Received and perceived support subscales of the Berlin Social Support Scales in women diagnosed with breast cancer attending the breast clinic at Tygerberg hospital: structure and correlates

Abstract

Research in the field of psycho-oncology in South Africa is increasing, and there is a need for validated measures that assess factors associated with cancer, such as social support. The Berlin Social Support Scales are a battery of instruments that measure various types and functions of social support. The measure was originally developed for use among adult cancer patients, and their partners but has also been used among other clinical populations and healthy adults. We investigated the psychometric properties of the English version of the perceived and received sub-scales, Berlin Social Support Scales. Our sample included South African women (N = 201) who were diagnosed with breast cancer and receiving treatment at a public health care facility. We administered several measures, including a demographic questionnaire, the Berlin Social Support subscales, the Duke-UNC Functional Social Support Questionnaire, and The Functional Assessment of Cancer Therapy to participants. Validity and reliability analyses were conducted. Factor analysis resulted in the retention of 17 items that clustered on two factors, namely received support and perceived support. The 17-item version of the Berlin Social Support Scale demonstrated strong reliability and validity in the sample. The two subscales are quick to administer, easy to interpret, and are a reliable measure of social support among breast cancer patients in South Africa.

Keywords

Berlin social support scale breast cancer factor analysis oncology validation

Social support refers to the quality of supportive interactions that a person has with other individuals (Schwarzer & Leppin, 1991) and can play an important role in well-being. It has been theorised that social support acts as a buffer to protect individuals from the physical and mental effects of stress (Cohen & Wills, 1985). Support has been categorised into two distinct types, namely perceived support and received support (e.g., Barrera, 1986). Perceived support is assessed prospectively and refers to the expectation that others in one’s social network will be available to provide assistance if needed, whereas received support is a retrospective appraisal of support that has already been given (e.g., Cohen, Gottlieb, & Underwood, 2001). A meta-analysis conducted on 23 studies found an average correlation of r = .35 between perceived support and received support (Haber, Cohen, Lucas, & Baltes, 2007), indicating a medium association between these constructs. Moreover, perceived social support predicts beneficial psychosocial and physical health outcomes more robustly than received social support (Holt-Lunstad, Smith, & Bradley Layton, 2010; Melrose, Brown, & Wood, 2015).

Several qualitative studies have highlighted the importance of social support to patients and survivors of breast cancer (Patel, Harcourt, Naqvi, & Rumsey, 2014; Suwankhong & Liamputtong, 2016; van Ee et al., 2017; Zhang, Xiao, & Ren, 2018). Quantitative studies demonstrate that social support provides numerous benefits to patients with cancer and cancer survivors, including increased survivorship and improved quality of life (Bakan, 2017; Leung, Pachana, & McLaughlin, 2014; Pinquart & Duberstein, 2010) and emotional well-being (Applebaum et al., 2014; Eom et al., 2013; Thompson et al., 2017). A meta-analysis of 87 studies showed that perceived social support played an instrumental role in cancer survivorship (Pinquart & Duberstein, 2010). Specifically, perceived social support was significantly associated with a lower risk of mortality (Pinquart & Duberstein, 2010).

Social support has been shown to be positively associated with quality of life among oncology patients. Among 170 Turkish cancer patients, those with higher levels of perceived social support from friends reported superior global quality of life as measured by the Short Form 36 (SF-36) Quality of Life Scale than patients with lower levels of social support from friends (r_s = .17, p = .02) (Bakan, 2017). Among 412 Australian breast cancer patients, perceived social support positively predicted physical and mental dimensions of health-related quality of life 3 years after diagnosis (Leung et al., 2014).

Poor perceived social support has been shown to be associated with symptoms of depression and anxiety. For example, among African American breast cancer patients, lower perceived social support was associated with more severe symptoms of depression (Thompson et al., 2017). Furthermore, among oncology patients in a multi-centre survey in South Korea, those with lower perceived social support reported significantly higher levels of depressive symptoms, lower functionality, and poorer quality of life than those with higher perceived social support (Eom et al., 2013). Regarding received social support, German prostate cancer patients reported less negative affect and higher positive affect up to 7 months following radical prostatectomy, when they had received support from their spouses and when the intensity of supportive interaction had matched patients’ concurrent goals for independence (Knoll et al., 2015).

Social support remains an important aspect following treatment. For example, among Canadian breast cancer survivors (N = 157), a decrease in the quality of perceived social support, as measured by the Social Support Survey, was associated with increases in stress, depression, and negative affect (Fong, Scarapicchia, McDonough, Wrosch, & Sabiston, 2017). Finally, a significant negative correlation was found between perceived social support and anxiety (r = −.34, p < .01) among 168 patients with advanced cancer who reported low optimism (Applebaum et al., 2014).

Research on social support in South Africa is minimal. Indeed, most health-related research on social support in South Africa has been conducted among caregivers of patients living with HIV/AIDS (e.g., Casale, Wild, Cluver, & Kuo, 2014; Kuo, Fitzgerald, Operario, & Casale, 2012; Singh, Chaudoir, Escobar, & Kalichman, 2011). Other locally conducted studies on social support have been conducted among patients with fibromyalgia (Cooper & Gilbert, 2017), type II diabetes (Ramkisson, Pillay, & Sibanda, 2017), and orthopaedic-related injuries (Maselesele & Idemudia, 2013). Even though breast cancer is the most commonly diagnosed type of cancer among women in South Africa, accounting for 21.78% of new diagnoses (South African National Cancer Registry, 2014), we were unable to find published research measuring social support among this population.

The South African research cited above only investigated perceived social support, not received social support. In these studies, perceived social support was conceptualised in terms of sources of support (i.e., persons who provided support) (Cooper & Gilbert, 2017; Kuo et al., 2012; Ramkisson et al., 2017; Singh et al., 2011) and the availability of types of support (i.e., emotional, instrumental, informational, and appraisal support) (Casale et al., 2014). Measures used therefore assessed perceived support using these dimensions. Instruments used to measure perceived social support include (1) the Multidimensional Scale of Perceived Support (MDSPS), which assesses overall perceived support, family support, friends support, and significant other support (Zimet, Dahlem & Farley, 1988) and (2) the Medical Outcomes Study Social support survey (MOS-SSS) (Sherbourne & Stewart, 1991), which assesses types of support. Singh et al. (2011) developed their own measure of social support, conceptualising sources of support (e.g., nurses, family members, and broader community) but did not include any information on reliability and validity of this measure. Current research on social support therefore is either focused on sources of support or types of support and excludes received support. The accurate assessment of social support is essential in explaining variation in emotional well-being, quality of life, and longevity. Assessment of social support introduces the possibility of determining a relationship between support as a psychosocial construct and several medical outcomes in cancer. To do so, the availability of valid and reliable measures of social support among this population is necessary.

The Berlin Social Support Scales

The Berlin Social Support Scales (BSSS; Schulz & Schwarzer, 2003) measure various types and functions relating to social support. The measure was originally developed for use among adult cancer patients and their partners but has also been used among other clinical populations and healthy adults (Schwarzer & Schulz, 2013). The original version of the BSSS was developed in German, but the measure has been translated into several other languages, including English (Schulz & Schwarzer, 2003). The items of the BSSS form six subscales that assess the cognitive and behavioural aspects of support. These subscales assess (1) perceived support (8 items), (2) received support (14 items + 1 stand-alone item on support satisfaction), (3) need for support (4 items), (4) support seeking (5 items), (5) protective buffering (6 items), and (6) provided support (14 items; Schulz & Schwarzer, 2003). The first four subscales are completed by the patient and the last two (protective buffering and provided support) are completed by persons providing support to the patient. In the original validation study, the ‘need for support’ subscale showed a fairly low internal consistency (Cronbach’s alpha = .63; Schulz & Schwarzer, 2003). Moreover, the latent factors ‘need for support’ and ‘support seeking’ were correlated at .91, indicating that they are in fact measuring the same underlying construct. The manifest versions were not correlated as strongly (r = .66), as they still included measurement error which in the case of ‘need for support’ was fairly strong. Based on these issues, Schulz and Schwarzer (2003) recommended revising these scales, should this high overlap continue to emerge in the future. In addition, three items on the received support scale are reverse scored but were not used in the original BSSS validation study due to variance problems (Schulz and Schwarzer, 2003).

The BSSS has been used extensively in a variety of contexts such as patients living with HIV in India, new mothers in Norway, melanoma patients in Canada, couples seeking in-vitro fertilisation treatment in Germany, and pregnant women in Italy (Brondino et al., 2013; Dimillo, Hall, Ezer, Schwarzer, & Körner, 2017; Haga et al., 2012 Luszczynska, Sarkar, & Knoll, 2007).

The various scales of the BSSS have produced good internal consistency among the patient samples where it has been used. For instance, the received support scale that integrated a stand-alone support satisfaction item produced an internal consistency of .78, as measured by Cronbach’s alpha among HIV patients in India (Luszczynska et al., 2007). Three scales, perceived support, received support, and support seeking produced strong internal consistencies of .88, .84, and .81, respectively, among Norwegian mothers who had recently given birth. However, consistent with Schulz and Schwarzer’s (2003) findings, the internal consistency of the need for support scale was lower than that of the other scales (Cronbach’s alpha = .61) among the same sample (Haga et al., 2012). Finally, the Canadian version of BSSS’ received social support subscale produced a strong internal consistency (Cronbach’s alpha = .90) among patients with melanoma (Dimillo et al., 2017).

There is a paucity of published research on psychosocial aspects of breast cancer treatment among patients in South Africa. The studies cited above indicate that social support is beneficial to breast cancer patients. One of the barriers to conducting research on social support within local patients with breast cancer is the availability of validated measures of social support. In this article, we report on the psychometric properties of the perceived and received subscales of the BSSS among a sample of patients receiving care for breast cancer at a public hospital in the Western Cape, South Africa. We draw on the definition of social support provided by Schwarzer and Leppin (1991) that was referred to at the beginning of this article, and categorise the construct into two distinct types of support namely perceived support and received support (e.g., Barrera, 1986). These subscales of the BSSS differ conceptually from other measures of social support used in South Africa, as they differentiate between perceived support and received support. We assessed the factor structure, internal consistency, and construct validity of these subscales. We hypothesised the following based on the studies reviewed: (1) two correlated factors would emerge from and be confirmed by factor analysis procedures, that is, perceived support and received support and (2) scores on the perceived and received subscales of the BSSS would be highly correlated with scores on a perceived functional support scale (Duke Functional Social Support Scale [FSSQ]), moderately correlated with social well-being (Functional Assessment of Cancer Therapy [FACT]; Social Well-being Subscale [SWBS]), and low to moderately correlated with emotional well-being (FACT; Emotional Well-being Subscale [EWBS]).

Method

Participants

The sample consisted of 201 breast cancer patients recruited from a public, tertiary hospital in the Western Cape, South Africa. All participants were female and their ages ranged between 27 and 83 years (M = 55.80; SD = 11.80). Most of the participants reported their race as ‘Coloured’ (71.0%), followed by White (22%), African (6.5%), and Indian (0.5%). Most of the participants indicated that they were married (37.8%) and resided with other adults and children (45.0%). The participants reported low levels of education and income, with only 22.9% of participants having completed Grade 12 and most participants (43.4%) reporting a household income of less than $190 per month.

Most women were diagnosed with stage II cancer (51.7%), followed by stage III (27.5%), stage I (14.6%), and finally stage IV (6.2%). Most participants (76.9%) were in remission and were receiving aromatase inhibitors. Finally, the mean time since first diagnosis was 248.3 weeks (SD = 254.77; range = 7.3–1263.3 weeks).

Instruments

BSSS

The BSSS measures both cognitive and behavioural aspects of social support in a total of six subscales and one stand-alone item on support satisfaction. In the present study, we did not administer the provided support and protective buffering subscales as these were completed by persons providing support to patients with cancer and not by the patient herself, unless used in fully reciprocal dyadic designs with patients and caregivers. We administered four subscales (i.e., received support, perceived support, need for support, and support seeking) and one stand-alone support satisfaction item of the measure to participants (Schulz & Schwarzer, 2003). However, because need for support and support seeking were shown to be highly inter-correlated in the original validation study and conceptually measure support-related cognitions and behaviour at a different stage of the support interaction process (Schulz & Schwarzer, 2003), the focus of the present study was on structural characteristics and correlates of received (11 items) and perceived social support (8 items) only. The stand-alone support satisfaction item as well as three reverse scored items of the received support scale (originally 14 items) were also omitted from the analyses. The reverse scored items had produced variance problems and were thus not included in the original validation analyses (Schulz & Schwarzer, 2003). Also, in preliminary analyses of the present data, they had consistently loaded on a separate factor, suggesting that they do not measure received support in a reverse scored manner, but likely undermining behaviours of patients’ social network members.

Each of the remaining 19 items of the received and perceived support subscales was phrased as a statement and participants responded to each statement using a four-point Likert-type scale. Response options ranged from strongly disagree (1), somewhat disagree (2), somewhat agree (3), to strongly agree (4). Subscale scores can be calculated as sum or mean scores.

As the BSSS had not been used among patients with cancer in South Africa, prior to data collection the South African researchers of this study inspected the items to determine their suitability for use among the patient population and determined that they would be comprehensible to patients. The local researchers are experienced in psychometry, both having developed psychometric measures among samples from contexts similar to this study. They also conducted several research projects at Tygerberg hospital and have a good understanding of the patient population. The measures (including the BSSS) were also approved by the Health Research Ethics Committee at the hospital. Participants did not report any negative feedback regarding items on the BSSS and the scale and subscales demonstrated strong internal consistency reliability (see Results).

FSSQ

The FSSQ measures the strength of the person’s perceived social support network (Broadhead, Gehlbach, De Gruy, & Kaplan, 1988) and consists of eight items. Responses are indicated on a five-point Likert-type scale, with options labelled (1) As much as I would like, (2) Almost as much as I would like, (3) Some, but would like more, (4) Less than I would like, and (5) Much less than I would like. The measure has been used in patients with cancer and cancer survivors in South Korea, producing an internal consistency reliability of .84 (Yang et al., 2013). The single factor structure of the FSSQ has been demonstrated in several studies (Broadhead et al., 1988; Yang et al., 2013). The FSSQ produced a high internal consistency of .92 in the current sample.

FACT-B

The FACT-B is based on the Functional Assessment of Cancer Therapy – General Questionnaire (FACT-G) that was originally developed for use and validated among cancer patients (Perry, Kowalski, & Chang, 2007). The measure was adapted for breast cancer patients by including items related to treatment such as being bothered by hair loss, having swollen or tender arms, and not being able to feel like a woman. The FACT-B consists of 44 items that encompass the domains of physical, emotional, functional, social, and cognitive functioning. We administered all the scales, but in the current article, we refer only to the SWBS and the EWBS. The SWBS contains seven items and produced an internal consistency score of .76 within the current sample. Items in the SWBS ask patients to reflect on their satisfaction with support, closeness to family and friends, family communication, and sex life. The EWBS consists of 6 items and produced an internal consistency score of .79 within the current sample. The items ask patients to rate their lack of well-being, that is, sadness, coping, anxiety, and worry. A low score on the EWBS indicates high emotional well-being, while a high score on the measure indicates poor emotional well-being. We therefore expected a negative relationship between this scale and the BSSS. The FACT-G, a general measure of well-being has demonstrated strong reliability among patients in South Africa (Cronbach’s alpha = .89) and the equivalent Pedi, Tswana, and Zulu versions have also demonstrated strong reliability, producing internal consistency reliabilities of .92, .89, and .82, respectively (Mullin et al., 2000).

Procedure

At the time of the study, there was no accessible electronic database of patient information, but patient folders were made available to us. We recruited a convenience sample of patients and the main inclusion criterion was that participants were proficient in English. Exclusion criteria included being under the age of 18 years and being diagnosed with any other imminent life-threatening conditions.

Data were collected by a team of trained research assistants. Research assistants introduced themselves to patients in the reception area of the clinic and handed each patient a flyer. Patients wishing to learn more about the study were advised to meet with a research assistant in a private consulting room. They were then informed about the study and invited to participate. Those interested in participating were asked to complete an informed consent form and were handed a booklet containing a battery of instruments, including the BSSS, which took participants approximately 45 min to complete. The research assistants were available to answer questions and participants were given a R50 gift voucher as a token of appreciation for participating in the study.

Ethical considerations

The study obtained ethical clearance from the Health Research Ethic Committee at Tygerberg hospital (Reference #N15/08/077) and approval to conduct the study at the hospital was granted by the Western Cape Department of Health. Participants were informed of their rights (i.e., voluntary participation, withdrawal, and confidentiality), and all participants provided written informed consent. The data are only accessible to the investigators, and the hard copies of completed forms are being kept in a locked cupboard in the co-investigator’s office and will be destroyed 5 years after completion of the study.

Data analysis

The data were entered by the research assistants and checked for accuracy. The data were exported into Statistical Package for the Social Sciences (IBM SPSS), version 24. We conducted an exploratory and a confirmatory factor analysis (CFA) of the BSSS and calculated the internal consistency of the subscales. The 19 items measuring received (11 items) and perceived (8 items) social support were analysed using principal axis factoring and direct oblimin rotation. In determining the number of factors to retain, we used the scree plot, the eigenvalues greater than one rule as well as the Veliver’s MAP and parallel analysis (O’Connor, 2000). Items that loaded at a level of .40 were retained (Hair, 2010). Items that cross-loaded or failed to load using this criterion were deleted from the measure before assessing the final factor structure.

In addition, we conducted CFA using AMOS (Version 24). The hypothesised model included two covarying latent factors: received support, with received support items as manifest indicators and perceived support, with perceived support items as manifest indicators. Maximum likelihood estimation was used and the following fit indices were assessed: χ² statistics (ratio of χ² / df < 2), root mean square error of approximation, root mean square error approximation (RMSEA) < .10, comparative fit index (CFI) > .95 (Tabachnick & Fidell, 2014), and Tucker–Lewis Index (TLI) > .90 (Hu & Bentler, 1995). We also conducted Cronbach’s alpha internal consistency analyses on the remaining 17 items to determine the reliability. We explored the criterion and discriminant validity by correlating the BSSS subscales with the DUKE social support scale and the EWBS and SWBS of the FACT-B. The magnitude of the correlations was categorised in terms of an effect-size classification suggested by Cohen (1988; small: up to r = .10; moderate: from r = .30; strong: from r = .50).

Results

Exploratory factor analysis

We conducted the factor analysis on 19 items of the BSSS. The subject-to-variable ratio in this study exceeded the 10:1 recommendation (Anthoine, Moret, Regnault, Sebille, & Hardouin, 2014). We inspected the correlation matrix and found moderate correlations among items, indicating that it was appropriate to conduct factor analysis on these data. Furthermore, the Kaiser-Meyer-Olkin measure was .93, indicating excellent sampling adequacy (Field, 2009). Bartlett’s test of sphericity χ²(171) = 2828.197, p < .01 was significant which indicated large correlations between items. In summary, our data were well-suited to exploratory factor analysis (EFA).

In determining the number of factors to retain, we first assessed the scree plot, which indicated that the measure contains two distinct factors. In addition, inspection of the variance indicated two factors with eigenvalues greater than one. The Velicer’s MAP test achieved a minimum of .02 and demonstrated that there were two factors. This was supported by the parallel analysis.

Table 1 displays the results of the factor analysis from the rotated factor matrix. A factor also required a minimum of three significant item loadings to be considered a stable factor (Costello & Osborne, 2005). The factor analysis identified two items that cross-loaded. These items were removed from further analyses in this study. The results confirmed our interpretation gleaned from the scree plot, the eigenvalues greater than one rule, Velicer’s MAP, and parallel analysis of two distinct factors.

Table 1.

Results from exploratory factor analysis pattern matrix.

	Factor
	1	2	3
(1) There are some people who truly like me.	.126	.407	.222
(2) Whenever I am not feeling well, other people show me that they are fond of me.	.074	.628	.170
(3) Whenever I am sad, there are people who cheer me up.	.126	.699	.067
(4) There is always someone there for me when I need comforting.	.059	.725	.010
(5) I know some people upon whom I can always rely.	.078	.718	.076
(6) When I am worried, there is someone who helps me.	−.063	.904	−.053
(7) There are people who offer me help when I need it.	−.134	.788	−.244
(8) When everything becomes too much for me to handle, others are there to help me.	.079	.737	−.092
(9) The person showed me that he or she loves and accepts me.	.815	−.004	.089
(10) This person comforted me when I was feeling bad.	.740	.015	.043
(11) This person made me feel valued and important.	.909	−.100	.063
(12) This person expressed concern about my condition.	.776	.082	.111
(13) This person assured me that I can rely completely on him or her.	.850	.017	−.030
(14) This person encouraged me not to give up.	.821	.088	.172
(15) This person was there when I needed him or her.	.788	.111	−.082
(16) This person took care of many things for me.	.682	.005	−.493
(17) This person took care of things I could not manage on my own.	.566	.245	−.427
(18) This person helped me find something positive in my situation.	.775	.070	−.175
(19) This person suggested activities that might distract me.	.403	.135	−.164

Factor loadings above .39 indicated in bold.

The first factor consisted of nine original received social support items, and the second factor consisted of eight original perceived social support items. We therefore named the first factor received support and the second one perceived support.

CFA

Informed by results of the EFA reported above, we also conducted CFAs, using a maximum likelihood estimation. The hypothesised model included two latent factors, received support and perceived support, that were allowed to covary. Manifest indicators of received support were nine items, omitting the two items that had cross-loaded in prior EFA (see Table 1). Indicators of perceived support were eight items. Initial model fit was poor with χ² = 261.827 (df = 118, p < .001; χ² / df = 2.219); RMSEA (lower; upper 90% confidence interval [CI]) = 0.078 (0.065, 0.091); CFI = 0.937, TLI = 0.918. Because unaccounted for factors, such as increasing fatigue while answering the questionnaire, may influence item responses in similar ways, we next searched for manifest indicators (i.e., items) with covarying measurement errors. Based on modification indices, a total of three additional covariations between measurement errors of perceived support items (one covariation) and received support items (two covariations) were added to the model. In their standardised form, these ranged between r_ee = .32 and r_ee = .35 (all p < .001). As a result of the added covariances, the model fit improved significantly Δχ²(df) = 59.389 (df = 3), p < .001. Fit indices of this final model now indicated acceptable fit: χ² = 202.438 (df = 115, p < .001; χ² / df = 1.760); RMSEA (lower; upper 90% CI) = .062 (.047; .075); CFI = .962; TLI = .949. Latent factors received support and perceived support were highly correlated (r = .71, p < .001) that measurement models’ standardised regression coefficients were all in excess of .47 (all p < .001). The CFA model is presented in Figure 1.

Figure 1.

Results of the confirmatory factor analysis. Item numbers correspond to numbering in Table 2. For item wording, see Table 2. N = 202. All p < .001. Standardised coefficients are reported. Fit indices of the final model: χ² = 202.438 (df = 115, p < .001; χ² / df = 1.760); RMSEA (lower; upper 90% CI) = .062 (.047; .075); CFI = .962; TLI = .949. Items 16 and 17 were excluded from the analysis due to double loading in prior EFA (see Table 1).

Reliability analysis

The individual scales produced high internal consistency scores of .93 for factor 1 (received support) and .90 for factor 2 (perceived support). These results indicated good reliability in the current sample.

Validity

Table 2 contains the results of the validity analysis based on the factor-analytically determined scales. Both BSSS subscales were correlated at r = .56. The perceived social support subscales of the BSSS (8 items) produced a strong correlation with perceived functional social support (FSSS) (r = .60), a moderate correlation with SWBS (r = .48), and a small but statistically significant negative correlation with EWBS (r = −.25). The last association indicates that higher levels of BSSS perceived support were associated with higher emotional well-being. The received social support subscale of the BSSS (9 items) produced a high correlation with SWBS (r = .54), a moderate correlation with perceived FSSS (r = .41), and a small but statistically significant negative correlation with EWBS (r = −.27). The last result again indicates that higher levels of received support as assessed by the BSSS were associated with higher levels of emotional well-being.

Table 2.

Results from confirmatory factor analyses, final model.

	Latent factor
	Received support	Perceived support
(1) There are some people who truly like me.		.483
(2) Whenever I am not feeling well, other people show me that they are fond of me.		.643
(3) Whenever I am sad, there are people who cheer me up.		.768
(4) There is always someone there for me when I need comforting.		.776
(5) I know some people upon whom I can always rely.		.770
(6) When I am worried, there is someone who helps me.		.846
(7) There are people who offer me help when I need it.		.654
(8) When everything becomes too much for me to handle, others are there to help me.		.732
(9) The person showed me that he or she loves and accepts me.	.754
(10) This person comforted me when I was feeling bad.	.706
(11) This person made me feel valued and important.	.832
(12) This person expressed concern about my condition.	.794
(13) This person assured me that I can rely completely on him or her.	.882
(14) This person encouraged me not to give up.	.840
(15) This person was there when I needed him or her.	.883
(16) This person took care of many things for me.^a	–
(17) This person took care of things I could not manage on my own.^a	–
(18) This person helped me find something positive in my situation.	.828
(19) This person suggested activities that might distract me.	.496
	r
received support <> perceived support	.710
e (7) <> e (8)	.346
e (9) <> e (10)	.338
e (12) <> e (14)	.322

RMSEA: root mean square error approximation; CFI: comparative fit index; TLI: Tucker–Lewis Index; CI: confidence interval; EFA: exploratory factor analysis.

N = 202. All p < .001. Standardised coefficients are reported. Fit indices of the final model: χ² = 202.438 (df = 115, p < .001; χ² / df = 1.760); RMSEA (lower; upper 90% CI) = .062 (.047; .075); CFI = .962; TLI = .949.

Items 16 and 17 were excluded from the analysis due to double loading in prior EFA (see Table 1).

Discussion

Our aim was to examine the psychometric properties of the BSSS perceived and received support subscales in a sample of breast cancer patients (N = 201) in South Africa. We conducted an EFA and CFA to determine the factor structure of the measure in the current sample, calculated the internal consistencies of the final scales, and explored the criterion and discriminant validity of the scales by comparing them with other measures.

The EFA produced two stable factors which we named received support (9 items) and perceived support (8 items), both were confirmed with a subsequent CFA. The scales demonstrated higher internal consistency in the current study, in comparison with the reported reliability of scales in other studies (Dimillo et al., 2017; Haga et al., 2012; Luszczynska et al., 2007).

We correlated the two subscales with measures of perceived FSSS, SWBS and EWBS. As hypothesised, the perceived social support subscale of the BSSS correlated highly with the FSSS, as both measure perceived support. The received subscale of the BSSS showed the strongest correlation with SWBS. While the SWBS measures social well-being in terms of satisfaction related to closeness with friends and family and familial communication, it contains two items relating to satisfaction with support. It is likely that these items play a role in the correlation between these scales. Furthermore, we expected the two subscales to show only small to moderate correlations with EWBS as they measured different constructs and this was indeed the case. However, received support tends to be less consistently related to emotional well-being than perceived support (e.g., Finch et al., 1999), and we therefore expected a somewhat stronger correlation between perceived support and emotional well-being than received support and emotional well-being, which, however, was not the case. Nominally, both associations were of about the same strength. Future research with South African populations might determine the stability of this finding. Nevertheless, the results indicated acceptable validity of the BSSS perceived and received support subscale in this sample of women with breast cancer.

There are some limitations associated with this study. The sample was recruited using convenience sampling which limits the generalisability of findings. In addition, participants were recruited from one breast clinic at a tertiary hospital in the Western Cape and the demographic characteristics are not representative of all patients seeking breast cancer treatment in the Western Cape or South Africa. However, on the basis of these data, we believe that the BSSS may be appropriately used among South African breast cancer patients, as well as medical patients with other conditions.

Conclusion

A 17-item version of the perceived and received subscales of the BSSS demonstrated good reliability and validity in a sample of South African breast cancer patients. The two subscales, received support and perceived support, are quick to administer, easy to interpret, and are a reliable measure of social support among breast cancer patients in South Africa.

Research investigating psychosocial aspects of breast cancer in South Africa is lacking. The literature indicates that social support is beneficial to patients with cancer as it can improve survivorship, and may result in improved quality of life and mental well-being. However, the level of social support among women with breast cancer in South Africa is unknown, as are its correlates. In addition, the received and perceived subscales of the BSSS can be used to test the efficacy of social support interventions among patients with breast cancer. The validation of these subscales in the current context therefore introduces a tool that can be used for research purposes.

Footnotes

Funding

Funding for this project was received from the University of Stellenbosch.

ORCID iDs

Rizwana Roomaney

Ashraf Kagee

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