1. Introduction
External threats such as economic recession constitute adversities for individuals and families [
1,
2]. Particularly, the COVID-19 pandemic has brought physical and psychological hazards to individuals and families [
3], such as family dysfunctions and disorganization [
4,
5]. However, some families can overcome the disruptions that are created by adversities, and they also become stronger and more resilient [
6,
7]. Hence, family scholars have paid special attention to the family processes that protect families from dysfunctions and disorganization under adversity [
8,
9]. For example, in the family adjustment and adaptation response (FAAR) model, which was proposed by Patterson [
10], four family processes (family meaning, cohesion, flexibility, and communication) can help families to cope with family stress and challenges. McCubbin et al. [
11] also proposed the resiliency model of family adjustment and adaptation to describe the processes that are involved in family problem solving in response to stresses that are faced by the family. In the family resilience framework, which was proposed by Froma Walsh [
9], family resilience includes nine qualitatively distinctive domains subsuming under three broader dimensions. These include family beliefs system (making positive meaning about adversity, a positive outlook, and transcendence and spirituality), organizational patterns (flexibility, connectedness, and social and economic resources), and communication processes (clear information about adversity, open emotional expression, and collaborative problem solving). The framework [
9] and the related assessment tool have been widely adopted in family resilience research in the West [
12,
13].
1.1. Research Gaps
Despite the crucial role that family resilience plays in positive psychology and family wellbeing [
14], research on family resilience is still in its infancy [
15]. One of the hurdles is the severe lack of validated measures that can adequately assess family resilience within a culture. Based on Walsh’s conceptualization of family resilience [
14], Rocchi et al. [
12] developed and validated the 26-item Italian Walsh family resilience questionnaire in a clinical sample and their relatives. However, only three domains (i.e., shared beliefs and support, family organization and interaction, and the utilization of social resources) were supported by confirmatory factor analysis (CFA). Sixbey [
13] developed the 54-item family resilience assessment scale (FRAS), which has been widely adopted and translated into different versions [
16,
17,
18,
19,
20]. However, only six dimensions (i.e., family communication and problem solving, social and economic resources, a positive outlook, family connectedness, family spirituality, and making a meaning of adversity) were extracted by exploratory factor analysis (EFA) in a sample of 418 respondents in the US. In Chinese societies, the factor structure of the translated Chinese versions of the FRAS is unclear. For instance, in a sample of 502 Chinese primary caregivers of children with developmental delay in Taiwan, Chiu et al. [
17] confirmed a six-factor structure that resembled the extracted factor structure in Sixbey’s [
13] study. However, Li et al. [
20] identified a three-factor structure (i.e., family communication and problem solving, the utilization of social resources, and the maintenance of a positive outlook) using CFA in a sample of 991 university students in China. Besides, in Li et al.’s [
20] study, only 32 items out of the 54 items were retained in the measurement, with 22 of the items dropped because of low factor loadings (<0.40) or poor representations of the subscales, with three of the subscales dropped eventually. In a sample of 323 Chinese family caregivers in Hong Kong, Chu et al. [
18] identified a five-factor structure (i.e., the ability to make a meaning of adversity, family communication and problem solving, family spirituality, maintaining a positive outlook, and utilizing social and economic resources), with 12 items dropped from the analysis. The inconsistency of the findings on the factor structure across the studies may be due to the employment of different scales, different informants, and/or the utilization of translated measures.
From a cross-cultural perspective, there are challenges regarding the direct borrowing of family measures that are developed in Western societies [
21] because there are different family beliefs and processes in families in different cultures [
22]. While the Western conceptualization of family processes focuses mainly on individualism and independence, the Chinese view emphasizes the importance of collectivism and interdependence [
23].
Another problem in the existing studies is that the sample size is generally small, which suggests that the findings that are based on factor analyses may not be stable. In Chew and Haase’s [
16] study of a sample of young people with epilepsy in Singapore, the sample size was 152. In Chu et al.’s [
18] study, EFA and CFA were analyzed in two samples of 150 and 173 caregivers, respectively. Leone, Dorstyn, and Ward’s [
19] study was based on a sample of 155 caregivers who had a child suffering from neurodevelopmental disorders. Moreover, most of the studies employed caregivers of family members with difficulties (e.g., [
17,
18,
19]), while studies using community samples are few. Obviously, while it is important to examine the psychometric properties of family resilience measures in clinical samples, validation research that is based on community samples is equally as important [
24]. The small sample size also suggests that the basic assumptions of factor analysis are not adequately met.
Besides, another weakness of the existing studies is that researchers commonly use a single source of informants, which is mostly the caregivers [
12,
17,
18]. However, based on family systems theories [
25,
26], fathers, mothers, and children are important members of the family, and they are interdependent. Hence, studies using multiple informants can give a comprehensive picture of the family processes and dynamics within a family.
Finally, most of the existing studies were conducted in a non-pandemic context. As COVID-19 is stressful for families [
27,
28], there is a need to understand family resilience under COVID-19.
1.2. The Current Study
In response to the above-mentioned research gaps, this current study has attempted to develop and validate a family resilience measure of Chinese families under pandemic conditions based on the family resilience framework of Walsh [
9]. There are two phases of this study. The first phase involved the development of the family resilience scale for Chinese families. After developing the initial item pool, we conducted content validation by involving family experts to examine the relevance, the representativeness, and the clarity of the items. In the second phase, we validated the scale based on samples of fathers, mothers, and children aged 10 to 22 years of age in Chinese families in Hong Kong.
2. Materials and Method
2.1. Phase I Study: Development and Content Validation of the C-FRS
Based on Walsh’s family resilience framework [
9], the first two authors developed an item pool containing 51 items to cover all nine dimensions (making positive meaning about adversity, positive outlook, transcendence and spirituality, flexibility, connectedness, social and economic resources, clear information about adversity, open emotional expression, and collaborative problem solving), with each dimension consisting of five to seven items. We paid particular attention to the indigenous Chinese context when developing the items. We then conducted a content validation of the C-FRS by inviting experts in social services to assess the relevance, representativeness, and clarity of items in the item pool.
2.2. Participants and Procedure
Sixteen social workers who provided social work service for children, adolescents, and their families were invited to participate in the content validation study. The participants were recruited from four non-governmental organizations (NGOs) in Hong Kong. Five of them were social work supervisors, three participants were school social workers, three participants worked in family social work service centers, and five participants worked in children and youth service centers. Among the participants, 15 (93.8%) were female. They were experienced social workers who had worked in children, youth, and family services for over 5 years. Nine participants (56.3%) had social work experience of over 20 years, five (31.3%) had social work experience between 11 and 20 years, and two (12.5%) had experience between 5 and 10 years. They were requested to examine the following: (1) relevance (i.e., whether the test items are relevant to the construct or the dimension related to the construct); (2) clarity (i.e., whether the wording and phases of the items are clear and concise), and (3) representativeness of the items to a particular content domain (i.e., how well the items represent the construct) using a structured questionnaire. The participants completed the questionnaire separately in an anonymous manner.
2.3. Measurement
A self-administered questionnaire was used to collect the views of the experts. The participants were informed of the definitions, the related literature, and the domains of family resilience, as well as the assessment instrument. They were requested to fill out the questionnaire based on their judgment. Regarding the “relevance” of the test items for the construct, a 4-point rating scale (1 = irrelevant; 2 = item needs revision or otherwise would no longer be relevant; 3 = relevant but needs minor amendment; and 4 = relevant) was used. If the participants rated “1” or “2”, they were required to write down the justifications. When they rated “2” or “3”, they were asked to suggest improvement for the items. Regarding the “clarity” of the items, a 4-point Likert scale (1 = very unclear, 2 = unclear, 3 = clear, and 4 = very clear) was used. Again, recommendations for modification of wording and phases were requested when an item was perceived as unclearly presented. To evaluate how well the items would represent the domains, a 4-point Likert scale (1 = very inadequate, 2 = inadequate, 3 = adequate, and 4 = very adequate) was used. When the participants suggested that the items are inadequate to represent the domain, they were asked for an explanation about their view.
2.4. Data Analysis
We analyzed the content validity with the following two strategies: (a) computation of content validity index (CVI) on the relevance, clarity, and representativeness, and (b) qualitative recommendations of experts on improving the items. While the CVI of each item was calculated by dividing the number of experts who rated positively (three or four) on the item by the total number of experts, the CVI for the measure was calculated by averaging the CVI across the items within the measure. A CVI of 0.80 was recommended as supporting the content validity for a new measure [
29].
3. Results and Discussion
Regarding relevance of the item to the construct, the CVI
(relevance) of each item ranged from 0.69 to 1.00. The overall CVI
(relevance) was 0.94, with 41 out of the 51 items showing a CVI
(relevance) of over 0.80. Five of the items (Items 3, 8, 19, 21, and 24) showed values of less than 0.80 (
Table 1). Regarding the clarity of the items, the CVI
(clarity) of each item ranged from 0.63 to 1.00, with an overall CVI
(clarity) of 0.90. While 41 out of the 51 items showed a CVI
(clarity) of over 0.80, 10 of the items (Items 3, 17, 19, 21, 24, 36, 37, 38, 39, and 40) were less than 0.80. For all of the domains, the CVI
(representativeness) were over 0.80, ranging from 0.81 to 1.00, with an overall CVI
(representativeness) of 0.93. A summary of the qualitative comments and decisions are listed in
Table 1. As most of the items could be modified, we decided to retain all 51 of the items for validation.
The content validation findings provide support for most of the items in the initial item pool based on the cutoff criteria of 0.80, which was proposed by Davis [
29]. This study is very important because no study has been published on the content validation of family resilience measures. Hence, our effort is pioneering in the field of family resilience.
4. Phase II Study: Validation of the C-FRS
At this phase, we validated and refined the 51-item C-FRS. The father, the mother, and a child aged 10 to 22 years within a family were invited to be the respondents in the validation study. Three psychometric properties of the assessment tool were assessed, including the reliability, the convergent validity, and the factorial validity among the different family members (fathers, mothers, and children). Regarding the reliability, internal consistency was used based on Cronbach’s alpha and inter-item correlation coefficients [
30]. Regarding the validity, convergent validity (with family functioning as the criterion) and factorial validity (EFA and CFA) were examined. While EFA provides exploratory evidence of a conceptual model [
31], CFA serves to confirm the proposed conceptual model [
32]. This two-step analytic approach has been widely used to establish the factorial validity of an instrument [
33,
34,
35]. Regarding the convergent validity, given that family resilience was positively associated family functioning [
36] and communication [
37] in previous studies, it was hypothesized that the mean C-FRS scores would be positively associated with the mean scores of family functioning that were reported by the father, the mother, and the adolescent participants (Hypotheses 1a, 1b, and 1c), respectively.
For the measurement invariance, configural invariance (i.e., invariance of the factor pattern), metric invariance (i.e., invariance of the factor loadings), scalar invariance (i.e., invariance of the intercepts), invariance of factor variance, and factor covariance of the measurement across the father’s sample, the mother’s sample, and the children’s sample were performed.
4.1. Participants and Procedure
We recruited 1020 Chinese families (N = 2858) in Hong Kong with the help of NGOs and tertiary institutions. The NGOs provided the family social work service, the children and youth services, and the school social work service in Hong Kong. They helped us to identify the service users from their membership lists and invited family members to participate in this study. The two inclusion criteria were as follows: (a) families with Chinese ethnicity, and (b) those with a child or an adolescent aged between 10 and 22 years. If the participating family had more than one eligible child, the elder child was invited to participate because they could comprehend the questionnaire better. A supermarket coupon (with a value of HKD 250, which was roughly equal to USD 32) was given to each participating family as a compensation of their time and transportation expenses.
The mean ages of the fathers, the mothers, and the adolescents in the sample were 51.2 (SD = 8.3), 46.6 (SD = 7.0), and 16.4 (SD = 4.7), respectively. There were 462 (45.3%) male adolescents and 556 (54.5%) female adolescents (2 of the participants did not disclose their gender). Regarding the participants’ family status, 818 (80.2%) were intact families, 29 (2.8%) were single-father families, and 173 (17.0%) were single-mother families. The majority of the families (n = 504; 49.4%) earned a monthly household income of between HKD 10,001 (USD 1282.2) and HKD 30,000 (USD 3846.2), and 375 (36.8%) of the families had monthly household income of over HKD 30,000 (USD 3846.2). There were 125 (12.3%) families receiving financial assistance (i.e., Comprehensive Social Security Assistance) from the Government.
Trained social workers or researchers introduced the research to all of the family members. Written informed consent of all of the family members was obtained. The participants were invited to respond to a questionnaire including measures of family resilience, family functioning, and demographic characteristics. The data collection was performed either in social service units or in the participants’ homes, depending on the participants’ preference. The family members filled out the questionnaire in a self-administered format separately, in order to safeguard confidentiality. The participants put the completed questionnaire into a sealed envelope and returned it to the social workers/researchers. This study followed the ethical standards of the Human Subjects Ethics Sub-committee of an internationally recognized University and the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
4.2. Measures
The Chinese family resilience scale (C-FRS). Based on the initial findings, we used the newly developed 51-item C-FRS with nine subdomains (i.e., meaning making, a positive outlook, transcendence and spirituality, flexibility, connectedness, social and economic resources, clear information about adversity, open emotional expression, and collaborative problem solving). The respondents rated each item on a six-point Likert scale ranging from one = “totally disagree” to six = “totally agree”. Higher mean scores indicate higher levels of family resilience. The C-FRS showed excellent internal consistency in this study (Cronbach’s alphas of fathers: 0.98, mothers: 0.98, and children: 0.98).
The Chinese family assessment instrument (C-FAI). The C-FAI that was adopted in the present study was a nine-item instrument [
38] that was selected from the original 33-item version, which was developed by Shek [
39]. It contains three stable reliable dimensions in the construct of family functioning, namely communication, mutuality, and harmony. A sample item reads “Family members support each other”. The respondents were asked whether their family resembled the situation that was described by the item and rated their responses on a five-point Likert scale ranging from “very dissimilar” to “very similar.” A higher mean score indicates a higher level of family functioning. The C-FAI that was reported by the fathers, the mothers, and their children showed good internal consistencies (Cronbach’s alphas of fathers: 0.89, mothers: 0.90, and children: 0.90).
4.3. Data Analyses
We first split the data randomly into two halves (Subsets A and B). While Subset A was used for testing EFA, Subset B was used for testing CFA [
34]. We first conducted EFA in order to explore the factor structures of the C-FRS using IBM SPSS 26 software (IBM, Armonk, NY, USA). Principal axis factoring (PAF) extraction with a direct oblimin rotation (δ = 0) was used to determine the factor structure [
40,
41] of the C-FRS. The following two well-known criteria for determining the number of components were considered: Kaiser’s [
42] criterion to retain eigenvalues that are greater than 1 (K1) and Cattell’s [
43] scree test. In order to confirm the proposed factor structure, CFA based on structural equation modeling (SEM) was further performed using AMOS 26. We adopted the following goodness-of-fit indictors to evaluate the adequacy of models: the comparative fit index (CFI) and the Tucker–Lewis index (TLI) of greater than 0.90 for an adequate model; root mean square error of approximation (RMSEA) of smaller than 0.06 for a good fit model, and between 0.06 and 0.08 for an acceptable model fit [
44]. After testing the factor structure of the C-FRS, we examined the higher-order factor structure of the tested model by CFA. As recommended by Hu and Bentler [
44], when a higher order model fits the data, the higher order model is preferred as the final model, as it contains a parsimonious factor structure for the construct.
In order to examine the factorial invariance of the C-FRS across the family members (fathers, mothers, and children), we performed multiple group factor analyses in this study by adopting a mean and covariance structures analysis (MACS) approach [
45,
46]. First, we assessed the configural invariance (i.e., free from any constraints; Model 0). The first-order factor loading invariance was then evaluated (i.e., the equality constraints were imposed on first-order factor loadings; M1). We compared Model 0 and Model 1 using the indicators of model invariance that were suggested by Cheung and Rensvold [
47], i.e., the non-significant chi-square difference and change in CFI is less than 0.01. Next, we assessed the second-order factor loading invariance (i.e., the equality constraints on the first- and second-order factor loadings were imposed; Model 2). Again, we compared Model 2 and Model 1 using indicators that were suggested by Cheung and Rensvold [
47]. Then, we tested the different nested models subsequently, including the invariance of the intercepts of the measured variables (i.e., constraining the first- and second-order factor loadings and the intercepts of the measured variables to be equal across the groups; Model 3), the invariance of the intercepts of the first-order latent factors (i.e., constraining the first- and second-order factor loadings, and the intercepts of the measured variables and first-order factors to be equal across the groups; Model 4), the invariance of disturbances of the first-order factors (i.e., constraining the first- and second-order factor loadings, intercepts, and disturbances of the first-order factors to be equal across the groups; Model 5), and the invariance of the residual variance of the observed variables (i.e., constraining the first- and second-order factor loadings, intercepts, disturbances of the first-order factors, and the residual variances of the measured variables to be equal across the groups; Model 6) [
46]. Again, the indicators that were suggested by Cheung and Rensvold [
47] were used for the model comparison.
6. Discussion
This study examined the psychometric properties (the convergent validity, the factorial validity, and the internal consistency) of the Chinese family resilience scale (C-FRS). There are four unique attributes of this study. Primarily, this is a study in a non-Western context, with a particular focus on Chinese people. Although family researchers have paid increasing attention to family resilience in the Chinese context (e.g., [
18,
20]), researchers have commonly used translated family resilience measures that were developed in Western societies [
13]. In our study, although we used Walsh’s [
9] conceptualization of family resilience as the theoretical framework, the items were indigenously developed, which fitted the Chinese culture, where familism and collectivism are emphasized [
55]. For instance, rather than focusing on self-differentiation and individualism, which are based on an individualistic orientation (e.g., a sample item of Sixley’s FRAS reads “We can deal with family differences in accepting a loss”), the C-FRS focuses on family solidity and interdependence among family members (e.g., a sample item of the C-FRS reads “Family members are united”). Furthermore, we invited experts in the social work field to rate the items in terms of their relevance, their representativeness, and their clarity (i.e., content validity), and give comments on how the items could be improved. The findings showed that the C-FRS is culturally fit for assessing the family resilience in Chinese communities.
Second, this study provides support for Walsh’s model consisting of three domains and nine dimensions. Our findings have shown that the 35-item C-FRS showed a hierarchical factor structure with nine first-order factors subsumed under three second-order factors, namely the following: family beliefs system (meaning making, a positive outlook, and transcendence and spirituality), family organizational patterns (flexibility, connectedness, and social and economic resources), and family communication (clarity, open emotional expression, and collaborative problem solving); thus supporting the theoretical structure that is proposed by Walsh’s family resilience framework [
9]. In contrast to the observation that results that are based on family resilience scales are not consistent with Walsh’s [
9] conceptualization of family resilience in local and global contexts [
24], the C-FRS fits Walsh’s family resilience framework well. The scale and its subscales are valid and reliable in assessing family resilience and its corresponding components in the present study. The previous Chinese studies did not provide support for Walsh’s model, which was likely because of two reasons. First, they did not employ large samples. Second, the translated measures may not be able to capture the characteristics of Chinese families.
Moreover, the hierarchical factor model offers a parsimonious structure on how first-order factors are interrelated into meaningful patterns [
33]. Besides, hierarchical factor analysis removes random measurement error of the first-order factors and suggests that the variance of the second-order factors can be explained by the first-order factors [
56]. Measurement invariance tests to assess the invariance of the C-FRS across different members in a family is also a methodological advance in this study, which encourages more family-based research to be conducted using multiple data sources.
Third, we used multiple informants to provide support for the invariance of the factor structure across fathers, mothers, and adolescent children. Instead of just focusing on an individual perspective, we endorsed a family systems perspective [
25,
26] and recruited the father, the mother, and a child/adolescent within a family to fill out the questionnaire. This is critically important for a family assessment tool because each family member contributes to the family processes and wellbeing. A measurement that can adequately assess the characteristics and the patterns of family processes and strengths among family members is important in order to capture the different perspectives from the different family members. Unfortunately, previous research studies employed only a single source of informant [
17,
18], which restricts the development of family resilience research adopting a family-based perspective and involving different family members.
In this study, the measurement invariance tests showed that the scale was invariant among the fathers, the mothers, and the children/adolescents, suggesting that each family member shares similar interpretations about the characteristics and the patterns of family resilience. Moreover, as the participants were mainly recruited from the community and the sample size was considered to be large in a validation study, the 35-item C-FRS can be widely used to assess the family resilience of Chinese families in facing global external threats (e.g., the COVID-19 pandemic, economic downturn, etc.). The scale and its subscales can help us to identify the strengths and the wellbeing of the families in facing crises and adversities, which is important for formulating social policies and designing appropriate social services that can buffer the negative impacts during the post-crisis stage.
Despite its pioneering nature, there are several limitations of this study. First, the findings of the EFA did not provide support for Walsh’s model. This is reasonable because EFA commonly assumes that measurement errors are uncorrelated with each other [
57]. Secondly, although the literature points out that residual invariance is less relevant in testing the factorial invariance of a measurement tool between groups (e.g., [
54]), further studies on the difference in residuals of measured factors of the C-FRS is suggested. Third, as we collected the data during the COVID-19 pandemic, the responses may have been influenced by different forms of adversities and hardship that different family members might have encountered, such as infections, loss of beloved ones, social isolation, and financial insecurity [
58,
59]. Nevertheless, the factorial invariance findings are robust across the different informants within the family. Fourth, we collected data from families with children and adolescents who were aged between 10 and 22 years, which covered a large age range of children and adolescents. As younger children may have difficulties in understanding the complex concepts of family resilience, we should explore this issue in future studies. Finally, our study was conducted using a Hong Kong Chinese family sample. It is recommended to replicate the current research in other Chinese communities (e.g., American Chinese, Mainland China, etc.,) and some Asian countries sharing similar cultural features (e.g., Japan and Singapore) [
33].
7. Conclusions
Despite the limitations, the present study underscores the need to develop an indigenous family resilience scale based on the Chinese cultural characteristics, emphasizing familism, collectivism, and interdependence [
23]. Besides, the content validation was performed by recruiting family social workers in order to assess the relevance, the representativeness, and the clarity of the items corresponding to the components of family resilience. Furthermore, this study used a large sample of multiple family members to assess the reliability, the concurrent validity, and the dimensionality of the measure. The findings suggest that the 35-item C-FRS is a valid and reliable measurement that objectively measures family resilience in Chinese communities. The C-FRS supports Walsh’s [
9] theoretical conceptualization of family resilience by indicating a hierarchical factor structure of nine first-order factors, which are subsumed under three second-order factors, namely the following: family beliefs system (meaning making, a positive outlook, and transcendence and spirituality), family organizational patterns (flexibility, connectedness, and social and economic resources), and family communication (clarity, open emotional expression, and collaborative problem solving). Moreover, the C-FRS showed good internal consistency, convergent validity, and factorial invariance across the family members. Thus, the scale showed good psychometric properties in assessing family resilience among fathers, mothers, and child/adolescents in Chinese families. In view of a strong demand for, but a dearth of validated instruments that objectively measure the family resilience among different family members in Chinese contexts, our study takes a pioneering step by developing and validating the C-FRS that can be objectively used to assess family resilience in Chinese communities.