Shared Distress Normalisation Theory (SDNT): Indirect Pathways to Psychological Relief via Resilience and Loneliness ()
1. Introduction
Psychological distress is a prevalent and multifaceted experience, encompassing symptoms such as anxiety, depression, and emotional strain. Established approaches to understanding and alleviating distress have primarily focused on active coping strategies, therapeutic interventions, and the protective role of social support (Lazarus & Folkman, 1984; Cohen & Wills, 1985). While these approaches have demonstrated substantial effectiveness, they largely emphasise behavioural and interpersonal mechanisms of psychological relief, with comparatively less attention given to internal cognitive-perceptual processes through which individuals interpret and contextualise their experiences.
One such process involves recognising that personal distress is not unique, but shared by others. Within psychological literature, this concept is reflected in the construct of common humanity, a central component of self-compassion, defined as perceiving one’s difficulties as part of the broader human experience rather than as isolated or personal failures (Neff, 2003). Empirical evidence has consistently linked self-compassion, particularly its common humanity component, to lower levels of psychological distress, enhanced resilience, and improved perceptions of social connectedness (Neff, 2003; Neff & Germer, 2013; Zessin et al., 2015).
In parallel, resilience has been widely recognised as a key protective factor in psychological wellbeing, reflecting the capacity to adapt to stress and adversity (Smith et al., 2008). Conversely, loneliness—defined as the subjective perception of social isolation—has been strongly associated with increased psychological distress and adverse mental health outcomes (Hawkley & Cacioppo, 2010; Heinrich & Gullone, 2006). Together, these constructs highlight the importance of how individuals cognitively and emotionally frame their experiences, particularly in relation to perceived connectedness versus isolation.
Existing psychological frameworks have addressed aspects of shared experience primarily through active processes. For example, self-compassion involves intentional cognitive and emotional reframing of personal difficulties (Neff, 2003), while cognitive reappraisal requires deliberate reinterpretation of emotional experiences (Gross, 1998). Similarly, therapeutic normalisation techniques and social support models often rely on interpersonal interaction or guided cognitive engagement to reduce distress (Cohen & Wills, 1985). While these approaches are effective, they are inherently effortful and intervention-based. In contrast, the present study proposes that the mere awareness that one’s distress is shared by others—without deliberate cognitive effort or direct interaction—may itself contribute to psychological relief. This distinction highlights a potentially underexplored passive mechanism of psychological adjustment.
Despite these insights, existing research has predominantly examined these constructs either independently or within broader frameworks such as self-compassion. There remains limited theoretical development specifically addressing whether the awareness of shared distress itself may function as a distinct cognitive mechanism of psychological adjustment. In particular, it remains unclear whether such awareness directly reduces psychological distress or whether its effects operate indirectly through related processes such as enhanced resilience and reduced perceived loneliness.
Although SDNT overlaps conceptually with related ideas such as common humanity within self-compassion, social comparison, and psychological normalisation, it proposes a more specific explanatory mechanism. SDNT suggests that the passive recognition of one’s distress as part of a shared human experience may itself influence psychological adjustment, even in the absence of deliberate emotional regulation, active coping, or direct interpersonal support. In this respect, SDNT differs from self-compassion models, which typically involve broader affective and regulatory components, and from social comparison models, which often depend on evaluative judgments about the self in relation to others. A key testable prediction of SDNT is that shared distress awareness will be associated with lower psychological distress primarily through indirect pathways, such as greater resilience and lower loneliness, rather than through a strong direct independent effect.
To address this gap, the present study introduces Shared Distress Normalisation Theory (SDNT). SDNT proposes that psychological relief may arise not necessarily from active coping or direct interpersonal support, but from the passive cognitive recognition that one’s distress is part of a shared human condition. This recognition may reduce perceived isolation and facilitate adaptive psychological responses, thereby contributing to improved psychological outcomes. Importantly, SDNT extends existing frameworks by conceptualising shared distress awareness as a potentially independent cognitive mechanism, rather than solely as a component of broader constructs such as self-compassion.
The present study aims to examine the relationships between common humanity, psychological distress, resilience, and loneliness, and to test whether the association between shared distress awareness and psychological distress operates indirectly through resilience and loneliness. By empirically investigating these relationships, this study seeks to provide initial support for SDNT and to contribute to a more precise understanding of cognitive-perceptual mechanisms underlying psychological wellbeing.
Based on SDNT, it was hypothesised that higher levels of shared distress awareness (common humanity) would be associated with lower psychological distress, higher resilience, and lower loneliness. It was further hypothesised that resilience and loneliness would function as parallel pathways through which shared distress awareness influences psychological distress. Specifically, higher shared distress awareness was expected to be associated with greater resilience and lower loneliness, which in turn would be associated with lower psychological distress. The relationship between shared distress awareness and psychological distress was therefore expected to be attenuated when resilience and loneliness are included in the regression model, consistent with an indirect pathway.
This parallel pathway conceptualisation is supported by evidence indicating that resilience and perceived social connectedness independently contribute to psychological outcomes (Hawkley & Cacioppo, 2010; Smith et al., 2008).
2. Method
2.1. Study Design
A quantitative cross-sectional survey design was used to examine associations between shared distress normalisation (operationalised as common humanity), psychological distress, loneliness, and resilience in adults. This design enabled the assessment of relationships between variables at a single time point.
2.2. Participants
Participants were adults aged 18 years or older recruited from the general population. Inclusion criteria required participants to be fluent in English and able to provide informed consent. Individuals under 18 years were excluded.
Participants were recruited using online convenience sampling through distribution of a survey link via LinkedIn and personal professional networks, including colleagues from diverse national backgrounds. Recruitment was not restricted to specific countries; however, the use of professional networks may have influenced the demographic composition of the sample. Participation was voluntary and no incentives were offered.
An a priori power analysis conducted using G*Power (α = .05, power = .80, medium effect size) indicated a minimum required sample size of 120 participants. The final sample consisted of 145 participants.
2.3. Measures
All variables were assessed using validated self-report measures.
Shared distress normalisation was operationalised using the Common Humanity subscale of the Self-Compassion Scale (Neff, 2003), which consists of 4 items. Responses are rated on a 5-point Likert scale ranging from 1 (“almost never”) to 5 (“almost always”), with total scores ranging from 4 to 20. Higher scores indicate greater endorsement of common humanity. Reverse scoring was applied to negatively worded items in accordance with scale guidelines.
Psychological distress was measured using the Kessler Psychological Distress Scale (K10; Kessler et al., 2002), a 10-item measure assessing symptoms of anxiety and depression over the past four weeks. Responses are rated on a 5-point Likert scale ranging from 1 (“none of the time”) to 5 (“all of the time”), with total scores ranging from 10 to 50. Higher scores indicate greater psychological distress. No reverse scoring is required.
Loneliness was assessed using the UCLA Loneliness Scale-Short Form (ULS-8; Hays & DiMatteo, 1987), an 8-item measure of perceived social isolation. Responses are rated on a 4-point Likert scale ranging from 1 (“never”) to 4 (“often”), with total scores ranging from 8 to 32. Higher scores indicate greater loneliness. Reverse scoring was applied where appropriate.
Resilience was measured using the Brief Resilience Scale (BRS; Smith et al., 2008), which consists of 6 items assessing the ability to recover from stress. Responses are rated on a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), with total scores ranging from 6 to 30. Higher scores indicate greater resilience. Reverse scoring was applied to negatively worded items in accordance with scale guidelines.
2.4. Procedure
The study was conducted online using QuestionPro. Participants accessed the survey via a distributed link, reviewed the participant information sheet, and provided informed consent prior to participation.
Participants completed demographic items followed by the study measures in a fixed order. The survey required approximately 10 minutes to complete. Participants could withdraw prior to submission by exiting the survey. A debrief page provided additional information and support resources.
Ethical approval for this study was obtained from the University of Wolverhampton Ethics Committee. The study adhered to British Psychological Society ethical guidelines, and participation was voluntary and anonymous.
2.5. Data Analysis
Data were analysed using IBM SPSS Statistics (Version 27). Descriptive statistics were calculated for all variables. Normality was assessed using the Shapiro-Wilk test, indicating non-normal distributions.
Spearman’s rank-order correlation was used to examine associations between variables. Simple linear regression analyses were conducted to assess associations between shared distress normalisation and each outcome variable (resilience, loneliness, and psychological distress).
Resilience and loneliness were conceptualised as parallel predictors in the model, reflecting independent pathways through which shared distress awareness may influence psychological distress. A multiple regression analysis was conducted with psychological distress as the dependent variable and common humanity, resilience, and loneliness entered simultaneously to examine their relative contributions and potential indirect associations, consistent with SDNT.
Statistical significance was set at α = .05.
3. Results
3.1. Data Preparation and Screening
Data were collected via an online survey platform over a five-week period. Responses were screened for completeness and validity prior to analysis. Cases with missing psychometric scale data were excluded.
A total of 626 individuals accessed the survey, of whom 259 initiated participation and 195 completed the survey. Following data screening, 31 responses were excluded due to missing psychometric data and a further 19 due to incomplete scale responses. The final analytic sample consisted of 145 participants with complete data.
Reverse scoring was applied where appropriate, and total scores were computed for all measures prior to analysis.
3.2. Participant Characteristics
The final sample (N = 145) consisted of adults aged 18 years and above. The largest age group was 35 - 44 years (44.1%). The sample was relatively balanced by gender (55.2% female, 44.1% male).
Participants were predominantly highly educated, with the majority holding at least a bachelor’s degree. Most participants were employed full-time (86.2%). The sample was culturally diverse, with over half residing in Saudi Arabia (53.8%) and representation from multiple countries.
Demographic characteristics are presented in Table 1.
Table 1. Demographic characteristics of the sample (N = 145).
Variable |
N |
% |
Age group |
|
|
18 - 24 years |
5 |
3.4 |
25 - 34 years |
25 |
17.2 |
35 - 44 years |
64 |
44.1 |
45 - 54 years |
39 |
26.9 |
55+ years |
12 |
8.3 |
Gender |
|
|
Male |
64 |
44.1 |
Female |
80 |
55.2 |
Other/prefer not to say |
1 |
.7 |
Education level |
|
|
High school |
1 |
.7 |
Diploma |
8 |
5.5 |
Bachelor’s degree |
60 |
41.4 |
Master’s degree |
42 |
29.0 |
Doctorate |
33 |
22.8 |
Other |
1 |
.7 |
Employment status |
|
|
Student |
1 |
.7 |
Employed full-time |
125 |
86.2 |
Employed part-time |
14 |
9.7 |
Unemployed |
2 |
1.4 |
Retired |
2 |
1.4 |
Country of current residence |
|
|
Saudi Arabia |
78 |
53.8 |
United Kingdom |
18 |
12.4 |
United States |
16 |
11.0 |
United Arab Emirates/Dubai |
8 |
5.5 |
Other countries* |
25 |
17.3 |
Nationality |
|
|
Saudi Arabian |
22 |
15.2 |
British |
21 |
14.5 |
Filipino |
14 |
9.7 |
Egyptian |
11 |
7.6 |
Jordanian |
10 |
6.9 |
American |
10 |
6.9 |
Indian |
9 |
6.2 |
Yemeni |
9 |
6.2 |
Sudanese |
8 |
5.5 |
South African |
6 |
4.1 |
Syrian |
5 |
3.4 |
Other nationalities* |
20 |
13.8 |
*Other countries and nationalities include low-frequency responses (N ≤ 3 each).
3.3. Reliability Analysis
Internal consistency reliability was assessed using Cronbach’s alpha. All measures demonstrated excellent reliability: common humanity (α = .955), psychological distress (α = .979), resilience (α = .903), and loneliness (α = .974).
Reliability coefficients are presented in Table 2.
Table 2. Internal consistency reliability of study measures (N = 145).
Scale |
Number of Items |
Cronbach’s α |
Common Humanity (Neff, 2003) |
4 |
.955 |
Psychological Distress (K10) |
10 |
.979 |
Brief Resilience Scale (BRS) |
6 |
.903 |
UCLA Loneliness Scale (ULS-8) |
8 |
.974 |
3.4. Descriptive Statistics
Descriptive statistics for all study variables are presented in Table 3. Mean scores indicated relatively high levels of common humanity (M = 16.57, SD = 4.36), moderate levels of psychological distress (M = 18.14, SD = 10.95), and moderate to high levels of resilience (M = 22.06, SD = 6.34). Loneliness scores demonstrated variability across participants (M = 13.54, SD = 8.05).
Table 3. Descriptive statistics for study variables (N = 145).
Variable |
Minimum |
Maximum |
Mean |
Standard Deviation |
Common Humanity (CH_total) |
5 |
20 |
16.57 |
4.36 |
Psychological Distress (K10_total) |
10 |
48 |
18.14 |
10.95 |
Resilience (BRS_total) |
6 |
30 |
22.06 |
6.34 |
Loneliness (ULS_total) |
8 |
32 |
13.54 |
8.05 |
3.5. Distribution of Data
The distribution of study variables was examined using the Shapiro-Wilk test of normality. All variables showed significant deviations from normality (p < .001), as presented in Table 4.
Given these findings, non-parametric analyses were used for correlation testing. Regression analyses were conducted following inspection of residuals, which indicated no substantial violations of assumptions.
Table 4. Shapiro-Wilk tests of normality for study variables (N = 145).
Variable |
Statistic |
df |
p |
Common Humanity (CH_total) |
.779 |
145 |
<.001 |
Psychological Distress (K10_total) |
.752 |
145 |
<.001 |
Resilience (BRS_total) |
.866 |
145 |
<.001 |
Loneliness (ULS_total) |
.696 |
145 |
<.001 |
3.6. Correlation Analysis
Spearman’s rank-order correlation analysis revealed significant associations among all study variables, as presented in Table 5.
Common humanity was strongly negatively correlated with psychological distress (rs = −.777, p < .001), strongly positively correlated with resilience (rs = .778, p < .001), and strongly negatively correlated with loneliness (rs = −.756, p < .001).
Psychological distress was strongly negatively associated with resilience (rs = −.847, p < .001) and strongly positively associated with loneliness (rs = .844, p < .001). Resilience and loneliness were also strongly negatively correlated (rs = −.796, p < .001).
Table 5. Spearman’s rank-order correlations between study variables (N = 145).
Variable |
1 |
2 |
3 |
4 |
1. Common Humanity |
— |
|
|
|
2. Psychological Distress |
−.777** |
— |
|
|
3. Resilience |
.778** |
−.847** |
— |
|
4. Loneliness |
−.756** |
.844** |
−.796** |
— |
**p < .001 (two-tailed).
3.7. Simple Regression Analyses
Simple linear regression analyses were conducted to examine associations between common humanity and key psychological outcomes.
Common humanity was positively associated with resilience (β = .851, p < .001), accounting for 72.4% of variance (R2 = .724). It was negatively associated with loneliness (β = −.878, p < .001), accounting for 77.1% of variance (R2 = .771), and negatively associated with psychological distress (β = −.853, p < .001), accounting for 72.8% of variance (R2 = .728).
3.8. Regression Assumptions
Multicollinearity diagnostics indicated Variance Inflation Factor (VIF) values ranging from 4.92 to 6.22 and tolerance values ranging from .161 to .203, as presented in Table 6.
These values indicate moderate multicollinearity, reflecting the strong interrelationships among common humanity, resilience, and loneliness. This degree of overlap is consistent with the conceptual relatedness of these constructs, which are all linked to broader cognitive and emotional processes such as perceived connectedness and adaptive coping.
Inspection of residual plots indicated no substantial violations of linearity, homoscedasticity, or normality of residuals.
Table 6. Multicollinearity diagnostics of Variance Inflation Factor (VIF) and tolerance.
Predictor |
Tolerance |
VIF |
Common Humanity |
.203 |
4.92 |
Resilience |
.194 |
5.15 |
Loneliness |
.161 |
6.22 |
3.9. Multiple Regression Analysis
A multiple regression analysis was conducted with psychological distress as the dependent variable and common humanity, resilience, and loneliness entered simultaneously as predictors.
The overall model was statistically significant, F(3, 141) = 318.00, p < .001, explaining 87.1% of the variance in psychological distress (R2 = .871, adjusted R2 = .868).
Regression coefficients are presented in Table 7.
Table 7. Multiple regression analysis of variables associated with psychological distress (N = 145).
Predictor |
B |
SE |
β |
t |
p |
95% CI |
Constant |
18.19 |
4.44 |
— |
4.10 |
<.001 |
[9.41, 26.97] |
Common Humanity |
−.28 |
.17 |
−.11 |
−1.68 |
.095 |
[−.62, .05] |
Resilience |
−.34 |
.12 |
−.20 |
−2.84 |
.005 |
[−.57, −.10] |
Loneliness |
.89 |
.10 |
.65 |
8.68 |
<.001 |
[.69, 1.09] |
Loneliness was the strongest predictor of psychological distress (β = .654, p < .001), followed by resilience (β = −.195, p = .005). Common humanity was not a significant independent predictor when included in the model (β = −.113, p = .095).
4. Discussion
The present study examined the relationships between shared distress awareness (operationalised as common humanity), psychological distress, resilience, and loneliness to evaluate the central assumptions of Shared Distress Normalisation Theory (SDNT). Overall, the findings provide preliminary empirical support for the proposed framework.
Consistent with expectations, common humanity was strongly associated with lower psychological distress, higher resilience, and reduced loneliness. However, a key finding emerged from the regression analysis: although common humanity demonstrated strong bivariate associations with psychological distress, it was not independently associated with distress when resilience and loneliness were included in the model. This pattern is consistent with shared distress awareness operating primarily through indirect psychological pathways rather than exerting a direct effect on distress.
4.1. Interpretation in Relation to SDNT
These findings provide important insight into the mechanism proposed by SDNT. Rather than functioning as a direct emotion-regulation strategy, shared distress awareness appears to function as a cognitive-perceptual framing process through which individuals interpret their experiences.
Specifically, recognising distress as part of a shared human experience may reduce perceived isolation and support adaptive psychological responses. This interpretation is supported by the strong associations observed between common humanity, resilience, and loneliness, and by the finding that resilience and loneliness remained significant predictors of psychological distress in the multivariate model.
This pattern aligns with stress-buffering models, which suggest that psychological resources influence how stress is experienced rather than eliminating stress itself (Cohen & Wills, 1985). Within the SDNT framework, shared distress awareness may reduce the subjective impact of distress by altering its perceived meaning, thereby supporting resilience and reducing loneliness.
Importantly, SDNT differs from existing self-compassion frameworks. While common humanity is a component of self-compassion, SDNT conceptualises shared distress awareness as a broader cognitive mechanism rather than an active emotional regulation strategy. Self-compassion typically involves deliberate processes such as self-kindness and emotional regulation (Neff, 2003), whereas SDNT emphasises a passive cognitive recognition of shared experience. This distinction positions SDNT as a process-based interpretive framework rather than a dispositional trait or intervention-based construct.
4.2. Integration with Existing Literature
The findings are consistent with previous research demonstrating that components of self-compassion, particularly common humanity, are associated with lower psychological distress, greater resilience, and enhanced social connectedness (Neff & Germer, 2013; Zessin et al., 2015). Similarly, the strong association between loneliness and psychological distress aligns with extensive evidence highlighting loneliness as a significant determinant of mental health (Hawkley & Cacioppo, 2010). These findings reinforce the relevance of common humanity as a psychologically meaningful construct while supporting the SDNT proposition that its influence may operate through broader cognitive-perceptual pathways.
Importantly, the present study extends existing literature by examining these constructs within a single analytical framework and by identifying a pattern consistent with an indirect pathway linking shared distress awareness to psychological outcomes. By integrating cognitive appraisal (common humanity), emotional resilience, and perceived social connectedness, the findings contribute to a more comprehensive understanding of psychological adaptation.
At the same time, the very strong correlations observed between common humanity, resilience, and loneliness indicate substantial overlap among these constructs. This is further reflected in the multiple regression analysis, where common humanity did not contribute significant unique variance to psychological distress when resilience and loneliness were included. This pattern suggests that the influence of shared distress awareness may operate primarily through its association with broader psychological processes rather than as an independent predictor. Importantly, this does not diminish the theoretical relevance of SDNT, but rather supports its conceptualisation as a higher-order cognitive-perceptual mechanism that shapes resilience and perceived connectedness.
4.3. Theoretical Implications
The findings provide preliminary support for SDNT as a process-based framework describing how individuals cognitively interpret and respond to distress. Rather than representing a stable personality trait, shared distress normalisation appears to function as a dynamic cognitive-perceptual mechanism.
This distinction is theoretically important. Unlike dispositional constructs such as optimism or trait resilience, shared distress awareness may vary across contexts and may be influenced by cognitive framing processes. Identifying resilience and loneliness as key pathways through which SDNT operates refines the theoretical structure of the model and differentiates it from related constructs within positive psychology and self-compassion research.
4.4. Practical and Clinical Implications
The findings suggest that promoting awareness of shared distress may support psychological wellbeing by reducing perceived isolation and strengthening adaptive coping processes. Interventions that emphasise the universality of human suffering and normalisation of distress may enhance affiliative processes and reduce self-focused threat responses (Gilbert, 2009, 2014).
In organisational and educational settings, SDNT-informed approaches may be particularly relevant during periods of collective stress, offering a psychologically sustainable means of supporting wellbeing without requiring intensive intervention.
4.5. Limitations
Several limitations should be acknowledged. First, the cross-sectional design prevents causal conclusions regarding the direction of relationships among variables. Second, reliance on self-report measures introduces the possibility of response bias. Third, the sample was predominantly highly educated and required English fluency, which may limit generalisability to broader populations. In addition, a substantial proportion of participants resided in Saudi Arabia, which may influence the cultural interpretation of distress, resilience, and perceived social connectedness. These factors should be considered when interpreting the findings, and future research should examine SDNT across more diverse and culturally representative populations.
A further limitation concerns measurement specificity. SDNT was operationalised using the common humanity subscale of the Self-Compassion Scale, which captures an important component of the proposed theory but may not fully represent the broader construct of shared distress normalisation. The use of a proxy measure was appropriate for an initial empirical investigation but highlights the need for development of SDNT-specific measurement tools.
Additionally, indirect pathways were inferred from regression patterns rather than formally tested using mediation analysis. Future studies should apply statistical mediation models to directly examine these relationships.
4.6. Future Research
Future research should employ longitudinal designs to examine temporal relationships and causal pathways. Structural equation modelling and mediation analyses would allow direct testing of the indirect mechanisms proposed by SDNT. The development and validation of a dedicated SDNT measurement scale is a priority for advancing the theoretical framework.
Intervention studies may also examine whether shared distress awareness can be enhanced through psychoeducational or therapeutic approaches. Further research should explore the influence of individual differences, including personality traits, emotional intelligence, and cultural factors, on engagement with shared distress normalisation.
4.7. Conclusion
The present study provides initial empirical support for Shared Distress Normalisation Theory (SDNT). Recognising distress as a shared human experience was associated with greater resilience and lower loneliness, which in turn were associated with lower psychological distress.
These findings are consistent with shared distress awareness functioning as a cognitive-perceptual mechanism contributing to psychological adjustment. SDNT offers a theoretically grounded framework for understanding how individuals adapt to adversity by reframing distress as part of a shared human experience, providing a foundation for future empirical and applied research.