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Biased processing of neutral facial expressions is associated with depressivesymptoms and suicide ideation in individuals at risk for major depression dueto affective temperaments

Roberto Maniglio, Francesca Gusciglio, Valentina Lofrese, Martino BelvederiMurri, Antonino Tamburello, Marco Innamorati

PII: S0010-440X(13)00309-XDOI: doi: 10.1016/j.comppsych.2013.10.008Reference: YCOMP 51170

To appear in: Comprehensive Psychiatry

Received date: 15 July 2013Revised date: 9 October 2013Accepted date: 14 October 2013

Please cite this article as: Maniglio Roberto, Gusciglio Francesca, Lofrese Valentina,Murri Martino Belvederi, Tamburello Antonino, Innamorati Marco, Biased processing ofneutral facial expressions is associated with depressive symptoms and suicide ideationin individuals at risk for major depression due to affective temperaments, ComprehensivePsychiatry (2013), doi: 10.1016/j.comppsych.2013.10.008

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Biased processing of neutral facial expressions is associated with depressive

symptoms and suicide ideation in individuals at risk for major depression due to

affective temperaments

Roberto Maniglioa, Francesca Gusciglio

b, Valentina Lofrese

b, Martino Belvederi

Murrid, Antonino Tamburello

b,c, Marco Innamorati

b,c,d

a University of Salento, Italy

b European University of Rome, Italy

c Skinner Institute, Naples, Italy

d University of Parma, Italy

Corresponding author. Roberto Maniglio, Psy.D., Ph.D., Department of History,

Society, and Human Studies, University of Salento, Via Stampacchia 45/47, 73100

Lecce, Italy. E-mail address: robertomaniglio@virgilio.it

Short title: Emotion processing and affective temperaments

Key words: depression; suicide; affective temperaments; facial emotion processing;

etiology; risk factors

Word count for text only: 3,258

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Abstract

Background: To elucidate whether abnormal facial emotion processing represents a

vulnerability factor for major depression, some studies have explored deficits in

emotion processing in individuals at familial risk for depression. Nevertheless, these

studies have provided mixed results. However, no studies on facial emotion processing

have been conducted in at-risk samples with early or attenuated signs of depression,

such as individuals with affective temperaments who are characterized by subclinical

depressive moods, cognitions, and behaviors that resemble those that occur in patients

with major depression.

Methods: Presence and severity of depressive symptoms, affective temperaments,

death wishes, suicidal ideation, and suicide planning were explored in 231 participants

with a mean age 39.9 years (SD = 14.57). Participants also completed an emotion

recognition task with 80 emotional face stimuli expressing fear, angry, sad, happy, and

neutral facial expressions.

Results: Participants with higher scores on affective temperamental dimensions

containing a depressive component, compared to those with lower scores, reported more

depressive symptoms, death wishes, suicide ideation and planning, and an increased

tendency to interpret neutral facial expressions as emotional facial expressions; in

particular, neutral facial expressions were interpreted more negatively, mostly as sad

facial expressions. However, there were no group differences in identification and

discrimination of facial expressions of happiness, sadness, fear, and anger.

Conclusions: A negative bias in interpretation of neutral facial expressions, but not

accuracy deficits in recognizing emotional facial expressions, may represent a

vulnerability factor for major depression. However, further research is needed.

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Introduction

A large amount of studies has reported abnormal processing of facial expressions of

emotions, especially a negative response bias in interpretation of facial expressions (i.e.

an increased tendency to interpret ambiguous, neutral, or other emotional expressions

negatively), in clinical and nonclinical samples of participants with major depression

(for reviews, see [1-3]).

However, it is unclear whether a biased processing of facial expressions of emotions

is a cause or an effect of depression [1]. To elucidate whether abnormal facial emotion

processing represents a vulnerability factor for major depression, some studies have

explored whether deficits and biases in the processing of facial expressions of emotions

are present in nonclinical samples of unaffected participants who are presumed to be at

risk for depression due to a family history of the illness. Nevertheless, these studies

have provided mixed results. Specifically, there is some evidence of an attentional bias

toward negative facial expressions [4-6] and emotion specific deficits in identification

and discrimination accuracy of facial expressions [7-9]; in contrast, evidence of a

negative bias in interpretation of ambiguous or neutral facial expressions is scant [9,10].

It is clear that further research is required. Importantly, future investigations should

address also other populations who may be at risk for depression, such as individuals

displaying early signs that resemble attenuated symptoms of the illness. In fact, these at-

risk samples of participants with early or attenuated signs of possible psychopathology

have been investigated by several studies aimed at exploring facial emotion processing

in other psychiatric disorders. For example, many of these studies have addressed

individuals considered at risk for schizophrenia, such as individuals from the general

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population who demonstrate relatively high levels of schizotypy or signs that resemble

attenuated symptoms of schizophrenia and treatment-seeking individuals in the putative

prodrome to schizophrenia who are displaying early clinical signs of possible psychosis

(for a review, see [11]).

However, it is surprising that, to our knowledge, no studies on facial emotion

processing have been conducted in at-risk samples of participants with early or

attenuated signs of possible depression, such as individuals with affective

temperaments. In fact, individuals with temperaments containing a depressive

component (i.e. depressive, cyclothymic, and irritable temperaments, and, to a lesser

extent, anxious temperament) are characterized by some affective signs such as

subclinical depressive moods, cognitions, and behaviors (e.g., dejection, unhappiness,

irritability, low self-esteem, negativism, pessimism, hypercriticism, introversion,

dependency, shyness, insecurity, apathy, or low energy levels) that resemble those that

occur in patients with major depression [12]. Therefore, these affective temperaments

are considered to be subclinical manifestations and precursors of major depression [13].

In fact, research findings from several studies on both clinical and nonclinical

populations have shown that there is a continuum between affective temperaments and

affective disorders, clearly supporting that depressive, cyclothymic, and irritable

temperaments, and, to a lesser extent, anxious temperament, may play an important role

in the development of major depression (for reviews, see [12,14]).

Despite a considerable body of literature suggesting that individuals with affective

temperaments are at increased risk for depression, there is little understanding of the

factors and mechanisms that contribute to this elevated risk [14]. However, it is possible

to hypothesize that emotion processing might be related to affective temperaments,

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given that emotions and temperaments are strictly related. In fact, affective

temperaments refer to the emotional domain of personality [14] and have a profound

and central role in emotional communication [13,15].

In sum, much more research on the etiology of depressive disorders is required in

order to implement prevention and treatment efforts, since depression can have adverse

effects on a person’s general health and quality of life [16]. In particular, depressed

people are at higher risk for suicidal ideation and behavior [17]. Awareness of these

negative effects should be reflected in the increase in research on risk factors for major

depression in order to understand how and why some people develop the illness.

To better understand the etiology of depression and implement research and

treatment strategies, it is important to clarify whether deficits and biases in facial

emotion processing represent a risk factor for major depression. Thus, for the first time,

the present study explored whether never-depressed individuals who were at risk for

depression due to significantly higher scores on affective temperamental dimensions

containing a depressive component differed from individuals with lower scores in the

processing of facial expressions of emotions.

Methods

The sample was composed of 231 participants (139 females and 92 males). All

participants were nonrandomly recruited from the general population between March

2012 and September 2012 through advertisement posted in established community

groups and university campuses located in Central and Southern Italy. Participants were

included if they were 18 years or older and provided written informed consent, while

they were excluded if they had a severe disabling condition or intellectual deficits

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affecting the ability to take the assessment, such as a severe medical diagnosis, any

major disorder of the central nervous system (e.g., dementia), and current florid

psychotic symptoms. All participants completed the assessment on a voluntarily basis

without receiving any honorarium. The study design was approved from the local ethics

committee.

Psychometric measures

Participants were administered the Beck Depression Inventory – II (BDI-II [18]), the

Temperament Evaluation of Memphis, Pisa, Paris, and San Diego – auto-questionnaire

(TEMPS-A [19]), and the Suicidal History Self-Rating Screening Scale (SHSS [20]).

The BDI-II is a 21-item self-report inventory designed to assess the presence and

severity of depressive symptoms according to the DSM-IV criteria. Respondents have

to endorse specific statements that reflect their feelings over the last two weeks. Each

statement is rated on a 4-point Likert-type scale ranging from 0 to 3 on the basis of

symptom severity. In the current study, the Cronbach’s alpha was .90.

The TEMPS-A is a 110-item self-report measure of the affective temperament that

defines the bipolar spectrum, with depressive, cyclothymic, hyperthymic, irritable, and

anxious subscales [21]. The TEMPS-A has demonstrated to be not affected by current

mood state (e.g., depressive vs. manic), while it is able to reliably identify

temperamental profiles in psychiatric patients [22].

The SHSS is a 16-item (Yes/No) questionnaire developed to obtain information

about lifetime or past-year suicidal ideation, suicide planning, and suicide attempts. For

the present study the participants responded to items measuring death wishes (“Have

you ever felt tired of living or have you ever thought that life wasn’t worth living during

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the last twelve months?” and “During the last twelve months, have you ever thought that

for you, for your family or for your friends, it would be better if you were dead?”),

suicidal ideation (“During the last twelve months, have you ever thought about taking

your own life?”), and suicide planning (“During the last twelve months, have you ever

planned a way of taking your own life?”) experienced in the past 12 months.

Cognitive task

Digitized color emotional face stimuli from the 2D Facial Emotional Stimuli

database [23] were used. Eighty stimuli expressing fear, angry, sad, happy, and neutral

facial expressions were presented to each participant. Eight stimuli at two different

levels of intensity (moderate intensity and full intensity) were presented for each

emotion and sex. Each trial consisted of a single stimulus presented for 10 s, and

participants were instructed to make mouse button presses with equal emphasis on

speed and accuracy to choose between five answers representing the classes of stimuli

presented. After the participant pressed the button, or after ten seconds from the

appearance of the stimulus, another stimulus was presented with an inter-trial-interval of

800±200 ms between two consecutive stimuli. Stimuli were presented with Affect 4.0

software for windows [24] using a portable PC with a 15 inches screen.

Statistical analysis

To measure prevalent affective temperaments, we calculated z-scores for all the

dimensions of the TEMPS-A. We considered prevalent the temperament having z-

scores of 1 or higher and being the highest in the profile of the individual. In this sense,

a participant had a prevalent affective temperament when he had scores on a specific

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dimension of the TEMPS-A equal or greater than the mean plus 1 standard deviation

scores obtained by the whole sample.

To measure recognition accuracy of facial expressions of emotions, we computed

percentages of correct responses for each emotional category and also reported accuracy

in the recognition of emotional facial expression as deviation from the accuracy in the

recognition of neutral facial expression using the following formula:

[(% of correct responses for emotional stimuli) – (% of correct responses for neutral

stimuli) / % of correct responses for neutral stimuli] x 100.

Negative scores indicate that the participant is more accurate in recognizing neutral

facial expressions than the emotional ones, while positive scores indicate that the

participant is more accurate in recognizing emotional facial stimuli than the neutral

ones. Higher scores indicate greater differences in recognition accuracy of emotional

and neutral facial expressions.

In order to reveal temperamental groupings (or clusters) within the data set, we used

a two Step Cluster Analysis procedure. This procedure can handle categorical and

continuous variables, using a likelihood distance measure which assumes that variables

in the cluster model are independent. For the analysis, we let the procedure

automatically determine the number of clusters. One-way ANOVAs were used for

comparisons between groups of participants on dimensional variables and chi-squared

tests (χ2) were used for NxN contingency tables; post-hoc comparisons between pairs of

groups were performed with the Tamhane’s T2 procedure.

All the variables significant at the bivariate analysis were entered as independent

variables in a series of multinomial logistic regression analyses with the groups as

dependent variable. Odds ratios (OR) and their 95% confidence interval (95% CI) were

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reported as measure of association. To reduce the problem of multicollinearity among

variables measured at the emotional test, those dimensions which were significant at the

bivariate analyses were inserted in a principal axis factoring analysis to extract common

factors explaining covariance among variables and factor scores were calculated and

used in the analyses.

Statistical analyses were performed with the Statistical Package for Social Sciences

for Windows 20.0 (IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM

Corp.).

Results

Characteristics of the sample

The mean age of the participants was 39.9 years (SD = 14.57; range: 47). In line with

the nonclinical nature of the sample, only 4.3% of the participants reported scores of 20

or higher on the BDI-II, suggestive of moderate to severe depression. Twenty-four

participants (10.4% of the sample) reported death wishes, 7 (3.0% of the sample)

reported suicidal ideation, and 3 (1.3% of the sample) reported suicide planning.

Regarding affective temperaments, while 54.5% of the sample had no prevalent

temperaments, 9.1% had a prevalent depressive temperament, 7.4% a cyclothymic

temperament, 10.0% a hyperthymic temperament, 8.2% an irritable temperament, and

10.8% an anxious temperament.

Factors associated with a dysregulated temperamental profile

The Two Step Cluster Analysis, performed to reveal natural groupings within the

participants’ response set, indicated a 3-cluster solution: the first group included 83

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participants (35.9% of the sample), the second group 100 participants (43.3% of the

sample), and the third group 48 participants (20.8% of the sample). The three groups

differed for all the TEMPS-A dimensions with a depressive-dysregulated component

(depression, cyclothymia, irritability, and anxiety) but not for hyperthymia (Table 1).

Participants included in the first cluster reported low or no temperamental

dysregulation. They had significantly lower mean scores on all the temperaments with a

depressive-dysregulated component when compared to the other groups. No participants

included in this group had a prevalent dysregulated temperament. The second group

included participants with a moderate temperamental dysregulation. They had higher

mean scores on all the affective temperaments with a depressive-dysregulated

component when compared to the first group and lower mean scores when compared to

participants included in the third group. The third group included participants with a

more severely dysregulated depressive component; about 96% of them had a

dysregulated prevalent temperament.

Groups of participants with different temperamental profile differed for several

variables (see Tables 2-4), although they did not differ for sex and age. Compared to the

other groups, participants with severe temperamental dysregulation reported more

frequently death wishes, suicidal ideation, and suicide planning and more depressive

symptoms (Table 2).

Groups also differed for the accuracy in recognizing fear and happy facial

expressions (at full intensity) and neutral facial expressions (Table 3). Participants with

moderate temperamental dysregulation were more accurate than those with low or no

dysregulation in recognizing fear and happy facial expressions, while participants with

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severe dysregulation were less accurate than those with moderate dysregulation in

recognizing neutral facial expressions.

When analyzing accuracy in recognizing emotional facial expressions as deviation

from accuracy in recognizing neutral facial expressions (Table 4), groups differed for

angry and fear facial expressions at their full intensity and for happy and sad facial

expressions at both moderate and full intensity. Participants with severe temperamental

dysregulation had the highest mean scores on all the categories, despite post-hoc

differences were significant only for comparisons between this group and participants

with moderate dysregulation for angry and sad facial expressions at their full intensity.

These analyses indicated that participants with low to moderate dysregulation were

similarly accurate when asked to recognize emotional and neutral facial expressions,

whereas participants with severe dysregulation were more accurate when asked to

recognize emotional facial expressions than when facing neutral facial expressions

which were interpreted as emotional facial expressions. Of nearly 1,500 errors in

interpreting neutral facial expressions, 64% were characterized by a negative

interpretative bias (i.e. neutral facial expressions were interpreted as sad facial

expressions) (not reported in the tables).

Multinomial logistic regression analyses with variables measuring accuracy in

recognizing emotional and neutral facial expressions that differentiated groups at the

bivariate analyses as independent variables and the groups as dependent variable (Table

5) indicated that participants with severe dysregulation, but not those with moderate

dysregulation (OR = 1.04; 95% CI = 0.99/1.02; p = 0.61), were less accurate in

recognizing neutral facial expressions than those with no or low dysregulation (OR =

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0.98; 95% CI = 0.96/0.997; p < 0.05) even when controlling for the severity of current

depressive symptoms.

A principal factor analysis of variables measuring accuracy in recognizing emotional

facial expressions (reported as deviation from the accuracy in recognizing neutral facial

expressions) indicated the presence of a single latent factor with eigenvalue higher than

1 which explained 92.4% of the variability of the data. All the variables inserted in the

analysis loaded on this factor with loading of 0.91 and higher (not reported in the

tables). Multinomial logistic regression analysis with the factor measuring accuracy in

recognizing emotional facial expressions as deviation from the accuracy in recognizing

neutral facial expressions, BDI-II scores, and suicidality as independent variables and

groups as dependent variable (Table 6) indicated that participants with severe

temperamental dysregulation were 1.6 times more likely to have higher scores on this

factor (95% CI OR = 1.01/2.54; p < 0.05).

Discussion

This study was aimed to investigate whether abnormal facial emotion processing

represents a vulnerability factor for depression by investigating whether unaffected

individuals at risk for depression due to affective temperaments carrying a depressive

component are characterized by deficits and biases in recognition and interpretation of

facial expressions of emotions.

Participants with a more severely dysregulated depressive profile (i.e. higher scores

on affective temperaments containing a depressive component), compared to those with

low or moderate dysregulation, reported more depressive symptoms, death wishes, and

suicide ideation and planning. These results are consistent with literature revealing that

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affective temperaments are significantly related to depression and suicidal behavior (for

reviews, see [12,14]). In particular, the results of the present study are consistent with

those from investigations suggesting that depression and/or suicidal ideation or behavior

are strongly related not only to depressive, cyclothymic, and irritable temperaments but

also to the anxious temperament (e.g. [25-29]). Since these affective temperaments

containing more or less of a depressive component provide a typical pattern of

cyclothymic-depressive-irritable-anxious temperamental constellation clearly associated

with depression and suicidal ideation or behavior, they represent a dysphoric-

dysregulated depressive profile.

Compared to participants with low temperamental dysregulation, participants with a

more severely dysregulated depressive component were not less accurate in recognizing

facial expressions of happiness, sadness, anger, and fear. A recent systematic review has

shown that evidence of reduced general or emotion-specific recognition accuracy of

facial emotion expressions is inconsistent, given that several studies have found no

group differences between depressed patients and healthy controls in identification and

discrimination of facial expressions of happiness, sadness, fear, anger, disgust, and

surprise [1]. Evidence of reduced identification accuracy of facial emotion expressions

is inconsistent also in studies on individuals at familial risk for depression [7-10]. In

fact, two studies have found that adult relatives of depressed patients did not differ from

controls in their identification and categorization of facial expressions of emotions with

varying intensities [8,10]. In contrast, two other studies have provided mixed results

[7,9]. Specifically, in one of these studies, high-risk girls, compared to low-risk girls,

needed more intensity to correctly identify sad expressions and made more errors when

identifying low-intensity angry expressions [7]. In the other study, high-risk boys, but

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not high-risk girls, identified sadness at significantly lower levels of emotional intensity

than did their low-risk peers, while the high and low-risk groups did not differ with

regard to identification of anger [9].

However, in the present study, participants with severe affective temperament

dysregulation were less accurate in recognizing neutral facial expressions which were

interpreted as emotional facial expressions; in particular, neutral facial expressions were

interpreted more negatively, mostly as sad facial expressions. These results are

consistent with literature suggesting a negative response bias in interpretation of

ambiguous and neutral facial expressions in individuals with major depression, so that

neutral or ambiguous facial expressions tend to be evaluated as more sad or less happy

compared with healthy control groups (for a review, see [1]). Nevertheless, the only two

studies that, to our knowledge, have addressed the hypothesis of a negative

interpretative bias for ambiguous and neutral facial expressions in individuals at familial

risk for depression have found that relatives of depressed patients did not differ from

controls in their interpretation of ambiguous and neutral facial expressions [9,10].

In sum, the results of the present study do not support the hypothesis that accuracy

deficits in recognizing facial expressions of emotions may represent a risk factor for

major depression. In fact, at present, evidence of deficits in recognition accuracy of

facial emotion expressions in either individuals who have current or past diagnosis of

major depression or unaffected individuals at risk for depression is scant or conflicting.

Nevertheless, the results of the present study show that a negative bias in interpretation

of neutral facial expressions, specifically an increased tendency to interpret neutral

facial expressions negatively, may exist in individuals at risk for depression. As such,

this may represent a vulnerability factor for major depression.

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Although the results of the present study may have important implications for the

development of appropriate prevention and treatment strategies, they should be

interpreted with caution and conclusions cannot be definitively drawn, given that, to our

knowledge, this is the first investigation of processing of facial expressions of emotions

in individuals with affective temperaments. Additionally, this study has some important

limitations, such as the use of a convenience sample and a cross-sectional design, that

might limit causal inferences and the generalizability of the findings. Therefore, further

research is needed. Importantly, since multiple biological, psychological, or social risk

factors contribute to the development of depressive symptoms and disorders [30-35],

future investigations should include facial emotion processing in more comprehensive,

multifactorial etiological models in order to explain how risk factors work together to

promote the onset and/or maintenance of major depression.

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Acknowledgments

This study has no external funding source and was not financial supported. The

authors report no financial interests, affiliations, conflicts of interest, or other

relationship relevant to the subject matter of this paper.

Author contributions: All authors had full access to all data in the study and take

responsibility for the integrity of the data and the accuracy of the data analysis. All

authors made substantial contributions to study concept and design, acquisition of data,

analysis and interpretation of data, drafting of the manuscript, critical revision of the

manuscript for important intellectual content, study supervision, and final approval of

the version to be published.

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a selective overview for the implications of suicide prevention. Eur Arch Psychiatry

Clin Neurosci 2010;260:583-600.

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TABLE 1. Temperamental profiles of clusters

1

Low or no temperamental

dysregulation

(n = 83)

2

moderate temperamental

dysregulation

(n = 100)

3

Severe temperamental

dysregulation

(n = 48)

F (2;228) p < 1 2

TEMPS-A Depression 5.10±1.76 7.84±2.17 10.19±2.46 94.28 <0.001 2↓,

3↓

1↑,

3↓

TEMPS-A

Cyclothymia 2.65±1.84 7.61±2.84 12.44±2.97 230.67 <0.001

2↓,

3↓

1↑,

3↓

TEMPS-A

Hyperthymia 12.78±3.69 12.26±3.59 11.98±4.60 0.76 0.47

TEMPS-A Irritability 1.49±1.85 4.19±2.42 9.94±3.47 173.93 <0.001 2↓,

3↓

1↑,

3↓

TEMPS-A Anxiety 3.35±2.45 8.53±3.88 13.79±4.15 139.47 <0.001 2↓,

3↓

1↑,

3↓

Prevalent

temperaments

χ210 =

136.40 <0.001

None 83.1% 56.0% 2.1%

Depressive 0.0% 11.0% 20.8%

Cyclothymic 0.0% 6.0% 22.9%

Hyperthymic 16.9% 8.0% 2.1%

Irritable 0.0% 4.0% 31.3%

Anxious 0.0% 15.0% 20.8%

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TABLE 2. Differences between groups for depression scores and suicide ideation and wishes

Low or no temperamental

dysregulation

(n = 83)

Moderate temperamental

dysregulation

(n = 100)

Severe temperamental

dysregulation

(n = 48)

F (2;228) p < 1 2

Men 43.4% 37.0% 39.6% χ

22 =

0.77 0.68

Age 42.23±13.68 39.31±15.29 37.10±14.20 2.05 0.13

BDI-II 2.36±3.01 6.70±4.56 12.90±8.44 62.79 <0.001 2↓,

3↓

1↑,

3↓

SHSS 0.05±0.31 0.16±0.44 0.50±0.95 10.49 <0.001 3↓

Death wishes 2.4% 12.0% 20.8% χ

22 =

11.58 0.003

For family’s and friends’ sake, I have

better to be dead 1.2% 3.0% 12.5%

χ22 =

10.12 0.006

Suicidal ideation 1.2% 1.0% 10.4% χ

22 =

11.26 0.004

Suicidal planning 0.0% 0.0% 6.3% χ

22 =

11.59 0.003

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TABLE 3. Accuracy in emotional stimuli recognition

Low or no temperamental

dysregulation

(n = 83)

Moderate temperamental

dysregulation

(n = 100)

Severe temperamental

dysregulation

(n = 48)

F

(2;228)

p < 1 2

Anger – moderate intensity 18.22±17.27 21.38±18.83 19.01±19.29 0.72 0.49

Anger – full intensity 83.28±15.03 79.88±15.17 78.91±17.52 1.57 0.21

Fear – moderate intensity 53.61±20.71 56.88±17.17 51.82±17.86 1.39 0.25

Fear – full intensity 72.14±23.37 80.63±19.49 73.70±21.30 3.99 0.05 2↓ -

Happiness – moderate

intensity

93.07±12.23 95.00±9.57 93.23±13.63 0.75 0.47

Happiness – full intensity 91.27±12.91 95.88±9.58 91.41±14.62 4.10 0.05 2↓ -

Neutral 67.62±24.60 71.44±21.36 56.25±28.68 6.45 0.01 - 3↑

Sadness – moderate intensity 70.78±18.34 71.63±18.45 72.40±25.13 0.10 0.90

Sadness – full intensity 78.16±20.18 75.75±19.45 79.43±23.84 0.60 0.55

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TABLE 4. Accuracy in emotional stimuli recognition (as deviation from accuracy in recognition of neutral stimuli)

Low or no temperamental

dysregulation

(n = 83)

Moderate temperamental

dysregulation

(n = 100)

Severe temperamental

dysregulation

(n = 48)

F

(2;228)

p < 1 2

% of correct responses for anger –

moderate intensity -64.85±52.45 -62.27±65.15 -58.13±49.14 0.20 0.82

% of correct responses for anger – full

intensity 48.99±104.36 26.52±81.59 117.00±232.40 7.37 0.001 3↓

% of correct responses for fear – moderate

intensity -3.20±82.96 -7.35±68.68 26.39±105.97 2.83 0.06

% of correct responses for fear – full

intensity 23.05±70.53 29.89±103.32 98.42±220.21 5.92 0.01

% of correct responses for happiness –

moderate intensity 65.40±106.96 57.51±155.98 148.25±247.65 5.25 0.01

% of correct responses for happiness – full

intensity 61.39±100.17 57.27±137.62 135.48±222.55 4.96 0.01

% of correct responses for sadness –

moderate intensity 23.45±78.06 17.00±101.53 105.34±261.88 6.62 0.01

% of correct responses for sadness – full

intensity 32.54±77.79 18.31±80.79 119.01±258.91 9.09 <0.001 3↓

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TABLE 5. Multinomial regression analysis (group with low or no temperamental dysregulation is the reference category)

B Std. Error Wald df Sig.

Odds

ratio

95% Confidence

Interval for odds ratio

Lower

Bound

Upper

Bound

Moderate temperamental

dysregulation

BDI-II 0.32-0.35 0.06

31.89-

34.06 1 <0.001 1.38-1.41 1.24-1.26 1.55-1.59

Suicidality -0.30

–

-0.44

0.50-0.51 0.37-0.75 1 0.39-0.54 0.65-0.74 0.24-0.28 1.74-1.96

Fear – full intensity 0.02 0.01 4.04 1 0.05 1.02 1.00 1.03

Happiness – full intensity 0.05 0.02 7.87 1 0.01 1.05 1.01 1.08

Neutral 0.004 0.01 0.26 1 0.61 1.04 0.99 1.02

Severe temperamental

dysregulation

BDI-II 0.49-0.50 0.07-

53.79-

54.21 1 <0.001 1.63-1.65 1.43-1.45 1.86-1.89

Suicidality -0.40-

-0.44 0.55-0.56 0.52-0.64 1 0.42-0.47 0.64-0.67 0.22-0.29 1.91-1.98

Fear – full intensity 0.00 0.01 0.00 1 0.99 1.00 0.98 1.02

Happiness – full intensity 0.03 0.02 1.85 1 0.17 1.03 0.99 1.07

Neutral -0.02 0.01 4.94 1 0.05 0.98 0.96 0.997

Model fitting criteria

Final models: -2 Log Likelihood = 191.23-239.79; Likelihood Ratio χ26 = 117.69-122.17; all significant for p < 0.001; Nagelkerke R

2 = 0.45-0.47.

Reduced models: BDI-II: -2 Log Likelihood = 285.20-391.06; Likelihood Ratio χ22 = 91.48-93.97; all significant for p < 0.001; Suicidality: -2 Log Likelihood =

191.96-297.74; Likelihood Ratio χ22

= 0.50-0.73; p = 0.70-0.78; Fearfull: -2 Log Likelihood = 245.61; Likelihood Ratio χ

22 = 5.83; p = 0.054; Happinessfull: -2 Log

Likelihood = 200.18; Likelihood Ratio χ2

2 = 8.95; p < 0.05; Neutral: -2 Log Likelihood = 307.52; Likelihood Ratio χ

22

= 10.31; p < 0.01.

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TABLE 6. Multinomial regression analysis (group with low or no temperamental dysregulation is the reference category)

B Std. Error Wald df Sig.

Odds

ratio

95% Confidence

Interval for odds ratio

Lower

Bound

Upper

Bound

Moderate temperamental

dysregulation

BDI-II 0.34 0.06 34.47 1 <0.001 1.41 1.26 1.58

Suicidality -0.37 0.51 0.55 1 0.46 0.69 0.26 1.85

Accuracy in emotional

recognition as deviation from

accuracy in the recognition of

neutral stimuli

-0.18 0.28 0.44 1 0.51 0.83 0.48 1.43

Severe temperamental

dysregulation

BDI-II 0.49 0.07 52.77 1 <0.001 1.64 1.43 1.87

Suicidality -0.31 0.56 0.31 1 0.58 0.73 0.25 2.19

Accuracy in emotional

recognition as deviation from

accuracy in the recognition of

neutral stimuli

0.47 0.23 4.01 1 0.05 1.60 1.01 2.54

Model fitting criteria

Final model: -2 Log Likelihood = 363.50; Likelihood Ratio χ2

6 = 117.84; p < 0.001; Nagelkerke R

2 = 0.46.

Reduced models: BDI-II: -2 Log Likelihood = 452.88; Likelihood Ratio χ2

2 = 89.38; p < 0.001; Suicidality: -2 Log Likelihood = 364.02; Likelihood Ratio χ

22 =

0.53; p = 0.77; Accuracy in emotional recognition as deviation from accuracy in recognition of neutral stimuli: -2 Log Likelihood = 371.75; Likelihood Ratio

χ2

2= 8.25; p = 0.05.