抑郁症患者与健康对照者的日常人际情绪调节比较：一项 Frontiers in Psychology 研究
Interpersonal emotion regulation in daily life: a comparison of individuals with and without depressive disorders
一项 Frontiers in Psychology 研究用两周每日 3 次提示的生态瞬时评估，比较 17 名抑郁症患者与 18 名健康对照者在人际互动中的认知重评、社会分享与表达抑制，未发现组间差异，抑郁症状严重度也与策略强度无关。事后分析显示述情障碍与抑郁严重度正相关，且在抑郁组内与社会分享负相关。作者提示样本量小，需谨慎解读这一零结果。
Abstract
Background:
Emotion dysregulation is strongly linked to depressive disorders, yet distinctions between interpersonal and intrapersonal forms remain underexplored in daily life. This study examines emotion dysregulation in depression during close interpersonal interactions, comparing individuals with depression and healthy controls (HC), and exploring associations with alexithymia and childhood maltreatment.
Methods:
Participants (18 HC, 17 with depression) reported three emotion regulation (ER) strategies (cognitive reappraisal, social sharing, suppression) during interpersonal interactions over 2 weeks (3 prompts/day). Group (depression vs. HC) was the independent variable, and ER strategies the dependent variables. Alexithymia, childhood maltreatment, and depressive symptoms were assessed at baseline. Data were analyzed using two-level hierarchical linear modeling.
Results:
No group differences in ER strategy use were observed, and depressive symptom severity was not associated with strategy intensity. Post-hoc analyses showed that alexithymia was positively associated with depressive severity across the full sample and negatively associated with social sharing within the depressed group. Cognitive reappraisal showed heterogeneous associations with childhood maltreatment subdomains.
Conclusion:
Interpersonal emotion dysregulation did not differentiate depressed from healthy individuals. Given the small sample size, these null findings should be interpreted cautiously. Nevertheless, alexithymia and childhood maltreatment appear relevant for ER in close relationships, highlighting their importance in depression research.
1 Introduction
Globally, an estimated 4.4% of the population suffers from depressive disorders [], with a worldwide increase of 18.4% between 2005 and 2015 (). Depressive disorders, characterized by persistent low mood and diminished interest or pleasure (), are closely linked to emotion dysregulation, a core process that remains insufficiently understood. Research suggests that individuals with depression rely more on maladaptive emotion regulation (ER) strategies and less on adaptive ones compared to healthy controls (HC) (; ). However, prior work has not consistently distinguished between intrapersonal and interpersonal forms of ER, with interpersonal regulation remaining comparatively underexplored. In this study, social sharing is conceptualized as an inherently interpersonal strategy, whereas reappraisal and suppression are considered intrapersonal processes assessed within interpersonal contexts. This study aims to contribute to the growing body of research on interpersonal ER in depressive disorders. In addition, dispositional factors such as childhood maltreatment and alexithymia are considered, as both have been linked to altered ER and increased vulnerability to depression.
1.1 Emotion regulation: from adaptive—maladaptive dichotomy to context dependence
ER refers to the processes by which individuals influence their emotional experiences, including when emotions arise and how they are expressed (). Early frameworks classified ER strategies as either adaptive or maladaptive based on their general associations with psychopathology (; ). However, recent evidence indicates that their effectiveness is highly context-dependent (), particularly in interpersonal situations. Research in non-clinical samples shows that the use of social sharing and expressive suppression varies with interpersonal context: when individuals perceive their environment as high in social support, they engage in more sharing and less suppression, whereas lower perceived support reduces sharing and increases suppression (). Similarly, following the 1989 California earthquake, social sharing initially had beneficial effects, but became less effective over time as interpersonal receptivity decreased, illustrating how “social constraint” can alter its adaptiveness (). Building on this evidence, the present study examines ER strategies in real-world interpersonal contexts, focusing on cognitive reappraisal, suppression, and social sharing due to their relevance for both general functioning and depressive disorders (; ; ; ).
1.2 Contextual influences on reappraisal, suppression, and social sharing in depression
Existing research indicates that cognitive reappraisal, suppression, and social sharing exert context-dependent effects on negative emotions and depressive symptoms, although most evidence stems from non-clinical samples (; ). Cognitive reappraisal, reframing situations to alter emotional impact (), has been shown to reduce depressive symptoms under uncontrollable stress but may exacerbate them in controllable situations in healthy populations (), suggesting that its adaptiveness is context-dependent. Suppression, defined as the inhibition of emotional expression (), has been associated with increased depressive symptoms in a non-clinical sample (). However, in a non-clinical sample with high intolerance of uncertainty, suppression appeared linked to lower contamination-related anxiety (), suggesting that in high-risk contexts expressive suppression may serve as an adaptive function by facilitating more effective regulation of worry (). Social sharing, defined as verbalizing emotions to obtain support (), occurs less frequently in depressive disorders than in HC, potentially reducing perceived social support and contributing to symptom persistence (). Its effectiveness depends on relationship closeness, with support from close others being more beneficial than from strangers in healthy populations (; ). further showed that individuals with depression display more negative language with friends than with strangers, whereas healthy individuals do not, highlighting the relevance of close interpersonal contexts. found that, in a healthy population, the presence of close others (e.g., family, friends) modulates the adaptiveness of ER: greater use of suppression in the presence (vs. absence) of close others was associated with higher depressive symptoms. Additionally, a decrease in reappraisal following increased presence of close others was linked to improved mental health ().
Extending these findings, the present study examines ER in individuals with depressive disorders compared to HC within close interpersonal relationships. We hypothesize that in social situations with close partners, individuals with depressive disorders will exhibit greater use of reappraisal and suppression and reduced social sharing, compared to HC, reflecting maladaptive ER in interpersonal contexts. Higher depression severity is expected to correlate with greater reappraisal and suppression and lower social sharing. To capture these strategies in real-world settings, Ecological Momentary Assessment (EMA) will be employed, a method that captures relevant phenomena in an unbiased and immediate way within natural environments ().
1.3 The role of childhood maltreatment and alexithymia in emotion regulation
ER is central to depressive disorders, yet less is known which factors may shape this pattern. Childhood maltreatment has been linked to the onset and maintenance of depression (; ; ), potentially via disrupted ER (; ). Similarly, alexithymia, characterized by difficulties in identifying and expressing emotions (), is frequently elevated in depression () and associated with reduced adaptive and increased maladaptive ER strategies (). Based on theoretical considerations, both factors are expected to relate to less adaptive and more maladaptive ER in interpersonal contexts, as well as higher depressive symptoms. However, their specific interplay in close interpersonal settings remains insufficiently understood and may vary across associations. Therefore, these relationships are examined on an exploratory basis in individuals with depressive disorders.
2 Methods
2.1 Participants
From April to July 2023, 46 individuals were recruited via the Department of Psychiatry and Psychotherapy at Charité and social media. Inclusion criteria were: (a) age 18–65, (b) German fluency at C1 or higher, and (c) Android smartphone ownership. Exclusion criteria, assessed with the Mini-DIPS interview (), included active substance addiction (n = 1), psychotic symptoms (n = 2), acute suicidality (n = 1), or benzodiazepine use (n = 1). Depressive participants met ICD-10 criteria for a current depressive episode or persistent dysthymia; HC had no psychiatric diagnoses. Participants with compliance below 40% were excluded to ensure comparable response rates, as including all intention-to-treat participants showed no significant group differences. The final sample included 35 participants: 18 HC and 17 depressive subjects (17 female, 18 male; Age: MHealthy = 43.22, SD = 13.05; MDepressive = 42.53, SD = 10.79). Most were single (n = 22, 62.85%). Reports of physical violence (n = 9, 52.94%), sexual violence (n = 2, 11.76%), and other highly distressing events (n = 15, 88.23%) were exclusive to depressive participants, as assessed with the Childhood Trauma Questionnaire. Among them, 15 had chronic/recurrent (n = 8, 47%) or episodic depression (n = 7, 41%), and 2 (12%) had a current episode without formal diagnosis, assessed using the Mini-DIPS. At survey start, all depressive participants had Beck-Depression-Inventory II (BDI-II) > 13 (M = 26.47, SD = 11.51), whereas HC averaged M = 5.22 (SD = 4.50).
2.2 Procedure
The assessment procedure consisted of a baseline screening, a diagnostic interview, self-report questionnaires, and a subsequent EMA phase. After providing consent, participants completed a baseline assessment on REDCap, including demographics and current mental state (e.g., depressive symptoms). They then underwent a Mini-DIPS diagnostic interview. The Mini-DIPS is a structured clinical interview based on ICD-10 criteria, administered by trained Bachelor’s students in psychology either in person at Charité Campus Mitte or via telephone (≈ 60 min). It was used to assign participants to the depressive or HC group, independent of prior diagnoses. Assessors were not blinded to recruitment status. Eligible participants then completed online questionnaires assessing childhood maltreatment, alexithymia, and depressive symptoms (≈30 min). All participants subsequently took part in a 14-day EMA survey via the movisensXS app (.) on their smartphones. Participants received up to €30 for achieving at least 65% compliance.
2.3 Measures
2.3.1 Baseline measures
Depression severity was measured with the 21-item BDI-II (; German version: ), rated on a 0–3 scale and classified as none/negligible (0–13), mild (14–19), moderate (20–28), or severe (≥29) (; ). Childhood maltreatment was assessed via self-report using the 28-item Childhood Trauma Questionnaire (CTQ; ; German version: ), which evaluates five domains: emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect, rated on a 5-point Likert scale. Alexithymia, reflecting difficulties in identifying and expressing emotions, was assessed with the 24-item Perth Alexithymia Questionnaire (PAQ; ; German version: ), rated on a 7-point Likert scale.
Internal consistency reliability was calculated for all measures in the present sample using Cronbach’s α with 95% confidence intervals. The BDI-II showed excellent internal consistency [α = 0.95, 95%-KI (0.93, 0.97)]. The PAQ demonstrated good internal consistency [α = 0.88, 95%-KI (0.82, 0.93)]. For the CTQ subscales the following values were obtained: emotional abuse [α = 0.89, 95%-KI (0.82, 0.94)], physical abuse [α = 0.78, 95%-KI (0.64, 0.88)], sexual abuse [α = 0.66, 95%-KI (0.43, 0.81)], emotional neglect [α = 0.82, 95%-KI (0.71, 0.90)], and physical neglect [α = 0.44, 95%-KI (0.08, 0.69)].
2.3.2 Ecological momentary assessment (EMA)
Using EMA via the movisensXS smartphone app, participants were prompted three times daily for 14 days to report on ER. Before the study, participants received brief training from researcher on app use and on the three ER strategies: reappraisal, suppression, and social sharing, including definitions, examples, and response options. These strategies were assessed in interpersonal situations, capturing both interpersonal (social sharing) and intrapersonal (reappraisal, suppression) regulatory processes in social interactions (e.g., through communication with close others). Random prompts were delivered between 10:00 and 18:00. EMA items were adapted and translated into German from pilot study, which investigated these ER strategies in interpersonal contexts within a non-clinical sample. At each prompt, participants recalled their most intense emotional event since the previous signal and reported on: (a) social context [close others (i.e., friends, family), non-close others (i.e., strangers), or alone], (b) emotional state (arousal, energy, valence; 11-point scales), and (c) ER strategies (reappraisal: “I thought about the situation in a different way,” social sharing: “I shared my feelings with others or talked to others about them,” expressive suppression: “I did not show my feelings”); 11-point scale from 0 = not at all to 10 = very much; see (). Item details are provided in Supplementary Table S1.
2.4 Data analysis
Linear mixed models (random-intercept models) were conducted using the nlme package in R (Version 2023.09.1 + 494) (). Measurement occasions (Level 1) were nested within individuals (Level 2), with group (depressive vs. healthy) included as a fixed effect. Three separate models were estimated with ER strategies (reappraisal, social sharing, suppression) as dependent variables. Each model included a random intercept for participants to account for repeated measurements nested within individuals and a fixed effect of group to examine between-group differences. The depressive group served as the reference level relative to the HC. The general model specification for the ER strategies was as follows:
Level 1
Level 2
where indexes measurement occasions, indexes individuals, and represents reappraisal, social sharing, or suppression.
Model assumptions were evaluated via visual inspection of diagnostic plots (linearity, normality of residuals, homoscedasticity, and influential observations), with no substantial violations observed.
Within the depressive subsample, associations between depression severity and ER strategy use were examined using two-level linear mixed models (Level 1: measurement occasions; Level 2: individuals). Depression severity (BDI-II) was entered as a Level-2 predictor in separate models for each strategy. Given the small sample size (N = 35), cross-group moderation effects could not be tested. Exploratory linear mixed models examined associations between ER strategy use in close relationships and alexithymia (PAQ) as well as childhood maltreatment (CTQ), each included separately as Level-2 predictors.
Missing data were handled using maximum likelihood estimation within the mixed models, assuming data are missing at random. This approach is well established for multilevel EMA data ().
A priori power analyses were not conducted, as the study was designed as a feasibility EMA study. A post hoc sensitivity analysis () indicated that the present design was only sufficiently powered (80%) to detect relatively large standardized fixed effects (β ≈ 0.70–0.80). Such effects are considered large in psychological research and are uncommon in EMA studies on ER and depression, which typically report small to medium effects (β = 0.01–0.39) (; ; ).
3 Results
3.1 Response rates and variability in emotion regulation strategies
Considering interactions with close individuals the final sample comprised 273 assessments in the healthy group and 126 in the depressive group. Over the 14-day period, the healthy group reported 59.2% of their total social interactions with close individuals, while the group with depressive disorders reported only 34.5%, approximately half the proportion of social interactions with close individuals compared to the healthy group. Mean scores, standard deviations, and intraclass correlations between variables are presented in Supplementary Table S2. Intraclass correlations (ICCs) were calculated using a one-way random-effects model [ICC(1)] to estimate between-person variance in the EMA data. Given that much of the variability in the use of ER strategies occurs within individuals (1 − ICC, Supplementary Table S2), the need for multilevel models becomes evident, affecting both the control group (43–55%) and the depressive group (55–62%).
3.2 Comparing maladaptive emotion regulation strategy usage in close relationships: healthy vs. depressive participants
The Hierarchical Linear Modelling (HLM) analyses revealed no significant differences between depressive patients and HC in the intensity of ER strategies within close relationships. Reappraisal [b = −0.28, t(33) = −0.39, p = 0.698], suppression [b = 0.07, t(33) = 0.09, p = 0.922], and social sharing [b = 0.16, t(33) = 0.19, p = 0.850] did not differ between groups (see Table 1). Group-wise descriptive statistics for ER strategy intensity are provided in Supplementary Table S3.
Table 1
| Predictors | Reappraisal | Suppression | Social sharing | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| b | SE b | 95% CI | p | b | SE b | 95% CI | p | b | SE b | 95% CI | p | |
| (Intercept) | 3.54 | 0.53 | [2.51, 4.57] | <0.001 | 4.48 | 0.53 | [3.43, 5.53] | <0.001 | 4.26 | 0.63 | [3.03, 5.49] | <0.001 |
| Group (healthy) | −0.28 | 0.72 | [−1.73, 1.17] | 0.698 | 0.07 | 0.72 | [−1.40, 1.54] | 0.922 | 0.16 | 0.86 | [−1.57, 1.90] | 0.850 |
| Marginal R2 | 0.004 | 0.000 | 0.001 | |||||||||
Differences between healthy and depressed participants in the use of emotion regulation strategies in close interpersonal contexts.
Group = fixed effect. Group of healthy participants n = 18 and 273 observations, group of depressed participants n = 17 and 126 observations. b = estimated fixed effect. SE b = standard error of the estimate. 95% CI, 95% confidence interval. Values in bold indicate statistical significance at p < 0.05, p < 0.01, and p < 0.001.
3.3 Correlation of depressive symptom severity with emotion regulation strategy usage in close relationships
We additionally examined whether baseline depressive symptom severity predicted the use of ER strategies in close relationships among individuals with depressive disorders. No significant associations were observed for any of the three strategies [reappraisal: b = −0.01, t(15) = −0.23, p = 0.822; suppression: b = 0.03, t(15) = 0.67, p = 0.514; social sharing: b = −0.08, t(15) = −1.61, p = 0.128; see Table 2]. Overall, depressive symptom severity did not significantly predict the intensity of ER strategies in close interpersonal contexts.
Table 2
| Predictors | Reappraisal | Suppression | Social sharing | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| b | SE b | 95% CI | p | b | SE b | 95% CI | p | b | SE b | 95% CI | p | |
| (Intercept) | 3.78 | 1.22 | [1.38, 6.17] | 0.002 | 3.71 | 1.26 | [1.24, 6.19] | 0.004 | 6.29 | 1.39 | [3.57, 9.02] | <0.001 |
| BDI | −0.01 | 0.04 | [−0.10, 0.08] | 0.822 | 0.03 | 0.04 | [−0.06, 0.12] | 0.514 | −0.08 | 0.05 | [−0.18, 0.02] | 0.128 |
| Marginal R2 | 0.003 | 0.022 | 0.129 | |||||||||
Associations between the severity of depressive symptoms and the intensity of emotion regulation strategies in close interpersonal contexts.
n = 17 depressive patients and 126 observations. BDI = severity of depressive symptoms. b = estimated fixed effect of depression severity on the intensity of ER strategies in close interpersonal contexts. SE b = standard error of the estimate. 95% CI, 95% confidence interval. Values in bold indicate statistical significance at p < 0.05, p < 0.01, and p < 0.001.
3.4 Exploratory analyses
First, group differences in alexithymia severity were examined across the full sample (healthy vs. depressive). Participants with depressive disorders reported significantly higher alexithymia scores compared to HC, t(33) = 2.40, p = 0.02, Cohen’s d = 0.81 (see Supplementary Figure 1).
Subsequently, post-hoc analyses were conducted to explore associations between alexithymia severity, childhood maltreatment (based on total scores from the respective questionnaires), and the use of ER strategies within the depressive group only (n = 17). Linear mixed models were applied separately for each strategy, focusing on their use in close interpersonal contexts.
Results showed a significant negative association between alexithymia severity (PAQ scores) and social sharing among individuals with depression [b = −0.04, t(15) = −2.67, p = 0.017; Supplementary Table S4]. No significant associations were found for reappraisal or suppression (all ps ≥ 0.68, see Supplementary Table S4).
Post-hoc analyses further examined associations between childhood maltreatment (CTQ) and ER strategies in the depressed group using three linear mixed models (one per strategy). Cognitive reappraisal was significantly associated with all five facets of childhood maltreatment (Table 3). Emotional abuse [b = 0.31, t(11) = 5.27, p < 0.001], sexual abuse [b = 1.07, t(11) = 5.05, p < 0.001], and physical neglect [b = 0.39, t(11) = 3.75, p = 0.003] were positively associated with greater reappraisal intensity. By contrast, physical abuse [b = −0.21, t(11) = −2.34, p = 0.039] and emotional neglect [b = −0.24, t(11) = −2.64, p = 0.023] were negatively associated with reappraisal intensity. These findings suggest that depressive individuals who experienced more emotional or sexual abuse or physical neglect in childhood may engage in greater reappraisal, whereas more severe physical abuse or emotional neglect is associated with less intensive reappraisal use. No significant associations were found for suppression or social sharing (all ps > 0.124; see Supplementary Table S5).
Table 3
| Predictors | Reappraisal | ||
|---|---|---|---|
| b | 95% CI | p | |
| (Intercept) | −4.91 | [−6.93, −2.88] | <0.001 |
| Emotional abuse | 0.31 | [0.18, 0.44] | <0.001 |
| Physical abuse | −0.21 | [−0.41, −0.02] | 0.039 |
| Sexual abuse | 1.07 | [0.61, 1.52] | <0.001 |
| Emotional neglect | −0.24 | [−0.43, −0.04] | 0.023 |
| Physical neglect | 0.39 | [0.17, 0.61] | 0.003 |
| Marginal R2 | 0.418 | ||
Associations between childhood maltreatment subdomains and reappraisal intensity in close interpersonal contexts.
n = 17 depressive patients and 126 observations. b = estimated fixed effect of childhood maltreatment subdomains on the intensity of cognitive reappraisal in close interpersonal contexts. 95% CI, 95% confidence interval. Values in bold indicate statistical significance at p < 0.05, p < 0.01, and p < 0.001.
4 Discussion
Our findings did not reveal significant differences in the intensity of ER strategy use between depressive and healthy participants in interactions with close others. This is in contrast with meta-analytic evidence from , who found that depressed individuals generally use more maladaptive strategies (e.g., suppression, rumination) and less adaptive strategies (e.g., reappraisal) than HC. A possible explanation for these heterogenous outcomes may be not accounting for social context, whereas our study focused specifically on close interpersonal relationships. Supporting this interpretation, neurological research shows that attachment-related cues, such as the familiar faces of close others, activate semantic networks involved in voluntary ER, including cognitive reappraisal (; ). Close relationships may therefore naturally increase the likelihood of attempting to reinterpret interpersonal situations. Compared to HC, depressed individuals tend to rely more rigidly on cue-driven, stimulus-triggered reappraisal rather than on flexible cost–benefit evaluations (; ), a pattern associated with poorer strategy-situation fit (). Together, these findings provide a theoretical rationale for expecting heightened, but potentially inflexible, reappraisal use in close interpersonal contexts among individuals with depression. Given the focus on close interpersonal interactions, the lack of group differences may reflect the “dilution” effect of social connectedness (), where supportive partners or relational dynamics reduce the influence of both maladaptive and adaptive strategies. In this sense, proximal social context may buffer the impact of maladaptive ER strategies while also reducing the relative benefit of adaptive strategies, which could therefore have influenced results of this study. However, additional exploratory analyses including broader social contexts (non-close interactions and being alone) did not reveal significant group-by-context interactions, suggesting that the absence of group differences cannot be fully explained by the restriction to close relationships. This interpretation therefore remains speculative, highlighting the need for further research on how relationship quality, such as intimacy, trust, and perceived support, moderates ER in depressive disorders, as explored by . Overall, ER differences observed in broader contexts may be less pronounced in supportive close relationships. Given the sample size, the study was not sufficiently powered to examine group as a moderator of associations between ER strategies and depressive symptoms. Future studies should investigate whether these relationships differ between individuals with and without depressive disorders.
Exploratory analyses revealed that individuals with depression exhibited significantly higher levels of alexithymia compared to HC (Supplementary Figure 1). Alexithymia was positively associated with depression severity (Supplementary Table S6), consistent with prior findings (). Among depressed individuals, alexithymia was significantly negatively correlated with social sharing (Supplementary Table S4). This aligns with evidence that alexithymia is linked to reduced use of adaptive strategies and increased reliance on maladaptive ones (). Given the social function of emotions in communicating internal states and eliciting responses (), social sharing can be understood as an interpersonal strategy that relies on emotional expression to obtain support. Difficulties in these processes, as seen in alexithymia, may therefore hinder social sharing, particularly in depression and among individuals with adverse childhood experiences, who often struggle with emotional communication (). These findings suggest a potential pathway whereby childhood maltreatment contributes to elevated alexithymia (; ), which may impair interpersonal ER (), and increase vulnerability to depressive symptoms (). Future research should test this sequence empirically to clarify the interplay between early adversity, alexithymia, and interpersonal ER in depression.
In addition, post-hoc analyses revealed mixed associations between reappraisal and childhood maltreatment. Emotional abuse, sexual abuse, and physical neglect were associated with higher reappraisal use, whereas physical abuse and emotional neglect were associated with lower reappraisal use. Given the small sample size and multiple comparisons without statistical adjustment, these findings should be considered preliminary and interpreted with caution. Moreover, the low internal consistency of the physical neglect subscale in the present sample further limits the interpretation and stability of its association with reappraisal. However, prior evidence suggests that childhood maltreatment may limit the capacity to implement reappraisal effectively (), indicating that increased reappraisal attempts might not achieve the desired regulation of negative affect and could be linked to tendencies such as emotional withdrawal. This process should be interpreted with caution due to limited empirical evidence supporting such mechanisms. The observed mixed pattern also complicates clear conclusions regarding the role of reappraisal in close interpersonal contexts. In light of , childhood maltreatment may be most informative when examined using cluster-based approaches. However, this was not feasible here due to the small sample size, which can produce unstable clustering solutions (; ). Traditional CTQ subscales may oversimplify the complexity of early adversity and its links to ER and interpersonal functioning. Future research should therefore apply cluster-based methods to better capture maltreatment profiles and their implications for depression and ER.
Although reappraisal is typically considered an adaptive strategy, reliance on self-report may introduce bias (), limiting conclusions about its effective implementation. Accordingly, reported reappraisal may reflect maladaptive cognitive processes such as minimization (downplaying the importance of negative events) or avoidance (trying to escape negative feelings). Future research should clarify the conditions under which reappraisal is beneficial and develop more objective measures of its use.
Regarding the hypothesis of elevated suppression in depressed individuals, several factors may explain the lack of significant group differences. First, item wording for suppression may have led to misunderstandings (see Supplementary Table S1). Second, suppression may be emotion-specific, and averaging across emotions could have reduced sensitivity. Third, responses may reflect habitual rather than situation-specific tendencies.
Depressive participants also reported substantially fewer close interpersonal interactions than HC (34.5% vs. 59.2%). This imbalance may have reduced statistical power to detect between-group differences. Moreover, the unequal frequency of close interactions may have resulted in systematic differences in the interpersonal contexts sampled across groups, thereby limiting the comparability of the observed experiences. Thus, the lack of significant group differences should be interpreted cautiously and may not necessarily indicate true regulatory equivalence.
4.1 Limitations
As the sensitivity analysis revealed, the present study was limited in statistical power and therefore primarily sensitive to relatively large between-group effects. Furthermore, the study relied solely on self-report measures of ER strategy use, which may not accurately reflect actual behavior or strategy effectiveness. The EMA single-item measures in the present study were adopted from previously published EMA protocols () and have been used in subsequent research (). Although similar single-item EMA measures have shown evidence of reliability and validity (), the specific measures used in the present study have not been formally validated. Their use may therefore not fully capture the complexity of each ER strategy and may limit the generalizability of the findings. Finally, a single baseline assessment of depressive symptoms may not capture temporal fluctuations.
Despite these limitations, the findings may tentatively indicate that individuals with depression, particularly those with higher symptom severity, could engage less in social interactions, which might be relevant for ER use in close relationships. Future studies should employ larger samples, repeatedly assess depressive symptoms, and consider momentary affect to further clarify mechanisms of interpersonal ER in depression.
5 Conclusion
In summary, no distinct maladaptive ER pattern emerged between depressed and healthy participants in close relationships. Given the small sample size, smaller or moderate group differences may have gone undetected. Cognitive reappraisal may nevertheless be influenced by specific adverse childhood experiences in depressed individuals, which may lead to either increased or decreased use of reappraisal depending on the type of maltreatment. This suggests that, despite being generally adaptive, reappraisal may be less effective or more complex in close interpersonal interactions among those with depressive disorders. Additionally, the study found that higher alexithymia was associated with reduced social sharing among individuals with depressive disorders, highlighting the importance of considering alexithymia in understanding and addressing interpersonal ER difficulties in depressive disorders. Overall, the present findings provide valuable insights and directions for future research on ER and depression. While some results were conflicting, they highlight important associations and mechanisms that warrant further investigation, particularly regarding the influence of social context (i.e., close interpersonal contexts), comorbid alexithymia, and histories of childhood maltreatment on ER patterns in depressive disorders.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Ethikkommission—Ethikausschuss am Campus Benjamin Franklin. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
PKLV: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualisation, Writing – original draft, Writing – review & editing. KO: Methodology, Writing – review & editing, Formal analysis, Validation. LD: Conceptualization, Methodology, Validation, Writing – review & editing. SK: Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing, Project administration, Validation.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This study was conducted at Charité—Universitätsmedizin Berlin.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2026.1773706/full#supplementary-material
References
1
AbravanelB. T.SinhaR. (2015). Emotion dysregulation mediates the relationship between lifetime cumulative adversity and depressive symptomatology. J. Psychiatr. Res.61, 89–96. doi: 10.1016/j.jpsychires.2014.11.012,
2
AldaoA.Nolen-HoeksemaS. (2012). The influence of context on the implementation of adaptive emotion regulation strategies. Behav. Res. Ther.50, 493–501. doi: 10.1016/j.brat.2012.04.004,
3
AldaoA.Nolen-HoeksemaS.SchweizerS. (2010). Emotion-regulation strategies across psychopathology: a meta-analytic review. Clin. Psychol. Rev.30, 217–237. doi: 10.1016/j.cpr.2009.11.004,
4
Armbruster-GençD. J. N.SpilgerE.BastenU. (2025). Emotion regulation after childhood maltreatment: suppression tendency and reappraisal capacity. Child Abuse Negl.166:107511. doi: 10.1016/j.chiabu.2025.107511,
5
BatesD.MächlerM.BolkerB.WalkerS. (2015). Fitting linear mixed-effects models using lme4. J. Stat. Softw.67, 1–48. doi: 10.18637/jss.v067.i01
6
BeckA. T.SteerR. A.BrownG. (1996). Manual for Beck Depression Inventory II (BDI-II). San Antonio, TX: Psychology Corporation. doi: 10.1037/t00742-000
7
BernsteinD. P.SteinJ. A.NewcombM. D.WalkerE.PoggeD.AhluvaliaT.et al. (2003). Development and validation of a brief screening version of the childhood trauma questionnaire. Child Abuse Negl.27, 169–190. doi: 10.1016/S0145-2134(02)00541-0,
8
BuhleJ. T.SilversJ. A.WagerT. D.LopezR.OnyemekwuC.KoberH.et al. (2014). Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies. Cereb. Cortex24, 2981–2990. doi: 10.1093/cercor/bht154,
9
ChapmanD. P.WhitfieldC. L.FelittiV. J.DubeS. R.EdwardsV. J.AndaR. F. (2004). Adverse childhood experiences and the risk of depressive disorders in adulthood. J. Affect. Disord.82, 217–225. doi: 10.1016/j.jad.2003.12.013,
10
ChoiG.SohE.YoonS. (2025). The role of depression in relationships between reappraisal affordances, choice, and success. Clin. Psychopharmacol. Neurosci.23, 628–637. doi: 10.9758/cpn.25.1300,
11
EndersC. K. (2022). Applied Missing Data Analysis. New York: Guilford Publications.
12
GobbiniM. I.LeibenluftE.SantiagoN.HaxbyJ. V. (2004). Social and emotional attachment in the neural representation of faces. NeuroImage22, 1628–1635. doi: 10.1016/j.neuroimage.2004.03.049,
13
GoerigkS.ElsaesserM.ReinhardM. A.KristonL.HärterM.HautzingerM.et al. (2024). Childhood trauma questionnaire-based child maltreatment profiles to predict efficacy of the cognitive behavioral analysis system of psychotherapy versus non-specific psychotherapy in adults with early-onset chronic depression: cluster analysis of data from a randomised controlled trial. Lancet Psychiatry11, 709–719. doi: 10.1016/S2215-0366(24)00209-8,
14
GreenP.MacLeodC. J. (2016). SIMR: an R package for power analysis of generalized linear mixed models by simulation. Methods Ecol. Evol.7, 493–498. doi: 10.1111/2041-210x.12504
15
GrossJ. J. (1998). The emerging field of emotion regulation: an integrative review. Rev. Gen. Psychol.2, 271–299. doi: 10.1037/1089-2680.2.3.271
16
GrossJ. J.JohnO. P. (2003). Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J. Pers. Soc. Psychol.85, 348–362. doi: 10.1037/0022-3514.85.2.348
17
GrossJ. J.MuñozR. F. (1995). Emotion regulation and mental health. Clin. Psychol. Sci. Pract.United Kingdom: Blackwell Publishing2, 151–164. doi: 10.1111/j.1468-2850.1995.tb00036.x
18
HainesS. J.GleesonJ.KuppensP.HollensteinT.CiarrochiJ.LabuschagneI.et al. (2016). The Wisdom to Know the Difference: Strategy-Situation Fit in Emotion Regulation in Daily Life is Associated with Well-Being. Thousand Oaks, California: Association for Psychological Science (SAGE).
19
HautzingerM.KellerF.KühnerC. (2023). Beck-Depressions-Inventar Revision (3. Aufl.). Pearson.
20
HogeveenJ.GrafmanJ. (2021). Alexithymia. Handb. Clin. Neurol.183, 47–62. doi: 10.1016/B978-0-12-822290-4.00004-9,
21
FalkaiP.WittchenH-U.DöpfnerM.GaebelW.MaierW.RiefW. (Hrsg.). (2025) Diagnostisches und Statistisches Manual Psychischer Störungen – Textrevision – DSM-5-TR®. Hogrefe.
22
HonkalampiK.FlinkN.LehtoS. M.RuusunenA.Koivumaa-HonkanenH.Valkonen-KorhonenM.et al. (2020). Adverse childhood experiences and alexithymia in patients with major depressive disorder. Nord. J. Psychiatry74, 45–50. doi: 10.1080/08039488.2019.1667430,
23
HovensJ. G. F. M.GiltayE. J.WiersmaJ. E.SpinhovenP.PenninxB. W. J. H.ZitmanF. G. (2012). Impact of childhood life events and trauma on the course of depressive and anxiety disorders. Acta Psychiatr. Scand.126, 198–207. doi: 10.1111/j.1600-0447.2011.01828.x,
24
KaemmererM.GrüningD. J.LuminetO.PreeceD.German translation of the Perth alexithymia questionnaire. PsyArXiv; (2021). Available online at: https://osf.io/gj5e3 (accessed February 22, 2023)
25
KeltnerD.GrossJ. J. (1999). Functional accounts of emotions. Cogn. Emot.13, 467–480. doi: 10.1080/026999399379140
26
KhanA. N.JaffeeS. R. (2022). Alexithymia in individuals maltreated as children and adolescents: a meta-analysis. J. Child Psychol. Psychiatry63, 963–972. doi: 10.1111/jcpp.13616,
27
KhatibiA.SharpeL.DehghaniM.GhalibafE.HosseinchiP.MazidiM.et al. (2021). Suppression may improve adaptation to worry when facing uncertainty: studying COVID-19 pandemic. Front. Psych.12:778375. doi: 10.3389/fpsyt.2021.778375,
28
KlinitzkeG.RomppelM.HäuserW.BrählerE.GlaesmerH. (2012). The German version of the childhood trauma questionnaire (CTQ): psychometric characteristics in a representative sample of the general population. Psychother. Psychosom. Med. Psychol.62, 47–51. doi: 10.1055/s-0031-1295495,
29
LakeyB.CroninA. (2008). “Low social support and major depression: research, theory and methodological issues,” in Risk Factors in depression, eds. Keith S. Dobson, David J.A. Dozois (San Diego: Elsevier Academic Press), 385–408.
30
MargrafJ.CwikJ. C.Mini-DIPS Open Access: Diagnostisches Kurzinterview bei psychischen Störungen. Bochum, Germany: OMP Ruhr-Universität Bochum. (2020). Available online at: https://omp.ub.rub.de/index.php/RUB/catalog/book/102 (accessed August 19, 2025)
31
MarroquínB. (2011). Interpersonal emotion regulation as a mechanism of social support in depression. Clin. Psychol. Rev.31, 1276–1290. doi: 10.1016/j.cpr.2011.09.005,
32
MarroquínB.Nolen-HoeksemaS. (2015). Emotion regulation and depressive symptoms: close relationships as social context and influence. J. Pers. Soc. Psychol.109, 836–855. doi: 10.1037/pspi0000034,
33
MorawetzC.BerbothS.BodeS. (2021). With a little help from my friends: the effect of social proximity on emotion regulation-related brain activity. NeuroImage230:117817. doi: 10.1016/j.neuroimage.2021.117817,
34
movisens GmbH. Experience Sampling Platform—movisensXS. Available online at: https://www.movisens.com/en/products/movisensxs/ (accessed September 22, 2025).
35
MuellerI.PruessnerL.HoltD. V.ZimmermannV.SchulzeK.StrakoschA.-M.et al. (2024). If it Ain’t broke, Don’t fix it: positive versus negative emotion regulation in daily life and depressive symptoms. J. Affect. Disord.348, 398–408. doi: 10.1016/j.jad.2023.12.037,
36
NanniV.UherR.DaneseA. (2012). Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: a meta-analysis. Am. J. Psychiatry169, 141–151. doi: 10.1176/appi.ajp.2011.11020335,
37
NowickiP. (2025). The severity of alexithymia and difficulties in extrinsic and intrinsic interpersonal emotion regulation. Adv. Cogn. Psychol.21, 11–18. doi: 10.5709/acp-0443-2
38
Nylund-GibsonK.ChoiA. Y. (2018). Ten frequently asked questions about latent class analysis. Transl. Issues Psychol. Sci.4, 440–461. doi: 10.1037/tps0000176
39
PachecoA. M.ZetscheU.NeumannP.Sanchez-LopezA.VázquezC.KosterE. H. W.et al. (2026). Regulating affect through prohedonic goals in major depressive disorder: an experience sampling study. Behav. Ther.57, 835–848. doi: 10.1016/j.beth.2026.03.004,
40
PaulS.PruessnerL.StrakoschA.-M.MianoA.SchulzeK.BarnowS. (2023). Examining the strategy-situation fit of emotion regulation in everyday social contexts. Emotion23, 1971–1984. doi: 10.1037/emo0001209,
41
PauwL. S.MedlandH.PalingS. J.MoeckE. K.GreenawayK. H.KalokerinosE. K.et al. (2022). Social support predicts differential use, but not differential effectiveness, of expressive suppression and social sharing in daily life. Affect. Sci.3, 641–652. doi: 10.1007/s42761-022-00123-8,
42
PennebakerJ. W.HarberK. D. (1993). A social stage model of collective coping: the Loma Prieta earthquake and the Persian Gulf war. J. Soc. Issues49, 125–145. doi: 10.1111/j.1540-4560.1993.tb01184.x
43
PetschauerS.FrankeG. H.HäringM.BlaserM.Jagla-FrankeM. (2022). Emotion regulation in patients with a depressive episode. Open Conf. Proc.2, 1–7. doi: 10.52825/ocp.v2i.153
44
PodsakoffP. M.MacKenzieS. B.LeeJ.-Y.PodsakoffN. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol.88, 879–903. doi: 10.1037/0021-9010.88.5.879
45
PreeceD.BecerraR.RobinsonK.DandyJ.AllanA. (2018). The psychometric assessment of alexithymia: Development and validation of the Perth Alexithymia Questionnaire. Personality and Individual Differences, 132, 32–44. doi: 10.1016/j.paid.2018.05.011
46
PreeceD. A.MehtaA.PetrovaK.SikkaP.BjurebergJ.BecerraR.et al. (2023). Alexithymia and emotion regulation. J. Affect. Disord.324, 232–238. doi: 10.1016/j.jad.2022.12.065,
47
PruessnerL.HoltD. V.HartmannS.SchulzeK.BarnowS. (2023). Moving emotion regulation measurement to everyday life: reliability and validity of ecological momentary assessment. Affect. Sci.4, 191–198. doi: 10.1007/s42761-022-00172-z
48
RiméB. (2009). Emotion elicits the social sharing of emotion: theory and empirical review. Emot. Rev.1, 60–85. doi: 10.1177/1754073908097189
49
SagarR.TalwarS.DesaiG.ChaturvediS. K. (2021). Relationship between alexithymia and depression: a narrative review. Indian J. Psychiatry63, 127–133. doi: 10.4103/psychiatry.IndianJPsychiatry_738_19,
50
SchraubE. M.StegmaierR.SonntagK. (2011). The effect of change on adaptive performance: does expressive suppression moderate the indirect effect of strain?J. Chang. Manag.11, 21–44. doi: 10.1080/14697017.2010.514002
51
SchraubE. M.TurgutS.ClavairolyV.SonntagK. (2013). Emotion regulation as a determinant of recovery experiences and well-being: a day-level study. Int. J. Stress. Manag.20, 309–335. doi: 10.1037/a0034483
52
SegrinC.FloraJ. (1998). Depression and verbal behavior in conversations with friends and strangers. J. Lang. Soc. Psychol.(US: Sage Publications)17, 492–503.
53
ShiffmanS.StoneA. A.HuffordM. R. (2008). Ecological momentary assessment. Annu. Rev. Clin. Psychol.4, 1–32. doi: 10.1146/annurev.clinpsy.3.022806.091415,
54
TeinJ.-Y.CoxeS.ChamH. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Struct. Equ. Modeling20, 640–657. doi: 10.1080/10705511.2013.824781,
55
TroyA. S.ShallcrossA. J.MaussI. B. (2013). A person-by-situation approach to emotion regulation: cognitive reappraisal can either help or hurt, depending on the context. Psychol. Sci.24, 2505–2514. doi: 10.1177/0956797613496434,
56
VistedE.VøllestadJ.NielsenM. B.SchancheE. (2018). Emotion regulation in current and remitted depression: a systematic review and Meta-analysis. Front. Psychol.9:756. doi: 10.3389/fpsyg.2018.00756,
57
VosT.AllenC.AroraM.BarberR. M.BhuttaZ. A.BrownA.et al. (2016). Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the global burden of disease study 2015. Lancet388, 1545–1602. doi: 10.1016/S0140-6736(16)31678-6
58
WagnerU.GalliL.SchottB. H.WoldA.van der SchalkJ.MansteadA. S. R.et al. (2015). Beautiful friendship: social sharing of emotions improves subjective feelings and activates the neural reward circuitry. Soc. Cogn. Affect. Neurosci.10, 801–808. doi: 10.1093/scan/nsu121
59
World Health Organization (WHO). Depressive Disorder (Depression). Geneva, Switzerland: WHO (2023). Available online at: https://www.who.int/news-room/fact-sheets/detail/depression (accessed July 10, 2025)
60
YinW.PanY.ZhouL.WeiQ.ZhangS.HuH.et al. (2022). The relationship between childhood trauma and depressive symptom among Zhuang adolescents: mediating and moderating effects of cognitive emotion regulation strategies. Front. Psych.13:994065. doi: 10.3389/fpsyt.2022.994065
Keywords
alexithymia, childhood maltreatment, cognitive reappraisal, depression, ecological momentary assessment (EMA), emotion regulation, social sharing, suppression
Citation
Vu PKL, Ollrogge K, Daldrup L and Köhler S (2026) Interpersonal emotion regulation in daily life: a comparison of individuals with and without depressive disorders. Front. Psychol. 17:1773706. doi: 10.3389/fpsyg.2026.1773706
Received
24 December 2025
Revised
02 September 2026
Accepted
04 September 2026
Published
30 September 2026
Volume
17 - 2026
Updates
Copyright
© 2026 Vu, Ollrogge, Daldrup and Köhler.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Karen Ollrogge karen-anna.ollrogge@charite.de
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
来源：Frontiers in Psychology · frontiersin.org
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