Hostname: page-component-848d4c4894-8kt4b Total loading time: 0 Render date: 2024-06-24T17:39:57.084Z Has data issue: false hasContentIssue false

Moment-to-moment affective dynamics in schizophrenia and bipolar disorder

Published online by Cambridge University Press:  07 August 2023

Suzanne Ho-wai So*
Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
Anson Kai Chun Chau
Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China Institute of Health Equity, The Chinese University of Hong Kong, Hong Kong, China
Lawrence Kin-hei Chung
Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
Chung-ming Leung
Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
George H.C. Chong
Department of Clinical Psychology, Kwai Chung Hospital, Hong Kong, China
Wing Chung Chang
Department of Psychiatry, The University of Hong Kong, Hong Kong, China State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
Arthur D.P. Mak
Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
Sandra S.M. Chan
Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
Sing Lee
Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong, China
Iris E. Sommer
Department of Psychiatry, University Medical Centre Groningen, The Netherlands
Corresponding author: Suzanne Ho-wai So; Email:



Affective disturbances in schizophrenia and bipolar disorder may represent a transdiagnostic etiological process as well as a target of intervention. Hypotheses on similarities and differences in various parameters of affective dynamics (intensity, successive/acute changes, variability, and reactivity to stress) between the two disorders were tested.


Experience sampling method was used to assess dynamics of positive and negative affect, 10 times a day over 6 consecutive days. Patients with schizophrenia (n = 46) and patients with bipolar disorder (n = 46) were compared against age-matched healthy controls (n = 46).


Compared to controls, the schizophrenia group had significantly more intense momentary negative affect, a lower likelihood of acute changes in positive affect, and reduced within-person variability of positive affect. The bipolar disorder group was not significantly different from either the schizophrenia group or the healthy control group on any affect indexes. Within the schizophrenia group, level of depression was associated with weaker reactivity to stress for negative affect. Within the bipolar disorder group, level of depression was associated with lower positive affect.


Patients with schizophrenia endured a more stable and negative affective state than healthy individuals, and were less likely to be uplifted in response to happenings in daily life. There is little evidence that these affective constructs characterize the psychopathology of bipolar disorder; such investigation may have been limited by the heterogeneity within group. Our findings supported the clinical importance of assessing multiple facets of affective dynamics beyond the mean levels of intensity.

Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
© The Author(s), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association


Schizophrenia and bipolar disorder, presented as distinct and severe mental disorders, share important similarities [Reference Grove, Tso, Chun, Mueller, Taylor and Ellingrod1, Reference Reininghaus, Böhnke and Hosang2]. There is a high level of comorbidity of psychotic and affective symptoms across both disorders [Reference Buckley, Miller, Lehrer and Castle3Reference Upthegrove, Marwaha and Birchwood8]. Common DNA variants and brain changes that appear to influence the risk of both schizophrenia and bipolar disorder have been identified [Reference Purcell and Wray9, Reference Xu, Zhang and Hochwalt10], and an individual’s risk of suffering from either schizophrenia or bipolar disorder is elevated if a first-degree relative has one of the disorders [Reference Lichtenstein, Yip and Björk11], indicating a significant overlap in genetic factors underlying the two disorders [Reference Craddock and Owen12]. Therefore, it would be of theoretical and clinical value to examine similarities and differences in psychological processes across disorders [Reference Harvey, Watkins, Mansell and Shafran13, Reference Mansell, Harvey, Watkins and Shafran14].

Affective instability encompasses the following key dimensions: affective valence, affect amplitude/intensity, rapid affect shifting/oscillation, low reactivity threshold to environmental triggers, and the perceived capacity to control affect [Reference Marwaha, He and Broome15, Reference Renaud, Corbalan and Beaulieu16]. While affective instability is most well-researched in conditions where it is a core symptom, such as borderline personality disorder [Reference Marwaha, He and Broome15, Reference Koenigsberg17Reference Santangelo, Reinhard and Mussgay19], it is frequently documented by clinicians of individuals with bipolar disorder, personality disorder, and schizophrenia [Reference Patel, Lloyd and Jackson20]. Across disorders, implications of affective instability on clinical outcomes such as poor functioning and quality of life, prolonged hospitalization, increased use of healthcare services, and suicidality have been reported [Reference Patel, Lloyd and Jackson20Reference Marwaha, Parsons, Flanagan and Broome24].

Abnormalities in affective dynamics, assessed by structured interviews or questionnaires such as Affective Lability Scale (ALS) [Reference Harvey, Greenberg and Serper25] and Affective Intensity Measure (AIM) [Reference Larsen, Diener and Emmons26], are strongly implicated in schizophrenia and bipolar disorder. Despite the fact that schizophrenia-spectrum disorder is sometimes named “non-affective psychosis,” high negative affect and low positive affect are common among individuals with this diagnosis [Reference Horan, Blanchard, Clark and Green22, Reference Yee, Strauss, Allen, Haase, Kimhy and Mittal27]. It has been replicated that mood disturbances and instability predate and maintain psychotic symptoms [Reference Birchwood28Reference Hoegh, Melle and Aminoff33]. Among individuals with liability to develop schizophrenia, it has been shown that individuals with negative schizotypy had reduced trait positive affect, whereas those with both negative and positive schizotypy had heightened trait negative affect and diminished emotional clarity [Reference Li, Fung, Moore and Martin34]. Patients with bipolar disorder (both types I and II) are characterized by an increase in mood intensity and lability [Reference Angst, Gamma and Endrass35Reference Judd, Schettler and Akiskal39]. Notably, mood intensity and lability are evident even among euthymic or at-risk individuals [Reference Henry, Van den Bulke and Bellivier37, Reference Bonsall, Wallace-Hadrill, Geddes, Goodwin and Holmes40, Reference Hofmann and Meyer41].

While affective dynamics may represent a transdiagnostic risk factor for psychopathology in general, little evidence has specified the nuanced similarities and differences in patterns of these dynamics across specific forms of psychopathology [Reference Patel, Lloyd and Jackson20, Reference Broome, Saunders, Harrison and Marwaha42, Reference Fernandez, Jazaieri and Gross43]. This is especially important for severe mental disorders such as schizophrenia and bipolar disorder, where affective disturbances are common, complex, and persisting, and have been suggested as targets for treatment [Reference Henry, Van den Bulke and Bellivier37, Reference Marwaha, Broome, Bebbington, Kuipers and Freeman44]. In addition, it has been argued that research on the affectivity of schizophrenia has emphasized more on observed expressions than subjective affective experiences [Reference Myin-Germeys, Delespaul and DeVries45], and that of bipolar disorder has focused on mood periods rather than momentary affect [Reference Taylor, Ulrichsen, Young and Strawbridge46]. Therefore, examination of various dimensions of affective instability across disorders using time-intensive methods such as experience sampling methodology (ESM) would help to advance this area of research [Reference Houben, Van Den Noortgate and Kuppens47Reference Trull, Lane, Koval and Ebner-Priemer49].

ESM is a diary method that records the moment-by-moment context and subjective experiences in the flow of daily life [Reference aan het Rot, Hogenelst and Schoevers50Reference Shiffman, Stone and Hufford55]. ESM provides a prospective and ecologically valid representation of how experiences unfold and interact, avoiding retrospective recall bias. This is best-suited for assessing affective experiences, which are brief and can shift rapidly, as opposed to moods, which are more static and prolonged [Reference LeDoux56]. ESM questionnaires can provide a fine-grained record of the following parameters of affective dynamics within and between individuals and groups [Reference Trull, Lane, Koval and Ebner-Priemer49, Reference Jahng, Wood and Trull57Reference Wichers59]: (i) valence and intensity of affect, (ii) successive/acute changes in affect, (iii) overall variability of affect, (iv) affective reactivity to stress, and (v) affective modulation. Unlike major depressive disorder, where merely the mean level of negative affect is implicated [Reference Dejonckheere, Mestdagh and Houben60], the affective dynamics of schizophrenia and bipolar disorder may be more complex; hence, comparisons on mean levels of positive affect (PA) and negative affect (NA) as well as the full range of affective instability subcomponents will be more informative in predicting clinical outcomes [Reference Santangelo, Reinhard and Mussgay19, Reference Trull, Lane, Koval and Ebner-Priemer49, Reference Kashdan and Rottenberg61Reference van de Leemput, Wichers and Cramer63].

ESM studies in schizophrenia reported that patients experienced more intense and more variable NA, and less intense and less variable PA, than controls [Reference Myin-Germeys, Delespaul and DeVries45, Reference Oorschot, Lataster and Thewissen64, Reference Vakhrusheva, Khan and Chang65]. Among patients with schizophrenia, NA not only sustain each other (e.g., sadness leading to diminished happiness [Reference Badal, Parrish, Holden, Depp and Granholm66]) but also co-occur with PA, leading to difficulty in mood regulation [Reference Raugh and Strauss67Reference Visser, Esfahlani, Sayama and Strauss69]. In terms of affective reactivity to stress, patients with schizophrenia have been shown to report more NA (and less PA) following stressful daily-life events than healthy individuals [Reference Lataster, Valmaggia, Lardinois, van Os and Myin-Germeys70Reference Reininghaus, Kempton and Valmaggia74]. On the other hand, they fail to maintain or increase the intensity of PA over time – a deficit that has been suggested to be associated with anhedonia [Reference Strauss, Esfahlani and Granholm75].

Several ESM studies for bipolar disorder were conducted with non-clinic samples, where the psychometric risk for bipolar disorder was associated with more intense PA and NA, greater variability of NA, and greater affective reactivity to daily-life stress [Reference Kim76Reference Sperry and Kwapil78]. Variability and successive changes in NA predicted the subsequent emergence of bipolar spectrum disorders 3 years later [Reference Sperry, Walsh and Kwapil62]. The anecdotal ESM studies that involved patients with bipolar disorder reported higher NA and lower PA than healthy individuals, greater affect variability, and comparable affective reactivity to daily-life stress except for patients with depressive symptoms [Reference Havermans, Nicolson, Berkhof and DeVries79, Reference Schwartz, Schultz, Reider and Saunders80]. So far, one ESM study [Reference Myin-Germeys, Peeters and Havermans71] had compared the two clinical groups, which was on affective reactivity to stress only. They reported that while daily-life stress triggered an increase in NA and a decrease in PA in patients with psychosis, it only triggered a decrease in PA in the bipolar disorder group.

Using ESM that can provide unique time-sensitive information about affective dynamics not captured by questionnaires [Reference Solhan, Trull, Jahng and Wood81], the present study aimed to compare various parameters of affective instability in schizophrenia and bipolar disorder.

The key hypotheses are as follows:

  1. 1. Compared to healthy controls, the intensity of momentary NA will be higher in the two clinical groups, whereas the intensity of momentary PA will be lower in the schizophrenia group only

  2. 2. Compared to healthy controls, successive/acute changes and overall variability in NA will be greater in the two clinical groups, whereas successive/acute changes and overall variability in PA will be greater in the bipolar disorder group only

  3. 3. Compared to healthy controls, momentary stress will lead to reduced PA in both clinical groups, and increased NA in the schizophrenia group only

In view of the accumulating evidence that affective dynamics may be differentially associated with symptoms, especially among individuals with schizophrenia [Reference Cowan, Mittal, Allen, Gold and Strauss82Reference Westermann, Grezellschak, Oravecz, Moritz, Lüdtke and Jansen86], we also explored the association between specific parameters of affective dynamics and severity of symptoms within the two clinical groups respectively.


This project was approved by the Joint Chinese University of Hong Kong – New Territories East Clinical Ethics Committee (CRE-2013.652-T, 2015.685-T and 2020.477), the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW15–194), and the Survey and Behavioral Research Committee (SBRE-19-788). All participants provided written informed consent for study participation.


The sample consisted of three groups of adults (age range: 18–64). The inclusion criterion of the schizophrenia group (“SCZ”) was a diagnosis of schizophrenia, whereas the inclusion criterion of the bipolar disorder group (“BD”) was a diagnosis of bipolar I or II disorder. Diagnoses were individually assessed by the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, fourth edition (SCID-IV) [Reference So, Kam, Leung, Chung, Liu and Fong87]. In order to obtain clearly defined diagnostic groups, individuals who had schizoaffective disorder or a comorbid schizophrenia and bipolar disorder were excluded from the study. Age-matched healthy controls (“HC”), who reported no psychiatric diagnoses (confirmed by SCID), were recruited. Exclusion criteria for all groups were intellectual disability, substance-induced psychosis, organic brain syndrome, and a history of brain injury.

The clinical sample was referred by out-patient psychiatric clinics, with suitability of study participation being confirmed by the care teams. Healthy individuals were recruited through a university subject pool, public channels including social media, and dissemination of leaflets. A proportion of the clinical sample was shared with previous studies [Reference Leung, So and Kwok88Reference So, Chung and Tse90], but the analysis of the present study was novel. All healthy controls were new.

For sample size calculation, G*power suggested a total sample size of 159 for 3-group comparisons with a medium effect size (f = 0.25, power = 0.80, alpha = 0.05). On the contrary, since multiple ESM observations are nested within an individual, Hox [Reference Hox, Moerbeek and Van de Schoot91] suggested the “50/20 rule” for testing cross-level interactions of nested data, where a minimum of 20 ESM measurements nested within a minimum of 50 participants in total would be adequately powered for group differences in ESM variables.


Experience sampling method

All participants were required to complete repeated measures using a mobile phone app developed by our research team [Reference Leung, So and Kwok88]. The app was installed either on their own mobile phone or on an iPod Touch borrowed from our team. The app emitted a signal at 10 random moments during the day over 6 consecutive days. Upon each signal, participants were probed to answer the same set of questions that concerned their momentary affective experiences, contextual information, and perceived stress of the event that had happened since the last signal. The questionnaire was only active for 15 min after the signal, and successive signals were at least 30 min apart. Except for contextual information, all other ESM items were rated on 7-point Likert scales (1 = not at all; 7 = very). Only participants who completed one-third of the ESM entries were included in data analysis [Reference Palmier-Claus, Myin-Germeys and Barkus92].

Three items on PA (happy, relaxed, contented) and three items on NA (irritated, low, nervous) were included. As these items have been shown to represent PA and NA reliably in previous studies [Reference Leung, So and Kwok88, Reference Chan, So, Mak, Siah, Chan and Wu93, Reference So, Peters, Swendsen, Garety and Kapur94], we reported intensity of momentary PA and NA by averaging the three respective items per time point [Reference Myin-Germeys, Peeters and Havermans71]. In our sample, the within-person reliabilities of the PA index score and the NA index score were good (SCZ = 0.74, BD = 0.80, HC = 0.85) and satisfactory (SCZ = 0.68, BD = 0.61, HC = 0.73), respectively. The between-person reliabilities of the PA index score and the NA index score were excellent (SCZ = 0.98, BD = 0.97, HC = 0.96) and good (SCZ = 0.92, BD = 0.93, HC = 0.85), respectively [Reference Geldhof, Preacher and Zyphur95].

Following Jahng et al. [Reference Jahng, Wood and Trull57] and Sperry and Kwapil [Reference Sperry and Kwapil96], successive changes and acute changes in PA and NA were calculated using the adjusted squared successive differences (ASSD) and probabilities of acute change (PAC), respectively. ASSD captures the moment-to-moment fluctuations in affect, taking into consideration the within-person variability and temporal dependency (i.e., autocorrelation). The formula for ASSD calculation is shown below [Reference Jahng, Wood and Trull57, Reference Sperry and Kwapil96]:

$$ {ASSD}_{i+1}={\left(\frac{\left({x}_{i+1}-{x}_i\right)}{{\left[\frac{t_{i+1}-{t}_i}{Mdn\Big({t}_{i+1}-{t}_{i\Big)}}\right]}^{\lambda }}\right)}^2 $$

Lambda (λ) was computed using non-parametric smoothing regressions that minimize the sum of squares between successive differences, which were adjusted by the median (Mdn) of the time intervals. In the calculation of the successive differences, the first ESM entry of each day was treated as missing, where Mdn time for all intervals = 71.1 mins, λ for NA = 0.38 and λ for PA = 0.02.

PAC determines if the momentary fluctuation in affect is considered as large relative to the ASSD. Following Jahng et al. [Reference Jahng, Wood and Trull57] and Sperry and Kwapil [Reference Sperry and Kwapil96], ASSDs above the 90th percentile were considered as acute (coded as 1), and ASSDs below that cutoff were coded as 0.

Overall variability was represented by the within-person standard deviation in PA or NA item responses for each participant respectively [Reference Dejonckheere, Mestdagh and Houben60]. Affective reactivity to stress was calculated based on Myin-Germeys et al. [Reference Myin-Germeys, Peeters and Havermans71]. At each momentary questionnaire, participants were asked to identify the key activity between the current and preceding beeps, and to evaluate their subjective stress level with the question “How stressful was the activity?” [Reference Chan, So, Mak, Siah, Chan and Wu93]. Therefore, within-moment associations between activity stress and PA and NA could be understood as the lagged effect of stress (experienced between two moments) on affect at the current moment [Reference Myin-Germeys, Peeters and Havermans71, Reference Myin-Germeys, van Os, Schwartz, Stone and Delespaul72].

Clinical rating scales

The schizophrenia group completed the Positive and Negative Syndrome Scale (PANSS) [Reference Kay, Fiszbein and Opler97] and the Calgary Depression Scale for Schizophrenia (CDSS) [Reference Addington, Addington and Schissel98], which measured the severity of psychotic and depressive symptoms, respectively. The bipolar disorder group completed the Young Mania Rating Scale (YMRS) [Reference Biggs, Ziegler and Meyer99] and the Montgomery-Asberg Depression Scale (MADRS) [Reference Montgomery and Åsberg100], which assessed levels of manic and depressive symptoms, respectively.


Upon informed consent, participants went through a structured interview, consisting of the SCID, PANSS, and CDSS (for SCZ), YMRS and MADRS (for BD), conducted by a trained and supervised graduate-level psychologist. After the interview, participants were guided through the ESM assessment so that they felt confident completing the subsequent assessment on their own. During the ESM assessment period, the experimenter contacted the participant occasionally to encourage assessment compliance and to provide technical support.

Statistical analysis

Group differences in intensity, ASSD, and PAC of PA and NA were tested with Group as a categorical independent variable in the multilevel regression models [Reference Jahng, Wood and Trull57], as ESM data involve momentary observations (level 1) nested within each participant (level 2) [Reference Kimhy, Myin-Germeys, Palmier-Claus and Swendsen101]. As PAC of each moment is a binary variable, group differences were tested using a logistical multilevel model. For overall variability, ANOVA tests were conducted to compare groups on within-person SD of PA and NA, respectively. For affective reactivity to stress, the association between level of stress and affect was estimated by multilevel regression models, with momentary stress level as independent variable and momentary PA and NA as outcome variables in separate models. Group comparisons in affective reactivity were examined by multilevel models where Group, Stress, and Group × Stress interaction terms were entered as independent variables, and their random effects modeled. Group differences in affective reactivity would be implicated by the statistical significance of the Group × Stress interaction term. Three-group comparisons were followed by pairwise comparisons on each variable.

As exploratory analyses, person-level correlation and regression were tested to examine associations between affective dynamics and severity of symptoms within each clinical group. All analyses were conducted with JAMOVI v [102].


A total of 61 patients with schizophrenia and 65 patients with bipolar disorder were eligible and recruited for the study, among whom 46 (75.4%) and 46 (70.8%) met the ESM completion rate threshold, respectively. An equal number of healthy controls were randomly selected from our existing datasets (age and gender stratified), making a final sample of 138 participants (SCZ = 46, BD = 46, HC = 46) for data analysis.

Sample characteristics

Demographic characteristics of the sample are presented in Table 1. The three groups were matched on age and gender (ps > 0.050). HC had a higher education level than the two clinical groups (SCZ vs HC: t(87.93) = 4.93, p < 0.001; BD vs HC: t(89.30) = 3.11, p = 0.002). The highest income category was most common in HC, whereas the lowest income category was most common in SCZ.

Table 1. Sample characteristics

Abbreviations: BD, bipolar disorder; HC, healthy controls; SCZ, schizophrenia.

The SCZ group consisted of patients with a SCID diagnosis of schizophrenia (100%). The average duration of illness was 14.18 years (SD = 12.13, range = 1–44). Mean scores of clinical rating scales were as follows: PANSS positive score = 17.52 (SD = 6.70, range = 9–32), PANSS negative score = 10.72 (SD = 3.86, range = 7–23), PANSS general score = 25.09 (SD = 6.74, range = 16–45), PANSS total score = 53.33 (SD = 13.55, range = 33–83), CDSS total score = 3.24 (SD = 3.20, range = 0–12).

The BD group had an average duration of illness of 11.16 years (SD = 10.80, range = 0–40). The majority of the group (n = 33, 71.7%) had a diagnosis of bipolar I disorder, whereas 13 patients (28.3%) had bipolar II disorder. Eighteen patients (39.1%) were in an active episode at the time of assessment (mixed: n = 7, depressive: n = 3, manic/hypomanic: n = 8). Mean scores of clinical rating scales were as follows: YMRS = 2.16 (SD = 3.94, range = 0–15), MADRS = 6.77 (SD = 7.91, range = 0–29).

Diagnostic interviews revealed that none of the healthy controls reached the diagnostic threshold for any DSM-IV psychiatric disorders. As shown in Table 2, there was a significant group difference in ESM compliance, with HC completing more entries than SCZ (t(135) = −1.93, p = 0.056, d = 0.40) and BD (t(135) = −2.59, p = 0.011, d = 0.54).

Table 2. Indicators of affective dynamics across groups

Abbreviations: BD, bipolar disorder; HC, healthy controls; NA, negative affect; PA, positive affect; SCZ, schizophrenia.

Group comparisons of intensity of momentary affect (Hypothesis 1)

There was a marginally significant 3-group difference in NA (F(2, 138.06) = 2.89, p = 0.059, ηReference Reininghaus, Böhnke and Hosang 2=0.04). Pairwise comparisons revealed that the level of NA was significantly higher in SCZ than HC (t(137.86) = 2.40, p = 0.018, d = 0.41). There was no significant difference in NA between BD and HC, or between SCZ and BD (ps > 0.050).

The momentary level of PA was not significantly different across groups (p > 0.050).

Group comparisons of instability and overall variability of affect (Hypothesis 2)

There was a marginally significant three-group difference in PAC of PA (Χ Reference Reininghaus, Böhnke and Hosang 2(2) = 5.77, p = 0.056, V = 0.14). Pairwise comparisons revealed that PAC of PA was significantly lower in SCZ than HC (Z = -2.30, p = 0.021, OR = 0.47). There was no significant difference in PAC of PA between BD and HC, or between SCZ and BD (ps > 0.050). The mean ASSDs of PA and NA, and the mean PAC of NA were not significantly different across groups (ps > 0.050).

There was a significant three-group difference in variability of PA (F(2, 135) = 3.52, p = 0.032, ηReference Reininghaus, Böhnke and Hosang 2=0.05). Pairwise comparisons revealed that variability of PA was significantly lower in SCZ than HC (t(135) = −2.60, p = 0.010, d = 0.54). Variability of NA was not significantly different across groups (p > 0.050).

Group comparisons of affective reactivity to stress (Hypothesis 3)

As shown in Table 2, there was no overall group difference in momentary level of event-related stress (p > 0.050).

Across the entire sample, momentary level of event-related stress was positively associated with NA (B = 0.25, p < 0.001) and negatively associated with PA (B = -0.18, p < 0.001). The effects of Group × Stress interaction on either PA (F(2, 134.38) = 0.44, p = 0.643, ηReference Reininghaus, Böhnke and Hosang 2=0.01) or NA (F(2, 133.24) = 1.44, p = 0.241, ηReference Reininghaus, Böhnke and Hosang 2=0.02) were not significant, indicating no group difference in affective reactivity to stress.

Group comparisons on all affective dynamics are summarized in Figures 1 and 2.

Figure 1. Box plots of affective dynamics across groups. *p < 0.050. BP, bipolar disorder; HC, healthy controls; SCZ, schizophrenia.

Figure 2. Affective reactivity to stress for PA (left) and NA (right) across groups. BP, bipolar disorder; HC, healthy controls; SCZ, schizophrenia.

Exploratory analyses: Relationships between affective dynamics and symptom severity

Within the SCZ group, CDSS total score was associated with weaker affective reactivity to stress for NA (stress × CDSS total score interaction: B = -0.02, p = 0.024). PANSS total score and subscores were not significantly correlated with any of the affective indexes (ps > 0.050).

Within the BD group, the MADRS total score and intensity of PA were negatively correlated (rho = −0.44, p = 0.003). Patients diagnosed with Type I versus Type II BD did not differ on any of the affective dynamics (p > 0.050). On the other hand, compared with patients who were not in an active episode (n = 28), patients who were in an active episode (n = 18) had a lower intensity of PA (t(46.17) = −2.79, p = 0.008, d = 0.82), a higher intensity of NA (t(45.95) =2.65, p = 0.011, d = 0.78), and greater PAC for PA (Z = 1.97, p = 0.049, OR = 2.33).


This study compared moment-to-moment affective dynamics between patients with schizophrenia, patients with bipolar disorder, and healthy controls. Using subjective reports on the ESM, various components of affective intensity and instability were operationalized for both PA and NA. This allowed a systematic approach to examining the construct across disorders in context [Reference Marwaha, Broome, Bebbington, Kuipers and Freeman44, Reference Sperry, Walsh and Kwapil62].

Except for affective reactivity to stress, the other three aspects of affective dynamics (intensity, successive/acute changes, and variability) were different across groups. It is noteworthy that these overall differences were mainly driven by differences between the schizophrenia group and healthy controls.

Consistent with previous studies [Reference Myin-Germeys, Delespaul and DeVries45, Reference Oorschot, Lataster and Thewissen64, Reference Vakhrusheva, Khan and Chang65], we found a higher momentary level of NA in the schizophrenia group than controls, even though only one patient in this group was in a major depressive episode. This is an important finding because schizophrenia is sometimes translated as “non-affective psychosis,” denying the prominent presence of affective disturbances [Reference Horan, Blanchard, Clark and Green22, Reference Yee, Strauss, Allen, Haase, Kimhy and Mittal27]. In terms of fluctuations in affect, while successive changes of either PA or NA (represented by ASSD) were not different across groups, a lower PAC was observed in the schizophrenia group than controls. That is, patients were approximately half as likely (OR = 0.47) to experience a large acute fluctuation in PA compared to healthy individuals. In addition, within-person variability of PA was reduced in the schizophrenia group than controls. Recently, there has been considerable debate about the extent to which measures of affective dynamics provide additional information above and beyond mean levels of affect [Reference Dejonckheere, Mestdagh and Houben60]. The multi-faceted differences between patients and controls in the present study suggested that a comprehensive assessment of affective dynamics beyond mean levels of affect may provide clinically relevant information.

Our finding that the schizophrenia group endured a more stable and negative affective state than healthy individuals, which are less likely to be uplifted in response to happenings in daily life, is consistent with Strauss et al.’s [Reference Strauss, Esfahlani and Granholm75] suggestion that patients with schizophrenia are characterized with a deficit in augmenting positive affect. According to Scheffer et al. [Reference Scheffer, Bascompte and Brock103, Reference Scheffer, Carpenter and Lenton104], stronger density and inertia of negative affect are features of a system that is slow to recover from minor perturbations, leading to transitions into negative outcomes.

While the overall scores of the bipolar disorder group fell between the two other groups, there was no significant pairwise difference with either the schizophrenia group or the healthy control group. Post-hoc analyses within the bipolar disorder group revealed nuances in affective dynamics between patients of different episodic statuses. Specifically, patients who were in an active episode were more negative (and less positive) in affect, and had more acute changes in positive affect than those who were not in an active episode. Therefore, the lack of group differences against healthy controls could possibly be attributed to the fact that only a minority of patients in the bipolar disorder group were in an active episode. However, limited by small subgroups and imbalanced group sizes, we did not conduct formal comparisons between bipolar disorder subgroups and healthy controls. This is something that can be further visited by future research.

It is of note that the results for PA and NA were not entirely consistent, where group differences were not significant for the level of PA and fluctuations of NA. This suggests that the affective dynamics for PA and NA should be considered as separate constructs rather than direct opposites to each other, and hence assessing both PA and NA would be more informative. This also informs clinical care, as regulation of both PA and NA warrants therapeutic attention [Reference Garland, Fredrickson, Kring, Johnson, Meyer and Penn105].

For both patients and controls, daily-life stress led to more NA and less PA in the next moment. The level of affective reactivity to stress did not significantly differ across groups. Although the clinical groups were symptomatic, including some who were in an active episode, their subjective levels of stress were not higher than healthy individuals. A possible explanation is that patients tend to engage in fewer activities, which may contribute to the narrow score range of stress and hence limits the effect of stress on affect. Another possibility is that patients are not more sensitive to daily stressors. Muddle et al.’s [Reference Muddle, Jones, Taylor and Jacobsen106] meta-analysis on stress reactivity between patients and controls reported only a small difference and marked heterogeneity. Therefore, affective reactivity to stress in schizophrenia and bipolar disorder remains a topic for further research.

Our exploratory correlation analysis between clinical symptoms and affective dynamics did not lend support to the recent proposition that positive symptoms are related to increased intensity and frequency of affect change whereas negative symptoms are related to increased resistance to change from baseline [Reference Li, Schiffman and Martin85]. It is of note that recent studies that found differential relationships between symptom profiles and specific aspects of affective dynamics tended to have larger samples of patients [Reference Cowan, Mittal, Allen, Gold and Strauss82] and non-patients [Reference Kemp, Sperry, Hernández, Barrantes-Vidal and Kwapil83, Reference Kwapil, Brown, Silvia, Myin-Germeys and Barrantes-Vidal84]. In our study, within both clinical groups alike, severity of depressive symptoms was correlated with affective dynamics. The findings that depression was associated with lower PA (in the BD group) and lower NA reactivity to stress (in the SCZ group) may reflect a state of inertia.

This study has certain limitations. Informed by previous research, we analyzed PA and NA as groups of affective states. Separating the specific affective states, albeit leading to multiple comparisons, may result in a more complete representation of affective dynamics because variability in anxiety, anger, and sadness could potentially be distinct from each other [Reference Lamers, Swendsen and Cui107]. In addition, in view of reports that psychiatric patients may display difficulties in identifying and labelling emotions [Reference Kimhy, Myin-Germeys, Palmier-Claus and Swendsen101, Reference Kimhy, Gill, Brucato, Vakhrusheva, Arndt and Gross108], the use of physiological assessment of affective experiences may supplement the subjective report and provide a more comprehensive understanding of affective dynamics. Lastly, as different clinical rating scales were selected to measure symptom severity for the two clinical groups respectively, the exploratory analyses on the association between symptom severity and affective dynamics could only be conducted within group.

In summary, the present study showed that patients with schizophrenia have elevated NA and reduced variability of PA. Addressing affective dynamic subcomponents across both positive and negative affect may inform illness management and affective regulation efforts.

Author contribution

S.H.S., A.K.C. and I.E.S. conceived of the research question and methodology. L.K.C., C.L., G.H.C., W.C.C., A.D.M., S.S.C., and S.L. coordinated data collection and supervision at various sites. Data management was done by A.K.C. and L.K.C. Data analysis was done by A.K.C., under the supervision of S.H.S. S.H.S came up with the first draft of the paper. All authors were involved in editing the drafts and approved the final version of the manuscript.

Financial support

This work was supported by The Chinese University of Hong Kong (4052054, 4052240) and the Health Bureau (13140131).

Competing interest

The authors declare none.


Grove, TB, Tso, IF, Chun, J, Mueller, SA, Taylor, SF, Ellingrod, VL. et al. Negative affect predicts social functioning across schizophrenia and bipolar disorder: findings from an integrated data analysis. Psychiatry Res. 2016;243:198206. doi:10.1016/j.psychres.2016.06.031.CrossRefGoogle ScholarPubMed
Reininghaus, U, Böhnke, JR, Hosang, G, et al. Evaluation of the validity and utility of a transdiagnostic psychosis dimension encompassing schizophrenia and bipolar disorder. Br J Psychiatry. 2016;209(2):107–13. doi:10.1192/bjp.bp.115.167882.CrossRefGoogle ScholarPubMed
Buckley, PF, Miller, BJ, Lehrer, DS, Castle, DJ. Psychiatric comorbidities and schizophrenia. Schizophr Bull. 2009;35(2):383402. doi:10.1093/schbul/sbn135.CrossRefGoogle ScholarPubMed
Craddock, N, O’Donovan, MC, Owen, MJ. The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J Med Genet. 2005;42(3):193204. doi:10.1136/jmg.2005.030718.CrossRefGoogle ScholarPubMed
Dunayevich, E, Keck, PE. Prevalence and description of psychotic features in bipolar mania. Curr Psychiatry Rep. 2000;2(4):286–90. doi:10.1007/s11920-000-0069-4.CrossRefGoogle ScholarPubMed
Etchecopar-Etchart, D, Korchia, T, Loundou, A, et al. Comorbid major depressive disorder in schizophrenia: a systematic review and meta-analysis. Schizophr Bull. 2021;47(2):298308. doi:10.1093/schbul/sbaa153.CrossRefGoogle ScholarPubMed
Goodwin, FK, Jamison, KR. Manic-depressive illness: bipolar disorders and recurrent depression. 2nd ed. Oxford, UK: Oxford University Press; 2007.Google Scholar
Upthegrove, R, Marwaha, S, Birchwood, M. Depression and schizophrenia: cause, consequence, or trans-diagnostic issue? Schizophr Bull. 2017;43(2):240–4. doi:10.1093/schbul/sbw097.Google ScholarPubMed
International Schizophrenia Consortium, Purcell, SM, Wray, NR, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460(7256):748–52. doi:10.1038/nature08185.Google ScholarPubMed
Xu, M, Zhang, W, Hochwalt, P, et al. Structural connectivity associated with familial risk for mental illness: a meta-analysis of diffusion tensor imaging studies in relatives of patients with severe mental disorders. Hum Brain Mapp. 2022;43(9):2936–50. doi:10.1002/hbm.25827.CrossRefGoogle ScholarPubMed
Lichtenstein, P, Yip, BH, Björk, C, et al. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet. 2009;373(9659):234–9. doi:10.1016/S0140-6736(09)60072-6.CrossRefGoogle ScholarPubMed
Craddock, N, Owen, MJ. The Kraepelinian dichotomy – going, going… But still not gone. Br J Psychiatry. 2010;196(2):92–5. doi:10.1192/bjp.bp.109.073429.CrossRefGoogle Scholar
Harvey, AG, Watkins, ER, Mansell, W, Shafran, R. Cognitive behavioural processes across psychological disorders: a transdiagnostic approach to research and treatment. Oxford, UK: Oxford University Press; 2004.CrossRefGoogle Scholar
Mansell, W, Harvey, A, Watkins, E, Shafran, R. Conceptual foundations of the transdiagnostic approach to CBT. J Cogn Psychother. 2009;23(1):619. doi:10.1891/0889-8391.23.1.6.CrossRefGoogle Scholar
Marwaha, S, He, Z, Broome, M, et al. How is affective instability defined and measured? A systematic review. Psychol Med. 2014;44(9):1793–808. doi:10.1017/S0033291713002407.CrossRefGoogle Scholar
Renaud, S, Corbalan, F, Beaulieu, S. Differential diagnosis of bipolar affective disorder type II and borderline personality disorder: analysis of the affective dimension. Compr Psychiatry. 2012;53(7):952–61. doi:10.1016/j.comppsych.2012.03.004.CrossRefGoogle ScholarPubMed
Koenigsberg, HW. Affective instability: toward an integration of neuroscience and psychological perspectives. J Personal Disord. 2010;24(1):6082. doi:10.1521/pedi.2010.24.1.60.CrossRefGoogle ScholarPubMed
Nica, EI, Links, PS. Affective instability in borderline personality disorder: experience sampling findings. Curr Psychiatry Rep. 2009;11(1):7481. doi:10.1007/s11920-009-0012-2.CrossRefGoogle ScholarPubMed
Santangelo, P, Reinhard, I, Mussgay, L, et al. Specificity of affective instability in patients with borderline personality disorder compared to posttraumatic stress disorder, bulimia nervosa, and healthy controls. J Abnorm Psychol. 2014;123(1):258–72. doi:10.1037/a0035619.CrossRefGoogle ScholarPubMed
Patel, R, Lloyd, T, Jackson, R, et al. Mood instability is a common feature of mental health disorders and is associated with poor clinical outcomes. BMJ Open. 2015;5(5):e007504. doi:10.1136/bmjopen-2014-007504.CrossRefGoogle ScholarPubMed
Bowen, R, Balbuena, L, Leuschen, C, Baetz, M. Mood instability is the distinctive feature of neuroticism. Results from the British health and lifestyle study (HALS). Pers Individ Dif. 2012;53(7):896900. doi:10.1016/j.paid.2012.07.003.CrossRefGoogle Scholar
Horan, WP, Blanchard, JJ, Clark, LA, Green, MF. Affective traits in schizophrenia and Schizotypy. Schizophr Bull. 2008;34(5):856–74. doi:10.1093/schbul/sbn083.CrossRefGoogle ScholarPubMed
Marwaha, S, Parsons, N, Broome, M. Mood instability, mental illness and suicidal ideas: results from a household survey. Soc Psychiatry Psychiatr Epidemiol. 2013;48:1431–7. doi:10.1007/s00127-013-0653-7.CrossRefGoogle ScholarPubMed
Marwaha, S, Parsons, N, Flanagan, S, Broome, M. The prevalence and clinical associations of mood instability in adults living in England: results from the adult psychiatric morbidity survey 2007. Psychiatry Res. 2013;205(3):262–8. doi:10.1016/j.psychres.2012.09.036.CrossRefGoogle ScholarPubMed
Harvey, PD, Greenberg, BR, Serper, MR. The affective lability scales – development, reliability, and validity. J Clin Psychol. 1989;45(5):786–93. doi:10.1002/1097-4679(198909)45:5<786::AID-JCLP2270450515>3.0.CO;2-P.3.0.CO;2-P>CrossRefGoogle ScholarPubMed
Larsen, RJ, Diener, E, Emmons, RA. Affect intensity and reactions to daily life events. J Pers Soc Psychol. 1986;51(4):803–14. doi:10.1037/0022-3514.51.4.803.CrossRefGoogle Scholar
Yee, CI, Strauss, GP, Allen, DN, Haase, CM, Kimhy, D, Mittal, VA. Trait emotional experience in individuals with schizophrenia and youth at clinical high risk for psychosis. BJPsych Open. 2019;5(5):e78. doi:10.1192/bjo.2019.64.CrossRefGoogle ScholarPubMed
Birchwood, M. Pathways to emotional dysfunction in first-episode psychosis. Br J Psychiatry. 2003;182(5):373–5. doi:10.1192/bjp.182.5.373.CrossRefGoogle ScholarPubMed
Broome, MR, Woolley, JB, Tabraham, P, et al. What causes the onset of psychosis? Schizophr Res. 2005;79(1):2334. doi:10.1016/j.schres.2005.02.007.CrossRefGoogle ScholarPubMed
Freeman, C, Garety, PA. Connecting neurosis and psychosis: the direct influence of emotion on delusions and hallucinations. Behav Res Ther. 2003;41(8):923–47. doi:10.1016/S0005-7967(02)00104-3.CrossRefGoogle ScholarPubMed
Freeman, D, Stahl, D, McManus, S, Brugha, T, Wiles, N, Bebbington, P. Insomnia, worry, anxiety and depression as predictors of the occurrence and persistence of paranoid thinking. Soc Psychiatry Psychiatr Epidemiol. 2012;47:1195–203. doi:10.1007/s00127-011-0433-1.CrossRefGoogle ScholarPubMed
Garety, PA, Kuipers, E, Fowler, D, Freeman, D, Bebbington, PE. A cognitive model of the positive symptoms of psychosis. Psychol Med. 2001;21(2):189–95. doi:10.1017/S0033291701003312.CrossRefGoogle Scholar
Hoegh, MC, Melle, I, Aminoff, SR, et al. Affective lability across psychosis spectrum disorders. Eur Psychiatry. 2020;63(1):e53. doi:10.1192/j.eurpsy.2020.44.CrossRefGoogle ScholarPubMed
Li, LY, Fung, CK, Moore, MM, Martin, EA. Differential emotional abnormalities among schizotypy clusters. Schizophr Res. 2019;208:285–92. doi:10.1016/j.schres.2019.01.042.CrossRefGoogle ScholarPubMed
Angst, J, Gamma, A, Endrass, J. Risk factors for the bipolar and depression spectra: mood disorders and risk factors. Acta Psychiatr Scand Suppl. 2003;108(418):15–9. doi:10.1034/j.1600-0447.108.s418.4.x.CrossRefGoogle Scholar
Henry, C, Mitropoulou, V, New, AS, Koenigsberg, HW, Silverman, J, Siever, LJ. Affective instability and impulsivity in borderline personality disorder and bipolar II disorders: similarities and differences. J Psychiatr Res. 2001;35(6):307–12. doi:10.1016/S0022-3956(01)00038-3.CrossRefGoogle ScholarPubMed
Henry, C, Van den Bulke, D, Bellivier, F, et al. Affective lability and affect intensity as core dimensions of bipolar disorders during euthymic period. Psychiatry Res. 2008;159(1–2):16. doi:10.1016/j.psychres.2005.11.016.CrossRefGoogle ScholarPubMed
Judd, LL, Akiskal, HS, Schettler, PJ, et al. A prospective investigation of the natural history of the long-term weekly symptomatic status of bipolar II disorder. Arch Gen Psychiatry. 2003;60(3):261–9. doi:10.1001/archpsyc.60.3.261.CrossRefGoogle ScholarPubMed
Judd, LL, Schettler, PJ, Akiskal, HS, et al. Long-term symptomatic status of bipolar I vs. bipolar II disorders. Int J Neuropsychopharmacol. 2003;6(2):127–37. doi:10.1017/S1461145703003341.CrossRefGoogle ScholarPubMed
Bonsall, MB, Wallace-Hadrill, SMA, Geddes, JR, Goodwin, GM, Holmes, EA. Nonlinear time-series approaches in characterizing mood stability and mood instability in bipolar disorder. Proc R Soc Lond B Biol Sci. 2012;279(1730):916–24. doi:10.1098/rspb.2011.1246.Google ScholarPubMed
Hofmann, BU, Meyer, TD. Mood fluctuations in people putatively at risk for bipolar disorders. British J Clin Psychol. 2010;45(1):105–10. doi:10.1348/014466505X35317.CrossRefGoogle Scholar
Broome, MR, Saunders, KEA, Harrison, PJ, Marwaha, S. Mood instability: Significance, definition and measurement. Br J Psychiatry. 2015;207(4):283–5. doi:10.1192/bjp.bp.114.158543.CrossRefGoogle ScholarPubMed
Fernandez, KC, Jazaieri, H, Gross, JJ. Emotion regulation: a transdiagnostic perspective on a new RDoC domain. Cognit Ther Res. 2016;40(3):426–40. doi:10.1007/s10608-016-9772-2.CrossRefGoogle ScholarPubMed
Marwaha, S, Broome, MR, Bebbington, PE, Kuipers, E, Freeman, D. Mood instability and psychosis: analyses of British national survey data. Schizophr Bull. 2014;40(2):269–77. doi:10.1093/schbul/sbt149.CrossRefGoogle ScholarPubMed
Myin-Germeys, I, Delespaul, PA, DeVries, MW. Schizophrenia patients are more emotionally active than in assumed based on their behaviour. Schizophr Bull. 2000;26(4):847–54. doi:10.1093/oxfordjournals.schbul.a033499.CrossRefGoogle Scholar
Taylor, RH, Ulrichsen, A, Young, AH, Strawbridge, R. Affective lability as a prospective predictor of subsequent bipolar disorder diagnosis: a systematic review. Int J Bipolar Disord. 2021;9(1):3344. doi:10.1186/s40345-021-00237-1.CrossRefGoogle ScholarPubMed
Houben, M, Van Den Noortgate, W, Kuppens, P. The relation between short-term emotion dynamics and psychological well-being: a meta-analysis. Psychol Bull. 2015;141(4):901–30. doi:10.1037/a0038822.CrossRefGoogle ScholarPubMed
Miller, ML, Raugh, IM, Strauss, GP, Harvey, PD. Remote digital phenotyping in serious mental illness: focus on negative symptoms, mood symptoms, and self-awareness. Biomark Neuropsychiatry. 2022;6:100047. doi:10.1016/j.bionps.2022.100047.CrossRefGoogle Scholar
Trull, TJ, Lane, SP, Koval, P, Ebner-Priemer, UW. Affective dynamics in psychopathology. Emot Rev. 2015;7(4):355–61. doi:10.1177/1754073915590617.CrossRefGoogle ScholarPubMed
aan het Rot, M, Hogenelst, K, Schoevers, RA. Mood disorders in everyday life: a systematic review of experience sampling and ecological momentary assessment studies. Clin Psychol Rev. 2012;32(6):510–23. doi:10.1016/j.cpr.2012.05.007.CrossRefGoogle ScholarPubMed
Bolger, N, Davis, A, Rafaeli, E. Dairy methods: capturing life as it is lived. Annu Rev Psychol. 2003;54(1):579616. doi:10.1146/annurev.psych.54.101601.145030.CrossRefGoogle Scholar
Csikszentmihalyi, M, Larson, R. Validity and reliability of the experience-sampling method. J Nerv Ment Dis. 1987;175(9):526–36. doi:10.1007/978-94-017-9088-8_3.CrossRefGoogle ScholarPubMed
Ebner-Priemer, UW, Trull, TJ. Ecological momentary assessment of mood disorders and mood dysregulation. Psychol Assess. 2009;21(4):463–75. doi:10.1037/a0017075.CrossRefGoogle ScholarPubMed
Oorschot, M, Kwapil, T, Delespaul, P, Myin-Germeys, I. Momentary assessment research in psychosis. Psychol Assess. 2009;21(4):498505. doi:10.1037/a0017077.CrossRefGoogle ScholarPubMed
Shiffman, S, Stone, AA, Hufford, MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:132. doi:10.1146/annurev.clinpsy.3.022806.091415.CrossRefGoogle ScholarPubMed
LeDoux, JE. Emotion: clues from the brain. Annu Rev Psychol. 1995;46(1):209–35. doi:10.1146/ ScholarPubMed
Jahng, S, Wood, PK, Trull, TJ. Analysis of affective instability in ecological momentary assessment: indices using successive difference and group comparison via multilevel modelling. Psychol Methods. 2008;13(4):354–75. doi:10.1037/a0014173.CrossRefGoogle Scholar
Kuppens, P, Allen, NB, Sheeber, LB. Emotional inertia and psychological maladjustment. Psychol Sci. 2010;21(7):984–91. doi:10.1177/0956797610372634.CrossRefGoogle ScholarPubMed
Wichers, M. The dynamic nature of depression: a new micro-level perspective of mental disorders that meets current challenges. Psychol Med. 2014;44(7):1349–60. doi:10.1017/S0033291713001979.CrossRefGoogle ScholarPubMed
Dejonckheere, E, Mestdagh, M, Houben, M, et al. Complex affect dynamics add limited information to the prediction of psychological well-being. Nat Hum Behav. 2019;3(5):478–91. doi:10.1038/s41562-019-0555-0.CrossRefGoogle Scholar
Kashdan, TB, Rottenberg, J. Psychological flexibility as a fundamental aspect of health. Clin Psychol Rev. 2010;30(7):865–78. doi:10.1016/j.cpr.2010.03.001.CrossRefGoogle ScholarPubMed
Sperry, SH, Walsh, MA, Kwapil, TR. Emotion dynamics concurrently and prospectively predict mood psychopathology. J Affect Disord. 2020;261:6775. doi:10.1016/j.jad.2019.09.076.CrossRefGoogle ScholarPubMed
van de Leemput, IA, Wichers, M, Cramer, AO, et al. Critical slowing down as early warning for the onset and termination of depression. Proc Natl Acad Sci USA. 2014;111(1):8792. doi:10.1073/pnas.1312114110.CrossRefGoogle ScholarPubMed
Oorschot, M, Lataster, T, Thewissen, V, et al. Emotional experience in negative symptoms of schizophrenia – no evidence for a generalised hedonic deficit. Schizophr Bull. 2013;39(1):217–25. doi:10.1093/schbul/sbr137.CrossRefGoogle ScholarPubMed
Vakhrusheva, J, Khan, S, Chang, R, et al. Lexical analysis of emotional responses to “real-world” experiences in individuals with schizophrenia. Schizophr Res. 2020;216:272–8. doi:10.1016/j.schres.2019.11.045.CrossRefGoogle ScholarPubMed
Badal, VD, Parrish, EM, Holden, JL, Depp, CA, Granholm, E. Dynamic contextual influences on social motivation and behavior in schizophrenia: a case-control network analysis. NPJ Schizophr. 2021;7(1):62. doi:10.1038/s41537-021-00189-6.CrossRefGoogle ScholarPubMed
Raugh, IM, Strauss, GP. Deconstructing emotion regulation in schizophrenia: the nature and consequences of abnormalities at the identification stage. Eur Arch Psychiatry Clin Neurosci. 2022;272(6):1061–71. doi:10.1007/s00406-021-01350-z.CrossRefGoogle ScholarPubMed
Strauss, GP, Zamani Esfahlani, F, Visser, KF, Dickinson, EK, Gruber, J, Sayama, H. Mathematically modeling emotion regulation abnormalities during psychotic experiences in schizophrenia. Clin Psychol. 2019;7(2):216–33. doi:10.1177/2167702618810233.CrossRefGoogle Scholar
Visser, KF, Esfahlani, FZ, Sayama, H, Strauss, GP. An ecological momentary assessment evaluation of emotion regulation abnormalities in schizophrenia. Psychol Med. 2018;48(14):2337–45. doi:10.1017/S0033291717003865.CrossRefGoogle ScholarPubMed
Lataster, T, Valmaggia, L, Lardinois, M, van Os, J, Myin-Germeys, I. Increased stress reactivity: a mechanism specifically associated with the positive symptoms of psychotic disorder. Psychol Med. 2013;43(7):1389–400. doi:10.1017/S0033291712002279.CrossRefGoogle ScholarPubMed
Myin-Germeys, I, Peeters, F, Havermans, R, et al. Emotional reactivity to daily life stress in psychosis and affective disorders: an experience sampling study. Acta Psychiatr Scand. 2003;107(2):124–31. doi:10.1034/j.1600-0447.2003.02025.x.CrossRefGoogle ScholarPubMed
Myin-Germeys, I, van Os, J, Schwartz, JE, Stone, AA, Delespaul, PA. Emotional reactivity to daily life stress in psychosis. Arch Gen Psychiatry 2001;58(12):1137–44. doi:10.1001/archpsyc.58.12.1137.CrossRefGoogle ScholarPubMed
Palmier-Claus, JE, Taylor, PJ, Gooding, P, Dunn, G, Lewis, SW. Affective variability predicts suicidal ideation in individuals at ultra-high risk of developing psychosis: an experience sampling study. Br J Clin Psychol. 2012;51(1):7283. doi:10.1111/j.2044-8260.2011.02013.x.CrossRefGoogle ScholarPubMed
Reininghaus, U, Kempton, MJ, Valmaggia, L, et al. Stress sensitivity, aberrant salience, and threat anticipation in early psychosis: an experience sampling study. Schizophr Bull. 2016;42(3):712–22. doi:10.1093/schbul/sbv190.CrossRefGoogle ScholarPubMed
Strauss, GP, Esfahlani, FZ, Granholm, E, et al. Mathematically modeling anhedonia in schizophrenia: a stochastic dynamical systems approach. Schizophr Bull. 2020;46(5):1191–201. doi:10.1093/schbul/sbaa014.CrossRefGoogle ScholarPubMed
Kim, BN. Behavioral activation system (BAS) dysregulation and bipolar spectrum psychopathology in daily life: an online-diary study. Psychiatry Res. 2020;291:113180. doi:10.1016/j.psychres.2020.113180.CrossRefGoogle ScholarPubMed
Kwapil, TR, Barrantes-Vidal, N, Armistead, MS, et al. The expression of bipolar spectrum psychopathology in daily life. J Affect Disord. 2010;130(1–2):166–70. doi:10.1016/j.jad.2010.10.025.CrossRefGoogle ScholarPubMed
Sperry, SH, Kwapil, TR. Affective dynamics in bipolar spectrum psychopathology: modelling inertia, reactivity, variability, and instability in daily life. J Affect Disord. 2019;251:195204. doi:10.1016/j.jad.2019.01.053.CrossRefGoogle ScholarPubMed
Havermans, R, Nicolson, NA, Berkhof, J, DeVries, MW. Mood reactivity to daily events in patients with remitted bipolar disorder. Psychiatry Res. 2010;179(1):4752. doi:10.1016/j.psychres.2009.10.020.CrossRefGoogle ScholarPubMed
Schwartz, S, Schultz, S, Reider, A, Saunders, EFH. Daily mood monitoring of symptoms using smartphones in bipolar disorder: a pilot study assessing the feasibility of ecological momentary assessment. J Affect Disord. 2016;191:8893. doi:10.1016/j.jad.2015.11.013.CrossRefGoogle ScholarPubMed
Solhan, MB, Trull, TJ, Jahng, S, Wood, PK. Clinical assessment of affective instability: comparing EMA indices, questionnaire reports, and retrospective recall. Psychol Assess. 2009;21(3):425–36. doi:10.1037/a0016869.CrossRefGoogle ScholarPubMed
Cowan, HR, Mittal, VA, Allen, DN, Gold, JM, Strauss, GP. Heterogeneity of emotional experience in schizophrenia: trait affect profiles predict clinical presentation and functional outcome. J Abnorm Psychol. 2020;129(7):760–7. doi:10.1037/abn0000554.CrossRefGoogle ScholarPubMed
Kemp, KC, Sperry, SH, Hernández, L, Barrantes-Vidal, N, Kwapil, TR. Affective dynamics in daily life are differentially expressed in positive, negative, and disorganized schizotypy. J Psychopathol Clin Sci. 2023;132(1):110–21. doi:10.1037/abn0000799.CrossRefGoogle ScholarPubMed
Kwapil, TR, Brown, LH, Silvia, PJ, Myin-Germeys, I, Barrantes-Vidal, N. The expression of positive and negative schizotypy in daily life: an experience sampling study. Psychol Med. 2012;42(12):2555–66. doi:10.1017/S0033291712000827.CrossRefGoogle ScholarPubMed
Li, LY, Schiffman, J, Martin, EA. Affect-dynamic signatures of psychosis risk across multiple time scales and contexts. Clin Psychol Sci. 2022;10(5):960–80. doi:10.1177/21677026211070794.CrossRefGoogle Scholar
Westermann, S, Grezellschak, S, Oravecz, Z, Moritz, S, Lüdtke, T, Jansen, A. Untangling the complex relationships between symptoms of schizophrenia and emotion dynamics in daily life: findings from an experience sampling pilot study. Psychiatry Res. 2017;257:514–8. doi:10.1016/j.psychres.2017.08.023.CrossRefGoogle ScholarPubMed
So, E, Kam, I, Leung, CM, Chung, D, Liu, Z, Fong, S. The Chinese-bilingual SCID-I/P project: stage 1—reliability for mood disorders and schizophrenia. Hong Kong J Psychiatry. 2003;13:718.Google Scholar
Leung, MH, So, SH, Kwok, NTK, et al. Moment-to-moment interaction between affectivity and coping behaviours in bipolar disorder and the role of cognitive appraisals. BJPsych Open. 2019;5(3):e44. doi:10.1192/bjo.2019.35.CrossRefGoogle ScholarPubMed
So, SH, Mak, AD, Chan, P, et al. Efficacy of phase 1 of life goals programme on symptom reduction and mood stability for bipolar disorder. J Affect Disord. 2021;281:949–57. doi:10.1016/j.jad.2020.11.019.CrossRefGoogle ScholarPubMed
So, SHW, Chung, LKH, Tse, CY, et al. Moment-to-moment dynamics between auditory verbal hallucinations and negative affect and the role of beliefs about voices. Psychol Med. 2021;51(4):661–7. doi:10.1017/S0033291719003611.CrossRefGoogle ScholarPubMed
Hox, JJ, Moerbeek, M, Van de Schoot, R. Multilevel analysis: techniques and applications. London: Routledge; 2017.CrossRefGoogle Scholar
Palmier-Claus, JE, Myin-Germeys, I, Barkus, E, et al. Experience sampling research in individuals with mental illness: reflections and guidance: experience sampling research in individuals with mental illness. Acta Psychiatr Scand. 2011;123(1):1220. doi:10.1111/j.1600-0447.2010.01596.x.CrossRefGoogle ScholarPubMed
Chan, Y, So, SHW, Mak, ADP, Siah, KTH, Chan, W, Wu, JC. The temporal relationship of daily life stress, emotions, and bowel symptoms in irritable bowel syndrome—diarrhea subtype: a smartphone‐based experience sampling study. Neurogastroenterol Motil. 2019;31(3):e13514. doi:10.1111/nmo.13514.CrossRefGoogle ScholarPubMed
So, SH, Peters, ER, Swendsen, J, Garety, PA, Kapur, S. Detecting improvements in acute psychotic symptoms using experience sampling methodology. Psychiatry Res. 2013;210(1):82–8. doi:10.1016/j.psychres.2013.05.010.CrossRefGoogle ScholarPubMed
Geldhof, GJ, Preacher, KJ, Zyphur, MJ. Reliability estimation in a multilevel confirmatory factor analysis framework. Psychol Methods. 2014;19(1):72. doi:10.1037/a0032138.CrossRefGoogle Scholar
Sperry, SH, Kwapil, TR. Comparing static and dynamic measures of affect intensity and affective lability: do they measure the same thing? Motiv Emot. 2020;4:870–9. doi:10.1007/s11031-020-09840-8.CrossRefGoogle Scholar
Kay, SR, Fiszbein, A, Opler, LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261–76. doi:10.1093/schbul/13.2.261.CrossRefGoogle ScholarPubMed
Addington, D, Addington, J, Schissel, B. A depression rating scale for schizophrenics. Schizophr Res. 1990;3(4):247–51. doi:10.1016/0920-9964(90)90005-r.CrossRefGoogle ScholarPubMed
Young RC, Biggs, JT, Ziegler, VE, Meyer, DA. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry. 1978;133(5):429–35. doi:10.1192/bjp.133.5.429.Google Scholar
Montgomery, SA, Åsberg, M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134(4):382–9. doi:10.1192/bjp.134.4.382.CrossRefGoogle ScholarPubMed
Kimhy, D, Myin-Germeys, I, Palmier-Claus, J, Swendsen, J. Mobile assessment guide for research in schizophrenia and severe mental disorders. Schizophr Bull. 2012;38(3):386–95. doi:10.1093/schbul/sbr186.CrossRefGoogle ScholarPubMed
The Jamovi Project [Computer Software] Version 2.3. JAMOVI; 2022.Google Scholar
Scheffer, M, Bascompte, J, Brock, WA, et al. Early-warning signals for critical transitions. Nature. 2009;461:53–9. doi:10.1038/nature08227.CrossRefGoogle ScholarPubMed
Scheffer, M, Carpenter, SR, Lenton, TM, et al. Anticipating critical transitions. Science. 2012;338(6105):344–8. doi:10.1126/science.1225244.CrossRefGoogle ScholarPubMed
Garland, EL, Fredrickson, B, Kring, AM, Johnson, DP, Meyer, PS, Penn, DL. Upward spirals of positive emotions counter downward spirals of negativity: Insights from the broaden-and-build theory and affective neuroscience on the treatment of emotion dysfunctions and deficits in psychopathology. Clin Psychol Rev. 2010;30(7):849–64. doi:10.1016/j.cpr.2010.03.002.CrossRefGoogle ScholarPubMed
Muddle, S, Jones, B, Taylor, G, Jacobsen, P. A systematic review and meta‐analysis of the association between emotional stress reactivity and psychosis. Early Interv Psychiatry. 2022;16(9):958–78. doi:10.1111/eip.13247.CrossRefGoogle ScholarPubMed
Lamers, F, Swendsen, J, Cui, L, et al. Mood reactivity and affective dynamics in mood and anxiety disorders. J Abnorm Psychol. 2018;127(7):659–69. doi:10.1037/abn0000378.CrossRefGoogle ScholarPubMed
Kimhy, D, Gill, KE, Brucato, G, Vakhrusheva, J, Arndt, L, Gross, JJ, et al. The impact of emotion awareness and regulation on social functioning in individuals at clinical high risk for psychosis. Psychol Med. 2016;46(14):2907–18. doi:10.1017/S0033291716000490.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Sample characteristics

Figure 1

Table 2. Indicators of affective dynamics across groups

Figure 2

Figure 1. Box plots of affective dynamics across groups. *p < 0.050. BP, bipolar disorder; HC, healthy controls; SCZ, schizophrenia.

Figure 3

Figure 2. Affective reactivity to stress for PA (left) and NA (right) across groups. BP, bipolar disorder; HC, healthy controls; SCZ, schizophrenia.

Submit a response


No Comments have been published for this article.