
eigenvalue is 3.13, which indicated that the unidimensionality of the scale was satisﬁed. Finally, thePMDD rating scale was 7.81, 0.94, 0.64, ..., and the ratio of the first eigenvalue to the second
eigenvalue was 6.87, which is large, and the unidimensionality of the scale was judged to besatisfying. Next, the GRM was employed in this study to estimate the item parameters by calculating
the discrimination parameter ( ) and the diﬃculty parameter ( ) for each item using the marginal
maximum likelihood estimation method. The value of the discrimination parameter ( ) was
determined to satisfy the range > 0.75. The sub‑threshold ASD traits questionnaire was 1.97 > ,the sub‑threshold ADHD traits questionnaire was 1.42 > , and the PMDD rating scale was 1.50 > ,meeting the > 0.75 level of Ironson et al. (1989). The value of the difficulty parameter ( ) was
determined to satisfy the range 4.00 > > ‑4.00 for all items. The sub‑threshold ASD traits
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Journal of Developmental Disabilities Research No. 1

questionnaire was 2.75 > > ‑1.56, the sub‑threshold ADHD trait questionnaire was 3.26 > > ‑1.86,
and the PMDD rating scale was 2.92 > > ‑1.15, meeting the Kijima (1999) level of 4.00 > > ‑4.00.
Finally, Cronbachʼs alpha coeﬃcient was determined for each scale as an estimate of the reliability
coefficient. As a result, a value of α= 0.91 was calculated for the sub‑threshold ASD traits
questionnaire, α= 0.84 for the sub‑threshold ADHD traits questionnaire, and α= 0.93 for the PMDD
rating scale. The values were determined to be suﬃciently internally consistent (Tables 1, 2, and 3).
The English translations of all items of each scale were prepared independently by the authors after
examining their content validity.
3.2

Extraction of female high school students with high scores on each scale
Twenty‑three female high school students (16.8% of the female students) had high scores (meanTable 1

Parameter estimates for each model (sub‑threshold ASD traits questionnaire)

Item

Location Parameters ＊2 ＊3

Slope
Parameters ＊1
Standard
Error

1

2

3

4

Standard
Error

Standard
Error

Standard
Error

Standard
Error

1. Past experiences come backto life as if they are happening
in the present, and feelings
become unstable

1. 97

0. 13

‑1. 25

0. 08

0. 19

0. 06

1. 52

0. 09

2. 75

0. 19

2. Cannot talk as well as otherpeople

3. 26

0. 19

‑1. 03

0. 07

0. 06

0. 04

1. 06

0. 07

2. 25

0. 15

3. Have trouble feeling thatthey are diﬀerent from theusual person

3. 00

0. 18

‑0. 94

0. 06

0. 23

0. 04

1. 43

0. 09

2. 64

0. 20

4. Have trouble feelingcomfortable in group activities

3. 00

0. 18

‑1. 06

0. 07

0. 12

0. 04

1. 24

0. 08

2. 46

0. 17

5. Feelings are easily hurt

2. 62

0. 16

‑1. 390. 09‑0. 09

0. 05

1. 18

0. 07

2. 25

0. 14

6. I am not good at making
new friends when I go toschool or change classes

2. 20

0. 13

‑1. 56

0. 10‑0. 34

0. 05

0. 80

0. 06

2. 05

0. 12

7. I think other people see me
as being out of place all the
time

2. 76

0. 17

‑1. 14

0. 08

0. 21

0. 05

1. 91

0. 12

2. 72

0. 21

2. 69

‑1. 19

0. 05

1. 31

2. 45

0. 47

0. 22

0. 20

0. 36

0. 27

＊1

Parameter ( ): an indicator of the extent to which the respondentʼs latent characteristics can be identiﬁed(characteristic value proportional to the slope of the item characteristic curve at ability value (θ) = )＊2
Parameter ( ): Indicator of item difficulty (characteristic value representing the position of the item
characteristic curve)＊3
In this study, the GRM was employed and responses were requested using the ﬁve‑case method, so fourdiﬃculty parameters ( ) were estimated for each item (Iwabuchi and Kato, 2018).
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Journal of Developmental Disabilities Research No. 1+1 SD or higher) on the sub‑threshold ASD traits questionnaire. There were 16 female high school
students (11.7% of the female students) with high scores (mean +1 SD or higher) on the sub‑threshold ADHD traits questionnaire. In addition, 13 female high school students (9.49% of the female
students) had high scores on both the sub‑threshold ASD traits questionnaire and the sub‑threshold
ADHD traits questionnaire. Twelve female high school students (8.8% of the female students) had
high scores only on the sub‑threshold ASD traits questionnaire, and four female high school students(2.9% of the female students) had high scores only on the sub‑threshold ADHD traits questionnaire.
Twenty‑ﬁve female high school students (18.3% of the female students) had high scores (mean +1 SD
or higher) on the PMDD rating scale.
3.3

Gender Comparison on sub‑threshold ASD and ADHD traits questionnaire
To begin, an unpaired t‑test was conducted on the sub‑threshold ASD traits questionnairescores of female and male high school students. The results showed no signiﬁcant diﬀerence between
Table 2

Parameter estimates for each model (sub‑threshold ADHD traits questionnaire)

Item

Location Parameters ＊2 ＊3

Slope
Parameters ＊1
Standard
Error

1

2

3

4

Standard
Error

Standard
Error

Standard
Error

Standard
Error

1. I have trouble remembering
things

1. 64

0. 12

‑0. 87

0. 08

0. 70

0. 07

1. 73

0. 11

3. 26

0. 25

2. I have trouble withirregularity in my life

1. 67

0. 12

‑1. 27

0. 09

0. 11

0. 06

1. 25

0. 08

2. 64

0. 17

3. I have trouble with my room
being so messy that I can't
invite people over

1. 42

0. 11

‑1. 14

0. 09

0. 11

0. 07

1. 37

0. 10

2. 78

0. 18

4. I cannot do well when there
are multiple things that need
to be done

3. 60

0. 21

‑1. 340. 09‑0. 13

0. 04

0. 94

0. 06

1. 97

0. 13

5. I am always busy withthings that need to be done
and have no time to spare

2. 67

0. 16

‑1. 440. 09‑0. 08

0. 05

1. 12

0. 07

2. 27

0. 15

6. I get irritated easily

1. 94

0. 13

‑1. 19

0. 08

0. 25

0. 06

1. 57

0. 10

2. 76

0. 19

7. I work hard, but the results
are not as expected

2. 02

0. 13

‑1. 86

0. 12‑0. 41

0. 06

1. 00

0. 07

2. 47

0. 16

2. 14

‑1. 30

0. 08

1. 28

2. 59

0. 76

0. 31

0. 35

0. 29

0. 41

＊1

Parameter ( ): an indicator of the extent to which the respondentʼs latent characteristics can be identiﬁed(characteristic value proportional to the slope of the item characteristic curve at ability value (θ) = )＊2
Parameter ( ): Indicator of item difficulty (characteristic value representing the position of the item
characteristic curve)＊3
In this study, the GRM was employed and responses were requested using the ﬁve‑case method, so fourdiﬃculty parameters ( ) were estimated for each item (Iwabuchi and Kato, 2018).
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Journal of Developmental Disabilities Research No. 1

conditions ( (244.12) = 0.09, = 0.93). Similarly, sub‑threshold ADHD traits questionnaire scores ((251.75) = 0.15, = 0.88) did not diﬀer signiﬁcantly by gender.
3.4

Comparison of scores on the sub‑threshold ASD and ADHD traits questionnaire by age
To begin, an unpaired t‑test was conducted on the sub‑threshold ASD traits questionnaire
Table 3

Item

Parameter estimates for each model (PMDD Rating Scale)
Location Parameters ＊2 ＊3

Slope
Parameters ＊1
Standard
Error

1

2

3

4

Standard
Error

Standard
Error

Standard
Error

Standard
Error

1. feeling depressed or
hopeless

4. 09

0. 38

0. 08

0. 05

0. 54

0. 07

1. 40

0. 13

2. 35

0. 24

2. feeling anxious or nervous

3. 89

0. 34

‑0. 23

0. 06

0. 53

0. 07

1. 26

0. 11

2. 16

0. 20

3. tearfulness or sudden
sadness

2. 72

0. 27

0. 21

0. 07

0. 57

0. 08

1. 52

0. 14

2. 20

0. 21

4. Becoming angry or irritableor hitting others

2. 52

0. 22

‑0. 42

0. 08

0. 55

0. 08

1. 21

0. 11

2. 20

0. 20

5. Loss of interest (in school,
hobbies, etc. )

3. 37

0. 31

0. 04

0. 06

0. 54

0. 07

1. 51

0. 13

1. 97

0. 18

6. diﬃculty concentrating

2. 81

0. 25

‑0. 69

0. 08

0. 66

0. 08

1. 24

0. 11

2. 34

0. 22

7. Tiredness or loss of energy

2. 43

0. 22

‑0. 77

0. 09

0. 55

0. 08

1. 12

0. 10

2. 13

0. 19

8. Increased appetite orcravings for certain foods(e.g., sweets, etc.)

1. 75

0. 17

‑0. 65

0. 10

0. 21

0. 09

1. 02

0. 11

2. 24

0. 19

9. Sleeps more than usual

1. 50

0. 15

‑1. 15

0. 13

0. 00

0. 10

0. 90

0. 11

2. 19

0. 19

10. Sleeps less than usual

1. 94

0. 21

0. 21

0. 09

0. 53

0. 09

1. 87

0. 17

2. 92

0. 31

11. Feeling out of control

3. 44

0. 32

0. 05

0. 06

0. 37

0. 06

1. 54

0. 14

2. 18

0. 21

12. Any of the following
physical symptoms (breast
pain or tightness, abdominal
tightness, abdominal pain,
headache, joint pain, muscle
pain, feeling swollen, weight
gain, constipation)

1. 84

0. 18

‑0. 64

0. 10

0. 36

0. 09

1. 23

0. 12

2. 03

0. 17

2. 69

‑0. 33

0. 45

1. 32

2. 24

0. 86

0. 45

0. 19

0. 26

0. 24

＊1

Parameter ( ): an indicator of the extent to which the respondentʼs latent characteristics can be identiﬁed(characteristic value proportional to the slope of the item characteristic curve at ability value (θ) = )＊2
Parameter ( ): Indicator of item difficulty (characteristic value representing the position of the item
characteristic curve)＊3
In this study, the GRM was employed and responses were requested using the ﬁve‑case method, so fourdiﬃculty parameters ( ) were estimated for each item (Iwabuchi and Kato, 2018).
─ 67 ─

Journal of Developmental Disabilities Research No. 1

scores of female high school and college students. The results showed no significant differences
between conditions ( (232.36) = 0.20, = 0.84). Similarly, there was no signiﬁcant diﬀerence in scoreson the sub‑threshold ADHD traits questionnaire ( (222.87) = 0.42, = 0.67) due to age.
3.5 Comparison by age on PMDD rating scale scores (group with higher scores on sub‑threshold
ASD and ADHD traits questionnaire)
Unpaired t‑tests were conducted on PMDD rating scale scores for the groups with higherscores on the sub‑threshold ASD traits questionnaire for female high school students and female
college students. The results showed a trend toward signiﬁcant diﬀerences between conditions ((28.51) = 1.95, = 0.06). That is, female high school students with higher scores on the sub‑threshold
ASD traits questionnaire ( = 35.13,= 9.56) were more likely to feel uncomfortable before
menstruation than female college students ( = 28.67,= 10.27). Similarly, an unpaired t‑test was
conducted on PMDD rating scale scores for the group with higher scores on the sub‑threshold
ADHD traits questionnaire. The results showed a signiﬁcant diﬀerence between conditions ( (27.87)= 2.10, = 0.05). That is, female high school students ( = 36.250,= 11.02) with higher scores on
the sub‑threshold ADHD traits questionnaire were more uncomfortable before menstruation thanfemale college students ( = 29.00,= 8.30).
3.6 Comparison of PMDD assessment scores among high‑scoring groups of female high school
students on the sub‑threshold ASD and ADHD traits questionnaire
A one‑way ANOVA was conducted on the PMDD scores of female high school students in thegroups on the sub‑threshold ASD‑only (12 students) and on the sub‑threshold ADHD‑only (4students) and on students who fell within the overlap of both the sub‑threshold of ASD and ADHD
(13 students), as well as on randomly selected typically developing students (29 students). The results
showed a significant main effect for female high school students with sub‑thresholdneurodevelopmental disabilities traits with respect to the overall PMDD scores ( (3,54) = 40.72, =0.00). The results of multiple comparisons (Holm method) showed that the with overlapping on the
sub‑threshold ASD and ADHD groups (sub‑threshold ASD:
= 31.92,= 7.93, sub‑threshold
ADHD:= 27.25,= 9.95, overlapping:= 39.08,= 9.57) scored signiﬁcantly higher on PMDD
than did typically developing students ( = 17.24,= 1.55) (sub‑threshold ASD: (54) = 6.77,= 0.00, sub‑threshold ADHD: (54) = 2.97,= 0.01, duplicate: (54) = 10.34,= 0.00). Note that
there was no signiﬁcant diﬀerence between the on the sub‑threshold ASD‑only group and the on
the sub‑threshold ADHD‑only group for overall PMDD scores ( (54) = 1.28,.). Therefore, a one‑factor analysis of variance was conducted for each item of the PMDD scale, and the main eﬀect ofscores on the sub‑threshold neurodevelopmental disabilities traits was found to be signiﬁcant for theitem “feeling depressed or hopeless" ( (3,54) = 23.68, = 0.00). In addition, a signiﬁcant main eﬀect of
sub‑threshold neurodevelopmental disabilities traits scores was found for the item “feeling anxious
or nervous" ( (3,54) = 22.64, = 0.00). Multiple comparisons (Holm method) showed that the on‑the‑subthreshold ASD‑only group ( = 3.17,= 1.27) scored signiﬁcantly higher on PMDD than theon‑the‑subthreshold ADHD‑only group ( = 1.50,= 1.00) ( (54) = 3.36,= 0.04).
3.7 Sub‑threshold neurodevelopmental disabilities traits scores predict premenstrual unpleasantmood and problems with school adjustment
A mediation analysis was conducted to prove whether PMDD is mediated by the assumptionthat sub‑threshold neurodevelopmental disabilities traits affect school adjustment in female high
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Journal of Developmental Disabilities Research No. 1

school students. First, multiple regression analysis were conducted using scores on the school
adjustment item “It interfered with my eﬃciency in school life and studies" as the objective variable,
and with scores on sub‑threshold ASD as the explanatory variable. The results showed that sub‑threshold ASD scores significantly predicted “It interfered with my efficiency in school life andstudies" ( = 0.10,= 0.02, (135) = 5.37, = 0.00). Furthermore, when PMDD scores were added
as explanatory variables, PMDD signiﬁcantly predicted “It interfered with my eﬃciency in school lifeand studies” ( = 0.07,= 0.01, (134) = 9.59, = 0.00), while sub‑threshold ASD eﬀect becamenon‑signiﬁcant ( = 0.02,= 0.02, (134) = 1.50, = 0.14). The results of the indirect eﬀect test
(Bootstrap method, 2000 runs) showed that the 95% conﬁdence interval ( [0.05,0.10] ) did not include 0,
indicating signiﬁcant mediation of PMDD.
Next, multiple regression analysis was conducted using sub‑threshold ADHD scores as the
explanatory variable. The results showed that sub‑threshold ADHD scores signiﬁcantly predicted “Itinterfered with my eﬃciency in school life and studies”= 0.12,= 0.02, (135) = 6.78, = 0.00).
Furthermore, when PMDD was added as an explanatory variable, PMDD signiﬁcantly predicted “Itinterfered with my eﬃciency in school life and studies” ( = 0.07,= 0.01, (134) = 8.67, = 0.00).
The eﬀect of sub‑threshold ADHD scores was also signiﬁcant but smaller ( = 0.04,= 0.02, (134)= 2.29, = 0.02).
Similarly, multiple regression analysis was conducted using the school adjustment item “Itinterfered with my relationships with people at school” as the objective variable and sub‑threshold
ASD scores as the explanatory variable. The results showed that sub‑threshold ASD scoressigniﬁcantly predicted “It interfered with my relationships with people at school" ( = 0.10,= 0.01,(135) = 7.17, = 0.00). Furthermore, when PMDD scores were added as an explanatory variable,
PMDD signiﬁcantly predicted “It interfered with my relationships with people at school" ( = 0.05,= 0.01, (134) = 6.88, = 0.00). The eﬀect of sub‑threshold ASD scores was also signiﬁcant, but
the eﬀect was smaller ( = 0.06,= 0.01, (134) = 4.00, = 0.00).
Next, multiple regression analysis were conducted using sub‑threshold ADHD scores as the
explanatory variable. The results showed that sub‑threshold ADHD scores signiﬁcantly predicted “Itinterfered with my relationships with people at school” ( = 0.08,= 0.02, (135) = 4.93, = 0.00).
Furthermore, when PMDD scores were added as explanatory variables, PMDD significantly
predicted “It interfered with my relationships with people at school” ( = 0.06,= 0.01, (134) =7.51, = 0.00), while sub‑threshold ADHD scores eﬀect became non‑signiﬁcant ( = 0.01,= 0.02,(134) = 0.77, = 0.45). The results of the indirect eﬀect test (Bootstrap method, 2000 times) showedthat the 95% conﬁdence interval ( [0.04,0.10] ) did not include 0, indicating signiﬁcant mediation of
PMDD.

4.

Discussion

The analysis in this study showed, ﬁrst, that female high school students with sub‑threshold
ASD and ADHD were not signiﬁcantly diﬀerent from both male high school students and female
college students. Second, that female high school students with sub‑threshold neurodevelopmental
disabilities traits were more uncomfortable before menstruation than female college students or
female high school students with typical development. In particular, female high school students with
sub‑threshold ASD traits were more likely than female high school students with sub‑threshold
ADHD traits to experience depressed or hopeless moods and to have higher levels of anxiety andtension. Since the results of this study indicate that four female high school students had sub‑
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threshold ADHD traits, it is desirable to survey a larger number of subjects in the future.
The results showed that sub‑threshold ASD scores among female high school students wereassociated with PMDD, summarized as “it interfered with my eﬃciency in school life and studies”.
Women with ASD experienced heightened sensory sensitivity and severe premenstrual symptoms
before menstruation, which have been proven to be related to the diﬃculty of living in ASD women(Noda et al., 2021). In addition, more than 75% of women with ASD who are aware of PMS symptoms,
tend to become hypersensitive due to changes in themselves, becoming aware of mental symptoms
like lethargy, diﬃculty concentrating, and crying before menstruation. In addition, there is evidenceof premenstrual changes in lifestyle behaviors such as poor performance, forgetfulness, and increased
compulsive behaviors (Kyrkou, 2005).
In addition, in the case of female high school students with sub‑threshold ADHD traits, it wasdemonstrated that PMDD caused them to respond “It interfered with my relationships with peopleat school”. The prevalence of PMDD has been shown to be higher in women with ADHD comparedto the general female population (Dorani et al., 2021). In addition, prevalence diﬀerences for ADHD‑
related mental disorders have also been demonstrated to be signiﬁcantly greater in women than inmen for anxiety, depression, bipolar disorder, and personality disorders (Solberg et al.,2017).
Adolescence is a unique period in human development, both psychologically and physiologically.
In addition, it is a critical and vulnerable period between childhood and adulthood (Takeda etal.,2010). Many female high school students experience stress in their daily lives, and with little
accurate information on reproductive health, they may experience significant stress related to
menstruation. It has also been noted that when PMS and other symptoms occur, these females may
have negative thoughts that further reinforce premenstrual symptoms (Kitamura et al., 2012).
A woman with sub‑threshold neurodevelopmental disabilities traits experience a state of help‑
seeking, which is noted when she expresses her diﬃculty in talking to others about her menstruation,
while seeking understanding from those around her (Noda et al.,2021). In order to promote
adjustment of female high school students with sub‑threshold neurodevelopmental disabilities traits
to the school environment, reproductive health education should be actively provided in a standard
classroom accounting for sub‑threshold neurodevelopmental disabilities traits. Furthermore, it isexpected that female students with sub‑threshold neurodevelopmental disabilities traits will gain
understanding of their own diﬃculties from the female high school students around them, and willdevelop supportive techniques that facilitate good communication experiences with them.
Acknowledgments
We thank Dr. Anna Di Gregorio, Dr. Yutaka Nibu, and Ms. Marianna Nibu for editing the text
and critically reading the manuscript.

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