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Self-compassion and association with distress, depression, and anxiety among displaced Syrians: A population-based study
Self-compassion and association with depression and distress among displaced Syrians
https://orcid.org/0000-0002-9865-041X
Alsamman Sarah Conceptualization Data curation Formal analysis Writing – original draft 1
Dajani Rana Conceptualization Data curation Supervision Writing – review & editing 2 3
https://orcid.org/0000-0001-8292-0510
Al-Delaimy Wael K. Conceptualization Formal analysis Methodology Resources Supervision Writing – review & editing 4 *
1 University of California, San Diego School of Medicine, San Diego, California, United States of America
2 Department of Biology and Biotechnology, The Hashemite University, Zarqa, Jordan
3 MIT Refugee Action Hub (ReACT), Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
4 Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, California, United States of America
Uysal Mete Sefa Editor
University of Exeter, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
Competing Interests: The authors have declared that no competing interests exist.

* E-mail: waldelaimy@health.ucsd.edu
19 9 2024
2024
19 9 e030905121 12 2023
6 8 2024
© 2024 Alsamman et al
2024
Alsamman et al
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Displaced communities are at increased risk of poor mental health with limited resources for treatment. Self-compassion moderates the impacts of stressors on mental health in high-income country general population samples, but its impact has not been described among people who have experienced displacement and associated trauma. The aim of this study was to characterize the associations between self-compassion, mental health, and resilience in a sample of displaced Syrian adults living in Jordan. This is a cross-sectional study using four validated survey tools measuring self-compassion, resilience, mental health, and traumatic exposure. Syrian adults who presented to four different community organizations serving refugees within Amman, Jordan were invited to participate. A total of 272 displaced Syrians were included in the final analysis. A majority of those surveyed were positive for emotional distress (84.6%), depression (85.7%), and anxiety (76.5%). In univariate analysis there was a significant lower risk of emotional distress, depression, and anxiety, with both higher resilience and self-compassion. However, in the multivariate model only self-compassion remained significantly associated with less emotional distress, depression, and anxiety, independent of resilience and other covariates. Female gender, poor financial stability, and high levels of traumatic exposure were also identified as persistent predictors of mental health morbidity. The findings of this study suggest that self-compassion is associated with less distress, depression, and anxiety in displaced individuals; suggesting it might be protective against poor mental health. Self-compassion is a modifiable factor that can be utilized as a tool by healthcare professionals and communities caring for refugees to promote positive mental health outcomes.

T. Denny Sanford Institute for Empathy and Compassion https://orcid.org/0000-0002-9865-041X
Alsamman Sarah This study was funded by the T. Denny Sanford Institute for Empathy and Compassion at UC San Diego to support SA to conduct the study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data AvailabilityAll relevant data are within the manuscript and its Supporting Information files. we removed all identifying information.
Data Availability

All relevant data are within the manuscript and its Supporting Information files. we removed all identifying information.
==== Body
pmcIntroduction

More than a decade into the conflict, Syrians make up nearly one-third of displaced populations worldwide [1]. Since 2011, 6.8 million Syrians have been displaced, 5.6 million of whom are hosted in neighboring countries Turkey, Lebanon, Jordan, Iraq, and Egypt [1]. Refugees are exposed to numerous stressors pre-migration in their country of origin and during transit to a different country, including violence, torture, death of loved ones, and lack of healthcare and basic resources [2]. Post-migration, during resettlement, they face new challenges including discrimination, language barriers, and unemployment [2]. As a result of these stressors, refugee populations have a well-documented higher mental health morbidity with increased rates of post-traumatic stress disorder (PTSD), depression, and anxiety when compared to the general population [3]. In a systematic review of studies on mental health of refugees of various origins from 2003 to 2020 the prevalence of PTSD was 31.46%, the prevalence of depression was 31.5%, and the prevalence of anxiety was 11% [3]. A recent systematic review of 15 studies conducted in 10 different countries demonstrates Syrian refugees have a 10 times higher prevalence of PTSD (43%), anxiety (26%), and depression (40%) than the general population [4]. Understanding the factors that contribute to positive mental health despite suffering and trauma can aid in the development of interventions to improve mental health outcomes in these communities.

Resilience describes the individual positive response and adaptation to adversity. This concept encompasses both individual skills and attributes as well as supportive social environments and family networks that work in unison to overcome traumatic experiences [5]. Amongst cancer patients, resilience is associated with psychological adjustment in the setting of oncological treatment and its consequences [6]. Another study found that resilience is protective against postpartum depression in survivors of childhood trauma [7]. Some studies have demonstrated that resilience is a protective factor against development of psychopathology in refugees and recent immigrants, including Syrians [8, 9]. However, other studies report that resilience is not predictive of distress or mental health symptoms after major life events or traumatic experiences [10, 11]. Resilience is complex and multidimensional as it captures a set of individual traits within a social environment [12]. Therefore, interventions that effectively modulate resilience may act through other mechanisms like self-compassion to improve mental health outcomes.

Self-compassion is defined as being kind and understanding towards oneself, perceiving one’s experiences as part of the larger human experience, and holding painful thoughts and feelings in balanced awareness [13]. It has been shown to moderate the impact of stressors on mental health [14]. Studies have demonstrated the role of self-compassion in reducing depression and anxiety in the context of various stress exposures including chronic illness and domestic violence [14–17]. Additionally, self-compassion interventions in the general population are shown to effectively increase self-compassion and improve mental health [18]. Amongst refugees, the literature on self-compassion and mental health is growing. In a sample of Kurdish refugees resettled in Norway, self-compassion was associated with fewer symptoms of depression [19]. In a study of Eritrean asylum seekers in the Middle East, self-compassion was significantly modulated by a Mindfulness Based Trauma Recovery for Refugees intervention and mediated therapeutic effects on PTSD outcomes [20]. A singular qualitative study on the understanding of self-compassion in Hazara refugees in Australia identified views on self-compassion that could act as barriers to its application [21]. The existing studies on communities exposed to trauma does not take into consideration the role of resilience and the complex interrelationships with mental health.

The link between self-compassion and resilience is complex and only recently being explored in the literature. Some studies have shown that resilience is promoted by engagement in self-compassion [17, 22]. In a study of patients with Multiple Sclerosis, the relationship between self-compassion and health related quality of life is found to be mediated by resilience [17]. Another study reports that resilience mediates the effect of self-compassion on depression in a general population sample, but not anxiety [23]. Multiple studies demonstrate that self-compassion is a predictor of resilience [24, 25]. These are promising early indications of the positive impact that the interplay of self-compassion and resilience may have on mental health care and prevention.

Given the lack of resources, high rates of poor mental health outcomes among displaced peoples, and the feasibility of learning self-compassion, this study focuses on the relationship of self-compassion and mental health outcomes amongst Syrian refugees in limited resource settings. Self-compassion is a learned behavior that can help prevent or decrease severity of poor mental health outcomes, especially in lower resource settings with limited access to mental health care. However, there is a complex network between self-compassion, resilience, and mental health. The aims of this study were to investigate the impact of self-compassion on mental health in a population of displaced Syrians living in Jordan, and to explore this effect in relationship to resilience. Specifically, we aimed to assess how levels of self-compassion relate to the prevalence and severity of mental health problems and examine the strength of association between self-compassion and resilience in modulating mental health outcomes. We hypothesized that self-compassion is a strong predictor of poor mental health and positively correlated with resilience. Our study seeks to provide insight into the protective factors that contribute to psychological well-being and provide a path towards novel interventions for mental health care among displaced populations.

Materials and methods

Study population

Data was collected through a cross-sectional survey conducted in August 2021 in Amman Jordan. We recruited our target population through local refugee-serving community organizations. Inclusion criteria was being a Syrian refugee adult. A total of 335 participants were recruited through community organizations serving refugees in the Amman area. The research protocol created in partnership with a Jordanian community organization was approved by the University of California, San Diego Institutional Review Board. Community members were invited to the community organization to complete a survey. Community members were informed that completion of the survey was voluntary and that they could withdraw from the study at any time. Written consent was obtained from each participant, and they were subsequently provided with a paper survey in Arabic to complete on their own. Participants received a small gift to thank them for their participation.

Fifteen surveys completed verbally through an interviewer were excluded from the final analysis in order to minimize social desirability bias given the stigma associated with mental health in this community. One survey completed by a participant less than 18 years of age was also excluded from the final analysis. Ten participants did not report their ages on the survey. We did not exclude them and assumed they were above the age of 18.

Surveys received a quality score of 1 = minimal missing data, 2 = missing more than 50% of the data in one section, 3 = missing data in multiple sections. Only surveys with a quality score of 1 were included in the final analysis. In total, 47 surveys with a quality score of 2 or 3 were excluded from the final analysis. A total of 272 surveys were included in the final analysis.

Inclusivity in global research

Additional information regarding the ethical, cultural, and scientific considerations specific to inclusivity in global research is included in the Supporting Information (S1 Checklist).

Study measures

Participants were presented the following study measures in the order listed below.

a. Self-Compassion Scale—Short form (SCS) (Arabic translation)

The SCS is a self-administered 12-item questionnaire measuring the three components of self-compassion including self-kindness, common humanity, and mindfulness [26]. Questions encompass both positive (“When I’m going through a very hard time, I give myself the caring and tenderness I need”) and negative (“I’m disapproving and judgmental about my own flaws and inadequacies”) aspects of self-compassion. Items are rated on a five-point response scale ranging from 1 (almost never) to 5 (almost always). A total self-compassion score is computed by reversing the negative subscale items and then averaging all subscale scores. The highest score indicates the highest level of self-compassion. Although there are no clinical norms that differentiate between low, moderate, and high self-compassion, a categorization of low SCS = 1.0–2.49, moderate SCS = 2.5–3.5, high SCS = 3.51–5.0 has been suggested in the literature based on population sample means and standard deviations [27]. This categorization is applied here. The translated version has been validated in other Arabic-speaking populations [28]. The scale had a high level of internal consistency, as determined by a Cronbach’s alpha of 0.820.

b. Trauma Experiences Checklist (TEC) (Arabic translation)

The TEC is a self-administered questionnaire, which measures exposure to trauma. It consists of 20 traumatic experiences pertinent to displacement such as “Have you ever had your home forcibly searched by police or armed militia” and “Have you ever seen someone else severely beaten, shot, or killed” to which participants answer “Yes, experienced” or “No, did not experience”. The number of items answered “Yes, experienced” is totaled giving a final score. A higher score indicates exposure to more traumatic events. The TEC was created based on the Harvard Trauma Questionnaire and Gaza Traumatic Event Checklist [29]. It has been used in multiple settings involving Arabic-speaking displaced people [30, 31]. The scale had a high level of internal consistency, as determined by a Cronbach’s alpha of 0.864.

c. Hopkins Symptom Checklist (HSCL-25) (Arabic translation)

The HSCL-25 is a symptom inventory that measures adults’ symptoms of distress, depression, and anxiety. It consists of 25 items: Part 1 has 10 items for anxiety symptoms and includes statements like “Suddenly scare for no reason”. Part II has 15 items for depression symptoms and includes statements like “Feeling low in energy, slowed down”. The period of reference is the past month. The scale for each question includes four categories of response (“Not at all”, “A little”, “Quite a bit”, “Extremely” rated 1 to 4, respectively). Three scores are calculated: the emotional distress score is the average of all 25 items, the depression score is the average of the 15 depression items, and the anxiety score is the average of the 10 anxiety items. Total score is highly correlated with severe emotional distress of unspecified diagnosis, and the depression score is correlated with major depression as defined by the DSM-IV based on past studies [32, 33]. A score >1.75 was considered symptomatically positive in our analysis. This cutoff was based on validation in other Arabic-speaking populations and has been used in studies on mental health in Arabic-speaking refugees [34, 35]. We included all three scores in our analysis as suggested by a study validating this scale in Arabic [34]. The scale had a high level of internal consistency for emotional distress, depression, and anxiety subfactors, as determined by Cronbach’s alpha’s of 0.943, 0.892, and 0.902 respectively.

d. Connor-Davidson Resilience Scale (CD-RISC) (Arabic translation)

CD-RISC is a self-administered questionnaire of 25 items designed as a Likert type additive scale with five response options (0 = never; 4 = almost always) to statements such as “Sometimes fate or God can help”. The final score of the questionnaire is the sum of the responses obtained on each item and the highest scores indicated the highest level of resilience [36]. The translated version has been validated in other Arabic-speaking populations [37]. The scale had a high level of internal consistency, as determined by a Cronbach’s alpha of 0.927.

Data analysis

Data analysis was conducted using Microsoft Excel and SPSS Statistics Version 29.0.2.0 [38]. Normality of emotional distress, depression, and anxiety across self-compassion groups was assessed by a Shapiro-Wilks test. Mean emotional distress, depression, and anxiety were compared across low, moderate, and high self-compassion groups using Kruskal-Wallis H test. Distributions of distress, depression, and anxiety scores were similar for all groups as determined by visual inspection of boxplots. Post hoc pairwise comparisons were preformed using Dunn’s (1964) procedure with a Bonferroni correction. Adjusted p-values are presented. Mean SCS and CD-RISC scores are compared between groups with and without emotional distress, depression, and anxiety using a two-tailed t-test. Homogeneity of variances was confirmed by a Levene’s test for equality of variances with p>0.05. We used univariate logistic regression to examine the individual associations of self-compassion, resilience, traumatic experiences, and demographic variables with emotional distress, depression, and anxiety. Multivariate logistic regression was subsequently used to study the combined effects of these variables on emotional distress, depression, and anxiety. A Spearman’s rank-order correlation was run to determine the magnitude and direction of the relationship between self-compassion and resilience. Missing values from surveys with a quality score of 1 were conservatively given a value of zero and included in the analysis. All significant values reported have a p-value <0.05.

Results

Descriptive analysis

The analysis sample consisted of 272 Syrian participants living in Jordan. Most participants were female (61.8%), married (81.3%), and poorly meeting financial needs (76.8%). The average length of displacement across our sample population was 8 years (SD 2.46). More than half of participants (52.5%) reported having lived in a refugee camp and more than a quarter (27.2%) reported having experienced or witnessed torture (Table 1).

10.1371/journal.pone.0309051.t001 Table 1 Sample population demographic data and mean measure scores stratified by low, moderate, and high SCS score.

	N (%)
Total N = 272	Low SCS
N (%)	Moderate SCS
N (%)	High SCS
N (%)	
Gender					
Male	104 (38.2)	5 (4.8)	58 (55.7)	41 (39.4)	
Female	168 (61.8)	11 (6.5)	102 (60.7)	55 (32.7)	
Age					
18–30	65 (23.9)	5 (7.7)	35 (53.8)	25 (38.4)	
31–40	86 (31.6)	7 (8.1)	53 (61.6)	26 (30.2)	
41–50	49 (18.0)	2 (4.1)	27 (55.1)	20 (40.8)	
51–60	47 (17.3)	1 (2.1)	32 (68.1)	14 (29.8)	
61+	15 (5.5)	1 (6.7)	7 (46.7)	7 (46.7)	
Not reported	10 (3.7)	0 (0)	6 (60.0)	4 (40.0)	
Marital Status					
Married	221 (81.3)	14 (6.3)	127 (57.5)	80 (36.2)	
Other	51 (18.8)	2 (3.9)	33 (64.7)	16 (31.4)	
Employed					
Yes	25 (9.2)	1 (4.0)	13 (52.0)	11 (44.0)	
No	241 (88.6)	15 (6.2)	142 (58.9)	84 (34.9)	
Not reported	6 (2.2)	0 (0)	5 (83.3)	1 (16.7)	
Able to meet financial needs					
Poorly	209 (76.8)	15 (7.2)	123 (58.9)	71 (34.0)	
Fairly Well	53 (19.5)	1 (1.9)	31 (58.5)	21 (39.6)	
Not reported	10 (3.7)	0 (0)	6 (60.0)	4 (40.0)	
Participants with emotional distress	230 (84.6)	16 (7.0)	142 (61.7)	73 (31.7)	
Participants with depression	233 (85.7)	16 (6.9)	141 (60.5)	76 (32.6)	
Mean Measure Scores (scale) a	Mean (SD)				
SCS (1–4)	3.339 (0.53)	2.202 (0.23)	3.113 (0.25)	3.906 (0.26)	
TEC (0–20)	8.699 (4.92)	9.94 (4.91)	8.49 (5.08)	8.84 (4.67)	
Emotional Distress (1–4)	2.411 (0.625)	3.10 (0.412)	2.469 (0.610)	2.20 (0.577)	
Depression (1–4)	2.433 (0.626)	3.195 (0.324)	2.488 (0.628)	2.21 (0.538)	
Anxiety (1–4)	2.385 (0.724)	2.954 (0.660)	2.451 (0.678)	2.181 (0.744)	
CD-RISC (0–100)	57.665 (19.526)	41.75 (19.831)	52.936 (19.057)	68.198 (15.01)	
Demographic characteristics stratified by low, moderate, and high SCS score reported as N with percentage of sample population in parenthesis unless otherwise indicated. Low SCS = 1.0–2.49, Moderate SCS = 2.5–3.5, High SCS = 3.51–5.0. Abbreviations: SCS, Self-Compassion Scale. TEC, Trauma Exposure Checklist. CD-RISC, Connor-Davidson Resilience Scale.

a Scale for measures depicted in parenthesis.

The average total HSCL score, which is highly correlated with emotional distress, was 2.411 (SD 0.625) in our sample. The average HSCL depression score was 2.433 (SD = 0.626) and the average HSCL anxiety score was 2.385 (SD = 0.724). For all HSCL scores, a score >1.75 is considered symptomatic. A majority of those surveyed reported emotional distress (84.6%), depression (85.7%), and/or anxiety (76.5%) (Table1).

The average CD-RISC score was 57.665 (SD = 19.526) which is low relative to the United States (US) general population mean score of 80.7, but comparable to mean scores previously collected among Syrian refugees in Jordan [36, 39]. The SCS average was 3.339 (SD = 0.53) (Table 1). Although there are no clinical norms for the SCS, between 2.5–3.5 can be considered a moderate score [26].

Additionally, a Spearman’s rank-order correlation demonstrates a statistically significant moderate positive correlation between self-compassion and resilience in our sample population (rs = 0.455, p<0.001).

Comparing emotional distress, depression, and anxiety scores across self-compassion groups

Emotional distress, depression, and anxiety were not normally distributed as determined by a Shapiro-Wilk test with p<0.05. Thus, Kruskal-Wallis H tests were conducted to determine if there were differences in emotional distress, depression, and anxiety between those with low, moderate, and high self-compassion. Distributions of emotional distress, depression, and anxiety scores were similar for all groups, as determined by visual inspection of boxplots. The difference in median emotional distress, depression, and anxiety scores were statistically significant between self-compassion groups (emotional distress: χ2(2) = 33.290, p = <0.001; depression: χ2(2) = 38.785, p = <0.001; anxiety: χ2(2) = 18.603, p = <0.001). Pairwise comparisons were preformed using Dunn’s (1964) procedure with a Bonferroni correction. Adjusted p-values are presented. This post hoc analysis revealed statistically significant differences in median emotional distress, depression, and anxiety scores across all pairwise self-compassion comparison groups (emotional distress and depression scores: for all pairwise comparisons p = 0.001, anxiety score: high-moderate p = 0.007, high-low p = 0.001, moderate-low p = 0.043) (Fig 1).

10.1371/journal.pone.0309051.g001 Fig 1 Emotional distress, depression, and anxiety scores boxplots stratified by low, moderate, and high self-compassion.

Low SCS = 1.0–2.49, Moderate SCS = 2.5–3.5, High SCS = 3.51–5.0. Emotional distress and depression scores greater than 1.75 are considered symptomatic. Within each box the bolded center line denotes the median value; boxes extend from the 25th percentile to the 75th percentile of each group; vertical extending lines denote adjacent values; white circles denote outlier values. *, Δ, and • indicate significant difference between each group as determined by Kruskal-Wallis H test (emotional distress: χ2(2) = 33.290, p = <0.001; depression: χ2(2) = 38.785, p = <0.001; anxiety: χ2(2) = 18.603, p = <0.001) and post hoc pairwise comparison using Dunn’s (1964) procedure with a Bonferroni correction (p<0.05). Abbreviation: SCS, Self-Compassion Scale.

Comparing self-compassion and resilience scores in presence and absence of emotional distress, depression, and anxiety

Amongst participants with emotional distress, the mean SCS is significantly lower than participants with no emotional distress (t(270) = -4.640, p<0.001) (Table 2). Similarly, participants with depression and participants with anxiety have significantly lower mean self-compassion scores than participants with no depression or anxiety (depression: t(270) = -3.933, p<0.001; anxiety: t(270) = -5.933, p<0.001). The mean CD-RISC score is also significantly lower amongst participants with emotional distress (t(270) = -3.527, p<0.001), depression (t(270) = -3.040, p = 0.003), and anxiety (t(270) = -3.625, p<0.001) (Table 2).

10.1371/journal.pone.0309051.t002 Table 2 Mean SCS and CD-RISC scores stratified by presence or absence of emotional distress, depression, and anxiety.

	No Emotional Distressa (SE)	Yes Emotional Distress (SE)	p-valueb	No Depression a (SE)	Yes Depression (SE)	p-value b	No Anxietya (SE)	Yes Anxiety (SE)	p-valueb	
Mean SCS	3.693 (0.078)	3.277 (0.034)	p <0.001	3.643 (0.08)	3.289 (0.034)	p<0.001	3.666 (0.058)	3.239 (0.036)	p<0.001	
Mean CD-RISC	67.488 (3.233)	55.922 (1.239)	p<0.001	66.333 (3.638)	56.215 (1.219)	0.003	65.230
(2.436)	55.340
(1.316)	p<0.001	
Abbreviations: SCS, Self-Compassion Scale. CD-RISC, Connor-Davidson Resilience Scale.

a Presence of emotional distress, depression, and anxiety determined by HSCL scores >1.75.

b P-values from two-tailed t-test displayed.

Logistic regression analysis on predictors of emotional distress, anxiety, and depression

In the logistic regression analysis, self-compassion significantly predicted lower emotional distress, depression, and anxiety in both a univariate and multivariate models that included gender, age, marital status, income, occupation, and number of years resettled (Tables 3–5). We also identified gender and ability to meet financial needs as strong predictors of emotional distress, depression, and anxiety. The number of years since displacement was not a predictor of any of these outcomes, however, the number of traumatic experiences was a positive predictor of all three (Tables 3–5). Interestingly, resilience was a predictor of emotional distress, depression, and anxiety in the univariate model. However, this effect became insignificant in the multivariate model for all outcomes (Tables 3–5).

10.1371/journal.pone.0309051.t003 Table 3 Univariate and multivariate logistic regression analysis on predictors of emotional distress.

	Univariate	Multivariate	
Variable	B	OR	95% CI	P-value	B	OR	95% CI	p-value	
Gender
Male
Female (ref)a	-1.166	0.312	(0.158–0.616)	<0.001	-2.943	0.053	(0.015–0.189)	<0.001	
Age	0	1	(0.973–1.028)	0.99	0.04	1.04	(0.999–1.083)	0.055	
Marital Status
Other (single, widowed, divorced)
Married (ref)	0.087	1.091	(0.453–2.629)	0.846	0.312	1.366	(0.371–5.021)	0.639	
Meeting Financial Needs
Fairly well
Poorly (ref)	-1.158	0.314	(0.153–0.646)	0.002	-1.509	0.221	(0.080–0.613)	0.004	
Currently Employed
Yes
No (ref)	-0.587	0.556	(0.208–1.487)	0.242	0.595	1.813	(0.454–7.236)	0.399	
Number of years resettled	-0.074	0.929	(0.832–1.038)	0.192	-0.061	0.941	(0.829–1.067)	0.342	
Trauma Exposure Checklist (TEC)	0.172	1.187	(1.095–1.287)	<0.001	0.313	1.367	(1.205–1.550)	<0.001	
Resilience (CDRISC)	-0.033	0.968	(0.950–0.986)	<0.001	-0.014	0.986	(0.962–1.011)	0.263	
Self-Compassion Scale (SCS)	-1.589	0.204	(0.099–0.420)	<0.001	-2.016	0.133	(0.043–0.415)	<0.001	
a (ref) indicates reference category where appropriate.

10.1371/journal.pone.0309051.t004 Table 4 Univariate and multivariate logistic regression analysis on predictors of depression.

	Univariate	Multivariate	
Variable	B	OR	CI	p-value	B	OR	CI	p-value	
Gender
Male
Female (ref)a	-1.005	0.366	(0.183–0.732)	0.004	-2.679	0.067	(0.019–0.234)	<0.001	
Age	0	1	(0.973–1.029)	0.981	0.038	1.038	(0.997–1.082)	0.071	
Marital Status
Other (single, widowed, divorced)
Married (ref)	0.193	1.213	(0.477–3.084)	0.684	0.61	1.84	(0.478–7.083)	0.375	
Meeting Financial Needs
Fairly well
Poorly (ref)	-1.581	0.206	(0.099–0.428)	<0.001	-1.978	0.138	(0.051–0.379)	<0.001	
Currently Employed
Yes
No (ref)	-0.42	0.657	(0.231–1.868)	0.431	0.924	2.521	(0.598–10.618)	0.208	
Number of years resettled	-0.058	0.944	(0.850–1.048)	0.281	-0.047	0.413	(0.853–1.068)	0.413	
Trauma Exposure Checklist (TEC)	0.15	1.162	(1.072–1.259)	<0.001	0.254	1.289	(1.148–1.448)	<0.001	
Resilience (CDRISC)	-0.029	0.972	(0.953–0.990)	0.003	-0.009	0.991	(0.967–1.016)	0.482	
Self-Compassion Scale (SCS)	-1.367	0.255	(0.124–0.522)	<0.001	-1.732	0.177	(0.059–0.533)	0.002	
a (ref) indicates reference category where appropriate.

10.1371/journal.pone.0309051.t005 Table 5 Univariate and multivariate logistic regression analysis on predictors of anxiety.

	Univariate	Multivariate	
Variable	B	OR	CI	p-value	B	OR	CI	p-value	
Gender
Male
Female (ref)a	-1.412	0.244	(0.135–0.440)	<0.001	-2.865	0.057	(0.020–0.161)	<0.001	
Age	-0.024	0.977	(0.954–0.999)	0.045	0.003	1.003	(0.971–1.035)	0.871	
Marital Status
Other (single, widowed, divorced)
Married (ref)	0.137	1.137	(0.550–2.393)	0.714	-0.091	0.913	(0.334–2.494)	0.859	
Meeting Financial Needs
Fairly well
Poorly (ref)	-0.880	0.415	(0.217–0.792)	0.008	-1.290	0.275	(0.112–0.677)	0.005	
Currently Employed
Yes
No (ref)	-0.473	0.623	(0.255–1.520)	0.298	0.534	1.706	(0.496–5.870)	0.396	
Number of years resettled	-0.046	0.956	(0.863–1.058)	0.383	0.001	1.001	(0.897–1.117)	0.990	
Trauma Exposure Checklist (TEC)	0.116	1.123	(1.055–1.195)	<0.001	0.248	1.281	(1.164–1.410)	<0.001	
Resilience (CDRISC)	-0.28	0.972	(0.957–0.988)	<0.001	-0.001	0.999	(0.977–1.020)	0.908	
Self-Compassion Scale (SCS)	-1.754	0.173	(0.090–0.331)	<0.001	-2.187	0.112	(0.042–0.298)	<0.001	
a (ref) indicates reference category where appropriate.

Discussion

Our study shows for the first time that self-compassion, independent of resilience and other covariates, is predictive of less emotional distress and depression amongst displaced Syrians resettled in Jordan. We demonstrate that self-compassion is, in fact, a more important inverse predictor of poor mental health than resilience in this population. These findings provide insight on how to better support and care for people who are displaced and are at increased risk of poor mental health.

Prevalence of emotional distress and depression

Across our study population >75% of participants have symptomatic emotional distress, depression, or anxiety. The rates of mental health morbidity in our study population are higher than those reported in other studies that range between 11–60% [40]. However, most of the existing literature documenting the prevalence of poor mental health in Syrian refugee populations focuses on those resettled in high income countries (HICs), such as Sweden and Germany [41–46]. The documented prevalence amongst those resettled in HICs is consistently lower than the prevalence found amongst those living in low- and middle-income countries (LMICs) [35, 47–50]. This might be explained by disparate access to resources in LMICs like Jordan as classified by the World Bank [51]. This is supported by our findings that the ability to meet financial needs is a significant predictor of less emotional distress, depression, and anxiety in both models (Tables 3–5). Other studies conducted in LMICs further support this point. In one study focused on displaced Syrian women attending clinics in Jordan, they report depression affects 62.9% of their sample; anxiety affects 57.5%; and PTSD affects 66.2% [49]. In another study focused on displaced Syrians living in Iraq’s Kurdistan Region, utilizing the same measurement tool and positive threshold score applied in our study, the prevalence of depression was 77.2% [35]. Furthermore, our study was conducted in the summer of 2021, 1.5 years into the COVID-19 pandemic. This likely contributed to more prevalent mental health symptoms in our sample population due to the social isolation, fear, and instability from unemployment and pause on resettlements associated with the pandemic.

Gender, financial status, and traumatic exposure are predictors of mental health

Regression models revealed female gender, poor financial stability, and high traumatic exposure to be persistent predictors of poor mental health. These findings are consistent with the literature on mental health in refugees. Several previous studied have documented that female refugees are more likely to suffer from poor mental health [52, 53]. This is tied to unemployment and weak social networks [53]. Financial instability and history of exposure to trauma are also well-documented predictors of poor mental health outcomes amongst forcibly displaced people [54–56].

Greater self-compassion is associated with less mental health morbidity

We observed a step-wise decrease in emotional distress, depression, and anxiety across low, moderate, and high self-compassion. Additionally, on average, those with poor mental health had less self-compassion. Furthermore, we found self-compassion to be consistently negatively associated with emotional distress, depression, and anxiety in both univariate and multivariate models. These findings align with existing literature on self-compassion. A meta-analysis of 14 studies from largely HICs measuring the strength of the relationship between self-compassion and psychopathology demonstrates that increased self-compassion is associated with lower levels of mental health symptoms [57]. Some studies have been specifically conducted in populations with traumatic exposure including interpersonal violence and life-threatening illness [14–17]. In one study, self-compassion is identified as a mediating factor between childhood abuse and PTSD [58], and another found that self-compassion modulates the degree of chronicity of PTSD symptoms among veterans [59]. One of the few studies on self-compassion in displaced populations demonstrated that a self-compassion-based intervention improved PTSD outcomes [20]. Another cross-sectional study on the association of self-compassion and depression among Kurdish refugees residing in Norway reports that while self-compassion is associated with depressive symptoms, post-migration work related stressors are a more important predictor of mental health outcomes [19]. Interestingly, in our sample the employment status is not a significant predictor of mental health. However, the employment rate (9.2%) in our sample is much lower than that in Rashidian 2023 (60.4%). Furthermore, both self-compassion and ability to meet financial needs were persistent predictors of mental health in our model. It is possible that self-compassion may moderate the effects of poverty on mental health but not work-related stressors. Further studies are needed to examine the social context in which self-compassion may be most effective in psychopathology prevention. Our study contributes to the growing body of literature that identifies self-compassion as a predictor of mental health outcomes in the setting of trauma. However, the mechanism by which self-compassion impacts mental health is not completely understood. It is suggested that self-compassion training alters the neural response to evoked pain suggesting that self-compassion has a direct effect on how the brain processes experiences [60]. Importantly, self-compassion has been shown to be modifiable by intervention making its association with improved mental health outcomes even more practically relevant [18, 61, 62]. A randomized control trial evaluating the effectiveness of a mindful self-compassion program found increases in self-compassion being maintained at 6 months and 1 year [18]. The modifiable nature of self-compassion further emphasizes the value of the findings presented in our study to clinicians and systems supporting displaced people.

Self-compassion is a consistent predictor of mental health independent of resilience

Interestingly, resilience was significantly associated with less emotional distress, depression, and anxiety in our univariate model, but significance was lost in the multivariate model. Resilience is demonstrated in the literature to be protective from negative mental health outcomes [8, 9, 30, 63–68]. However, studies specifically investigating resilience in displaced populations mostly focus on children and adolescents [30, 63–66]. Among the studies that do report on resilience in displaced adults, few utilize direct measures of resilience as we do and rather utilize qualitative approaches [67, 68]. One study reporting on adults displaced from Iraq and living in the US using the CD-RISC measure found that it was associated with less psychological distress but was not a significant predictor of PTSD [8]. Our findings suggest that self-compassion confounded the association of resilience and mental outcomes, and is a more important predictor of mental health outcomes than resilience. The CD-RISC tool measures resilience by evaluating multiple traits that have been described to contribute to resilience including humor, patience, and faith [36]. The complex factors that formulate resilience may introduce variability in predicting mental health outcomes. One longitudinal study examining resilience and mental health after a major life event found that resilience was not predictive of distress over time. In a study of inflammatory bowel disease patients with history of childhood trauma resilience was not a significant moderator between childhood trauma and depression [10]. They suggest that resilience is not innate but influenced by contextual factors such as family relationships.

Our data does demonstrate a moderate positive correlation between self-compassion and resilience that is statistically significant. It is possible that self-compassion alters or interacts with resilience to protect from mental health morbidity, however our findings suggest that self-compassion is the driving factor. Previous studies have linked self-compassion to resilience. In a nonclinical sample of adolescents one study found that self-compassion is positively associated with resilience [69], while another found resilience as a mediating factor between self-compassion and psychological well-being [70]. The relationship between resilience and self-compassion in refugee populations warrants further investigation. Future studies should consider a mediation analysis of these factors in other populations.

Limitations and future directions

There are a few limitations in our study that should be taken into consideration. We attempted to limit the impacts of social desirability bias by excluding participants who were preliterate from the analysis. However, this may introduce bias from missing information on the role that self-compassion plays in this subpopulation. Additionally, our study population was recruited through community organizations providing aid and educational opportunities to refugees living in Amman, Jordan, which can exclude less aid dependent Syrians. Conducting surveys at community organizations’ offices may have introduced response bias if participants believed they may receive more aid by expressing greater need. However, this should not undermine the internal validity of the results. Additionally, there are potential confounding factors that we did not account for in our analysis. For example, social support or faith practice may be playing a role here. Furthermore, this data was collected in 2021. Although our findings exclude years of resettlement as a predictor of mental health outcomes, it is possible that as we move from a peri-COVID to post-COVID environment the mental health landscape evolves. Therefore, while our study provides valuable insights, ongoing research on mental health is this population is needed. Lastly, the potential for reverse causality from the capability of individuals with less emotional distress, depression, and anxiety to impart self-kindness and understanding cannot be excluded given the cross-sectional design of the study.

Future studies should include randomized clinical trials of self-compassion based interventions in Syrian refugees living in Jordan. Furthermore, qualitative studies should be done to evaluate the receptiveness and cultural barriers to uptake of self-compassion interventions in these communities. A study conducted in Hazara refugees resettled in Australia reported that community views on self-compassion, such as the belief that self-compassion is selfish, may act as barriers to its application [21]. However, this was a small study of only eleven participants. More studies are needed to inform design of self-compassion interventions that are acceptable to displaced peoples.

Conclusion

Our study is one of the first to demonstrate that self-compassion is inversely predictive of emotional distress, depression, and anxiety independent of resilience in a displaced population. Self-compassion is a modifiable factor that can be utilized by healthcare professionals caring for refugees to promote positive mental health outcomes. Our findings also shed some interesting light on the relationship of resilience, self-compassion, and mental health among displaced vulnerable populations. These areas of positive psychology should be utilized as an addition or alternative, when there are no specialized services, to medical treatment of mild to moderate emotional distress and depression. As the magnitude of displacement increases across the globe due to conflict, climate change, and economic disparities, rates of mental health problems will also increase. Prevention and treatment are major challenges for LMICs, where most displaced populations reside. By better understanding the ways in which communities withstand adversity, we hope to evolve our capabilities to further support vulnerable populations and promote their well-being through efficient and low resource approaches. This is a significant finding that can open the doors for cost-effective interventions without the need for medications or specialized psychiatric care that are lacking in these communities. Randomized controlled trials and longitudinal studies should be implemented to further understanding of the utility of self-compassion for the prevention of poor mental health outcomes in displaced communities.

Supporting information

S1 Checklist Inclusivity in global research checklist.

(DOCX)

S1 Data Data file for open access.

(XLSX)

The authors would like to thank the participants who generously shared their experiences with us. We are grateful for the efforts of the Jordanian community organizations and their staff that facilitated our engagement with the community.

List of abbreviations

PTSD Post-traumatic stress disorder

US United States

TEC Trauma Experiences Checklist

HSCL Hopkins Symptom Checklist

CD-RISC Connor-Davidson Resilience Scale

SCS Self-Compassion Scale—Short Form

LMICs Low- and middle-income countries

HICs High income countries

10.1371/journal.pone.0309051.r001
Decision Letter 0
Uysal Mete Sefa Academic Editor
© 2024 Mete Sefa Uysal
2024
Mete Sefa Uysal
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version0
20 Mar 2024

PONE-D-23-39016Self-compassion and association with depression and distress among displaced Syrians: a population-based studyPLOS ONE

Dear Dr. Al-Delaimy,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

First, I am sorry to take so much time to make a decision and thank you for your patience. Two reviewers withdrew during the editorial process due to their health problems. I have now received one detailed review of your paper, which we have copied below. Of course, I have also thoroughly read the manuscript myself.

As you will see, the reviewer has raised several major issues that you need to address before the paper is considered for publication. Below, I list the major concerns that you will need to address if you decide to revise and resubmit the paper. Additionally, please address all other points raised by the reviewer (find below).

As pointed out by the Reviewer, the introduction can be improved further by going beyond the literature gap and highlighting the novelty and importance of the study.

More information is needed in the Materials and Method section. You shared the participants’ information in Table 1, but it would be helpful if you could summarise some general information about the participants in this section. Moreover, it is not clear whether materials were presented in randomised order or the order in the Study Measures section. More information is needed in Study Measures as well. Authors should provide more information on what exactly these materials measure. Providing a couple of sample items can help. Also, the psychometric properties of the scale are missing (see the Reviewer’s comment on this issue).

As the reviewer, one of my main concerns is regarding the use of two scores from HSCL-25, namely depression and emotional distress. Why did you choose to use one depression and one emotional distress score from the HSCL-25, instead of one depression and one anxiety or just one emotional distress total? What is the theoretical basis of this decision? What is the statistical basis of this decision? You should clarify this decision both theoretically and statistically (e.g., factor analyses).

You should either publish the data publicly available after you anonymised data and omit the sensitive contents or justify your decision to not make data publicly available.

You should avoid causal language as this is a cross-sectional survey study. Relatedly, you can tone down your findings to imply that self-compassion is protective against mental health disorders, due to the correlational nature of the study. Self-compassion is definitely associated with less emotional distress; hence, it might be protective against mental health disorders, but it should be further tested in longitudinal or experimental studies.

Do you have specific hypotheses you’re testing? Please clearly state that at the end of the introduction.

The potential reasons why resilience was significantly associated with less emotional distress and depression in the univariate model, while not in the multivariate model was not discussed thoroughly. I believe authors should further discuss this in the discussion. This finding does not necessarily mean that self-compassion is significantly more predictive of mental health outcomes than resilience. It can be more complex than this, and even if the findings suggest this, the question "why" should be answered. Please see the Reviewer’s points for further expand the discussion.

The limitation section is weak. I would like to see improvements concerning the “Limitations and Future Directions”. There is so much to say here about the confounding variables, the social context in which this study was conducted, and the potential of these findings can change from 2011 to 2024, as well as extending future research providing a brief roadmap on this topic.

You could directly report the final sample in the abstract to make the abstract shorter and clearer as much as possible.

P.3, lines 69-71. Please anonymise your manuscript by omitting information that links the citations to the authors’ details.  

In the results section, you should use the name of the concept, instead of the scale. For instance, low to high self-compassion, instead of low to high SCS groups.

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Reviewers' comments: 

Regarding the article, I have found significant strengths, especially for the findings of the study. In addition, the study may address the predictive roles of resilience and self-compassion for mental health outcomes in a disadvantaged population. However, there are some issues that may limit the potential contributions of this study. I hope that the authors will find helpful the following issues that I pointed. 

Introduction

The introduction of the manuscript requires improvement. One of my main concern is the lack of clarity regarding the novelty of the study, what this study adds novelty in relation to the existing literature. It is recommened to emphasize the relationship between resilience, self-compassion, and mental health outcomes, rather than simply saying that no study has examined these variables among refugees-this is not sufficient to establish novelty-. Another concern is the limited knowledge about the related variables and functions for traumatized individuals. Please, include the existing literature to understand the association of these variables in the scope of mental health. Lastly, please clarify the aim of the study.

Line.73 Please explain what you mean “work upstream”

Line.80-82. Self-compassion has been worked with refugees in contemporary research. Please check the relevant sentence and the related articles Rashidian et al. (2023), Ghasemy (2020) etc

Line.82-83. “Furthermore, the link between self-compassion and resilience is explored in the literature, but not defined in the context of displaced populations”

How these two factors, self-compassion and resilience, are associated in other sample as you stated in this sentence? Please, add more information.

Materials and Methods

Consider reorganizing this section by adding subtitles under methods and materials, such as participants, procedure, statistical analysis etc. Please refer to the journal archieves for guidance on how to organize this part.

Did you have any inclusion or exclusion criteria for sample selection in your study? If you had, please indicate.

Line.102-105. You excluded one participants as being younger than 18 years old. However, when I examined the Table 1, I noticed that the age section had a  “not reported” category. How did you determine that these 10 participants were older than 18 or younger than 80?

Line. 102-105. How did you detect social desirability in your sample? Did you use any validated measurement tool for identifying it?

Line. 106-109. I assume what you mean by “the quality scores” is missing values in dataset. If not, could you explain how you determined the quality of the data. I suggest that you provide statistical evidence why you excluded these data.

Measurement tools:

You employed Arabic version of all the scales. I wonder about the psychometric properties of these scales. Do the scales have adequate validity and realibility scores for Arabic individuals? In addition, how about the internal consistency scores of your sample for all measurement tools?

Line.118-128. Indeed, the HSCL-25 has two sub-dimensions: anxiety and depression. According to the references you cite (18 and 19) researchers have also calculated anxiety and depression seperately. The Arabic version (Fares et al., 2021) recommended bifactor model: two factors (anxiety/depression) and a thir factor (underlying 25-items). However, you calculated a total score for emotional distress and 15 items for depression separately- it was not calculated any score for anxiety-.The introduction part mentioned that anxiety is also common adverse mental health outcomes among refugees. I wonder why you did not measure anxiety for your sample?

I assume you have used the information for HSCL-25 and calculation of its from this website https://hprt-cambridge.org/screening/hopkins-symptom-checklist. I recommend that you cite this website in your manuscript or other articles which point the same total score and depression sub-dimension. Additionally, please paraphrase the sentences, as there is a high degree of similarity between your sentences and the text on this website.

Line.133 “This will be a secondary exposure to self-compassion measures” I did not understand what you meant with this sentence. Please explain.

Line.144-151. To make this section easier to read and avoid confusion, I suggest titling it as “statistical analysis”

This section requires additional information regarding the statistics that the authors used. Were there any missing values? As I read previous paragraph that you wrote (for participation selection), some individuals did not complete all items in the data set. Thus, please include information about missing value. If any missing values, how were missing values handled. There is some assumptions for conducting ANOVA. I wonder whether these assumptions were checked or not. Specifically, was the normality of the data checked? Did data distribute normally? Please check the assumptions of ANOVA and explain it in a clear way in the text.

Line.144.Which version of SPSS was used? All the statistics that you mentioned could be carried out in SPSS? Why did you use excel?

Line.144-146. How were the low, moderate, and high self-compassion scores of the participants determined? I knew that this scale does not have any cut-off scores. (If wrong, please inform me and add the text)

Line.146 “…. ANOVA followed by post hoc Tukey’s Honest Significance Test with Bonferroni correction”. Did you use Tukey or Bonferroni? I am confused.

Line.148. Please rewrite the sentence in a clearer way. For instance, we used univariate logistic regression for ….. and multivariate for ….. etc.

Results

In general, results section is a kind of complicated. It is hard to understand and follow the findings. I advise the authors adding subtitle under results section to make easier the interpretation for instance descriptive analysis, prevalence, logistic regression analysis -for emotional distress, for depression etc. This will be helping to increase understandability.

Line.174-176. Please, explain why did you conduct correlation? If you have a hypothesis, please indicate in the text or you may think to exclude it.

Line.203-211. As I suggested above, maybe you can add distinct subheadings for emotional distress and depression.

Discussion

In general, it is recommended that the authors may present their finding at first, and then discuss them based on the existing literature, providing possible explanations of their findings. Secondly, the authors discussed only findings of resilience and self-compassion. However, gender, meeting financial needs, and TEC were also found to be significant predictors of emotional distress and depression in logistic regression. Please, include a discussion about these findings in this part. Lastly, what does this study suggest for future studies or clinical implications? Please, provide your suggestions in a separate paragraph.

Please indicate that Jordan is one of the LMICs according to (World Bank?) …. Since you interpreted migration to LMICs could be an explanation.

Line.241 The authors specifically emphasized the term “severely traumatized…” in some sentences. When you said that, I expected an objective indicator that provides the trauma level of your sample or your sample just consisted of individuals with high levels of traumatic stress. I believe that simply stating this term will not enough to prove all of the sample experienced severe trauma. Maybe instead of emphasizing the term so much, it may be sufficient to briefly introduce about the trauma that experienced by Syrian refugees in the introduction part.

Line.249-250. As I stated previously, there have been some studies conducted on self-compassion among refugees. Please check it and add.

“Greater self-compassion is associated with less mental health morbidity”

First, you can present your findings of this study. Then, you can discuss how your finding placed in the existing literature. The psychosocial intervention findings that you cited may be incorporated into clinical or future implications by combining them with your findings.

“Self-compassion is a consistent predictor of lower emotional distress and depression independent of resilience ”

Please explain the finding of why resilience did not predict emotional distress and depression based on existing literature. You cited an article numbered 6, how they explain this finding? Moreover, some researchers argued that being resilient may not be associated with a reduction in distress (e.g., Blanke et al., 2023).

Line.274-283. The authors discussed this correlation finding. However, as previously stated, you should determine the aim of the manuscript and if you wish to include this finding, please clarify the aim of the study in introduction part.

Reviewer's Responses to Questions

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

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Reviewer #1: No

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Reviewer #1: Yes

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5. Review Comments to the Author

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Reviewer #1: The article highlights an intriguing topic and presents some notable findings for future clinical implications. However, there are some issues that should be improved. Introduction needs to be revised to include some additional knowledge based on the existing literature. The methods should be clarified, especially in terms of the statistical analysis and measurement tools that were used. The Results section should be reorganized. Lastly, the discussion part should be improved to interpret the findings of the current study and some other variables that were found significant predictors should be interpreted.

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Reviewer #1: No

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Attachment Submitted filename: REVIEW NOTES.docx

10.1371/journal.pone.0309051.r002
Author response to Decision Letter 0
Submission Version1
8 Jun 2024

Response to Reviewer comments

Regarding the article, I have found significant strengths, especially for the findings of the study. In addition, the study may address the predictive roles of resilience and self-compassion for mental health outcomes in a disadvantaged population. However, there are some issues that may limit the potential contributions of this study. I hope that the authors will find helpful the following issues that I pointed.

Response:

Thank you for your comments. We have incorporated your feedback into the manuscript and believe it has stregthened the presentation of our findings.

Introduction

1) The introduction of the manuscript requires improvement. One of my main concern is the lack of clarity regarding the novelty of the study, what this study adds novelty in relation to the existing literature. It is recommened to emphasize the relationship between resilience, self-compassion, and mental health outcomes, rather than simply saying that no study has examined these variables among refugees-this is not sufficient to establish novelty-. Another concern is the limited knowledge about the related variables and functions for traumatized individuals. Please, include the existing literature to understand the association of these variables in the scope of mental health. Lastly, please clarify the aim of the study.

Response:

The introduction was edited to calirfy the novelty of the study. Given the increase in displaced populations globally and the limited resources for mental health care, interventions of self-compassion can address this gap among the most vulnerable populaitons. We belive that this study presents valuable data regarding the relevance of self compassion as a protective factor from mental health morbidity in refugees independent of resilience. This is important given the high rates of mental health disorders in communities that have experienced forced displacement and the need for tailored interventions.

As suggested by the reviewer, we have added literature and text to the introduction to highlight the association between resilience and mental health and trauma, as well as the association between self-compassion and trauma.

We have also clarified the aim of the study in the last part of the introduction. To summarize the aims of this study were to investigate the impact of self-compassion on mental health disorders in a population of displaced Syrians living in Jordan, and to explore this effect in relationship to resilience.

2) Line.73 Please explain what you mean “work upstream”.

Response:

This phrasing was edited to clarify the meaning. Resilience is a complex multidimensional process that encompasses multiple subfactors. Interventions that improve resilience may act on specific subfactors like self-comapssion rather than attempt to modulate resilience directly.

3) Line.80-82. Self-compassion has been worked with refugees in contemporary research. Please check the relevant sentence and the related articles Rashidian et al. (2023), Ghasemy (2020) etc

Response:

Thank you for sharing these articles. We edited the introduction to include these and other studies on self-compassion in refugees.

4) Line.82-83. “Furthermore, the link between self-compassion and resilience is explored in the literature, but not defined in the context of displaced populations”

How these two factors, self-compassion and resilience, are associated in other sample as you stated in this sentence? Please, add more information.

Response:

We removed this sentence and provided more literature on the association between self-compassion and resilience.

Materials and Methods

5) Consider reorganizing this section by adding subtitles under methods and materials, such as participants, procedure, statistical analysis etc. Please refer to the journal archieves for guidance on how to organize this part.

Response:

Thank you for this suggestions. We added subtitles for clarity.

6) Did you have any inclusion or exclusion criteria for sample selection in your study? If you had, please indicate.

Response:

We did not have any exclusion criteria. Any Syrian refugee adult was included. We have added this to the Methods. However, during analysis we excluded those who participated and did not have completed surveys.

7) Line.102-105. You excluded one participants as being younger than 18 years old. However, when I examined the Table 1, I noticed that the age section had a “not reported” category. How did you determine that these 10 participants were older than 18 or younger than 80?

Response:

The reviewer raises a good point. We removed the age criteria because we included any adult 18 years or older. We do not know if the 10 participants who did not report their age included someone below the age of 18. We have added a sentence to the methods to clarify this.

8) Line. 102-105. How did you detect social desirability in your sample? Did you use any validated measurement tool for identifying it?

Response:

We did not use a social desirability measurement tool, however, after the interviews were completed the authors concluded that respondents were avoiding questions about mental health. This is likely because the setting was not conducive of discussing these stigmatized topics through interview and that is why we had self-report surveys for collection of data given the associated stigma and the inavailabilty of private office space during the data collection. We thus preferred to exclude those who were preliterate and had to be interviewed verbally in order to avoid potential bias in the results.

9) Line. 106-109. I assume what you mean by “the quality scores” is missing values in dataset. If not, could you explain how you determined the quality of the data. I suggest that you provide statistical evidence why you excluded these data.

Response:

We clarified in this sentence that these scores were related to data completion.

Measurement tools

10) You employed Arabic version of all the scales. I wonder about the psychometric properties of these scales. Do the scales have adequate validity and realibility scores for Arabic individuals? In addition, how about the internal consistency scores of your sample for all measurement tools?

Response:

We did not embark on psychometric analysis of these well validated scales because we made the assumption that the reliability scores would not change based on the language. However, the reviewer raises a valid point that can be addressed in future psychometric focused analyses and papers but that is beyond the scope of this paper. We did report on the internal consistency of each measure by including a Cronbach’s alpha all of which were greater than 0.8. Thank you for this suggestion.

11) Line.118-128. Indeed, the HSCL-25 has two sub-dimensions: anxiety and depression. According to the references you cite (18 and 19) researchers have also calculated anxiety and depression seperately. The Arabic version (Fares et al., 2021) recommended bifactor model: two factors (anxiety/depression) and a thir factor (underlying 25-items). However, you calculated a total score for emotional distress and 15 items for depression separately- it was not calculated any score for anxiety-.The introduction part mentioned that anxiety is also common adverse mental health outcomes among refugees. I wonder why you did not measure anxiety for your sample?

I assume you have used the information for HSCL-25 and calculation of its from this website https://hprt-cambridge.org/screening/hopkins-symptom-checklist. I recommend that you cite this website in your manuscript or other articles which point the same total score and depression sub-dimension. Additionally, please paraphrase the sentences, as there is a high degree of similarity between your sentences and the text on this website.

Response:

The reviewer brings up an important point here and we agree that anxiety should be included in the anlaysis. The updated manuscript now reports anxiety as an outcome in all analyses.

Additionaly, we cited the HPRT website and edited the text describing the HSCL-25 to reduce similarity with source text.

12) Line.133 “This will be a secondary exposure to self-compassion measures” I did not understand what you meant with this sentence. Please explain.

Response:

Thank you for pointing this out to us, we have removed this sentence.

13) Line.144-151. To make this section easier to read and avoid confusion, I suggest titling it as “statistical analysis”

Response:

Thank you for this suggestion. We included this subtitle.

14) This section requires additional information regarding the statistics that the authors used. Were there any missing values? As I read previous paragraph that you wrote (for participation selection), some individuals did not complete all items in the data set. Thus, please include information about missing value. If any missing values, how were missing values handled. There is some assumptions for conducting ANOVA. I wonder whether these assumptions were checked or not. Specifically, was the normality of the data checked? Did data distribute normally? Please check the assumptions of ANOVA and explain it in a clear way in the text.

Response:

The reviwer raises multiple excellent points here. Missing values were conservatively assigned a value of zero and were included in the analysis. We added this information to the Statistical Analysis section.

With the inclusion of anxiety in our analysis ANOVA assmuptions were not met, we therefore decided to conduct the nonparametric Kruskal-Wallis H test. The distribution of distress, depression, and anxiety scores were determined similar by visual inspection of boxplots. Post hoc pairwise comparisons were preformed using Dunn’s (1964) procedure with a Bonferroni correction. This is now clearly described in the text.

15) Line.144.Which version of SPSS was used? All the statistics that you mentioned could be carried out in SPSS? Why did you use excel?

Response:

SPSS Version 29.0.2.0 was used. We added this to the text and included a citation for SPSS. Because data was originally stored in Excel it was utilized for early calculations o the descriptive statistics. All other analysis was conducted in SPSS.

16) Line.144-146. How were the low, moderate, and high self-compassion scores of the participants determined? I knew that this scale does not have any cut-off scores. (If wrong, please inform me and add the text)

Response:

The reviewer is correct in that there are no clinical norms which differentiate between low, moderate, and high self compassion. However, we used an ad hoc rubric that has been suggested in the literature based on score means and standard deviations in population samples. We added information on this to the SCS scale description under Study Measures. More information on this can be found here:

https://self-compassion.org/wp-content/uploads/2022/01/Self-CompassionScaleChapter.pdf

17) Line.146 “…. ANOVA followed by post hoc Tukey’s Honest Significance Test with Bonferroni correction”. Did you use Tukey or Bonferroni? I am confused.

Response:

We apologize for the confusion this sentence has been removed from the manuscript.

18) Line.148. Please rewrite the sentence in a clearer way. For instance, we used univariate logistic regression for ….. and multivariate for ….. etc.

Response:

Thank you for this suggestion, we agree the original text was unclear. We edited the text to clarify.

Results

19) In general, results section is a kind of complicated. It is hard to understand and follow the findings. I advise the authors adding subtitle under results section to make easier the interpretation for instance descriptive analysis, prevalence, logistic regression analysis -for emotional distress, for depression etc. This will be helping to increase understandability.

Response:

Thank you for this suggestion. We added subtitles to clarify the results section.

20) Line.174-176. Please, explain why did you conduct correlation? If you have a hypothesis, please indicate in the text or you may think to exclude it.

Response:

We were interested in the magnitude of correlation between resilience and self compassion given the theoretical framework suggesting a relationship between these constructs in this population. We added a review of this literature to the introduction. Understanding the correlation between self-compassion and resilience also informed our statistical modeling. For example, if resilience and self compassion were highly related they may have led to multicollinearity issues and made the regression model unstable if both were included. The hypothesis is that resilience and self compassion are positively correlated. We edited our aims and hypothesis in the Introduction section to clarify these points.

21) Line.203-211. As I suggested above, maybe you can add distinct subheadings for emotional distress and depression.

Response:

We added subtitles to the results section to make it easier to read. We decided not to split up the summary of logistic regression results by emotional distress, depression, and anxiety in order to avoid being repetitive given similarity of results across the three outcomes.

Discussion

22) In general, it is recommended that the authors may present their finding at first, and then discuss them based on the existing literature, providing possible explanations of their findings. Secondly, the authors discussed only findings of resilience and self-compassion. However, gender, meeting financial needs, and TEC were also found to be significant predictors of emotional distress and depression in logistic regression. Please, include a discussion about these findings in this part. Lastly, what does this study suggest for future studies or clinical implications? Please, provide your suggestions in a separate paragraph.

Response:

Thank you for your suggestions. We incorporated them into our disucssion and overall we believe it has strengthened it. Specifcally, we added a discssuion of implications and suggestions for future studies. We also address gender, financial needs and TEC as predictors of emotional distress, depression, and anxiety.

23) Please indicate that Jordan is one of the LMICs according to (World Bank?) …. Since you interpreted migration to LMICs could be an explanation.

Response:

Thank you for pointing this out. We specified in the text that Jordan is classified as a LMIC by the World Bank and included a citation.

24) Line.241 The authors specifically emphasized the term “severely traumatized…” in some sentences. When you said that, I expected an objective indicator that provides the trauma level of your sample or your sample just consisted of individuals with high levels of traumatic stress. I believe that simply stating this term will not enough to prove all of the sample experienced severe trauma. Maybe instead of emphasizing the term so much, it may be sufficient to briefly introduce about the trauma that experienced by Syrian refugees in the introduction part.

Response:

The reviewer brings up a good point. We removed the term “severely” from the manuscript.

25) Line.249-250. As I stated previously, there have been some studies conducted on self-compassion among refugees. Please check it and add.

Response:

Thank you again for brining these papers to our attention. We added a discussion of these studies to the manuscript.

26) “Greater self-compassion is associated with less mental health morbidity”

First, you can present your findings of this study. Then, you can discuss how your finding placed in the existing literature. The psychosocial intervention findings that you cited may be incorporated into clinical or future implications by combining them with your findings.

Response:

We edited this section to present our findings first and then discuss in the context of existing literature. Thank you for this suggestion.

27) “Self-compassion is a consistent predictor of lower emotional distress and depression independent of resilience”

Please explain the findin

Attachment Submitted filename: Response to Reviewers .docx

10.1371/journal.pone.0309051.r003
Decision Letter 1
Uysal Mete Sefa Academic Editor
© 2024 Mete Sefa Uysal
2024
Mete Sefa Uysal
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version1
19 Jul 2024

PONE-D-23-39016R1Self-compassion and association with distress, depression, and anxiety among displaced Syrians: a population-based studyPLOS ONE

Dear Dr. Al-Delaimy,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

In addition to a reviewer who reviewed the initial submission, I read the manuscript thoroughly. Please carefully address the reviewer's point (see below), as they are crucial, particularly regarding the statistical considerations, although they are very straightforward and could be easily addressed. In addition to the reviewer's point, I have two minor, but important, points: 

- Abstract: Please simplify the abstract removing the statistical results such as p values and OR, and focusing on the summary of your research findings and contributions (please also see the reviewer's comment on the abstract)

- I suggest avoiding terms like “mental illnesses” or “mental health disorders” (for instance see the first paragraph in the introduction, lines 59-60, or page 5., lines 104 and 111; please check it throughout the manuscript), as they might refer clinical settings and not appropriate for non-hospitalised vulnerable groups like refugees. You could adopt the terms such as mental health problems instead.

Please submit your revised manuscript by Sep 02 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Mete Sefa Uysal, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments: 

Regarding the revision of the manuscript, I believe that this version exhibits greater strength than the previous version. I would like to appreciate the authors for their efforts.

In the abstract

In the abstract, depending on your findings, you might consider adding the predictive role of gender, financial status and traumatic exposure The incorporation of these variables, you might think about making abstract more attractive and interesting.

In Methods and Results sections

Lines 198-199. In the study population section, you wrote:  “In total, 47 surveys with a quality score of 2 or 3 were excluded from the final analysis.”. However, in this sentence you wrote “Missing values were conservatively given a value of zero and included in the analysis”. As before, you stated you exclude the data with missing values. Please, check it.

You applied non parametric test with the inclusion of anxiety. Regarding this information, I understand that the anxiety measurement was not normally distributed but what about other measurement such as depression, emotional distress? If only anxiety was non-normally distributed, I recommend using Kruskal-Wallis H test for anxiety, one-way ANOVA for other measurements if normal distrubiton was met.

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

**********

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Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

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Reviewer #1: Yes

**********

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Reviewer #1: Yes

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Attachment Submitted filename: Plos_One Revised Version Review.docx

10.1371/journal.pone.0309051.r004
Author response to Decision Letter 1
Submission Version2
29 Jul 2024

Self-compassion and association with distress, depression, and anxiety among displaced Syrians: a population-based study

-Regarding the revision of the manuscript, I believe that this version exhibits greater strength than the previous version. I would like to appreciate the authors for their efforts.

Response:

Thank you for the all thoughtful feedback you have provided which has ultimately strengthened this paper.

In the abstract

-In the abstract, depending on your findings, you might consider adding the predictive role of gender, financial status and traumatic exposure The incorporation of these variables, you might think about making abstract more attractive and interesting.

Response:

We included this finding in the abstract. Thank you for this suggestion.

In Methods and Results sections

-Lines 198-199. In the study population section, you wrote: “In total, 47 surveys with a quality score of 2 or 3 were excluded from the final analysis.”. However, in this sentence you wrote “Missing values were conservatively given a value of zero and included in the analysis”. As before, you stated you exclude the data with missing values. Please, check it.

Response:

Thank you for bringing this to our attention. We edited the text to further clarify the quality score assigned to each survery. To summarize, surveys received a quality score of if they had minimal missing data, 2 if they were missing more than 50% of the data in one section, and 3 if they were missing data in multiple sections. Missing values from surveys with a quality score of 1 were then conservatively given a value of zero.

-You applied non parametric test with the inclusion of anxiety. Regarding this information, I understand that the anxiety measurement was not normally distributed but what about other measurement such as depression, emotional distress? If only anxiety was non-normally distributed, I recommend using Kruskal-Wallis H test for anxiety, one-way ANOVA for other measurements if normal distrubiton was met.

Response:

Thank you for this comment. Depression, emotional distress, and anxiety were not normally distrubted across self compassion groups which is why Kruskal-Wallis H test was ultimatley applied. Absence of normality was determined by a Shapiro-Wilk test with p < 0.05.

Editor Comments:

-Abstract: Please simplify the abstract removing the statistical results such as p values and OR, and focusing on the summary of your research findings and contributions (please also see the reviewer's comment on the abstract)

Response:

We removed the statistical results from the abstract and included more of our findings per the reviewers suggestion (ie gender, financial status, and trauma exposure).

-I suggest avoiding terms like “mental illnesses” or “mental health disorders” (for instance see the first paragraph in the introduction, lines 59-60, or page 5., lines 104 and 111; please check it throughout the manuscript), as they might refer clinical settings and not appropriate for non-hospitalised vulnerable groups like refugees. You could adopt the terms such as mental health problems instead.

Response:

Thank you for this suggestion. The terms “mental illnessses” and “mental health disorders” have been removed from the manuscript and replaced with “poor mental health” or “mental health problems”.

Attachment Submitted filename: Response to Reviewers_7.21.docx

10.1371/journal.pone.0309051.r005
Decision Letter 2
Uysal Mete Sefa Academic Editor
© 2024 Mete Sefa Uysal
2024
Mete Sefa Uysal
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Submission Version2
6 Aug 2024

Self-compassion and association with distress, depression, and anxiety among displaced Syrians: a population-based study

PONE-D-23-39016R2

Dear Dr. Al-Delaimy,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

I have a minor suggestion that does not require another round of revision, but you can update it in the amendment and proofreading period. I recommend updating the following sentence in the abstract for clarity: “Female gender, poor financial stability, and high levels of traumatic exposure were also identified as persistent predictors of mental health morbidity.” You may prefer something like “Gender (i.e, females have poorer mental health compared to males), poor financial stability, and high levels of traumatic exposure were also identified as predictors of mental health problems.” 

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Mete Sefa Uysal, Ph.D.

Academic Editor

PLOS ONE

10.1371/journal.pone.0309051.r006
Acceptance letter
Uysal Mete Sefa Academic Editor
© 2024 Mete Sefa Uysal
2024
Mete Sefa Uysal
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
11 Sep 2024

PONE-D-23-39016R2

PLOS ONE

Dear Dr. Al-Delaimy,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Mete Sefa Uysal

Academic Editor

PLOS ONE
==== Refs
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