The aim of this study is to examine social functioning in patients with schizophrenia and bipolar disorder and explore the psychological and neurophysiological predictors of social functioning.
Twenty-seven patients with schizophrenia and thirty patients with bipolar disorder, as well as twenty-five healthy controls, completed measures of social functioning (questionnaire of social functioning), neurocognition (Verbal fluency, Korean-Auditory Verbal Learning Test), and social cognition (basic empathy scale and Social Attribution Task-Multiple Choice), and the childhood trauma questionnaire (CTQ). For neurophysiological measurements, mismatch negativity and heart rate variability (HRV) were recorded from all participants. Multiple hierarchical regression was performed to explore the impact of factors on social functioning.
The results showed that CTQ-emotional neglect significantly predicted social functioning in schizophrenia group, while HRV-high frequency significantly predicted social functioning in bipolar disorder patients. Furthermore, emotional neglect and HRV-HF still predicted social functioning in all of the subjects after controlling for the diagnostic criteria.
Our results implicated that even though each group has different predictors of social functioning, early traumatic events and HRV could be important indicators of functional outcome irrespective of what group they are.
Social functioning, which refers to the degree to which a person adjusts to daily-life domains such as work and interpersonal relationship [
A large number of studies have investigated the relationship between cognitive impairment and social functioning in patients with schizophrenia and bipolar disorder [
Furthermore, other studies have explored the relationship between traumatic childhood experiences and social functioning in schizophrenia and bipolar disorder [
In addition, neurophysiological factors may predict social functioning in schizophrenia and bipolar disorder. In this study, the mismatch negativity (MMN) and heart rate variability (HRV), which are considered as objective measures related to automatic responses [
In sum, even though a growing body of evidence has shown that cognitive impairments, childhood maltreatment, and neurophysiological factors are associated with functional outcomes in schizophrenia and bipolar disorder, few studies have examined the predictive effect of psychological and neurophysiological factors on the social functioning of both patients simultaneously. Therefore, the present study aimed to perform an exploratory examination of the predictor of psychological and neurophysiological components on social functioning in schizophrenia and bipolar disorder. We hypothesized that social functioning would be impaired in schizophrenia and bipolar disorder relative to healthy controls and explored which psychological and neurophysiological factors would significantly predict functional outcomes in each group.
A total of 82 subjects between the ages of 20 and 64 years participated in this study. The subjects included patients with schizophrenia [n=27, age: 42.48±11.86 (range: 21–60)] and bipolar disorder [n=30, age: 39.70±12.61 (range: 20–63)] as well as healthy controls [n=25, age: 42.48±12.60 (range: 23–64)]. All patients were assessed by a psychiatrist for Axis I disorders based on the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (SCID) [
To evaluate social functioning, the questionnaire of social functioning (QSF) [
To assess neurocognition, a verbal fluency test [
The Basic Empathy Scale (BES) [
Experience of childhood trauma was measured using the Childhood Trauma Questionnaire (CTQ) [
HRV was measured using a 5-min single-channel (3-lead) electrocardiogram (ECG) signal. The ECG electrode sensors were attached to the left and right wrists and left ankle. After each subject was given approximately 5 minutes of rest in order to adapt to the experimental conditions, recordings were performed in the seated position at complete rest using the SA-3000P HRV analyzer (Medicore Co., Ltd, Seoul, Korea). The analyzer detected signals at 500 Hz, and the ECG signal was amplified and digitized. The following HRV parameters were calculated using frequency domain spectral analysis: low-frequency power (LF; 0.04–0.15 Hz), high-frequency power (HF; 0.15–0.4 Hz), and the LF/HF ratio. HF is considered an index of parasympathetic modulation, whereas LF is often proposed to reflect both sympathetic and parasympathetic activity [
The subjects were seated in a comfortable chair in a sound-attenuated room. They were required to watch a Charlie Chaplin movie displayed on a computer screen (Mitsubishi, 22-inch CRT monitor) without paying attention to the auditory stimuli. The auditory stimuli consisting of sounds at 85 dB SPL and 1000 Hz were delivered via MDR-D777 headphones (Sony, Tokyo, Japan). Deviant tones lasting 100 ms were presented randomly, interspersed with standard tones lasting 50 ms (probabilities: 10% and 90%, respectively). A total of 750 auditory stimuli were presented with an interstimulus interval of 500 ms. The experiment took about 10 min to complete. The stimuli were generated using E-Prime software (Psychology Software Tools, Pittsburgh, PA, USA).
EEG recording was synchronized to stimulus presentation onset by E-Prime. EEG data was recorded using 64 Ag-AgCl electrodes mounted on a Quik-Cap using an extended 10–20 placement scheme. The ground electrode was placed on the forehead and the physically linked reference electrodes were attached to both mastoids. The vertical electrooculogram (EOG) channels were positioned above and below the left eye, and the horizontal EOG channels were recorded from the outer canthus of each eye. The electrode impedance was kept below 5 kΩ. EEG data were assessed using a NeuroScan SynAmps amplifier (Compumedics USA, Charlotte, NC, USA) with a sampling rate of 1000 Hz and a 0.1–100 Hz band pass filter.
The recorded EEG data were preprocessed using CURRY 7 (Compumedics USA). A trained person with no prior information regarding the data origin removed gross artifacts such as movement artifacts by visual inspection. Artifact rejection related to eye movement or eye blinks was conducted using the mathematical procedure implemented in the preprocessing software of CURRY 7. The data were filtered using a 0.1–30 Hz bandpass filter and epoched from 100 ms pre-stimulus to 600 ms post-stimulus. The epochs were subtracted from the average value of the pre-stimulus interval for baseline correction. If any remaining epochs contained significant physiological artifacts (amplitude exceeding±75 μV) in any site over 62 electrodes, they were excluded from further analysis. Only artifact-free epochs were averaged across trials and subjects for ERP analysis. The MMN wave was generated by subtracting the standard ERP wave from the deviant ones. MMN amplitude was measured as the mean voltage between 130 and 280 ms at nine electrode sites (F3, Fz, F4, FC3, FCz, FC4, C3, Cz, and C4), because the frontocentral electrodes show larger MMN amplitudes. The time window for MMN amplitudes was based on visual inspection of the grand-averaged waveforms at FCz. The number of epochs of deviant and standard stimuli used in the analysis did not significantly differ between patients with schizophrenia or bipolar disorder and healthy controls (deviant stimuli: 65.96±6.55 vs. 66.90±7.10 vs. 67.60±9.13, p=0.739, standard stimuli: 589.56±60.20 vs. 596.47±62.96 vs. 604.56±82.07, p=0.733, respectively).
A chi-squared test and one-way analysis of variance (ANOVA) were employed to examine differences in demographic variables between the three groups. Preliminary analyses identified a non-normal distribution for HRV-LF and LF/HF ratio in the bipolar disorder group and for CTQ-sexual abuse in the healthy controls. As a result, log transformation was performed on these variables. Furthermore, MMN amplitudes at the nine electrodes were averaged to represent and interpret the results more suitably than using each electrode. A partial Pearson’s correlation analysis was conducted between QSF and other variables, including psychological measures, HRV, and MMN. For the patient groups, variables such as sex, age, duration of illness, and medication (i.e., equivalent doses of chlorpromazine and sodium valproate) were chosen as covariates based on the previous studies [
Comparisons of demographic and psychological characteristics between the three groups are shown in
The ANOVA revealed no significant differences in HRV between the three groups. The average MMN amplitude for all nine channels for each group are shown in
Results of the hierarchical regression model in each group are presented in
This study aimed to identify psychological and neurophysiological factors that could predict social functioning in patients with schizophrenia and bipolar disorder, as well as in healthy controls. Overall, childhood trauma, especially emotional neglect, was a significant predictor of social functioning in schizophrenia, while HRV-HF was a significant predictor of functional outcome in bipolar disorder. In healthy controls, social functioning was significantly predicted by MMN. Also, CTQ-emotional neglect and HRV-HF significantly predicted functional outcome in all of eighty-two subjects after controlling for the diagnostic criteria.
Firstly, the social functioning of schizophrenia patients was negatively associated with HRV-LF/HF ratio and CTQ-emotional neglect. Further analysis revealed that only CTQ-emotional neglect was a significant predictor of social functioning. The increased HRV-LF/HF indicates the higher sympathetic nervous activity in comparison to parasympathetic nervous activity, which may result in less flexible autonomic system [
In patients with bipolar disorder, the social functioning was significantly associated with HRV-HF. The HRV-HF remained a significant predictor of functional outcome in bipolar disorder. HRV-HF has been regarded as a measure of cardiac parasympathetic neural activity [
However, the result of our study did not show any significant differences in HRV parameters between the three groups, which is contrary to previous studies reporting that HRV in bipolar disorder is reduced relative to that in healthy controls [
In healthy controls, social functioning was significantly associated with childhood trauma-emotional neglect, empathy, and MMN. Among those variables, MMN predicted functional outcomes in healthy controls. A significant association between emotional neglect and social functioning indicates that emotional support and security from a caregiver in childhood is important in acquiring social skills and forming relationships with others. Emotional neglect in childhood is known to influence social dysfunction in adulthood through the oxytocin level and attachment system in the general population [
After controlling for the diagnostic criteria, CTQ-emotional neglect and HRV-HF still significantly predicted social functioning in all of eighty-two subjects. This result shows that early traumatic events strongly affect later functional outcome. The main implication for caregivers that can be drawn from this finding is the importance of emotional support and security during early childhood in preventing impaired functioning during adulthood. Also, HRV-HF could be used as a biological marker of social functioning level regardless of whether they are clinical or healthy control. Given that HRV-HF is an indicator of emotional self-regulation [
Some limitations of the current study should be noted. Firstly, as subjective functioning measures were used, there is the possibility that patients’ self-report would not reflect the objective evaluation of a clinician. Second, the sample size was relatively small, thus further a study with larger sample is needed to generalize our results. To conclude, our results suggest that social functioning in patients with schizophrenia and bipolar disorder, as well as healthy controls, could be associated with different neurophysiological and psychological factors. Additionally, emotional neglect in childhood and HRV-HF were significant predictors of functional outcome irrespective of what group they are, thus these factors should be regarded as important markers of social functioning.
The online-only Data Supplement is available with this article at
This work was supported by a grant from the Korea Science and Engineering Foundation (KOSEF), funded by the Korean government (NRF2018R1A2A2A05018505).
The authors have no potential conflicts of interest to disclose.
Conceptualization: Seung-Hwan Lee, Yourim Kim. Data curation: Yourim Kim. Formal analysis: Sungkean Kim, Yourim Kim. Funding acquisition: Seung-Hwan Lee. Investigation: Aeran Kwon, Dongil Min. Methodology: Min Jin Jin, Sungkean Kim, Yourim Kim. Supervision: Seung-Hwan Lee. Writing—original draft: Yourim Kim. Writing—review & editing: Aeran Kwon, Dongil Min, Min Jin Jin.
Demographic characteristics of all study participants
Schizophreniaa (N=27) | Bipolar disorderb (N=30) | Healthy controlsc (N=25) | p | Post-hoc (LSD) | |
---|---|---|---|---|---|
Age (years) | 42.48±11.86 | 39.70±12.61 | 42.48±12.60 | 0.620 | |
Sex | 0.704 | ||||
Male | 11 (40.7) | 10 (33.3) | 11 (44.0) | ||
Female | 16 (59.3) | 20 (66.7) | 14 (56.0) | ||
Education (years) | 13.52±2.56 | 12.33±3.71 | 14.24±3.27 | 0.092 | |
Number of hospitalizations | 3.22±3.86 | 4.34±10.66 | 0.608 | ||
Duration of illness (years) | 11.22±7.70 | 10.10±6.81 | 0.562 | ||
Onset age (years) | 31.22±10.80 | 29.70±11.45 | 0.609 | ||
Dosage of medication (CPZ equivalent, mg) | 518.58±657.94 | 343.33±475.04 | 0.251 | ||
Dosage of medication (equivalent to sodium valproate dose, mg) | 83.33±250.00 | 752.57±443.20 | <0.001 | ||
PANSS | |||||
Positive | 13.78±8.49 | 9.37±3.01 | 0.015 | ||
Negative | 15.41±4.85 | 9.47±3.75 | <0.001 | ||
General | 30.63±10.32 | 24.40±6.72 | 0.011 | ||
Total | 59.81±21.59 | 43.23±11.87 | 0.001 | ||
YMRS | 5.86±6.73 | ||||
Verbal fluency | 15.00±5.21 | 15.07±5.25 | 19.40±6.12 | 0.006 | a<c, b<c |
KAVLT-trial 5 | 8.48±2.82 | 10.47±2.92 | 11.52±1.69 | <0.001 | a<b, a<c |
KAVLT-delayed recall | 6.15±3.70 | 8.10±3.73 | 9.96±1.81 | <0.001 | a<b<c |
KAVLT-delayed recognition | 10.44±2.98 | 11.77±2.66 | 13.92±1.26 | <0.001 | a<b<c |
BES | 67.72±8.47 | 70.97±10.75 | 73.08±9.17 | 0.103 | |
SATMC | 8.73±5.02 | 12.20±3.99 | 13.56±4.69 | <0.001 | a<c, b<c |
CTQ | |||||
Emotional abuse | 9.11±4.85 | 10.30±5.41 | 8.00±4.20 | 0.225 | |
Physical abuse | 8.63±3.62 | 11.03±5.61 | 8.04±2.78 | 0.024 | a<b, c<b |
Sexual abuse | 8.26±3.83 | 7.90±3.84 | 6.04±2.01 | 0.046 | c<a, c<b |
Emotional neglect | 11.00±5.14 | 13.53±6.10 | 10.92±3.67 | 0.099 | |
Physical neglect | 8.48±3.20 | 9.80±4.05 | 7.68±3.25 | 0.087 | |
HRV | |||||
LF | 209.50±214.66 | 187.03±273.17 | 275.53±262.59 | 0.416 | |
HF | 174.75±209.06 | 169.29±226.63 | 129.40±117.24 | 0.656 | |
LF/HF ratio | 2.18±2.02 | 2.46±3.36 | 2.62±1.82 | 0.817 | |
MMN (total average) | -1.51±0.98 | -2.12±1.38 | -3.33±1.76 | <0.001 | c<a, c<b |
QSF | 49.33±9.34 | 48.70±11.19 | 55.20±6.90 | 0.027 | a<c, b<c |
CPZ: chlorpromazine, PANSS: Positive and Negative Syndrome Scale, YMRS: Young Mania Rating Scale, KAVLT: Korean Auditory Verbal Learning Test, BES: Basic Empathy Scale, SATMC: social attribution task-multiple choice, CTQ: childhood trauma questionnaire, HRV: heart rate variability, LF: low frequency, HF: high frequency, MMN: mismatch negativity, QSF: questionnaire of social functioning
Partial Pearson’s correlations between QSF and neurocognition, social cognition, childhood trauma, HRV, and MMN (Bootstrapping=5000)
Patients with schizophrenia (N=27) | r | p | Healthy control subjects (N=25) | r | p |
---|---|---|---|---|---|
QSF–Verbal Fluency | 0.209 | 0.351 | QSF–Verbal Fluency | 0.112 | 0.609 |
QSF–KAVLT trial 5 | 0.173 | 0.441 | QSF–KAVLT trial 5 | 0.083 | 0.705 |
QSF–KAVLT recall | 0.241 | 0.281 | QSF–KAVLT recall | -0.051 | 0.818 |
QSF–KAVLT recognition | 0.141 | 0.531 | QSF–KAVLT recognition | -0.327 | 0.128 |
QSF–BES total | 0.418 | 0.053 | |||
QSF–SATMC | 0.203 | 0.364 | QSF–SATMC | 0.043 | 0.844 |
QSF–CTQ_EA | -0.089 | 0.694 | QSF–CTQ_EA | 0.097 | 0.659 |
QSF–CTQ_PA | 0.108 | 0.632 | QSF–CTQ_PA | -0.109 | 0.622 |
QSF–CTQ_SA | 0.139 | 0.537 | QSF–CTQ_SA | -0.303 | 0.160 |
QSF–CTQ_PN | -0.270 | 0.224 | QSF–CTQ_PN | 0.074 | 0.739 |
QSF–HRV LF | -0.083 | 0.714 | QSF–HRV LF | 0.070 | 0.750 |
QSF–HRV HF | 0.243 | 0.276 | QSF–HRV HF | -0.180 | 0.411 |
QSF–HRV LF/HF | 0.109 | 0.619 | |||
QSF–total MMN | 0.190 | 0.396 | |||
QSF–Verbal Fluency | 0.067 | 0.750 | QSF–Verbal Fluency | 0.155 | 0.174 |
QSF–KAVLT trial 5 | -0.295 | 0.153 | QSF–KAVLT trial 5 | 0.054 | 0.639 |
QSF–KAVLT recall | 0.097 | 0.645 | |||
QSF–KAVLT recognition | 0.249 | 0.231 | |||
QSF–BES total | 0.145 | 0.490 | |||
QSF–SATMC | -0.275 | 0.183 | QSF–SATMC | -0.022 | 0.846 |
QSF–CTQ_EA | -0.278 | 0.179 | QSF–CTQ_EA | -0.199 | 0.078 |
QSF–CTQ_PA | -0.250 | 0.229 | QSF–CTQ_PA | -0.156 | 0.169 |
QSF–CTQ_SA | -0.379 | 0.062 | QSF–CTQ_SA | -0.178 | 0.117 |
QSF–CTQ_EN | -0.111 | 0.597 | |||
QSF–CTQ_PN | -0.101 | 0.630 | |||
QSF–HRV LF | 0.285 | 0.167 | QSF–HRV LF | 0.171 | 0.131 |
QSF–HRV LF/HF | -0.247 | 0.233 | QSF–HRV LF/HF | -0.045 | 0.694 |
QSF–total MMN | -0.186 | 0.373 | QSF–total MMN | -0.217 | 0.055 |
The rows shaded in gray show the distinction among separate domains. The bold type highlights significant p-values (p=0.05). QSF: questionnaire of social functioning, KAVLT: Korean auditory verbal learning test, CTQ: childhood trauma questionnaire, EA: emotional abuse, PA: physical abuse, SA: sexual abuse, EN: emotional neglect, PN: physical neglect, BES: basic empathy scale, SATMC: social attribution taskmultiple choice, HRV: heart rate variability, LF: low frequency, HF: high frequency, MMN mismatch negativity