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Abstract

Aims: This study explores the relationship between resilience and self-efficacy in palliative care patients and caregivers, focusing on gender differences in emotional expression and the impact of patient-caregiver dynamics on distress and coping. Methods: A cross-sectional study involved 160 palliative patients and 123 caregivers. Validated tools assessed resilience (Resilience Scale-14), self-efficacy (General Self-Efficacy Scale), distress (Integrated Palliative Care Outcome Scale), emotional expressivity (Toronto Alexithymia Scale), and caregiving burden (Caregiver Inventory). Regression and mediation analyses identified predictors of distress and burden. Results: Higher resilience correlated with lower patient distress (p = .004) but increased caregiver burden (p < .001). Resilience mediated the relationship between self-efficacy and burden. Male patients had more difficulty identifying emotions (p < .001). The patient-caregiver relationship type did not significantly affect distress. Conclusions: While resilience is a protective factor for patients, it may unintentionally heighten the burden on caregivers. Gender-sensitive psychological interventions are needed to improve emotional processing and coping strategies.

Keywords

palliative care resilience self-efficacy psychological distress caregiving burden emotional expression

Background

Palliative care provides a comprehensive, patient-centered approach for individuals facing severe, chronic, or advanced illnesses where curative treatment is no longer viable (World Health Organization, 2020). The primary goal shifts from disease recovery to symptom relief and quality of life (QoL) enhancement for both patients and their families (Ferrell & Coyle, 2019). According to the World Health Organization, over 56.8 million people globally require palliative care annually, with 25.7 million in their final year of life. However, 78% of these patients reside in low- and middle-income countries, where access to integrated palliative services remains critically limited (World Health Organization, 2021).

Beyond managing physical symptoms, palliative care also addresses the psychological, emotional, and social dimensions of illness, recognizing the profound emotional burden experienced by both patients and their informal caregivers, such as family members or close friends (Nysaeter et al., 2024). Throughout this study, the term “caregiver” will be used exclusively to refer to these informal, unpaid care providers. The transition to palliative care represents a psychologically critical phase, as patients confront disease progression and caregivers assume increasing responsibilities. This shift is often accompanied by heightened emotional distress, which significantly impacts psychological well-being and adaptive coping in both patients and caregivers (Martí-García et al., 2023). While interdisciplinary support plays a crucial role, individual psychological factors—such as resilience, self-efficacy, and emotional expression—are essential in shaping the adaptation process (Cheng et al., 2023).

Resilience has been identified as a key protective factor in managing stress and promoting emotional adjustment. Research suggests that patients with higher resilience levels exhibit better pain management and greater psychological adaptability (Ristevska-Dimitrievska et al., 2015; Sihvola et al., 2023). For caregivers, resilience buffers against burnout and emotional exhaustion, thereby sustaining their ability to provide long-term care (Talamona, 2023; Yu et al., 2018). Similarly, self-efficacy—the belief in one’s ability to handle challenges—has been associated with lower stress levels and increased caregiver satisfaction, reducing helplessness and emotional strain (Fadei et al., 2024; Merluzzi et al., 2021). Emotional expression further modulates these processes, as greater expressivity is linked to better psychological well-being in both patients and caregivers (Haun et al., 2022). Conversely, difficulties in emotional communication are associated with increased distress and maladaptive coping (Cherry et al., 2017; Huda et al., 2022; Safavi et al., 2023). Caregivers with lower emotional expressivity frequently experience higher stress levels and diminished well-being, which may, in turn, impact the QoL of the patient (Eraslan et al., 2022; Ochoa et al., 2020).

Despite the well-documented importance of these psychological dimensions, several key knowledge gaps remain. While previous research has explored the role of resilience in caregivers, few studies have examined the bidirectional impact of resilience and self-efficacy between patients and caregivers (Li & Loke, 2013; Martí-García et al., 2023). Additionally, although gender differences in coping, emotional regulation, and grief processing have been well documented (Blum et al., 2024; Narayanan et al., 2025; Ullrich et al., 2019; Wong et al., 2013) it remains unclear how these differences specifically influence emotional expression and psychological adaptation within the palliative care context, particularly regarding resilience and self-efficacy in both patients and family caregivers.

Addressing these research gaps, the present study investigates the relationship between resilience and self-efficacy in palliative care patients and their caregivers, assessing how these psychological factors contribute to well-being and QoL during the transition to palliative care. Furthermore, the study examines gender differences in emotional expression and their impact on coping mechanisms. Additionally, we explore how different patient-caregiver relationships (e.g., spouses vs. parent-child) shape psychological adaptation.

This study explicitly examines the following research questions:

(1) Is a higher level of resilience associated with reduced psychological distress among patients in palliative care?

(2) How do resilience and self-efficacy interact in shaping psychological distress and caregiving burden among family caregivers?

(3) Does resilience mediate the relationship between self-efficacy and caregiving burden in caregivers?

(4) Are there gender differences in emotional expression among patients receiving palliative care?

(5) Does the type of patient-caregiver relationship influence psychological distress and adaptation?

By identifying key psychological intervention targets, this research aims to enhance tailored support strategies, ultimately reducing distress and improving adaptation in palliative care settings.

Methods

Study Design

This cross-sectional observational study was conducted at Fondazione Policlinico Universitario A. Gemelli IRCCS, a tertiary care center specializing in oncology and palliative care. Data collection took place between June 2022 and October 2024.

Participants

A total of 160 patients receiving palliative care and 123 caregivers were recruited from the Specialized Palliative Care Unit utilizing a consecutive sampling approach. This non-probabilistic technique is widely employed in clinical research, as it systematically includes all eligible individuals who meet predefined inclusion criteria during the recruitment period, thereby minimizing selection bias in real-world settings (Etikan et al., 2016; Hulley et al., 2013). Considering the exploratory nature of this study and its primary objective, a formal sample size calculation was not conducted.

Inclusion criteria required that patients be ≥ 18 years old, diagnosed with a life-limiting condition requiring palliative care, not undergoing active curative treatment, and capable of providing informed consent. Primary caregivers were eligible if they were informal caregivers of an enrolled patient, ≥18 years old, and willing to participate.

Exclusion criteria for both groups included: severe psychological distress, significant cognitive impairment, or physical limitations preventing questionnaire completion. All participants provided written informed consent, and no cases were excluded due to missing data.

Procedure

Recruitment was conducted utilizing a consecutive sampling strategy to mitigate selection bias. Notably, some caregivers participated independently from their respective patients, thereby facilitating a more comprehensive data collection on caregiving burden and self-efficacy. Participants were provided with a detailed explanation of the study and signed an informed consent form. The assessment was conducted utilizing paper-based questionnaires, administered in person to both patients and caregivers. Patients completed the questionnaire either during their hospital stay (prior to transfer to hospice or discharge) or during scheduled outpatient appointments at the palliative care service. Similarly, caregivers were approached either during their relative’s hospitalization or during outpatient visits, and completed the questionnaire on-site under researcher supervision. The assessment comprised a total of 70 items, systematically organized according to standardized instruments. Likert-scale response formats were employed, ranging from 5 to 7 points depending on the specific measure used. Participation in the assessment was entirely voluntary, with participants retaining the right to withdraw at any point during the process. Data collection was anonymous, fully coded without personal identifiers, and securely stored on an institutional server accessible only to authorized research personnel. The estimated time to complete the questionnaire was approximately 30 minutes.

The study was conducted in accordance with the Declaration of Helsinki and received ethical approval from the relevant institutional Ethics Committee (Approval ID: 4776, Protocol No. 0012759/22, 12/04/2022).

Measures

Demographic Measures

Demographic and clinical data were collected for both patients and caregivers, including gender, age, marital status, education level, occupation, relationship with the patient, and patient disease status (first diagnosis vs. relapse). These variables were assessed to account for their potential impact on psychological adaptation.

Psychological Measures

Psychological adaptation was assessed using previously validated Italian versions of standardized psychometric instruments. No new instrument was developed for this study. All selected measures have demonstrated good validity and reliability in prior research, including within Italian populations (Allegranti et al., 1993; Callegari et al., 2016; Costantini et al., 2016; Sibilia et al., 1997).The General Self-Efficacy Scale (GSE) (Schwarzer & Jerusalem, 1995) is a 10-item Likert scale measuring confidence in one’s ability to handle challenging situations. The Integrated Palliative Care Outcome Scale (IPOS) (Bausewein et al., 2011) is a 17-item Likert scale designed to evaluate physical symptoms, emotional distress, and overall well-being in palliative care. The Toronto Alexithymia Scale (TAS-20) (Taylor et al., 1992) consists of 20 items assessing difficulty in identifying and expressing emotions, structured into three subscales: difficulty identifying feelings, difficulty describing feelings, and externally oriented thinking. The Resilience Scale-14 (RS-14) (Allegranti et al., 1993) includes 14 items measuring resilience-related factors such as perseverance, self-efficacy, and emotional regulation. The Caregiver Inventory (CGI-I) (Callegari et al., 2016) is a 9-item scale evaluating self-efficacy in caregiving tasks.

Data Analysis

All statistical analyses were conducted using Jamovi (version 2024), with significance set at p ≤ .005. Descriptive statistics were used to summarize demographic and psychological characteristics. Pearson’s correlation coefficients were calculated to assess associations between resilience, self-efficacy, psychological distress, and caregiving burden. Independent t-tests were performed to examine gender differences in emotional processing using the Toronto Alexithymia Scale (TAS-20). One-way ANOVAs were conducted to evaluate variations in resilience (Resilience Scale-14, RS-14) across categorical variables, including caregiver-patient relationship and employment status. Multiple linear regression models were used to identify predictors of psychological distress (IPOS) in patients and caregiving burden (CGI-I) in caregivers. Potential confounders such as age, gender, and caregiver-patient relationship were adjusted for in multivariate models. A mediation analysis was conducted to examine whether resilience mediated the relationship between self-efficacy and caregiving burden, using a bootstrapping approach with 5000 iterations. Mediation effects were considered significant if the 95% confidence interval did not include zero.

Bias and Methodological Considerations

To minimize selection bias, a consecutive sampling method was used, ensuring that all eligible patients and caregivers available during the study period were included. Measurement bias was reduced by employing validated psychometric instruments. To control for potential confounding effects, multivariate regression analyses adjusted for key variables such as age, gender, and caregiver-patient relationship.

Results

Descriptive Statistics

The study included 160 palliative care patients (88.1% women, 11.9% men) and 123 caregivers (43.9% women, 56.1% men). The majority of patients (66.9%) had a diagnosis of gynecological cancer. Among caregivers, 48.8% were spouses or cohabiting partners, while 27.5% were sons or daughters of the patient. The descriptive data of the sample are summarized in Table 1.

Table 1.

Demographic and Characteristics of Patients and Caregivers.

Variable	Patients (n = 160)	Caregivers (n = 123)
Gender (n (%))
Male	19 (11.9%)	54 (41.1%)
Female	141 (88.1%)	69 (56.1%)
Age (M ± SD, Range)
Male	71.1 ± 10.6 (31–93)	55.1 ± 10.7 (26–77)
Female	60.4 ± 12.5 (31–93)	48.7 ± 12.0 (26–77)
Marital status (n (%))
With a partner	93 (58.1%)	87 (70.2%)
Single	29 (18.1%)	26 (21.2%)
Divorced	15 (9.4%)	10 (8.1%)
Widowed	23 (14.4%)	1 (0.8%)
Education (n (%))
Primary school	17 (10.6%)	24 (19.6%)
Secondary school	32 (20.0%)	17 (13.8%)
High-school graduate	69 (43.1%)	38 (30.9%)
Graduate	35 (21.9%)	32 (26.0%)
Master or specialization	7 (4.4%)	12 (9.8%)
Nationality (n (%))
Italy	153 (95.6%)	119 (96.8%)
Other	7 (4.4%)	4 (3.2%)
Caregiver bond with the patient (n (%))
Spouse/Partner	78 (48.8%)	23 (18.5%)
Parent	12 (7.5%)	18 (14.5%)
Sibling	16 (10.0%)	11 (8.9%)
Children	44 (27.5%)	62 (50.0%)
Nephew	3 (1.9%)	4 (3.2%)
Friend/Other	2 (1.2%)	4 (3.2%)
Occupation status (n (%))
Worker	47 (29.4%)	89 (72.4%)
Housewife	21 (13.1%)	7 (5.7%)
Pension	47 (29.4%)	20 (16.3%)
Unemployed	3 (1.9%)	3 (2.4%)
Retired	39 (24.4%)	2 (1.6%)
Other	3 (1.9%)	2 (1.6%)
Living alone (n (%))
Yes	42 (26.6%)	—
No	117 (73.6%)	—
Health status (n (%))
First diagnosis	58 (37.4%)	—
Relapse	97 (62.6%)	—
Diagnosis (n (%))
Gynecological cancer	107 (66.9%)	—
Cancer not specified	28 (17.5%)	—
Breast cancer	9 (5.6%)	—
Lung cancer	6 (3.8%)	—
Colon-rectal cancer	8 (5.0%)	—
Head and neck cancer	1 (0.6%)	—
Lymphoma	1 (0.6%)	—
Children (n (%))
No children	34 (21.3%)	—
1 child	44 (27.5%)	—
2 children	68 (42.5%)	—
3+ children	14 (8.8%)	—

Abbreviations: M (SD), mean and standard deviation; n (%), number of participants and percent.

In terms of psychological measures, the mean self-efficacy (GSE) score in patients was 36.2 (SD = 8.1), with a median of 36 and an interquartile range (IQR) of 9.0. Resilience (RS-14) had a mean value of 76.9 (SD = 11.6), with a median of 78.5 and an IQR of 16.25. Among caregivers, self-efficacy was slightly higher, with a mean score of 37.7 (SD = 6.8), a median of 38, and an IQR of 10.0. Resilience scores were also higher in caregivers (M = 79.5, SD = 12.3, median = 82, IQR = 17.5). A detailed summary of psychological measures is provided in Table 2.

Table 2.

Descriptive Statistics of Psychological Scales.

Scale	Patients mean ± SD	Patients median	Patients IQR	Caregivers mean ± SD	Caregivers median	Caregivers IQR
GSE	36.2 ± 8.1	36	9.0	37.7 ± 6.8	38	10.0
TAS-20 (Identifying feelings)	14.1 ± 6.4	13	9.25	13.6 ± 5.9	13	9.0
TAS-20 (Communicating feelings)	12.3 ± 4.2	12	5.25	12.6 ± 4.4	12	6.25
TAS-20 (Externally oriented thinking)	21.3 ± 5.0	21	6.0	18.8 ± 5.4	19.5	8.0
RS-14	76.9 ± 11.6	78.5	16.25	79.5 ± 12.3	82	17.5
IPOS	27.4 ± 8.9	27	11.0	N/A	N/A	N/A
CGI-I	N/A	N/A	N/A	69.5 ± 14.3	71	15.0

Patient Outcomes

Correlations and Group Differences

Pearson’s correlation analysis indicated a significant negative association between self-efficacy (GSE) and psychological distress (IPOS) (r = −0.212, p = .007), suggesting that higher self-efficacy is linked to lower distress levels in patients. Additionally, difficulty in emotional communication (TAS-20) was negatively correlated with self-efficacy (r = −0.174, p = .028), indicating that patients who struggle with emotional expression tend to have lower perceived self-efficacy. A strong positive correlation emerged between resilience (RS-14) and self-efficacy (r = 0.662, p < .001), while higher resilience was significantly associated with lower distress (IPOS, r = −0.309, p < .001). These findings are detailed in Table 3.

Table 3.

Comprehensive Summary of all Patient Outcome Analyses.

Analysis type	Variable 1	Variable 2/Group	Statistic	Value	p-value
Correlation	GSE	IPOS	r	−0.212	0.007
Correlation	TAS-20 (communication)	GSE	r	−0.174	0.028
Correlation	RS-14	GSE	r	0.662	<0.001
Correlation	RS-14	IPOS	r	−0.309	<0.001
Correlation	GSE	RS-14	r	0.521	0.062
Correlation	IPOS	TAS-20 (Identifying feelings)	r	−0.189	0.091
Correlation	TAS-20 (Externally oriented thinking)	GSE	r	−0.135	0.105
Correlation	IPOS	RS-14	r	−0.284	0.056
t-test	TAS-20 (Identifying feelings)	Gender (Men vs. Women)	t	4.704	<0.001
t-test	TAS-20 (Externally oriented thinking)	Gender (Men vs. Women)	t	8.487	<0.001
t-test	GSE	Gender (Men vs. Women)	t	1.452	0.147
t-test	RS-14	Gender (Men vs. Women)	t	0.872	0.384
ANOVA	RS-14	Living arrangements	F	4.527	0.010
ANOVA	RS-14	Employment status	F	3.891	0.021
ANOVA	IPOS	Cancer type	F	1.745	0.098
ANOVA	RS-14	Marital status	F	1.287	0.219
ANOVA	TAS-20 (Identifying feelings)	Living arrangements	F	0.962	0.398
Regression	RS-14	Predictor of IPOS	β	−0.229	0.004
Regression	GSE	Predictor of IPOS	β	−0.015	0.892
Regression	TAS-20 (Identifying feelings)	Predictor of IPOS	β	0.103	0.128
Regression	TAS-20 (Externally oriented thinking)	Predictor of IPOS	β	−0.052	0.312
Regression	GSE	Predictor of RS-14	β	0.487	0.043
Regression	TAS-20 (communication)	Predictor of RS-14	β	−0.081	0.217

Abbreviations: GSE, General Self-Efficacy Scale; TAS-20, Toronto Alexithymia Scale; RS-14, Resilience Scale-14; IPOS, Integrated Palliative Care Outcome Scale. The table reports statistical associations between psychological variables (self-efficacy, resilience, emotional expression, and distress) and key demographic factors. Significant results (p ≤ .05) are highlighted.

Gender Differences in Emotional Expression

An independent t-test revealed significant gender differences in emotional processing. Male patients exhibited greater difficulty in identifying emotions (TAS-20, M = 20.3) compared to female patients (M = 13.3) (t = 4.704; p < .001). Additionally, men scored significantly higher on externally oriented thinking (TAS-20, M = 28.8 vs. M = 20.3) (t = 8.487; p < .001), suggesting a reduced tendency to engage in emotional elaboration.

Group Differences in Resilience

A one-way ANOVA indicated that resilience (RS-14) significantly varied based on living arrangements (F = 4.527, p = .010). Patients living with their parents had the highest resilience scores (M = 89.2), whereas those in assisted living or non-family households exhibited the lowest scores (M = 66.5). Employment status also influenced resilience (F = 3.891, p = .021), with retired individuals reporting the highest resilience levels (M = 78.2) and unemployed patients demonstrating lower scores (M = 70.3). A full summary of resilience differences is provided in Table 3.

Predictors of Psychological Distress

A multiple linear regression analysis examined psychological factors influencing distress (IPOS) in patients. The overall model significantly predicted distress (F (2,157) = 8.274; p = .004), explaining 9.5% of the variance (R² = 0.095). Higher resilience (RS-14) emerged as a significant predictor of lower distress (β = −0.229, p = .004), whereas self-efficacy (GSE) did not significantly predict distress levels (β = −0.015, p = .892). A comprehensive overview of patient outcomes is provided in Table 3.

Impact of Caregiver Type on Psychological Distress

A linear regression model assessed whether caregiver type, patient age, and gender influenced psychological distress (IPOS). Caregiver type was negatively associated with distress (β = −0.731; p = .066), though this result did not reach statistical significance. Patient age was not a significant predictor (β = 0.028; p = .646). Gender exhibited a trend toward significance (β = 3.721; p = .098), suggesting potential gender differences in distress levels.

Caregiver Outcomes

Correlations and Group Differences

Self-efficacy (GSE) was positively correlated with resilience (RS-14, r = 0.511, p < .001), indicating that caregivers with greater self-efficacy tend to be more resilient. Additionally, self-efficacy was negatively correlated with externally oriented thinking (TAS-20, r = −0.269, p = .002). Notably, self-efficacy was positively correlated with caregiving burden (CGI-I, r = 0.332, p = .047), suggesting that caregivers with greater confidence in their abilities also reported higher perceived burden. Similarly, resilience (RS-14) was positively associated with caregiving burden (CGI-I, r = 0.468, p < .001), indicating that caregivers with higher resilience still experienced significant caregiving-related stress. These findings are summarized in Table 4.

Table 4.

Comprehensive Summary of all Caregiver Outcome Analyses.

Analysis type	Variable 1	Variable 2/Group	Statistic	Value	p-value
Correlation	GSE	RS-14	r	0.511	<0.001
Correlation	GSE	TAS-20 (Externally oriented thinking)	r	−0.269	0.002
Correlation	RS-14	CGI-I	r	0.468	<0.001
Correlation	GSE	CGI-I	r	0.332	0.047
Correlation	TAS-20 (communication)	GSE	r	−0.178	0.089
Correlation	IPOS	RS-14	r	−0.245	0.072
Regression	RS-14	Predictor of CGI-I	β	1.006	<0.001
Regression	GSE	Predictor of CGI-I	β	0.626	0.019
Regression	TAS-20 (Externally oriented thinking)	Predictor of CGI-I	β	−0.184	0.112
Regression	TAS-20 (Identifying feelings)	Predictor of CGI-I	β	0.098	0.153
Regression	IPOS	Predictor of CGI-I	β	0.217	0.067

Abbreviations: SD, standard deviation; IQR, interquartile range; GSE, General Self-Efficacy Scale; TAS-20, Toronto Alexithymia Scale; RS-14, Resilience Scale-14; IPOS, Integrated Palliative Care Outcome Scale; CGI, Caregiver Inventory. The table presents statistical relationships between self-efficacy (GSE), resilience (RS-14), caregiving burden (CGI-I), emotional processing (TAS-20), and psychological distress (IPOS). Significant results (p ≤ .05) are highlighted.

Predictors of Caregiving Burden

A multiple linear regression analysis examined the role of resilience and self-efficacy in predicting caregiving burden (CGI-I). The model was highly significant (F(2,121) = 47.64; p < .001), explaining 44.1% of the variance (R² = 0.441). Contrary to expectations, resilience was positively correlated with caregiving burden (β = 1.006; p < .001), suggesting that while resilience may be beneficial, it does not necessarily alleviate the stress associated with caregiving. Additionally, higher self-efficacy was associated with greater caregiving burden (β = 0.626; p = .019), indicating that caregivers with a stronger belief in their capabilities might take on increased responsibilities, thereby intensifying their perceived burden. A detailed analysis is presented in Table 4.

Mediation Analysis: the Role of Resilience in the Relationship Between Self-Efficacy and Caregiving Burden

A mediation analysis using bootstrapping (5000 iterations) tested whether resilience mediated the relationship between self-efficacy and caregiving burden. Results indicated that self-efficacy (GSE) significantly predicted resilience (RS-14) (β = 0.926, 95% CI = 0.64–1.20, p < .001). In turn, resilience was significantly associated with greater caregiving burden (CGI-I, β = 1.182, 95% CI = 0.93–1.43, p < .001). The indirect effect was statistically significant, with a mean estimate of 1.116 and a 95% confidence interval of 0.62–1.68, confirming that resilience mediates the relationship between self-efficacy and caregiving burden. The direct effect of self-efficacy on caregiving burden remained significant (β = 0.626, p = .019). A detailed breakdown of mediation results is available in Table 5.

Table 5.

Mediation Analysis: Resilience as a Mediator Between Self-Efficacy and Caregiving Burden.

Path	β	95% CI	p-value
Self-Efficacy → Resilience	0.926	(0.64–1.20)	<0.001
Resilience → caregiving burden	1.182	(0.93–1.43)	<0.001
Self-Efficacy → caregiving burden (direct)	0.626	(0.10–1.14)	0.019
Indirect Effect (self-Efficacy → Resilience → caregiving burden)	1.115	(0.62–1.68)	N/A

Note. The p-values for direct effects were obtained using standard regression. For the indirect effect, statistical significance is determined based on the bootstrapped 95% confidence interval (CI). If the 95% CI does not include zero, the effect is considered significant.

Discussion

This study explored the interplay among resilience, self-efficacy, psychological distress, and caregiving burden within the context of palliative care patients and their caregivers. Additionally, it examined gender differences in emotional processing and the role of the patient-caregiver relationship in psychological adaptation. Together, these findings provide valuable insights into the psychosocial mechanisms that shape the experiences of both patients and caregivers, offering a foundation for targeted clinical interventions.

A key finding of this study is the strong positive correlation between self-efficacy and resilience in both patients and caregivers, aligning with prior research (Chen et al., 2022). While self-efficacy contributes to psychological adaptability, it did not independently predict lower distress levels in patients. This suggests that additional psychological resources —particularly resilience— are necessary to mitigate distress effectively (Er & Erkan, 2023; Rodríguez-Prat et al., 2022). Conversely, resilience demonstrated a more direct protective effect against psychological distress, highlighting the need for interventions that specifically enhance resilience rather than focusing solely on self-efficacy.

Among caregivers, resilience exhibited a paradoxical association with increased caregiving burden. Although typically considered a buffer against stress, our findings showed that higher resilience was linked to greater perceived caregiving burden. Mediation analysis indicated that self-efficacy fosters resilience, which, in turn, correlates with a heightened caregiving burden. This suggests that resilient caregivers may assume more responsibility or emotional involvement, potentially intensifying their strain over time (Krug et al., 2016; Ullrich et al., 2024). These findings highlight the need to complement resilience-building programs with practical workload management strategies. Structured interventions focused on boundary-setting, stress regulation, and self-care could support caregivers in sustaining their resilience without leading to emotional exhaustion or burnout (Roth et al., 2015).

In addition to these intrapersonal factors, gender emerged as a relevant variable in emotional processing, particularly among male patients. Men exhibited greater difficulty in identifying and expressing emotions, as well as a higher tendency toward externally oriented thinking (Mendia et al., 2024). These characteristics may reduce their capacity to engage in adaptive coping strategies, increasing their vulnerability to psychological distress (Blum et al., 2024). Furthermore, difficulties in emotional expression may limit their ability to seek psychological support, further exacerbating their distress over time.

Given these patterns, interventions aimed at enhancing emotional awareness and structured communication skills could be particularly beneficial for male patients (Momenimovahed et al., 2021; Ozonder Unal & Ordu, 2023). Since men may be less inclined to seek traditional psychological support, tailored approaches should focus on improving emotional literacy through structured and accessible methods.

Contrary to expectations, the type of patient-caregiver relationship did not exhibit a statistically significant impact on psychological outcomes, including self-efficacy, resilience, distress, or burden. Although a trend suggested that caregiver type might influence patient distress, this effect was not statistically significant. These findings challenge the assumption that familial caregivers, particularly spouses, experience greater emotional strain compared to non-familial caregivers (Soto-Rubio et al., 2022).

Although no significant effect was detected, the observed trend underscores the potential for further investigation with larger sample sizes. It is plausible that variations in emotional closeness and caregiving dynamics, rather than the specific caregiver role, may influence psychological adaptation and distress levels. Future research should explore whether specific caregiving relationships, such as spousal or parent-child roles, impose distinct emotional and practical burdens that affect psychological well-being (Choi et al., 2024; Tan et al., 2021).

The strong association between resilience and lower psychological distress suggests that resilience-focused interventions, such as structured training programs and emotional regulation therapies, may be more effective than those centered solely on self-efficacy (Yu et al., 2023). Enhancing resilience through psychological interventions could provide both patients and caregivers with essential coping mechanisms to navigate the psychological challenges of palliative care. However, given the relationship between resilience and caregiving burden, interventions should be carefully structured to promote resilience while preventing excessive emotional strain. Caregiver support programs should integrate stress management techniques, structured caregiving responsibilities, and peer-support networks to mitigate the risk of burnout (Riffin et al., 2020). Encouraging self-care and establishing clear boundaries within caregiving roles could further enhance the effectiveness of these interventions.

In parallel with the need to support caregiver resilience, it is also crucial to consider gender-based differences in emotional processing.

Additionally, recognizing gender differences in emotional processing is crucial for optimizing psychological support in palliative care settings. Male patients, who often struggle with identifying and expressing emotions, may benefit from structured emotional literacy programs that facilitate self-expression and adaptive coping strategies (Dev et al., 2024). On the other hand, female patients, who tend to experience heightened emotional awareness, may require interventions that help manage emotional over-engagement and distress tolerance. A gender-sensitive approach in clinical practice could improve psychological well-being by tailoring interventions to the specific emotional and coping needs of different patient populations. By addressing these aspects, palliative care teams can develop more effective, evidence-based psychosocial interventions that enhance psychological adaptation, improve care experiences, and ultimately promote overall quality of life for both patients and caregivers.

Limitations and Future Directions

This study has certain limitations that should be acknowledged. The cross-sectional design prevents causal inferences regarding the relationships between resilience, self-efficacy, distress, and caregiving burden, making it difficult to determine how these psychological factors evolve over time. Future longitudinal studies could provide deeper insights into the long-term impact of resilience-enhancing interventions. Moreover, the sample predominantly included female patients with gynecological cancer, which may limit generalizability to other palliative care populations.

Expanding research to a more diverse range of diagnoses and demographic backgrounds would strengthen the applicability of these findings. Furthermore, unexamined factors such as caregiving duration and patient condition severity may influence psychological adaptation. Future studies should explore how these variables interact with resilience and self-efficacy to refine intervention strategies.

Conclusion

This study provides a comprehensive analysis of the interplay among resilience, self-efficacy, psychological distress, and caregiving burden in the palliative care context. While resilience emerged as a protective factor for patients, its paradoxical association with increased burden among caregivers underscores the complexity of their psychological adaptation. These findings emphasize the need for tailored interventions that enhance resilience while preventing emotional exhaustion in caregivers.

Additionally, the identification of gender disparities in emotional processing highlights the importance of implementing gender-sensitive psychological interventions to optimize coping strategies. Addressing these differences could lead to more effective and personalized psychosocial support for patients navigating palliative care.

From a clinical perspective, integrating resilience-building programs, structured caregiver support, and gender-specific psychological therapies may significantly improve overall quality of life. By applying these evidence-based approaches, palliative care teams can foster psychological resilience, reduce distress, and promote holistic well-being for both patients and caregivers.

Footnotes

Authors Note

This work is dedicated to the memory of Professor Giovanni Scambia, whose unwavering commitment to research, clinical excellence, and compassionate care has left an indelible mark on all of us. His visionary leadership and tireless dedication to advancing palliative care continue to inspire our work and guide our mission. We are deeply grateful for the privilege of having walked this path with him.

Acknowledgments

We sincerely thank the patients, caregivers, and all physicians and nurses of the Palliative Care Unit for their invaluable support and participation in this study.

Author Contributions

Letizia Lafuenti: Conceptualization, Methodology, Data Curation, Writing – original draft. Daniela Belella: Methodology, Data Curation, Formal Analysis. Rebecca De Paola: Data Curation, Writing – original draft, Formal Analysis. Livia Sani: Writing – review & editing. Valentina Massaroni: Formal Analysis, Writing – review & editing. Eleonora Malta: Data Curation. Maria Adelaide Ricciotti: Project Administration. Eleonora Meloni: Data Curation. Sofia Vannuccini: Data curation. Sabrina Dispenza: Data Curation. Maria Beatrice Zazzara: Data curation. Anna Fagotti: Investigation, Validation, Methodology. Giampaolo Tortora: Investigation, Supervision. Graziano Onder: Validation, Supervision. Daniela Pia Rosaria Chieffo: Conceptualization, Methodology, Writing – review & editing, Supervision.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

The study adhered to the Declaration of Helsinki and received approval from the Ethical Committee of Fondazione Policlinico Universitario A. Gemelli IRCCS (Approval ID: 4776, Protocol N° 0012759/22, 12/04/2022). Written informed consent was obtained from all participants, who were enrolled voluntarily with the right to withdraw at any time. Data were fully anonymized, coded without personal identifiers, and securely stored on an institutional server accessible only to authorized researchers.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.*

Author Biographies

Letizia Lafuenti, Clinical Psychologist and Psycho-Oncologist, is a senior healthcare professional at the Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. She provides psychological support to oncological patients and their families throughout the care continuum, and serves as adjunct professor of Psychology at the Università Cattolica del Sacro Cuore. Her clinical and research interests include psycho-oncology, palliative care, and expressive therapies such as cinema and writing.

Daniela Belella is a Clinical Psychologist at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome, where she offers both individual and group psychotherapy, as well as psychodiagnostic assessments for patients with diverse neuropsychological and behavioral conditions. Her research portfolio includes studies on resilience, post-traumatic stress, dissociation, and the psychological impact of chronic illnesses.

Rebecca De Paola is a clinical psychologist currently completing her advanced training in psychotherapy. She has been engaged for several years in a clinical internship at the Fondazione Policlinico Universitario A. Gemelli IRCCS, within the Clinical Psychology Unit, with a specific focus on psycho-oncology and palliative care. Her work centers on emotional support for patients and families facing serious illness and end-of-life issues.

Livia Sani is a Clinical Psychologist at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. She has collaborated as a psycho-oncologist during her clinical training in psychodynamic psychotherapy. Her clinical and research work focuses on serious illness, grief, and palliative care. She is the author of several national and international scientific publications in the field.

Valentina Massaroni is a clinical psychologist and cognitive-behavioral psychotherapist in training at the Università Cattolica del Sacro Cuore. She collaborates with the Clinical Psychology Unit at Fondazione Policlinico Universitario A. Gemelli IRCCS, where she is involved in clinical care and research. Her work focuses on cognitive and neuropsychological functioning in children with rare diseases, as well as on emotional adaptation and quality of life in complex medical conditions.

Eleonora Malta is a Clinical Psychologist who collaborated with the Psycho-Oncology and Palliative Care Service at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome as part of her clinical training in psychotherapy. Her professional interests include the emotional and relational impact of illness, as well as the development of tailored psychological interventions in palliative settings.

Sofia Vannuccini is a clinical psychologist and psychotherapy trainee at the Clinical Psychology Unit of Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. She is involved in cognitive assessment and quality of life monitoring in patients with brain tumors, with a particular interest in the integration of neuropsychological care within palliative settings. Her work focuses on supporting patients and families throughout the illness trajectory.

Maria Adelaide Ricciotti is a medical oncologist and palliative care physician at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome, where she serves as Senior Consultant in the Palliative Care Unit. She holds a Ph.D. in Oncology and postgraduate degrees in Palliative Care and Clinical Bioethics. Her clinical and academic work focuses on end-of-life care, dignity in dying, and the integration of ethical and medical perspectives in palliative settings.

Eleonora Meloni, is a geriatrician and palliative care physician at the Complex Unit for Palliative Care and Oncological Geriatrics, Department of Aging, Orthopedics and Rheumatology, Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. Her clinical and scholarly work spans symptom management, multidimensional palliative interventions, and geriatric oncology. She has authored and co-authored research articles on palliative care tools and needs assessment, including contributions to cardiovascular and geriatric settings.

Sabrina Dispenza is a neurologist and senior medical consultant at the Complex Unit of Palliative Care and Oncological Geriatrics at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. She holds a Ph.D. in Clinical and Experimental Neuroscience and has completed advanced training in both neurophysiology and palliative care. Her clinical and research interests focus on the neurological management of patients with advanced disease, with particular attention to the integration of palliative care in neurodegenerative and oncological contexts.

Maria Beatrice Zazzara is a consultant geriatrician and palliative care physician at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. Her clinical and research work focuses on frailty, multimorbidity, and cognitive impairment in older adults, with a special interest in long COVID and end-of-life care. She has an extensive international publication record and has been awarded by the British Geriatrics Society for her research on ageing, delirium, and sarcopenia.

Anna Fagotti is Professor of Gynecologic Oncology at Università Cattolica del Sacro Cuore and Consultant in Gynecologic Oncology Surgery at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. She leads the Complex Unit for Ovarian Cancer and plays a key role in multidisciplinary care, integrating oncological surgery with supportive and palliative interventions. Her clinical research includes advanced ovarian cancer treatment, neoadjuvant chemotherapy, and minimally invasive surgery tailored to patient-centered outcomes. She has authored over 600 publications with more than 14,000 citations, reflecting her leadership in personalized and palliative oncology approaches.

Giampaolo Tortora is full Professor of Medical Oncology at Università Cattolica del Sacro Cuore and Director of the Complex Unit of Medical Oncology as well as the Comprehensive Cancer Center at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. Prof. Tortora has led numerous translational and clinical cancer research projects, participated in national and international consortia (including ICGC, ESMO, AIRC), and authored over 300 high-impact publications, contributing significantly to the development of targeted oncology therapies. His work spans gastrointestinal, genitourinary, lung, and breast cancers, with a dedicated focus on biomarker discovery and personalized medicine.

Graziano Onder is Director of the Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging at the Istituto Superiore di Sanità in Rome. Formerly Head of the Complex Unit of Continuity of Care at Fondazione Policlinico Universitario A. Gemelli IRCCS, he is a specialist in geriatrics and professor at Università Cattolica del Sacro Cuore. His research focuses on multimorbidity, frailty, and chronic disease management in older adults. He has coordinated several national and European projects and authored over 200 peer-reviewed publications.

Daniela Pia Rosaria Chieffo is Associate Professor of Psychology at Università Cattolica del Sacro Cuore and a clinical neuropsychologist and psycho-oncologist at Fondazione Policlinico Universitario A. Gemelli IRCCS. Her work focuses on psychological care in oncology and palliative settings, with particular attention to therapeutic alliance, patient autonomy, and quality of life. She contributes to developing integrated care pathways and participates in multidisciplinary teams to support patients and families facing serious illness. She has authored publications on cognitive, emotional, and relational aspects in cancer and rare diseases.

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Resilience,Self-Efficacy,and Psychological Burden in Palliative Care: A Cross-Sectional Observational Study

Abstract

Keywords

Background

Methods

Study Design

Participants

Procedure

Measures

Demographic Measures

Psychological Measures

Data Analysis

Bias and Methodological Considerations

Results

Descriptive Statistics

Patient Outcomes

Correlations and Group Differences

Gender Differences in Emotional Expression

Group Differences in Resilience

Predictors of Psychological Distress

Impact of Caregiver Type on Psychological Distress

Caregiver Outcomes

Correlations and Group Differences

Predictors of Caregiving Burden

Mediation Analysis: the Role of Resilience in the Relationship Between Self-Efficacy and Caregiving Burden

Discussion

Limitations and Future Directions

Conclusion

Footnotes

Authors Note

Acknowledgments

Author Contributions

Declaration of conflicting interests

Funding

Ethical Statement

Data Availability Statement

Author Biographies

References