1. bookVolume 1 (2018): Issue 2 (November 2018)
Journal Details
License
Format
Journal
eISSN
2451-4950
First Published
16 Apr 2017
Publication timeframe
2 times per year
Languages
English
Open Access

Facial emotion recognition performance influences executive control impairment in Anorexia Nervosa: an exploratory study

Published Online: 22 Oct 2018
Volume & Issue: Volume 1 (2018) - Issue 2 (November 2018)
Page range: 53 - 60
Received: 20 Aug 2018
Accepted: 13 Sep 2018
Journal Details
License
Format
Journal
eISSN
2451-4950
First Published
16 Apr 2017
Publication timeframe
2 times per year
Languages
English
Introduction

Executive control encompasses a set of mechanisms that allow individuals to plan complex goal-directed behaviours, flexibly adjusting their performance and adapting to changing environmental and internal states (Alvarez & Emory, 2006).

Various deficits in executive control have been identified in the Eating Disorders (EDs) literature, in particular, as regards difficulties in set-shifting (e.g., Kittel, Brauhardt, & Hilbert, 2015). Deficits in executive control – including inhibitory control, cognitive flexibility, decision-making, and working memory – may be risk or maintenance factors for EDs (Manasse et al., 2015). Nonetheless, evidence is somehow mixed in several aspects (Wu et al., 2014), considering various socio-demographic and clinical confounders. Significant methodological weaknesses (e.g., use of a single executive control measure, omission of relevant covariates) in the current literature represent one reason for lack of consensus. For example, considering Anorexia Nervosa (AN), children and adolescents populations show little, if any, impairment in set-shifting ability (Lang et al., 2014). This might be due to the cognitive disturbances derived from alterations in the brain structure detectable in the adulthood among people with AN, and possibly exacerbated by starvation, which contribute to the maintenance of AN after recovery (Fonville et al., 2014). Similarly, evidence on impairments underlying poor executive control in Bulimia Nervosa (BN) is not conclusive (Van den Eynde et al., 2011). In addition, individual differences in clinical characteristics in ED samples provide further interpretative challenges, as these could distinctively affect each individual’s cognitive performance. For example, age of onset might influence inefficiencies in set-shifting that are apparent in the adult, since they do not appear to be as pronounced in children. This may suggest that set shifting difficulties in adult AN are the result of starvation or indicative of longer duration of illness (Lang et al., 2014).

In particular, Facial Emotion Recognition (FER), that is, the ability to accurately identify and name emotions of other people, has been shown compromised in women with AN (Caglar-Nazali et al., 2014). The facets of social-cognition that appear to be compromised in this patient group include difficulties identifying basic and complex emotions, with large to moderate effects found for poor FER (Cardi et al., 2015), particularly in women with AN. Although evidence remains not entirely convincing and definitive, difficulties in interpreting emotions may contribute to, and exacerbate, AN clinical symptoms (Treasure, Corfield, & Cardi, 2012). Also, for BN, the limited literature has found some difficulties in recognizing specific emotions (e.g., Kuhnpast, Gramann, & Pollatos, 2012; Aloi et al., 2017). In particular, authors using pooled subjects with BN and AN have reported contradictory findings, showing global difficulties recognising emotions in adolescents (Zonnevijlle-Bender, van Goozen, Cohen-Kettenis, van Elburg, & van Engeland, 2002), but not in adults (Cardi et al., 2015). However, considering BN only, some investigations have found slight difficulties recognising surprise (Kessler, Schwarze, Filipic, Traue, & von Wietersheim, 2006; Legenbauer, Vocks, & Ruddel, 2008), and anger, often misinterpreted as fear (Kuhnpast, Gramann, & Pollatos, 2012), but no problems recognising other emotions.

However, an association between impaired FER and executive control has been found in several other serious mental disorders, including alcohol dependence (Trick et al., 2014), schizophrenia (Bortolon, Capdevielle, & Raffard, 2015), and bipolar disorders (David et al., 2014). Prefrontal dysfunction may lead to impairments in executive control and FER (Adolphs, 2002). Emotion face perception is a complex process that cannot be related to a single neural event taking place in a single brain region, but rather implicates an interactive network with distributed activity in time and space. Traditional models have often assumed that facial expression and executive control are processed along separate pathways. However, evidence from fMRI suggests that emotional processing can strongly affect brain systems responsible for both face recognition and memory, with fear-related modulations of face processing driven by amygdala signals implicating not only fusiform cortex, but also earlier visual areas in occipital cortex involved in cognitive responses (Vuilleumier & Pourtois, 2007). Deficits in FER and executive control could thus be associated also in EDs. Consistently, determining whether the impairment in EDs is cognitive-affective may have key therapeutic implications, as these require different intervention strategies (Legenbauer, Vocks, & Rüddel, 2008). It might well be that, also in people with EDs, set-shifting and FER are jointly compromised, at least as regards the impairment of certain emotions. Nonetheless, to our knowledge, no empirical research exists, explicitly addressing this issue. We thus tested the hypothesis that difficulties in set-shifting experienced by people with AN or BN may be influenced by impaired FER. We used a real world sample of women with EDs, rigorously assessing diagnostic and clinical features, but also executive control and emotional recognition abilities. It was hypothesized that, after adjusting for important sociodemographic and clinical characteristics, impaired FER would influence executive control performance in people with AN or BN.

Material and methods
Design and sample

We conducted a cross-sectional study and, between October 2015 and May 2016, recruited, using a simple random procedure, women with a diagnosis of AN or BN from the Eating Disorders outpatient clinic of San Gerardo Mental Health Trust (Monza, Italy). This covers a 300,000 inhabitants catchment area in a mixed urban/rural region and provides specialized treatments for women suffering from EDs of any level of severity. In addition, we conveniently identified female healthy controls (HCs), easily accessible and geographically concentrated clients attending local shops, within the same age range. Power calculations to establish the required sample size were based on the data from similar clinical populations, which assessed IED total trials (adjusted) (Galimberti et al., 2012). Considering a Cohen’s d of 0.80 and 80% power, a sample size of 58 (39 cases and 19 HC) was needed to detect this effect size at the conventional significance level of 0.05, according to a 2:1 cases-controls ratio to account for both AN and BN subgroups. All hypothesis testing was two-tailed.

Inclusion and exclusion criteria

Eligible participants were women suffering from AN or BN and aged 18–50 years at the time of enrolment in the study. We excluded people with current drug or alcohol misuse, mental retardation, and any major psychiatric illness apart from depressive disorders (which are commonly comorbid among women with EDs) as well as those unable to provide consent.

Measures and procedures
Socio-demographic and clinical variables

Along with socio-demographic information (i.e., age, living and family conditions, employment status, education), several clinical variables, including body mass index (BMI), were collected. According to previous evidence from the literature, we selected clinically relevant variables that provide a broad picture of impairments related to psychological problems and emotional experience in EDs and that may influence specific domains we studied, that is, executive control and FER.

The Italian versions of the Eating Disorder Examination (EDE-17.0) (Calugi et al., 2017) and of the Eating Disorder Examination Questionnaire (EDE-Q 6.0) (Calugi et al., 2017), were used to generate DSM-5 ED diagnoses and to rule out (mean global score > 2.0) any possible EDs from HCs, respectively. Information on current symptom profile was collected on several domains. We used the Italian versions of Symptom Check List-SCL-90-R (Prunas et al., 2012) in order to get a broad picture of psychological problems and symptoms of psychopathology; the Beck Depression Inventory-BDI-II (Sica, Ghisi, & Lange, 2007) for measuring the severity of depression; the Eating Disorder Inventory-3 with subscales, a self-report tool, measuring constructs shown to be clinically relevant in individuals with EDs symptoms (i.e., drive for thinness-DT, bulimia-B and body dissatisfaction-BD) (Giannini et al., 2008); and the 20-item Toronto Alexithymia Scale-TAS-20 (Bressi et al., 1996), exploring difficulties in identifying and describing emotions and tendency to minimise emotional experience and focus attention externally. In addition, the Structured Clinical Interview AXIS II Personality Disorders (SCID-II) (First et al., 1997) for DSM-IV was administered to identify the relevant comorbid disorders.

Neuropsychological assessment

As far as cognition assessment, we distinguished two different domains.

First, in order to assess executive functions, we used the Intra-Extra Dimensional Set Shift (IED), a test of rule acquisition and reversal, sensitive to cognitive changes and widely adopted to assess executive control. IED is implemented on a computer-controlled touch screen, taking 7/10 min to be administered, assessing visual discrimination and attentional set formation maintenance, shifting, and flexibility of attention, using both simple stimuli for visual perceptual-dimensions, and compound ones, shown in nine different stages (Computerized Cambridge Cognition, 2013). Participants progress through the test completing the intra-dimensional shift stages and providing six consecutive correct responses. If at any stage the subject fails to reach this criterion after 50 trials, the test terminates. We used the adjusted number of errors as a measure of the participants’ ability in completing the overall task. Since the participants who do not complete one or more stages are less likely to make errors, the total errors were adjusted considering the non-completed stages. Thus, we chose the IED adjusted total errors as the main outcome measure, as recommended to study the impaired set-shifting.

Secondly, as regards emotion and social cognition, we used the Ekman 60 Faces Test-EK-60F for emotion recognition assessment (Dodich et al., 2014). This contains the grayscale photographs of 10 individuals, each displaying one of the six high-intensity prototypical basic emotions. Faces are presented in a random order for 5 seconds each, and participants choose which emotion term (anger, disgust, fear, happiness, sadness, and surprise) best describes the facial expression shown. Based on the number of correct responses, the overall score can range from 0 to 60. Each basic emotion has a maximum sub-score of 10.

Data analyses

Checking the data distribution for IED adjusted total errors and EK-60F scores, we identified outliers based on the interquartile range (iqr) rule. In particular, we calculated (value - upper quartile)/iqr for any value at or above the upper quartile as well as (value - lower quartile)/iqr for any value at or below the lower quartile, considering a threshold ratio of 3 (Tukey, 1977; Dawson, 2011). Thus, the participants bringing values whose ratio exceeded 3 (‘severe outliers’) were excluded from the analyses. In order to explore the potential differences between the diagnostic subgroups and HCs, univariate distributions were assessed. Univariate comparisons were made using Pearson’s chi-square test or Fisher’s exact test, where appropriate, for categorical data, and ANOVA or Kruskal-Wallis test, according to assumptions on distribution, for continuous variables. These analyses involved sociodemographic (i.e., age, living and family conditions, employment status, and education) and clinical variables, known as potential confounders among women suffering from EDs. Clinical variables included: DSM-IV personality disorders; history of childhood abuse; BMI; length of illness; IED adjusted total errors and scores of EK-60F; BDI-II (rated on a 4-point scale ranging from 0 to 3); TAS-20 (whose 20 items are rated using a 5-point Likert scale whereby 1 = strongly disagree and 5 = strongly agree); SCL-90 Global Severity Index (based on the average rating given to all 90 items); and EDI-3, whose 91 items – scoring from 0 to 4 – map into drive for thinness (DT), bulimia (B) and body dissatisfaction (BD) subscales. Adjustments for multiple comparisons, based on Bonferroni correction, were applied considering specific AN/BN diagnosis and different subscales of adopted instruments. Where appropriate, a mathematically equivalent adjustment was employed, multiplying the observed p-value by the number of comparisons made to obtain the Bonferroni-adjusted p-value.

In order to take into account the confounding effect, clinically relevant factors identified a priori from the literature and those covariates that were associated with specific EDs diagnostic subgroups (AN/BN) at univariate level were selected for multiple linear regression analyses. We compared the performances of the different models (i.e., including the different subsets of covariates as control variables) using Akaike Information Criterion (AIC), based on the maximized log-likelihood of the model and the number of parameters estimated (Akaike, 1973). Models with lower AIC values have better empirical support than those with higher values, still considering overall significance of the model. Statistical significance was set at p < 0.05. We analysed the data using the Stata statistical software package (version 14; Stata Corp, College Station, Texas).

Results

Checking the data distribution for IED adjusted total errors and EK-60F scores, we could detect two outliers based on interquartile range (iqr) rule (Tukey, 1977; Dawson, 2011), bringing values whose ratio exceeded 3 (‘severe outliers’). These participants were excluded from analyses, resulting in an overall sample of 58 women (AN = 19; BN = 20; HCs = 19). Consistent with our study hypothesis, we first explored the attributes of EDs, also in terms of performance in executive control and FER. Thus, Table 1 shows the univariate comparisons for sociodemographic and clinical characteristics across AN, BN and HCs subgroups. Mean age was comparable with participants usually in their late twenties, and not different in terms of living and family conditions, education and employment status. History of childhood abuse was rare, and BMI was obviously uneven between AN and BN. Women with AN performed significantly worse than HCs in terms of IED adjusted total errors. As regards EK-60F total and subscales scores, HCs scored significantly better than AN and BN only on fear subscale (subscale range 0–10). In addition, for measures describing current symptoms dimensions, that is, means of BDI-II, TAS-20, SCL-90 GSI, and EDI-3 subscales, women with AN and BN scored significantly worse than HCs.

Then, in order to explore the role of other factors, including FER performance and ED diagnostic subgroup, associated with IED adjusted total errors, we fitted several models that included significant attributes from the univariate analyses, and known to be relevant from the literature (Table 2). The first model considering the EDs diagnostic subgroups compared with HCs showed that IED set shifting performance was associated with AN (p = 0.008). However, in the second model, also taking into account age, EK-60F fear subscale, depression as measured by BDI-II, and alexithymia as measured by TAS-20, this association could not be confirmed. In addition, the performances of the two models in terms of AIC were comparable.

Discussion

This study aimed to investigate the influence of FER abilities on impaired executive control in women with EDs. As a measure of executive control, we used the IED, a standardized and validated test that is not timed and so may be less affected by potential deficits in speed of processing, and that was previously successfully used among women with EDs (e.g., Galimberti et al., 2012). This is critical, since the effect sizes for different measures of set-shifting among women with EDs across the studies differ significantly from each other (Wu et al., 2014). We could initially uncover an association between IED set-shifting adjusted total errors and just AN, that was not found in the previous studies. We possibly sampled a slightly older clinical population that might have had sufficient time to develop cognitive disturbances. However, taking into account different correlates, including fear recognition ability, this association was no longer significant. Fear recognition ability is likely to have a role on impairment in executive control in women with AN as much as alexithymia (Brewer et al., 2015) and other clinical variables (Wu et al., 2014) may have. As a whole, our findings are consistent with the cognitive-interpersonal maintenance model of AN (Treasure & Schmidt, 2013), as far as executive control is shown to be compromised in women with AN. Nonetheless, they provide incremental knowledge jointly exploring, for the first time, the influence of impaired interpretation of facial emotions and weak set shifting, an important measure of executive control. In sum, further research should pay closer attention to the evaluation of several potential confounders on executive control (Abbate-Daga et al., 2015).

Sociodemographic and clinical characteristics by diagnostic subgroups.

Anorexia Nervosa N = 19Bulimia Nervosa N = 20Healthy Controls N = 19P
Age yrs. mean (SD) median (IQR)27.26 (10.07) 23 (20-38)27.65 (9.48) 23.5 (20.5-33.5)26.79 (4.18) 26 (25-30)0.378
In a relationship3 (15.8%)3 (15.0%)5 (26.3%)0.701
Employed3 (15.8%)8 (40.0%)10 (52.6%)0.054
Living condition Alone1 (5.3%)3 (15.0%)2 (10.5%)
With family16 (84.2%)13 (65.0%)12 (63.2%)0.596
With partner2 (10.5%)3 (15.0%)5 (26.3%)
Other01 (5.0%)0
DSM-IV Personality disorders
None11 (57.9%)9 (45.0%)19 (100%)
Borderline Obsessive-compulsive2 (10.5%) 3 (15.8%)5 (25.0%) 00.001
Depressive1 (5.3%)1 (5.0%)
NAS2 (10.5%)5 (25.0%)
Lifetime major childhood abuse
Physical1 (5.3%)1 (5%)-
Sexual02 (10.0%)
BMI mean (SD)16.07 (1.09)21.91 (4.63)21.40 (2.50)0.0001
Median (IQR)16.10 (15.23-17.22)20.04 (19.48-21.55)21.20 (19.31-22.32)
Length of illness yrs. mean (SD)7.95 (11.54)8.30 (7.86)--
Median (IQR)3 (1-7)5 (3-12.5)
IED Set shifting mean (SD) adjusted40.32 (23.15)30.80 (20.51)21.74 (17.98)0.044
total errors
EK-60F, Total mean (SD)48.89 (4.66)48.75 (3.54)50.84 (4.19)0.316
Surprise9.37 (0.83)9.75 (0.55)9.10 (1.29)0.153
Happiness10.00 (0)9.65 (0.75)9.74 (0.45)0.289
Fear6.58 (2.63)6.05 (2.37)9.26 (1.15)0.0001
Disgust9.00 (1.45)8.55 (1.15)8.63 (1.46)0.328
Anger6.74 (1.66)6.45 (1.64)7.00 (1.73)0.666
Sadness7.21 (2.15)8.15 (1.46)8.42 (1.17)0.196
BDI-II mean (SD)24.21 (13.80)21.65 (12.55)2.68 (3.87)0.0001
TAS-20 mean (SD)57.00 (10.59)49.15 (14.38)32.42 (6.14)0.0001
SCL-90 GSI mean (SD)1.42 (0.74)1.26 (0.54)0.29 (0.28)0.0001
EDI-3 mean (SD)
DT79.26 (18.09)72.55 (25.62)9.58 (18.77)0.0001
B67.42 (21.48)63.80 (21.16)15.37 (18.87)0.0001
BD77.21 (15.03)71.40 (20.58)11.79 (17.72)0.0001

IQR = Interquartile range. Fisher’s exact test for categorical, ANOVA and Kruskal-Wallis test for continuous variables.

BMI: Body Mass Index; IED: Intra-Extra Dimensional Set Shift; EK-60F: Ekman 60 Faces; BDI-II: Beck Depression Inventory; TAS-20: Toronto Alexithymia Scale; SCL-90 GSI: Symptom Check List Global Severity Index; EDI-3: Eating Disorder Inventory 3rd version subscales: drive forthinness (DT), bulimia (B) and body dissatisfaction (BD).

Limitations

Studies of this type, relatively small in sample size, are inevitably exploratory in nature. Thus, our findings need to be interpreted with caution until replicated in studies that can be more accurately powered, based on our results. We acknowledge several further methodological limitations. First, we focused on a specific FER measure (EK-60F) arising from the extant literature to avoid confusing comparisons with different tools. Nonetheless, because the role of possible confounders has been addressed at the stage of design (random sampling) and of analysis (adjusting for a selected set of variables), we consider it unlikely that our results are driven by between-group differences in further unknown variables. However, we acknowledge that having treated age as a continuous variable, this might imply a multiplicative function that might distort the correlation studied. Also, we should acknowledge that arbitrary limits, based on the interquartile range rule (Tukey, 1977; Dawson, 2011), in order to identify the study outliers, might imply that important information is thrown out. In addition, we acknowledge the lack of a wider neuropsychological examination, including other, different, cognitive aspects, such as memory and attention, that would provide a more detailed picture of the affected domains.

Characteristics associated with IED adjusted total errors in different regression models.

IED adjusted total errors
Model 1Model 2
Regression coefficient95% CIPRegression coefficient95% CIP
AN

Reference category Healthy controls.

BN

Reference category Healthy controls.

18.58 9.065.15; 32.01 -4.20; 22.320.008 0.17612.56 1.39-9.25; 34.38 -18.56; 21.330.253 0.890
Age0.54-0.24; 1.320.171
EK-60F Fear-1.92-4.86; 1.020.195
BDI-II0.15-0.53; 0.820.665
TAS-20-0.10-0.83; 0.620.775
Model η20.120.19
AIC518.74522.28

IED = Intra-Extra Dimensional Set Shift; AN = Anorexia Nervosa; BN = Bulimia Nervosa; EK-60F = Ekman 60 Faces; BDI-II = Beck Depression Inventory; TAS-20 = Toronto Alexithymia Scale.

CI = confidence Interval; AIC = Akaike Information Criterion.

Conclusions

These limitations notwithstanding, our study provides preliminary insight about the influence of FER abilities on impaired executive control in women with AN. They may not be able to recognize complex emotional states, and this may provide clues on their executive control abilities, affecting the maintenance of severe EDs symptoms. This may have important implications that can be included in specialized treatment programmes and interventions aimed at improving socio-emotional processing in AN and updating the current programs dealing with emotion functioning (Tchanturia et al., 2015).

Sociodemographic and clinical characteristics by diagnostic subgroups.

Anorexia Nervosa N = 19Bulimia Nervosa N = 20Healthy Controls N = 19P
Age yrs. mean (SD) median (IQR)27.26 (10.07) 23 (20-38)27.65 (9.48) 23.5 (20.5-33.5)26.79 (4.18) 26 (25-30)0.378
In a relationship3 (15.8%)3 (15.0%)5 (26.3%)0.701
Employed3 (15.8%)8 (40.0%)10 (52.6%)0.054
Living condition Alone1 (5.3%)3 (15.0%)2 (10.5%)
With family16 (84.2%)13 (65.0%)12 (63.2%)0.596
With partner2 (10.5%)3 (15.0%)5 (26.3%)
Other01 (5.0%)0
DSM-IV Personality disorders
None11 (57.9%)9 (45.0%)19 (100%)
Borderline Obsessive-compulsive2 (10.5%) 3 (15.8%)5 (25.0%) 00.001
Depressive1 (5.3%)1 (5.0%)
NAS2 (10.5%)5 (25.0%)
Lifetime major childhood abuse
Physical1 (5.3%)1 (5%)-
Sexual02 (10.0%)
BMI mean (SD)16.07 (1.09)21.91 (4.63)21.40 (2.50)0.0001
Median (IQR)16.10 (15.23-17.22)20.04 (19.48-21.55)21.20 (19.31-22.32)
Length of illness yrs. mean (SD)7.95 (11.54)8.30 (7.86)--
Median (IQR)3 (1-7)5 (3-12.5)
IED Set shifting mean (SD) adjusted40.32 (23.15)30.80 (20.51)21.74 (17.98)0.044
total errors
EK-60F, Total mean (SD)48.89 (4.66)48.75 (3.54)50.84 (4.19)0.316
Surprise9.37 (0.83)9.75 (0.55)9.10 (1.29)0.153
Happiness10.00 (0)9.65 (0.75)9.74 (0.45)0.289
Fear6.58 (2.63)6.05 (2.37)9.26 (1.15)0.0001
Disgust9.00 (1.45)8.55 (1.15)8.63 (1.46)0.328
Anger6.74 (1.66)6.45 (1.64)7.00 (1.73)0.666
Sadness7.21 (2.15)8.15 (1.46)8.42 (1.17)0.196
BDI-II mean (SD)24.21 (13.80)21.65 (12.55)2.68 (3.87)0.0001
TAS-20 mean (SD)57.00 (10.59)49.15 (14.38)32.42 (6.14)0.0001
SCL-90 GSI mean (SD)1.42 (0.74)1.26 (0.54)0.29 (0.28)0.0001
EDI-3 mean (SD)
DT79.26 (18.09)72.55 (25.62)9.58 (18.77)0.0001
B67.42 (21.48)63.80 (21.16)15.37 (18.87)0.0001
BD77.21 (15.03)71.40 (20.58)11.79 (17.72)0.0001

Characteristics associated with IED adjusted total errors in different regression models.

IED adjusted total errors
Model 1Model 2
Regression coefficient95% CIPRegression coefficient95% CIP
AN

Reference category Healthy controls.

BN

Reference category Healthy controls.

18.58 9.065.15; 32.01 -4.20; 22.320.008 0.17612.56 1.39-9.25; 34.38 -18.56; 21.330.253 0.890
Age0.54-0.24; 1.320.171
EK-60F Fear-1.92-4.86; 1.020.195
BDI-II0.15-0.53; 0.820.665
TAS-20-0.10-0.83; 0.620.775
Model η20.120.19
AIC518.74522.28

Abbate-Daga, G, Buzzichelli, S, Marzola, E, Aloi, M, Amianto, F, Fassino, S 2015, ‘Does depression matter in neuropsychological performances in anorexia nervosa? A descriptive review’, International Journal of Eating Disorders, vol. 48, no. 6, pp. 73645.Abbate-DagaGBuzzichelliSMarzolaEAloiMAmiantoFFassinoS2015‘Does depression matter in neuropsychological performances in anorexia nervosa? A descriptive review’International Journal of Eating Disorders, vol4867364510.1002/eat.22399Search in Google Scholar

Adolphs, R 2002, ‘Recognizing emotion from facial expressions: psychological and neurological mechanisms.’, Behavioral and Cognitive Neuroscience Reviews, vol. 1, no. 1, pp. 21-62.AdolphsR2002‘Recognizing emotion from facial expressions: psychological and neurological mechanisms.’Behavioral and Cognitive Neuroscience Reviews, vol11216210.1177/1534582302001001003Search in Google Scholar

Akaike, H 1973, ‘Information theory and an extension of the maximum likelihood principle’ in BN Petrov & F Csaki (eds), Second International Symposium on Information Theory, pp. 267–281. Akailseoniai–Kiudo; Budapest.AkaikeH1973‘Information theory and an extension of the maximum likelihood principle’BNPetrov&FCsakiSecond International Symposium on Information Theory267281Akailseoniai–Kiudo; BudapestSearch in Google Scholar

Aloi, M, Rania, M, Caroleo, M, De Fazio, P, Segura-García, C 2017, ‘Social Cognition and Emotional Functioning in Patients with Binge Eating Disorder’, European Eating Disorders Review, vol. 25, no. 3, pp. 172-178.AloiMRaniaMCaroleoMDe FazioPSegura-GarcíaC2017‘Social Cognition and Emotional Functioning in Patients with Binge Eating Disorder’European Eating Disorders Review, vol25317217810.1002/erv.2504Search in Google Scholar

Alvarez, JA & Emory, E 2006, ‘Executive function and the frontal lobes: A meta-analytic review’, Neuropsychology Review, vol. 16, no. 1, pp. 17–42.AlvarezJA&EmoryE2006‘Executive function and the frontal lobes: A meta-analytic review’Neuropsychology Review, vol161174210.1007/s11065-006-9002-xSearch in Google Scholar

Bortolon, C, Capdevielle, D, Raffard, S 2015, ‘Face recognition in schizophrenia disorder: A comprehensive review of behavioral, neuroimaging and neurophysiological studies’. Neuroscience & Biobehavioral Reviews, vol. 53, pp. 79-107.BortolonCCapdevielleDRaffardS2015‘Face recognition in schizophrenia disorder: A comprehensive review of behavioralneuroimaging and neurophysiological studies’. Neuroscience & Biobehavioral Reviews, vol537910710.1016/j.neubiorev.2015.03.006Search in Google Scholar

Bressi, C, Taylor, G, Parker, J, Bressi, S, Brambilla, V, Aguglia, E, Allegranti, I, Bongiorno, A, Giberti, F, Bucca, M, Todarello, O, Callegari, C, Vender, S, Gala, C, Invernizzi, G 1996, ‘Cross validation of the factor structure of the 20-item Toronto Alexithymia Scale: an Italian multicenter study’ Journal of Psychosomatic Research, vol. 41, no. 6, pp. 551-559.BressiCTaylorGParkerJBressiSBrambillaVAgugliaEAllegrantiIBongiorno, A, Giberti, F, Bucca, M, Todarello, O, Callegari, C, Vender, S, Gala, CInvernizziG1996‘Cross validation of the factor structure of the 20-item Toronto Alexithymia Scale: an Italian multicenter study’ Journal of Psychosomatic Researchvol41655155910.1016/S0022-3999(96)00228-0Search in Google Scholar

Brewer, R, Cook, R, Cardi, V, Treasure, J, Bird, G 2015, ‘Emotion recognition deficits in eating disorders are explained by co-occurring alexithymia’ Royal Society Open Science, vol.2, no. 1. Available from: http://rsos.royalsocietypublishing.org/content/2/1/140382BrewerRCookRCardiVTreasureJBirdG2015‘Emotion recognition deficits in eating disorders are explained by co-occurring alexithymia’Royal Society Open Sciencevol.2, no. 1. Available fromhttp://rsos.royalsocietypublishing.org/content/2/1/14038210.1098/rsos.140382444879026064585Search in Google Scholar

Caglar-Nazali, HP, Corfield, F, Cardi, V, Ambwani, S, Leppanen, J, Olabintan, O, Deriziotis, S, Hadjimichalis, A, Scognamiglio, P, Eshkevari, E, Micali, N, Treasure, J 2014, ‘A systematic review and meta-analysis of ‘Systems for Social Processes’ in eating disorders’, Neuroscience & Biobehavioral Reviews, vol. 42, pp. 55-92.Caglar-NazaliHPCorfieldFCardiVAmbwaniSLeppanenJOlabintanODeriziotisSHadjimichalis, A, ScognamiglioPEshkevariEMicaliNTreasureJ2014‘A systematic review and meta-analysis of ‘Systems for Social Processes’ in eating disorders’Neuroscience & Biobehavioral Reviews, vol42559210.1016/j.neubiorev.2013.12.00224333650Search in Google Scholar

Calugi, S, Milanese, C, Sartirana, M, El Ghoch, M, Sartori, F, Geccherle, E, Coppini, A, Franchini, C, Dalle Grave, R 2017, ‘The Eating Disorder Examination Questionnaire: reliability and validity of the Italian version’ Eating and Weight Disorders, vol. 22, no. 3, pp. 509-514.CalugiSMilaneseCSartiranaMEl GhochMSartoriFGeccherleECoppiniAFranchiniCDalle GraveR2017‘The Eating Disorder Examination Questionnaire: reliability and validity of the Italian version’ Eating and Weight Disordersvol22350951410.1007/s40519-016-0276-627039107Search in Google Scholar

Calugi, S, Ricca, V, Castellini, G, Lo Sauro, C, Ruocco, A, Chignola, E, El Ghoch, M, Dalle Grave, R 2015, ‘The eating disorder examination: reliability and validity of the Italian version’. Eating and Weight Disorders, vol. 20, no. 4, pp. 505-511.CalugiSRiccaVCastelliniGLo SauroCRuoccoAChignolaEEl GhochMDalle GraveR2015‘The eating disorder examination: reliability and validity of the Italian version’. Eating and Weight Disordersvol20450551110.1007/s40519-015-0191-225850414Search in Google Scholar

Cardi, V, Corfield, F, Leppanen, J, Rhind, C, Deriziotis, S, Hadjimichalis, A, Hibbs, R, Micali, N, Treasure, J 2015, ‘Emotional Processing, Recognition, Empathy and Evoked Facial Expression in Eating Disorders: An Experimental Study to Map Deficits in Social Cognition’. PLoS ONE, vol. 10, no. 8. Available from: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133827CardiVCorfieldFLeppanenJRhindCDeriziotisSHadjimichalisAHibbsRMicaliN, Treasure, J2015‘Emotional Processing, Recognition, Empathy and Evoked Facial Expression in Eating Disorders: An Experimental Study to Map Deficits in Social Cognition’PLoS ONEvol108Available fromhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.013382710.1371/journal.pone.0133827452910526252220Search in Google Scholar

Computerized Cambridge Cognition. Computerized cognitive assessments. Available from: https://www.cambridgecognition.com [9 April 2016]Computerized Cambridge Cognition. Computerized cognitive assessmentsAvailable fromhttp://www.cambridgecognition.com9 April 2016Search in Google Scholar

David, DP, Soeiro-de-Souza, MG, Moreno, RA, Bio, DS 2014, ‘Facial emotion recognition and its correlation with executive functions in bipolar I patients and healthy controls’, Journal of Affective Disorders vol. 152-154, pp. 288-294.DavidDPSoeiro-de-SouzaMGMorenoRABioDS2014‘Facial emotion recognition and its correlation with executive functions in bipolar I patients and healthy controls’Journal of Affective Disorders vol152-15428829410.1016/j.jad.2013.09.02724211178Search in Google Scholar

Dawson, R 2011, ‘How significant is a Boxplot outlier?’ Journal of Statistics Education, vol. 19, no. 2. Available from: https://www.amstat.org/publications/jse/v19n2/dawson.pdf [9 April 2016].DawsonR2011‘How significant is a Boxplot outlier?’Journal of Statistics Educationvol192Available fromhttps://www.amstat.org/publications/jse/v19n2/dawson.pdf[9 April 2016]10.1080/10691898.2011.11889610Search in Google Scholar

Dodich, A, Cerami, C, Canessa, N, Crespi, C, Marcone, A, Arpone, M, Realmuto, S, Cappa, SF 2014, ‘Emotion recognition from facial expressions: a normative study of the Ekman 60-Faces Test in the Italian population’, Neurological Sciences vol. 35, no. 7, pp. 1015-1021.DodichACeramiCCanessaNCrespiCMarconeAArponeMRealmutoSCappaSF2014‘Emotion recognition from facial expressions: a normative study of the Ekman 60-Faces Test in the Italian population’Neurological Sciences vol3571015102110.1007/s10072-014-1631-x24442557Search in Google Scholar

First, MB, Gibbon, M, Spitzer, RL, Williams, JBW, Benjamin, LS 1997, Structured Clinical Interview for DSMIV Axis II personality disorders, (SCID-II). American Psychiatric Press; Washington.FirstMBGibbonMSpitzerRLWilliamsJBWBenjaminLS1997Structured Clinical Interview for DSMIV Axis II personality disorders, (SCID-II)American Psychiatric PressWashingtonSearch in Google Scholar

Fonville, L, Giampietro, V, Williams, SC, Simmons, A, Tchanturia, K 2014, ‘Alterations in brain structure in adults with anorexia nervosa and the impact of illness duration’ Psychological Medicine, vol. 44, no. 9, pp- 1965-1975.FonvilleLGiampietroVWilliamsSCSimmonsATchanturiaK2014‘Alterations in brain structure in adults with anorexia nervosa and the impact of illness duration’ Psychological Medicinevol4491965197510.1017/S003329171300238924074139Search in Google Scholar

Galimberti, E, Martoni, RM, Cavallini, MC, Erzegovesi, S, Bellodi, L 2012, ‘Motor inhibition and cognitive flexibility in eating disorder subtypes’. Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 36, no. 2, pp. 307-312.GalimbertiEMartoniRMCavalliniMCErzegovesiSBellodiL2012‘Motor inhibition and cognitive flexibility in eating disorder subtypes’. Progress in Neuro-Psychopharmacology and Biological Psychiatryvol36230731210.1016/j.pnpbp.2011.10.01722079108Search in Google Scholar

Giannini, M, Pannocchia, L, Dalle Grave, R, Muratori, F, Viglione, V 2008, EDI-3 Eating Disorder Inventory-3. Adattamento italiano, Giunti OS Organizzazioni Speciali; Firenze.GianniniMPannocchiaLDalle GraveRMuratoriFViglioneV2008EDI-3 Eating Disorder Inventory-3. Adattamento italiano, Giunti OS Organizzazioni SpecialiFirenzeSearch in Google Scholar

Kessler, H, Schwarze, M, Filipic, S, Traue, HC, von Wietersheim, J 2006, ‘Alexithymia and facial emotion recognition in patients with eating disorders.’, The International Journal of Eating Disorders, vol. 39, no. 3, pp. 245-251.KesslerHSchwarzeMFilipicSTraueHCvon WietersheimJ2006‘Alexithymia and facial emotion recognition in patients with eating disorders.’The International Journal of Eating Disorders, vol39324525110.1002/eat.2022816485269Search in Google Scholar

Kittel R, Brauhardt A, Hilbert A 2015 ‘Cognitive and emotional functioning in binge-eating disorder: A systematic review’, International Journal of Eating Disorders, vol. 48, no. 6, pp. 535-554.Kittel RBrauhardt AHilbertA2015‘Cognitive and emotional functioning in binge-eating disorder: A systematic review’International Journal of Eating Disordersvol48653555410.1002/eat.2241926010817Search in Google Scholar

Kuhnpast, N, Gramann, K, Pollatos, O 2012, ‘Electrophysiologic evidence for multilevel deficits in emotional face processing in patients with bulimia nervosa’, Psychosomatic Medicine vol. 74, no. 7, pp. 736–744.KuhnpastNGramannKPollatosO2012‘Electrophysiologic evidence for multilevel deficits in emotional face processing in patients with bulimia nervosa’Psychosomatic Medicine vol74773674410.1097/PSY.0b013e31825ca15a22826291Search in Google Scholar

Lang, K, Stahl, D, Espie, J, Treasure, J, Tchanturia, K 2014, ‘Set shifting in children and adolescents with anorexia nervosa: an exploratory systematic review and meta-analysis’. International Journal of Eating Disorders, vol. 47, no. 4, pp. 394-399.LangKStahlDEspieJTreasureJTchanturiaK2014‘Set shifting in children and adolescents with anorexia nervosa: an exploratory systematic review and meta-analysis’. International Journal of Eating Disordersvol47439439910.1002/eat.2223524347025Search in Google Scholar

Legenbauer, T, Vocks, S, Rüddel, H 2008, ‘Emotion recognition, emotional awareness and cognitive bias in individuals with bulimia nervosa’. Journal of Clinical Psychology, vol. 64, no. 6, pp. 687-702.LegenbauerTVocksSRüddelH2008‘Emotion recognitionemotional awareness and cognitive bias in individuals with bulimia nervosa’. Journal of Clinical Psychology, vol64668770210.1002/jclp.2048318473338Search in Google Scholar

Manasse, SM, Forman, EM, Ruocco, AC, Butryn, ML, Juarascio, AS, Fitzpatrick, KK 2015, ‘Do executive functioning deficits underpin binge eating disorder? A comparison of overweight women with and without binge eating pathology’, The International Journal of Eating Disorders, vol. 48, no. 6, pp. 677-683.ManasseSMFormanEMRuoccoACButrynMLJuarascioASFitzpatrickKK2015‘Do executive functioning deficits underpin binge eating disorder? A comparison of overweight women with and without binge eating pathology’The International Journal of Eating Disorders, vol48667768310.1002/eat.22383451670925644028Search in Google Scholar

Prunas, A, Sarno, I, Preti, E, Madeddu, F, Perugini, M 2012, ‘Psychometric properties of the Italian version of the SCL-90-R: a study on a large community sample’, European Psychiatry, vol. 27, no. 8, pp. 591-597.PrunasASarnoIPretiEMadedduFPeruginiM2012‘Psychometric properties of the Italian version of the SCL-90-R: a study on a large community sample’European Psychiatry, vol27859159710.1016/j.eurpsy.2010.12.00621334861Search in Google Scholar

Sica, C, Ghisi, M, Lange, MA 2007, ‘The Italian Versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric Properties and Discriminant Power’ In MA Lange (ed), Leading-Edge Psychological Tests and Testing, pp. 27-50. Nova Publisher; New York.SicaCGhisiMLangeMA 2007‘The Italian Versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric Properties and Discriminant Power’InMALangeLeading-Edge Psychological Tests and Testing2750Nova PublisherNew YorkSearch in Google Scholar

Tchanturia, K, Dapelo, MAM, Harrison, A, Hambrook, D 2015, ‘Why study positive emotions in the context of eating disorders?’, Current Psychiatry Reports, vol. 17, no. 1. Available from: https://link.springer.com/article/10.1007/s11920-014-0537-xTchanturiaKDapeloMAMHarrisonAHambrookD 2015‘Why study positive emotions in the context of eating disorders?’Current Psychiatry Reportsvol171Available fromhttps://link.springer.com/article/10.1007/s11920-014-0537-x10.1007/s11920-014-0537-x25413641Search in Google Scholar

Treasure, J, Corfield, F, Cardi, V 2012, ‘A three-phase model of the social emotional functioning in eating disorders’. European Eating Disorders Review, vol. 20, no. 6, pp. 431-438.TreasureJCorfieldFCardiV2012‘A three-phase model of the social emotional functioning in eating disorders’. European Eating Disorders Reviewvol20643143810.1002/erv.218122539368Search in Google Scholar

Treasure, J, Schmidt, U 2013, ‘The cognitive-interpersonal maintenance model of anorexia nervosa revisited: a summary of the evidence for cognitive, socio-emotional and interpersonal predisposing and perpetuating factors’. Journal of Eating Disorders, vol. 1. Available from: https://jeatdisord.biomedcentral.com/articles/10.1186/2050-2974-1-13TreasureJSchmidtU 2013‘The cognitive-interpersonal maintenance model of anorexia nervosa revisited: a summary of the evidence for cognitivesocio-emotional and interpersonal predisposing and perpetuating factors’. Journal of Eating Disordersvol. 1. Available fromhttps://jeatdisord.biomedcentral.com/articles/10.1186/2050-2974-1-1310.1186/2050-2974-1-13408171424999394Search in Google Scholar

Trick, L, Kempton, MJ, Williams, SCR, Duka, T 2014, ‘Impaired fear recognition and attentional set-shifting is associated with brain structural changes in alcoholic patients’. Addiction Biology, vol. 19, no. 6, pp. 1041–1054.TrickLKemptonMJWilliamsSCRDukaT2014‘Impaired fear recognition and attentional set-shifting is associated with brain structural changes in alcoholic patients’. Addiction Biologyvol1961041105410.1111/adb.12175428210425123156Search in Google Scholar

Tukey, JW 1977, ‘Exploratory data analysis.’, Reading, MA:Addison-Wesley.TukeyJW 1977‘Exploratory data analysisReading, MAAddison-WesleySearch in Google Scholar

Van den Eynde, F, Guillaume, S, Broadbent, H, Stahl, D, Campbell, IC, Schmidt, U, Tchanturia, K 2011 ‘Neurocognition in bulimic eating disorders: a systematic review’, Acta Psychiatrica Scandinavica, vol. 124, no. 2, pp. 120-140.Van den EyndeFGuillaumeSBroadbentHStahlDCampbellICSchmidtUTchanturia, K 2011 ‘Neurocognition in bulimic eating disorders: a systematic review’, Acta Psychiatrica Scandinavica, vol124212014010.1111/j.1600-0447.2011.01701.x21477100Search in Google Scholar

Vuilleumier, P, Pourtois, G 2007, ‘Distributed and interactive brain mechanisms during emotion face perception: evidence from functional neuroimaging’. Neuropsychologia, vol. 45, no. 1, pp. 174-194.VuilleumierPPourtoisG2007‘Distributed and interactive brain mechanisms during emotion face perception: evidence from functional neuroimaging’. Neuropsychologiavol45117419410.1016/j.neuropsychologia.2006.06.00316854439Search in Google Scholar

Wu, M, Brockmeyer, T, Hartmann, M, Skunde, M, Herzog, W, Friederich, HC 2014, ‘Set-shifting ability across the spectrum of eating disorders and in overweight and obesity: a systematic review and meta-analysis’. Psychological Medicine, vol. 44, no. 16, pp. 3365-3385.WuMBrockmeyerTHartmannMSkundeMHerzogWFriederichHC2014‘Set-shifting ability across the spectrum of eating disorders and in overweight and obesity: a systematic review and meta-analysis’. Psychological Medicinevol44163365338510.1017/S003329171400029425066267Search in Google Scholar

Zonnevijlle-Bender, MJ, van Goozen, SH, Cohen-Kettenis, PT, van Elburg, A, van Engeland, H 2002, ‘Do adolescent anorexia nervosa patients have deficits in emotional functioning?’, European Child & Adolescent Psychiatry, vol. 11, no. 1, pp. 38-42.Zonnevijlle-BenderMJvan GoozenSHCohen-KettenisPTvan ElburgAvan EngelandH2002‘Do adolescent anorexia nervosa patients have deficits in emotional functioning?’European Child & Adolescent Psychiatry, vol111384210.1007/s00787020000611942427Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo