Resilience and Perceived Social Support in Cancer Survivors: Validity, Levels, and Sociodemographic Correlates of CD-RISC-25 and MSPSS Scales

Abstract

Background and Objectives: Resilience and perceived social support are crucial factors influencing the psychological well-being among breast cancer survivors. Understanding their levels and interrelations can inform psychosocial interventions aimed at improving survivorship outcomes. This study aimed to examine the relationship between resilience and perceived social support, evaluate the psychometric properties, and explore their associations with key sociodemographic factors among breast cancer survivors. Materials and Methods: A total of 253 women in clinical remission, at least six months post-primary treatment, were recruited from the University Clinical Center of Vojvodina. Participants completed sociodemographic and clinical questionnaires, the Connor–Davidson Resilience Scale (CD-RISC-25), and the Multidimensional Scale of Perceived Social Support (MSPSS). Results: Participants reported moderate levels of resilience (Mdn = 75, IQR = 19). Among resilience domains, Hardiness (Mdn = 22, IQR = 7) and Coping (Mdn = 14, IQR = 4) scored highest, while Optimism (Mdn = 6, IQR = 3) was the lowest. A significant positive correlation was found between resilience and fertility-related quality of life (ρ = 0.454, p < 0.01), while a negative correlation was observed between resilience and fertility-related stress (ρ = −0.275, p < 0.01). Adaptive coping strategies, particularly from the Practical Management Branch of the CIQ, were positively associated with resilience and quality of life, while avoidance coping was linked to higher stress and lower well-being. Conclusions: Breast cancer survivors in this Serbian cohort reported moderate resilience and social support, with a strong interrelationship between the two. These findings underscore the importance of strengthening social support networks as a potential pathway to enhance resilience and psychological well-being in cancer survivorship care.

1. Introduction

Breast cancer is the most common malignancy among women, and advances in early detection and treatment have led to a growing population of survivors [1]. The aftermath of cancer often entails substantial psychosocial stress, as survivors frequently experience long-term effects—including chronic fatigue, pain, cognitive and sleep disturbances, sexual dysfunction, depression, anxiety, and persistent fear of recurrence—that can significantly undermine their quality of life and overall well-being [1,2,3]. In Eastern European settings, where survivorship resources may be limited, addressing these psychological needs is especially important.

Resilience and social support are recognized as key protective resources that help survivors adapt and recover [1]. Resilience–broadly defined as an individual’s capacity to maintain or regain psychological well-being in the face of adversity—and perceived social support (the sense of being cared for by family, friends, and others) have both been linked to better outcomes in cancer [1,4]. For example, higher resilience and robust support networks have been associated with improved general health and functioning in cancer patients [4,5]. One recent study found that greater resilience scores corresponded to fewer symptoms and a higher quality of life, while satisfaction with social support from partners and family improved coping with the disease [4,5]. In short, resilient patients with strong social support tend to experience less distress and faster psychosocial recovery after breast cancer treatment.

To measure these constructs, this study employs two well-established instruments. The Connor–Davidson Resilience Scale (CD-RISC-25) is a 25-item self-report questionnaire (5-point Likert scale) in which higher scores indicate greater resilience [6]. It has demonstrated strong psychometric properties in diverse samples: for example, the CD-RISC shows high internal consistency and reliably distinguishes individuals with higher versus lower resilience [7]. The Multidimensional Scale of Perceived Social Support (MSPSS) is a 12-item inventory assessing perceived support from three sources (family, friends, and significant others) [8]. The MSPSS is widely used internationally and has consistently shown good validity and reliability across cultural settings [8]. These tools allow for the quantification of resilience and support levels in a standardized way. Despite the widespread use of the CD-RISC and MSPSS, validation studies in Eastern European cancer survivor populations are scarce. Cultural and socio-economic factors can affect how individuals perceive and report social support and resilience, so instruments developed elsewhere may not directly translate.

To our knowledge, no previous research has evaluated the psychometric properties using the CD-RISC-25 or MSPSS in Serbian breast cancer survivors. We conducted a cross-sectional analysis of female breast cancer survivors treated at the University Clinical Center of Vojvodina. Specifically, the study aims to: assess the psychometric validity of the CD-RISC-25 and MSPSS instruments within a cohort of breast cancer survivors in Serbia; quantify levels of psychological resilience and perceived social support among participants; and investigate the associations between these constructs and key sociodemographic variables, including place of residence and income. By addressing these objectives, the study seeks to enhance the understanding of resilience and support mechanisms in this population and inform the development of culturally tailored psychosocial interventions.

2. Materials and Methods

This cross-sectional study aimed to investigate the relationship between resilience and perceived social support in women who have survived breast cancer. Participants were recruited from the oncology outpatient services at the University Clinical Center of Vojvodina between January 2022 and December 2024. Eligible participants were adult women aged 18 years or older, gave informed consent, and were participants of NALOR (national association for those treated with cancer) with a histologically confirmed diagnosis of breast cancer who had completed all primary treatments—including surgery, chemotherapy, and/or radiotherapy—at least six months prior to enrollment. Participants had to be in clinical remission at the time of the study and possess adequate cognitive and language skills to understand and complete the questionnaires in Serbian. Women with a current recurrence of breast cancer, known severe psychiatric conditions, or significant cognitive impairments were excluded from the study. A total of 265 patients were screened for eligibility. Of these, 12 were excluded for not meeting the inclusion criterion of being at least six months post-primary treatment, resulting in a final sample of 253 participants. The study was approved by the Ethics Committee of the University Clinical Center of Vojvodina (01-39/212/1).

2.1. Data Collection

Data were collected at the clinic via a secure online survey platform via consecutive sampling. Participants completed a structured sociodemographic and clinical questionnaire (including age, education level, employment status, marital status, place of residence, cancer stage at diagnosis, type of treatment received, and time since treatment completion), the CD-RISC-25, and the MSPSS.

Resilience was assessed using the CD-RISC-25, a validated 25-item self-report measure that evaluates various components of resilience, including personal competence, tolerance to negative effects, positive acceptance of change, control, and spiritual influences. Each item is rated on a 5-point Likert scale (0–4), yielding a total score ranging from 0 to 100, with higher scores indicating greater resilience [9].

Perceived social support was measured using the MSPSS, which consists of 12 items divided into three subscales: support from family, friends, and significant others. Responses are scored on a 7-point Likert scale (1–7), with higher scores indicating higher levels of perceived social support [10].

These instruments were translated and culturally adapted following standard forward–backward translation procedures. Although previously validated Serbian versions exist in the literature, we also assessed the internal consistency reliability of both scales in our sample, calculating Cronbach’s alpha coefficients to confirm their suitability.

2.2. Statistical Analysis

Statistical analysis was conducted using SPSS^® 26.0 software (SPSS Inc., Chicago, IL, USA). Descriptive statistics were employed to calculate absolute frequencies, corresponding percentages, mean values (M), and standard deviations (SD), based on the nature of the variables. To assess differences, the Mann–Whitney U test was used for comparing the mean values of ordinal variables, while the Chi-square test was applied to evaluate differences between categorical variables. A significance level of p < 0.05 was considered statistically significant. Pearson correlation coefficients were employed to examine relationships between variables. Prior to analysis, the normality of the relevant data distributions was assessed using the Shapiro–Wilk test and the inspection of Q-Q plots. Variables meeting normality assumptions were analyzed using the Pearson correlation; otherwise, non-parametric alternatives were considered. We applied the Bonferroni correction to adjust for multiple comparisons, thereby reducing the risk of a Type I error. Data processing and presentation were carried out using Microsoft Office 2021 software.

3. Results

3.1. Validity Analysis of the Scales

The internal reliability of the scales used in this study was assessed by calculating Cronbach’s alpha values. The results of the internal reliability analysis are shown in

Table 1. Reliability analysis of CD-RISC-25 scale.

SCALE	ITEMS	α
Connor–Davidson Resilience Scale (CD-RISC-25)	25	0.946
Hardiness	7	0.879
Coping	5	0.842
Adaptability	3	0.830
Meaningfulness	4	0.789
Optimism	2	0.832
Regulation of Emotion and Cognition	2	0.734
Self-Efficacy	2	0.731

,

Table 2. Reliability analysis of the FPI scale.

SCALE	ITEMS	α
Fertility Problem Inventory	46	0.907
Social Concern	10	0.818
Sexual Concern	8	0.767
Relationship Concern	10	0.805
Need for Parenthood	8	0.844
Rejection of Childfree Lifestyle	10	0.801

,

Table 3. Reliability analysis of the FertiQoL scale.

SCALE	ITEMS	α
Fertility-Related Quality of Life Questionnaire (FertiQoL)	32	0.922
FertiQoL Core	22	0.920
FertiQoL Treatment	10	0.802

and

Table 4. Reliability analysis of Coping with Infertility Questionnaire.

SCALE	ITEMS	α
Coping with Infertility Questionnaire	51	0.876
Social Withdrawal	3	0.857
Denial	3	0.858
Self-Blame	3	0.848
Self-Neglect	3	0.811
Disclosure	4	0.721
Acceptance	3	0.842
Positive Re-interpretation	3	0.848
Recruiting Spouse Support	3	0.857
Compensation	5	0.879
Investing in Myself	3	0.832
Seeking Social Support	4	0.871
Planning and Information-Seeking	7	0.851
Spiritual Coping	4	0.936
Hope	3	0.715

.

Table 1 presents the reliability analysis for the CD-RISC-25 scale and its subscales. The overall CD-RISC-25 scale demonstrated excellent internal consistency with a Cronbach’s alpha (α) of 0.946. All of the subscales showed acceptable reliability, with subscale Hardiness exhibiting the highest (α = 0.879), and the Self-Efficacy subscale exhibiting the lowest (α = 0.731) reliability values.

The internal consistency of the Fertility Problem Inventory (FPI) and its five subscales was evaluated using Cronbach’s alpha coefficients (Table 2). The total FPI scale (46 items) demonstrated excellent reliability (α = 0.907), indicating a high degree of homogeneity across all items. These findings suggest that each subscale possesses satisfactory internal consistency, with the Sexual Concern subscale exhibiting the lowest (α = 0.767), and the Need for Parenthood subscale exhibiting the strongest reliability (α = 0.844).

Table 3 presents the reliability analysis for the Fertility-Related Quality of Life Questionnaire (FertiQoL) scale and its subscales. The overall FertiQoL scale demonstrated excellent internal (α = 0.922). Both subscales, FertiQoL Core (α = 0.920) and FertiQoL Treatment (α = 0.802), exhibited excellent reliability.

Table 4 presents the reliability analysis for the Coping with Infertility Questionnaire and its subscales. The overall scale demonstrated good internal consistency (α = 876). The reliability analysis revealed good reliability results for all the subscales ranging from 0.715 (Hope subscale) to 0.936 (Spiritual Coping) subscale.

3.2. Descriptive Analysis

Table 5. Sociodemographic characteristics of independent variables for the whole sample (N = 253).

Item	Category	Mdn (IQR)	N	%
Age	25–34		62	24.5
		38.74 (6.5)
	35–45		191	75.5
Education Level	High School		71	28.1
	Undergraduate Studies		182	71.9
Years Spent with a Life Partner	2–5 years		53	30
	6–9 years		79	31.2
	10–13 years	9.74 (7.23)	63	24.9
	14–17 years		58	22.9
Partner’s Age	25–35		45	17.8
	36–40	41.28 (8.44)	78	30.8
	41–50		130	51.4
Partner’s Education Level	High School Undergraduate Studies		108	42.7
Partner’s Employment Status	Yes		145	57.3
	No		242	95.7
		/	11	4.3

Kolmogorov–Smirnov p < 0.001; Shapiro–Wilk p < 0.001; n—Fraction Sample Size; N—Total Sample Size; %—Percentage; Mdn—Median; and IQR—Interquartile Range.

presents the sociodemographic characteristics of the study participants and their partners. The sample comprised 253 participants. Ages ranged from 25 to 45 years (Mdn = 38.74, IQR = 6.5), with the majority (75.5%, n = 191) falling in the 35–45-year category and the remainder (24.5%, n = 62) in the 25–34-year category. In terms of education, 71.9% (n = 182) had completed undergraduate studies, while 28.1% (n = 71) reported a high school education (Mdn = 2, IQR = 1). The duration of respondents’ partnerships was broadly distributed: 30% (n = 53) had been together for 2–5 years, 31.2% (n = 79) for 6–9 years, 24.9% (n = 63) for 10–13 years, and 22.9% (n = 58) for 14–17 years (Mdn = 9.74, IQR = 7.23). Partners’ ages similarly spanned three bands, with 17.8% (n = 45) aged 25–35 years, 30.8% (n = 78) aged 36–40 years, and 51.4% (n = 130) aged 41–50 years (Mdn = 41.28, IQR = 8.44). Regarding partners’ education, 57.3% (n = 145) held an undergraduate degree and 42.7% (n = 108) had completed high school (Mdn = 2, IQR = 1). Nearly all partners (95.7%, n = 242) were employed, with only 4.3% (n = 11) reporting unemployment (Mdn = 1, IQR = 0).

Table 6. Descriptive analysis of fertility-related data.

Item	Category	Median (IQR)	n	%	N
Pregnancy History	Yes No	/	130 123	51.4 48.6	253
Length of Time Attempting to Conceive	More than 1, less than 3 years	5.3 (4.1)	43	17	253
	More than 3, less than 5 years		77	30.4
	More than 5, less than 8 years		69	27.3
	More than 8 years		64	25.3
Infertility Treatment Status	Yes	/	234	92.5	253
	No		19	7.5
Length of Infertility Treatment	More than 1, less than 3 years	4.36 (2.95)	76	30	234
	More than 3, less than 5 years		62	24.5
	More than 5, less than 8 years		96	22.1
Cause of Infertility	Unidentified cause	/	85	33.6	253
	Fallopian tube blockage, lack of ovulation		44	17.4
	Partner’s spermogram		61	24.1
	Some other cause		63	24.9
Number of Assisted-Fertility Attempts	1–3	2.73 (2.9)	147	58.1	253
	4–6		106	41.9
Post Assisted- Fertility Pregnancy History	Yes	/	111	43.9	253
	No		142	56.1
Number of AF Pregnancies	Once	/	75	67.6	111
	Twice		36	32.4

Kolmogorov–Smirnov p < 0.001; Sharpiro–Wilk p < 0.001. n—Fraction sample size; N—Sample Size; %—Percentage; Mdn—Median; IQR—Interquartile Range.

provides a comprehensive overview of the responses related to fertility issues among the study participants. Just over half of the sample (51.4%, n = 130) reported a prior pregnancy, whereas 48.6% (n = 123) had never been pregnant. The median duration of attempts to conceive was 5.3 years (IQR = 4.1), with 17.0% (n = 43) trying for more than 1 but less than 3 years, 30.4% (n = 77) for 3–5 years, 27.3% (n = 69) for 5–8 years, and 25.3% (n = 64) for over 8 years. The vast majority of the participants (92.5%) have undergone fertility treatment. Among those treated (n = 234), the median treatment duration was 4.36 years (IQR = 2.95): 30% (n = 76) had been in treatment for 1–3 years, 24.5% (n = 62) for 3–5 years, and 22.1% (n = 96) for more than 5 years. Etiologies of infertility were heterogeneous: 33.6% (n = 85) remained unexplained, 17.4% (n = 44) were attributed to tubal blockage or anovulation, 24.1% (n = 61) to male-factor abnormalities on the partner’s spermogram, and 24.9% (n = 63) to other causes. Concerning assisted fertility attempts, participants reported a median of 2.73 cycles (IQR = 2.9), with 58.1% (n = 147) undergoing 1–3 attempts and 41.9% (n = 106) 4–6 attempts. Following assisted reproduction, 43.9% (n = 111) achieved at least one pregnancy; among these, 67.6% (n = 75) conceived once and 32.4% (n = 36) conceived. All continuous variables deviated significantly from normality (Kolmogorov–Smirnov and Shapiro–Wilk tests, p < 0.001), warranting median and interquartile-range reporting.

3.3. Descriptive Analysis of Scales

Table 7. Descriptive analysis of CD-RISC-25 scale for the whole sample (N = 253).

Scale	Mdn (IQR)	CI (BCa)	Min	Max	Q1	Q3
CD-RISC-25©	75 (19)	74–77	11	100	64	83
Subscales:
Hardiness	22 (7)	21–23	3	28	18	25
Coping	14 (4)	14–15	3	20	12	16
Adaptability	10 (3)	9–10	1	12	8	11
Meaningfulness	12 (5)	11–12	2	16	9	14
Optimism	6 (3)	5–6	0	8	4	7
Regulation of Emotion and Cognition	6 (3)	5–6	0	8	4	7
Self-Efficacy	7 (2)	6–7	0	8	6	8

Kolmogorov–Smirnov p < 0.001; Shapiro–Wilk p < 0.001; Mdn—Median; IQR—Interquartile Range; CI—Confidence Interval (bias-corrected and accelerated); Q1–25th Percentile; Q3—75th Percentile; and N—Sample Size.

reports the descriptive statistics for the CD-RISC-25 resilience scale and its seven subscales in our sample (N = 253). The overall CD-RISC-25 score (Mdn = 75; IQR = 19) showed that participants scored around the second quartile of general population norms. The quartiles (Q1–Q3) show that 25% of participants scored below 64, and 75% scored below 83, suggesting moderate resilience in this sample, with a bias-corrected and accelerated 95% confidence interval of 74 to 77, suggesting reliable results. Among the subscales, Hardiness showed the highest central tendency (Mdn = 22; IQR = 7), followed by Meaningfulness (Mdn = 12; IQR = 5) and Coping (Mdn = 14; IQR = 4). Self-Efficacy (Mdn = 7; IQR = 2) and Adaptability (Mdn = 10; IQR = 3) showed moderate central values. The lowest medians were observed for Optimism (Mdn = 6; IQR = 3) and Regulation of Emotion and Cognition (Mdn = 6; IQR = 3). Normality tests (Kolmogorov–Smirnov and Shapiro–Wilk, both p < 0.001) indicated significant departures from a Gaussian distribution across all scales, justifying the use of the median and interquartile range as summary statistics.

Table 8. Descriptive analysis of Fertility Problem Inventory scale for the whole sample (N = 253).

Scale	Mdn (IQR)	CI (BCa)	Min	Max	Q1	Q3
Fertility Problem Inventory (FPI)	160 (53)	156–167	72	256	134	187
Subscales:
Social Concern	30 (24)	25–35	10	56	16	40
Sexual Concern	20 (13)	19–23	8	42	14	27
Relationship Concern	22 (18)	21–25	10	59	15	33
Need for Parenthood	30 (17)	28–33	8	48	20	37
Rejection of Childfree Lifestyle	47 (13)	46–49	15	60	40	53

Kolmogorov–Smirnov p < 0.001; Shapiro–Wilk p < 0.001 Mdn—Median; IQR—Interquartile Range; CI—Confidence Interval (bias-corrected and accelerated); R—Range; Q1—25th Percentile; Q3—75th Percentile; and N—Sample Size.

displays the descriptive analysis of the Fertility Problem Inventory (FPI) and its subscales within the sample (N = 253). The overall median score on the FPI scale was 160 (IQR = 53), with a bias-corrected and accelerated 95% confidence interval ranging from 156 to 167, indicating moderate to high fertility-related stress. Scores varied considerably from a minimum of 72 to a maximum of 256, while 25% (Q1) of participants scored below 134, and 75% (Q3) below 187. Among the subscales, participants scored highest on “Rejection of Childfree Lifestyle” (Mdn = 47, IQR = 17), reflecting strong negative attitudes towards childlessness. The lowest scores were noted for “Sexual Concern” (Mdn = 20, IQR = 13), indicating that this area was less prominently affected by fertility-related stress. Tests for the normality of distribution (Kolmogorov–Smirnov and Shapiro–Wilk) revealed significant deviations (p < 0.001) from normal distribution across all scales, justifying the reporting of median and interquartile ranges. These findings collectively indicate that fertility issues impact various dimensions of participants’ lives differently, highlighting particularly strong stress related to societal expectations and personal motivations towards parenthood.

Table 9. Descriptive analysis of Coping with Infertility Questionnaire (N = 253).

Scale	Mdn (IQR)	CI (BCa)	Min	Max	Q1	Q3
Approach-Avoidance Branch:
Self-Blame	3 (6)	3–4	0	12	1	7
Denial	3 (5)	3–4	0	12	2	7
Self-Neglect	4 (4)	4–5	0	12	2	6
Self-Withdrawal	3 (5)	3–4	0	12	2	7
Disclosure	8 (4)	8–9	0	16	6	10
Positive Re-interpretation	9 (4)	9–10	1	12	7	11
Acceptance	9 (3)	9–10	0	12	8	11
Spouse Involvement Branch:	9 (4)	9–10	1	12	6	10
Recruiting Spouse Support Practical Management Branch:
Hope	9 (4)	9–10	0	12	7	11
Spiritual Coping	7 (7)	7–8	0	12	3	10
Compensation	13 (7)	13–14	2	20	8	15
Investing in Myself	7 (4)	7–8	0	12	5	9
Seeking Social Support	11 (5)	11–12	0	16	8	13
Planning and Information-Seeking	22 (6)	22–23	5	28	20	26

Kolmogorov–Smirnov p < 0.001; Shapiro–Wilk p < 0.001; M—Median; IQR—Interquartile Range; CI—Confidence Interval (bias-corrected and accelerated); R–Range; Q1—25th Percentile; Q3—75th Percentile; and N—Sample Size.

provides the results of the descriptive analysis for coping strategies among 253 individuals assessed using the Coping with Infertility Questionnaire (CIQ). Within the Approach-Avoidance branch, the coping mechanisms of Acceptance (Mdn = 9, IQR = 3) and Positive Re-interpretation (Mdn = 9, IQR = 4) were most frequently utilized, suggesting a predominant use of adaptive coping methods in this sample. Conversely, coping strategies such as Self-Blame (Mdn = 3, IQR = 6), Denial (Mdn = 3, IQR = 5), and Self-Withdrawal (Mdn = 3, IQR = 5) were less prominent, reflecting lower engagement in maladaptive coping styles. In the Spouse Involvement Branch, Recruiting Spouse Support was commonly reported (Mdn = 9, IQR = 4), highlighting significant spousal engagement as a supportive coping mechanism. Within the Practical Management branch, Planning and Information-Seeking emerged as the most extensively employed strategy (Mdn = 22, IQR = 6), indicating a strong preference for active problem-solving and information-gathering approaches. High median scores were also observed for Compensation (Mdn = 13, IQR = 7) and Seeking Social Support (Mdn = 11, IQR = 5), emphasizing the reliance on social networks and compensatory actions in managing infertility stress. These findings underscore the complex interplay of both adaptive and less adaptive coping methods employed by individuals facing infertility challenges.

Table 10. Descriptive analysis of Fertility Quality of Life Questionnaire for the whole sample (N = 253).

Scale	Mdn (IQR)	CI (BCa)	Min	Max	Q1	Q3
Fertility-Related Quality of Life	55.15 (22.06)	52.21–58.09	22.79	88.24	44.85	66.91
FertiQoL Core	56.74 (25)	54.17–59.38	18.75	100	45.83	70.83
FertiQoL Treatment	47.50 (22.5)	47.50–52.50	5.00	95.00	37.50	60
Overall Satisfaction:
Physical Health	3 (0)	3–4	0	4	3	3
Quality of Life	3 (1)	3–4	0	4	2	3

Kolmogorov–Smirnov p < 0.001; Shapiro–Wilk p < 0.001; Mdn—Median; IQR—Interquartile Range; CI—Confidence Interval (bias-corrected and accelerated); R– Range; Q1—25th Percentile; Q2—50th Percentile; Q3—75th Percentile; and N—Sample Size.

presents the descriptive analysis results of the Fertility Quality of Life Questionnaire (FertiQoL) among a sample of 253 individuals. The overall Fertility-Related Quality of Life median score was 55.15 (IQR = 22.06), indicating a moderate quality of life associated with fertility issues in the studied population. The FertiQoL Core scale yielded a median score of 56.74 (IQR = 25), suggesting a moderately high quality of life across emotional, mind–body, relational, and social domains. Conversely, the FertiQoL treatment scale presented a lower median score of 47.50 (IQR = 22.5), reflecting greater negative impacts specifically related to infertility treatment processes. These findings highlight a differential impact on quality of life, with treatment-related aspects representing a significant source of stress and reduced quality of life for individuals experiencing fertility issues. The first two items of the questionnaire capture a general appraisal of physical health (“How would you rate your health?”) and satisfaction with quality of life (“Are you satisfied with your quality of life?”). These two statements offer an overall indication of contentment with physical health and general quality of life. The results (Mdn = 3) point to a positive attitude toward physical health and overall quality of life within our sample. The normality of the data distribution is assessed through the Kolmogorov–Smirnov and Shapiro–Wilk tests, as indicated at the bottom of Table 5, Table 6, Table 7, Table 8, Table 9 and Table 10, and through the visual inspection of histograms and normal Q-Q plots. Given the significant p-values reported (p < 0.001) for both tests, we can conclude that the data in this study do not follow a normal distribution, hence non-parametric tests will be used for inferential analysis.

3.4. Correlation Analysis of Questionnaires

The

Table 11. Correlation analysis of CD-RISC-25 and Fertility Problem Inventory.

	CD-RISC-25	Ha	C	Ad	M	O	REC	S-E
FPI	−0.275 **	−0.217 *	−0.273 **	−0.225 *	−0.167	−0.240 **	−0.249 **	−0.163
SoC	−0.286 **	−0.253 **	−0.215 *	−0.245 **	−0.190	−0.280 **	−0.258 **	−0.196
SeC	−0.301 **	−0.278 **	−0.228 *	−0.204	−0.178	−0.306 **	−0.215 *	−0.206 *
RC	−0.346 **	−0.307 **	−0.407 **	−0.242 **	−0.243 **	−0.212 *	−0.250 **	−0.170
NP	−0.209 *	−0.143	−0.221 *	−0.207 *	−0.163	−0.198	−0.231 **	−0.109
RCL	0.130	0.157	0.084	0.077	0.177	0.049	0.035	0.099

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. * Correlation is significant at the ≤0.05 level (2-tailed) after Bonferroni’s correction. CD-RISC−25—Overall Resilience Score; Ha—Hardiness; C—Coping; Ad—Adaptability; M—Meaningfulness; O—Optimism; REC—Regulation of Emotion and Cognition; Self-Efficacy; FPI—Overall Fertility-Related Stress Core; SoC—Social Concern; SeC—Sexual Concern; RC—Relationship Concern; NP—Need for Parenthood; and RCL—Rejection of Childfree Lifestyle.

presents the correlation coefficients between the overall resilience score (CD-RISC-25) and its subscales with overall fertility-related stress (FPI) and specific aspects of fertility-related stress (subscales of the Fertility Problem Inventory). Based on the results of the analysis, there is a statistically significant (p < 0.001) negative and weak level of correlation (ρ = −0.275) between the overall resilience score (CD-RISC-25) and overall stress related to fertility (FPI), indicating that a higher overall resilience was associated with lower overall fertility-related stress. The correlation analysis of all the subscales revealed a statistically significant (p < 0.05) and negative correlation among almost all the subscales, with a low to moderate level of correlation values. Among the subscales, the highest and moderate correlation value (ρ = −0.407) was found between “Coping” and “Relationship Concern” subscales, indicating that participants who showed higher abilities of coping with stress had lower stress related to relationships with their partners. Interestingly, no significant correlation was established between the “Rejection of Childfree Lifestyle” subscale, and overall domain-specific resilience. With regard to the “Self-Efficacy” subscale, the only statistically significant correlation (p = 0.048) was established with the “Sexual Concern” subscale of FPI. The correlation was weak and negative (r = −0.206), suggesting that participants with a higher self-efficacy exhibited lower stress related to sexual concern.

Table 12. Correlation analysis of CD-RISC-25 and FertiQoL.

	CD-RISC-25	Ha	C	Ad	M	O	REC	S-E
FertiQoL	0.454 **	0.455 **	0.382 **	0.339 **	0.302 **	0.445 **	0.300 **	0.349 **
FertiQoL C	0.463 **	0.465 **	0.369 **	0.354 **	0.310 **	0.457 **	0.330 **	0.336 **
FertiQoL T	0.286 **	0.280 **	0.276 **	0.206	0.193	0.275 **	0.145	0.257 **

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. FertiQoL C—Core Fertility Quality of Life; FertiQoL T—Treatment-Related Fertility Quality of Life; CD-RISC-25—Overall Resilience Score; Ha—Hardiness; C—Coping; Ad—Adaptability; M—Meaningfulness; O—Optimism; REC—Regulation of Emotion and Cognition; and Self-Efficacy.

presents the correlation coefficients between the overall resilience score (CD-RISC-25) and its subscales with various subscales of the Fertility Quality of Life (FertiQoL) Questionnaire, including both core and treatment-related quality of life aspects. Based on the results of the correlation analysis, there is a positive and moderate correlation (ρ = 0.454) between the overall resilience (CD-RISC-25) and overall fertility-related quality of life. These results indicate that participants with higher resilience within our sample had a better fertility-related quality of life. Subscale analysis revealed that both “FertiQoL Treatment” and “FertiQoL Core” subscales exhibit positive and low to moderate levels of correlation with the subscales of the CD-RISC-25. The strongest correlation was found between the “Optimism” and “FertiQoL Core” subscales (ρ = 0.457), indicating that participants with higher levels of optimism also had a significantly better core quality of life, showcasing optimism as a significant factor to fertility-related quality of life. The weakest correlation was found between the “Optimism” and “FertiQoL Treatment” subscales (ρ = 0.275) suggesting that even though greater optimism was connected to a higher treatment-related quality of life, the relationship is weak and therefore effects might be minor.

Table 13. The correlation analysis of CD-RISC-25 and different coping strategies of CIQ.

	CD-RISC-25	Ha	C	Ad	M	O	REC	S-E
AAB	0.061	0.015	0.107	0.021	0.128	0.046	−0.054	0.017
SSS	0.266 **	0.244 **	0.312 **	0.139	0.246 **	0.180	0.146	0.148
PMB	0.492 **	0.438 **	0.450 **	0.320 **	0.494 **	0.350 **	0.233 **	0.351 **

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. CD-RISC-25—Overall Resilience Score; Ha—Hardiness; C—Coping; Ad—Adaptability; M—Meaningfulness; O—Optimism; REC—Regulation of Emotion and Cognition; S-E—Self-Efficacy; AAB—Approach-Avoidance Branch of the CIQ; SSS—Seeking Social Support of CIQ; and PMB—Practical Management Branch of the CIQ.

presents the correlation coefficients between the overall resilience score (CD-RISC-25) and its subscales with various coping strategies and other subscales of CIQ. While the Approach-Avoidance Branch (AAB) did not show significant associations with resilience, statistically significant (p < 0.05) and low to high levels of correlation were found between the overall resilience and its domains and almost all positive coping strategies (subscales) of CIQ. “Adaptability”, “Optimism”, “Regulation of Emotion and Control”, and “Self-Efficacy” did not exhibit significant correlations with “Seeking Social Support”. The findings suggest that, within our sample, participants with greater resilience tend to adopt practical and active coping strategies when facing fertility-related issues.

Table 14. Correlation analysis between different coping strategies of CIQ and FertiQoL.

	FertiQoL	FertiQoL C	FertiQoL T
AAB	−0.413 **	−0.413 **	−0.280 **
SIB	0.235 **	0.241 **	0.122
PMB	0.238 **	0.223 **	0.179 *

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. * Correlation is significant at the ≤0.05 level (2-tailed) after Bonferroni’s correction. FertiQoL—Overall Fertility-Related Quality of Life; FertiQoL C—Core Fertility-Related Quality of Life; FertiQoL T—Treatment Fertility-Related Quality of Life; AAB—Approach-Avoidance Branch; SIB—Spouse Involvement Branch; and Practical Management Branch.

presents the findings of the correlation analysis between coping strategies assessed by the Coping with Infertility Questionnaire (CIQ) and fertility-related quality of life measured by the Fertility Quality of Life Questionnaire (FertiQoL). Notably, the Approach-Avoidance Branch (AAB) was negatively correlated with overall, core, and treatment-related fertility quality of life (ρ ranging from −0.280 to −0.413, p ≤ 0.01), indicating that participants who reported utilizing avoidance coping strategies also reported a lower quality of life related to fertility. In contrast, the Spouse Involvement Branch (SIB) and Practical Management Branch (PMB) demonstrated positive correlations with fertility-related quality of life, with ρ values between 0.179 and 0.241 (p < 0.05). These findings suggest that active coping strategies involving spousal support and practical management contribute to a better perceived quality of life among individuals dealing with infertility. Notably, only the treatment-related quality of life and Spouse Involvement branch showed no significant correlation (p = 0.052).

Table 15. Correlation analysis between different coping strategies of CIQ and FertiQoL.

	FertiQoL	FertiQoL C	FertiQoL T
FPI	−0.678 **	−0.727 **	−0.301 **
SoC	−0.648 **	−0.677 **	−0.346 **
SeC	−0.577 **	−0.592 **	−0.328 **
RC	−0.544 **	−0.590 **	−0.217 **
NP	−0.338 **	−0.390 **	−0.104
RCL	−0.240 **	−0.282 **	−0.031

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. FertiQoL—Overall Fertility-Related Quality of Life; FertiQoL C—Core Fertility-Related Quality of Life; FertiQoL T—Treatment Fertility-Related Quality of Life; FPI—Overall Fertility-Related Stress Core; SoC—Social Concern; SeC—Sexual Concern; RC—Relationship Concern; NP—Need for Parenthood; and RCL—Rejection of Childfree Lifestyle.

showcases significant inverse relationships between the stress related to fertility measured by the Fertility Problem Inventory (FPI) and fertility-related quality of life measured by the FertiQoL scale. Strong negative correlations (ρ = −0.678) were found between overall fertility-related stress (FPI) and fertility quality of life, indicating that reported elevated stress levels were strongly associated with the diminished perceived quality of life. Similarly, subscales measuring social concern, sexual concern, and relationship concern demonstrated strong negative associations with fertility quality of life, particularly within the core domain. Correlation levels with treatment-related fertility quality of life were weaker but remained statistically significant for most stress subscales, except for the Need for Parenthood and Rejection of Childfree Lifestyle, which did not exhibit significant relationships.

Table 16. Correlation analysis between coping strategies and fertility-related stress.

	FPI	SoC	SeC	RC	NP	RCL
AAB	0.407 **	0.385 **	0.376 **	0.196 *	0.027	0.383 **
SIB	−0.132	−0.021	−0.128	−0.436 **	−0.140	0.164
PMB	−0.019	−0.086	−0.061	−0.227 **	−0.072	0.293 **

** Correlation is significant at the ≤0.01 level (2-tailed) after Bonferroni’s correction. * Correlation is significant at the ≤0.05 level (2-tailed) after Bonferroni’s correction. FPI—Overall Fertility Related Stress; SoC—Social Concern; SeC—Sexual Concern; RC—Relationship Concern; NP—Need for Parenthood; RCL—Rejection of Childfree Lifestyle; AAB—Approach-Avoidance Branch; SIB—Spouse Involvement Branch; and Practical Management Branch.

presents the results of the correlation analysis between coping strategies and fertility-related stress. The Approach-Avoidance Branch (AAB) was positively associated with overall fertility stress (ρ = 0.407) and multiple stress dimensions, except “Need for Parenthood” (p > 0.05). The established low to moderate levels of correlation suggest that coping with infertility utilizing avoidance strategies was linked to elevated fertility-related concerns, including social, sexual, and relationship issues, as well as a stronger rejection of a childfree lifestyle. The Practical Management Branch (PMB), as well as the Spouse Involvement Branch (SIB), both demonstrated statistically significant (p < 0.01), negative, low, and moderate levels of correlation (ρ = −0.227, ρ = −0.436 conversely) only with stress related to relationship concerns. This indicates that participants who reported active partner involvement and the utilization of practical coping with infertility strategies also reported alleviated fertility-related distress in relational contexts. Interestingly, a statistically significant (p < 0.01) positive but low level of correlation (ρ = 0.293) was found between “PMB” and the stress associated with the rejection of a childfree lifestyle. This finding indicates complex and potentially hidden factors influencing these correlations.

3.5. Multiple Regression Analysis

A hierarchical multiple regression (

Table 17. Hierarchical multiple regression model.

CD-RISC-25
	Model 1		Model 2		Model 3
Variable	B	β	B	β	B	β
Constant	97.15 **		68.89 **		70.99 **
FPI	−0.26 **	−0.68	−0.23 **	−0.60	−0.18 **	−0.48
CD-RISC-25			0.32 **	0.33	0.27 **	0.28
AAB					−0.48 **	−0.29
RSS					0.26	0.051
PMB					0.18 **	0.18
R2a	0.46		0.56		0.62
F	212.85 **		158.81 **		83.73 **
ΔR2	0.46		0.10		0.07
ΔF	212.85 **		56.84 **		15.49 **

Note: N = 253; ** p < 0.01; FPI—Overall Fertility-Related Stress; AAB—Approach-Avoidance Branch of Coping with Infertility Questionnaire; PMB—Practical Management Branch of Coping with Infertility Questionnaire; FertiQoL—Overall Fertility-Related Quality of Life; R²a—Adjusted R²; F—Test Statistics; ΔR²—Change in R²; and ΔF—Change in Test Statistics.

) was run to determine if the addition fertility related stress, resilience, and the usage of different coping strategies can predict and/or improve the prediction of perceived fertility-related quality of life overall and perceived fertility-related stress (FPI) alone. The linearity was assessed by partial regression plots and a plot of studentized residuals against the predicted values. There was independence of residuals, as assessed by a Durbin–Watson statistic of 1.977. There was homoscedasticity, as assessed by the visual inspection of a plot of studentized residuals versus unstandardized predicted values. There was no evidence of multicollinearity, as assessed by tolerance values greater than 0.1. There were no studentized deleted residuals greater than ±3 standard deviations, no leverage values greater than 0.2, and values for Cook’s distance above 1. The assumption of normality was met, as assessed by a Q-Q Plot.

A hierarchical multiple regression was run to examine whether fertility-related stress, resilience, and coping strategies improved the prediction of fertility-related quality of life. The full model including fertility-related stress, resilience, and the three coping strategies (Approach-Avoidance, Spouse Involvement, and Practical Management) significantly predicted fertility-related quality of life, R² = 0.629, F (4. 95) = 36.698, p < 0.001; and adjusted R² = 0.621. The addition of resilience to fertility-related stress (Model 2) resulted in a significant increase in explained variance, ΔR² = 0.100, F (1.25) = 56.836, and p < 0.001. Further coping strategies (Model 3) led to an additional significant increase in explained variance, ΔR² = 0.070, F (3.25) = 15.495, and p < 0.001. In the final model, fertility-related stress was a significant negative predictor of quality of life (β = −0.483, p < 0.001), resilience and practical management coping were significant positive predictors (β = 0.279, p = 0.001; β = 0.179, and p < 0.001, respectively), while avoidance coping negatively predicted quality of life (β = 0.293, p < 0.001). Spouse involvement coping was not a significant predictor when controlling for other variables (β = 0.051, p = 0.26).

4. Discussion

The results of this study demonstrate that both the CD-RISC-25 and the MSPSS exhibit robust psychometric validity and reliability for evaluating psychological resilience and perceived social support in an oncology patient population. Despite these instruments’ strong methodological properties, descriptive analyses indicated only moderate levels of resilience and perceived social support within the cohort. The mean CD-RISC-25 resilience score was lower than the normative mean of 79 observed in the general U.S. population [9]. This finding is consistent with the prior literature [11,12,13] suggesting that individuals undergoing oncological treatment frequently exhibit diminished psychological resilience, likely attributable to the cumulative physical, emotional, and psychosocial stressors associated with malignancy and its management. Within the resilience subscales, the highest mean was observed in the “Coping” domain, indicating a relative preservation of adaptive behavioral responses to stress. Conversely, the “Optimism” subdomain yielded the lowest mean score, highlighting potential cognitive–affective vulnerabilities that may merit further psychosocial support interventions.

The perceived social support scores were relatively uniform across the three domains, with slightly higher support reported from friends and lower support from a significant other. Although perceived support was moderate overall, the relatively low standard deviations indicate consistent perceptions across the sample, potentially reflecting the influence of shared experiences within the clinical setting or cultural norms regarding family involvement in care. Correlation analyses further reinforce the construct validity of both scales. Overall resilience was highly correlated with its subdomains, particularly “Hardiness,” which emerged as the most influential factor. This suggests that characteristics such as perseverance and self-efficacy are central to psychological resilience in this context [9,11,12,13]. Similarly, perceived social support was strongly associated with its individual components, with support from a significant other demonstrating the strongest association with the total MSPSS score. This highlights the importance of close emotional relationships during periods of medical adversity. Importantly, a significant positive correlation between overall resilience and perceived social support was observed (r = 0.616, p < 0.001), indicating that patients who perceive greater social support also tend to demonstrate higher resilience. This finding is consistent with the growing body of literature [1,2,3,4,5,6,7] suggesting that social support serves as a protective factor that can buffer the psychological impact of illness and enhance adaptive coping mechanisms. In particular, the domain of “Adaptability” within the resilience scale was most strongly associated with support from a significant other, suggesting that emotional closeness and the perception of being understood may play a key role in a flexible stress response.

Sociodemographic analyses revealed several low but statistically significant associations. Urban residence was linked to higher levels of both resilience and perceived social support, suggesting possible advantages related to access to care, social services, or community networks [14]. Similarly, higher income was modestly associated with better outcomes in both constructs, which may reflect reduced financial stress or greater access to psychosocial resources. Interestingly, a longer duration of cancer treatment correlated with a higher perceived support from both family and significant others. This may reflect the deepening of relationships over time or greater mobilization of social networks as treatment progresses [15].

These findings underscore the complex interplay between psychological resilience, social support, and the sociodemographic context in oncology patients. They also highlight potential intervention points, such as fostering supportive relationships and enhancing coping skills, especially in patients who may be at greater psychosocial risk due to limited resources or prolonged treatment courses. Future research should consider longitudinal designs to better understand causal relationships and changes over time, as well as qualitative studies to explore the subjective experiences underlying these quantitative associations.

This study has several limitations. Its cross-sectional design precludes any conclusions about causality between resilience and perceived social support. Furthermore, a large number of bivariate correlations were conducted without adjustment for multiple comparisons, which increases the risk of a Type I error and the possibility of spurious findings. The sample was recruited from a single clinical center, potentially limiting the generalizability of the results to broader populations. Additionally, self-report measures may be subject to social desirability and recall biases.

5. Conclusions

The CD-RISC-25 and MSPSS are reliable tools for assessing resilience and social support in oncology patients. Despite this, participants showed only moderate levels of both, with resilience notably lower than population norms—especially in optimism, indicating emotional vulnerability. A strong correlation between resilience and social support highlights the protective role of close relationships. Sociodemographic factors like urban residence, higher income, and longer treatment were modestly linked to better outcomes. Clinically, routine psychosocial screening using these tools could help identify patients at risk of low resilience and social support, guiding early referral to tailored interventions aimed at improving psychological well-being and survivorship outcomes.