Skip to main content
NCBI home page
Journal of Community Genetics logoLink to Journal of Community Genetics
. 2023 Aug 31;14(6):593–603. doi: 10.1007/s12687-023-00665-9

Developing and assessing a kin keeping scale with application to identifying central influencers in African American family networks

Caitlin G Allen 1,2,✉, Colleen M McBride 2, Cam Escoffery 2, Yue Guan 2, Clarissa Hood 2, Jingsong Zaho 2, Gene Brody 2, Weihua An 2
PMCID: PMC10725405  PMID: 37648941

Abstract

Promoting family communication about inherited disease risk is an arena in which family systems theory is highly relevant. One family systems’ construct that can support promotion of family communication regarding inherited disease risk is the notion of “kin keeping.” However, kin keeping and whether it might be capitalized on to encourage family communication about inherited risk has been understudied. The goal of this report was to propose a broadened conceptualization of kin keeping that distinguishes between a structural functional perspective (role conceptualization) and transitional behaviors (skill conceptualization), and to develop and evaluate a scale that would enable this assertion to be tested among a sample of African American community health workers. We developed a scale using four steps: item development using concept analysis and content validity, scale development among a national sample (n = 312), scale evaluation using exploratory factor analysis (n = 52), and scale reduction. We then posed suppositions of associations that would indicate whether the developed kin keeping measure was assessing a specific family role or set of behaviors. Our results included the development of the first quantitative measure of kin keeping (9- and 15-item scales). Model fit for 9-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.09, SMRM = 0.06) and model fit for 15-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.06, SMRM = 0.05). These findings allow us to move toward more rigorous research about the role of kin keeping on information sharing and health decision making. Results also suggest that, contrary to the historical structural functional conceptualization of kin keeping as a role, kin keeping might also be conceptualized as a behavior or set of modifiable behaviors. Ultimately, the kin keeping scale could be used to operationalize kin keeping in various theoretical models and frameworks, guide intervention development to encourage or train for kin keeping behaviors, and test assumptions of whether families vary in the density of kin keeping.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12687-023-00665-9.

Keywords: Psychometrics, Genetic research, Community engagement

Introduction

Discoveries of genes associated with increased risk for common diseases (e.g., BRCA1/2 for breast cancer) in the mid-1990s offered hope to families with identified mutation carriers. These discoveries heightened awareness that some relatively common cancers had a strong inheritable component and affected multiple members within families. In turn, for affected families, this awareness guided recommendations for customized screening (e.g., those at greatest risk receive more frequent intervals of screening), and treatments (e.g., prophylactics and tumor-targeted treatments), bringing life-saving benefits (EGAPP 2009; Buchanan et al. 2020; Centers for Disease Control and Prevention 2014; Dotson et al. 2014).

For breast and ovarian cancer, diagnosis at an early age and strong family history became the signal for referring patients to genetic counseling and testing. A family member identified through genetic testing to be a mutation carrier (i.e., probands) was expected to communicate their risk status to at-risk relatives. Indeed, fostering family communication about risk has become among the most important avenues for achieving the full potential of genomic discovery. Yet almost 30 years have passed since these first discoveries and “appropriate” family-wide risk communication (i.e., conveying mutation status and its implications to family members and intergenerationally) remains a critical gap (Gaff et al. 2007; Wiseman et al. 2010; Chivers Seymour et al. 2010; Nycum et al. 2009; Srinivasan et al. 2020).

Arguably, promoting family and intergenerational communication about inherited risk is an arena in which social systems theory is highly relevant. In this view, families are cohesive systems of interrelated and interdependent parts that adaptively work together for cohesive functioning (Nguyen et al. 2022; Koehly et al. 2010; Lewis et al. 2006). Additionally, intergenerational nature of families, so important in the context of inherited health conditions, brings more layers of complexity in assumed interconnected roles, and shared beliefs and values (Hammarstrom 2005). With respect to inherited risk communication, the thinking is that individuals’ roles and interactions as a family and intergenerationally could be capitalized upon to achieve appropriate genetic risk communication (Peterson 2005; Koerner and Schrodt 2014; Braithwaite et al. 2010). System theories have been applied to a limited extent in a variety of health promotion interventions primarily targeted to dyads including HIV-discordant couples (Lewis and Rook 1999), partners’ smoking cessation (McBride et al. 2004), lung cancer patients’ family members who smoke (Bastian et al. 2013), and mother-daughter pairs for prevention of sexually transmitted disease (Donenberg et al. 2020). However, little research has applied this thinking to family communication regarding risk assessment such as family history (Ake et al. 2021) or for those identified as mutation carriers (Peters et al. 2011).

One systems’ construct that has obvious relevance for promoting family communication regarding inherited disease risk is the notion of “kin keeping.” Rosenthal first introduced the term kin keeping as a “designated family role within the family division of labor.” (Rosenthal 1985) Sociologists and family researchers have conducted numerous qualitative studies finding consistently that the kin keeper role tends to be occupied by one family member, most often a woman who takes on specific responsibilities and activities that enable extended families to stay in communication (Wellman and Wortley 1989).

Kin keeping may have particular relevance for family communication about inherited risk as studies consistently show that risk information is less likely to be disseminated beyond the nuclear family unit, and family health history of specific health conditions particularly intergenerationally often is unknown (Koehly et al. 2010, 2008, 2003; Thompson et al. 2013, 2015). However, the study of kin keeping specifically and whether it might be capitalized on to promote family communication about inherited risk has not progressed.

One important reason for this lack of progress is that kin keeping has yet to be fully conceptualized and empirically measured. In this report, we first propose a broadened conceptualization of kin keeping in which it may not be viewed exclusively as a structural role but could be a set of transactional behaviors that intergenerational families perform to varying degrees. Second, we will develop and evaluate a scale that would enable this assertion to be tested.

Broadening the conceptualization of kin keeping

Structural functional perspective

To date, kin keeping has been conceptualized from a structural functional perspective holding that intergenerational families (henceforth, “family”) comprise an integrated system of relationships, shared values, and traditional roles that together function to maintain a stable and cohesive family structure (Hammarstrom 2005; Kingsbury and Scanzoni 2016). From this viewpoint, the kin keeper role requires a person to take responsibility for a variety of family tending behaviors such as hosting gatherings, keeping track of birthdays, sharing family news, and assisting family members with health and personal business affairs (Brown and DeRycke 2010). The role of kin keeper is designated by the family and is occupied at a point in time by an individual. Thus, the role can be handed off to another family member should a kin keeper not be able to fulfill the responsibilities (e.g., age, illness, or death).

Maintaining health information is a common expectation of the kin keeping role and, as such, could serve to facilitate family-wide awareness of inherited risk. For example, Peters and colleagues took a structural functional approach to understand communication among families affected by a BRCA1/2 mutation. Sociograms were constructed to identify communication roles that family members played based on the perspective of the proband (Koehly et al. 2009; Peters et al. 2006, 2012). The authors characterized several different roles that family members played (e.g., information gatherers, disseminators and blockers) that affected the flow of information about inherited risk in the family. Communication interventions informed by this theoretical approach would require identifying the person in the family who is designated the role of information facilitator and once identified, these individuals would be targeted for genetic risk communication intervention activities.

Behavioral perspective

Less considered in the current literature is that kin keeping could be conceptualized as a shared responsibility to engage in emotional and instrumental support behaviors. In this view, kin keeping is performed to a greater or lesser degree by any number of family members whose shared value of such behaviors creates a collective conscience that emphasizes family solidarity (Hammarstrom 2005). It is well documented that family members provide a variety of interpersonal supports to each other that benefit health outcomes (Feeney and Collins 2015). These supports can take the form of interpersonal exchanges of empathy and trust (i.e., emotional), tangible aid and services (i.e., instrumental), advice and information to address problems (i.e., informational), and constructive feedback and affirmation (i.e., appraisal) (House et al. 1988). In the context of hereditary risk, den Heijier (2011) explored the association of perceived support exchanges and propensity for families to have open communication about BRCA1/2 risk finding that general social support was positively associated with communication among nuclear and extended family members.

Conceptualization of family support has relied almost entirely on well-validated multidimensional measures of general social support (e.g., Multidimensional Scale of Perceived Social Support) (Zimet et al. 1990). Interpersonal support behaviors largely have been assessed in the context of dyadic relationships (Sarason and Sarason 2009). Though some social support behaviors such as information sharing, providing feedback and affirmation align closely with how kin keeping has been conceptualized, these measures do not capture behaviors that are purposely aimed to keep an extended family unit intact and connected to each other. The latter behaviors include organizing family gatherings and keeping family members informed of important developments among network members not simply dyadic.

Genetic risk communication interventions based on this behavioral perspective would have the goal to activate families as a system (Baroutsou et al. 2021; Zhao et al. 2022). In this view, multiple or all family members might be encouraged to engage in behaviors that keep the family connected. This approach could foster broadened and shared responsibility for communication of inherited risk that in turn might be needed to foster appropriate inherited risk communication.

Current kin keeping assessment

Current assessments of kin keeping have been based on both qualitative and quantitative approaches. For example, some assess kin keeping using intensive qualitative methods. One approach is through observation of family interactions for bounded periods with the researcher recording these observations (Lareau and Rao 2020). While such methods provide important insights about family kin keeping, they are not appropriate for population-level research to test whether kin keeping is a role, a set of support behaviors or both.

Others have applied quantitative efforts in which researchers provide participants with a definition of kin keeping and then ask subjects to self-identify or be nominated by other family members as kin keepers (Williams 2008; Williams et al. 2009a, b). Using this approach, characterizing the frequency kin keeping behaviors performed by multiple family members would not be possible.

A valid survey assessment of behaviors associated with “kin keeping” could enable the identification of individuals who play kin keeping roles and characterize the frequency in which multiple family members perform kin keeping behaviors. In the sections to follow, we describe the sample for exploring kin keeping behaviors and our exploration of the potential for kin keeping to advance the public health translation of genomic discovery that has been called for nationally.

Community health workers: an optimal sample for testing the concept of kin keeping

Community health workers (CHWs) are an optimal sample to engage in posing the question of whether kin keeping might be conceptualized as a role or a behavioral skill set. CHWs are lay members of the community who work either for pay or as volunteers in association with local health care systems. As community members, CHWs commonly share the ethnicity and life experiences of the community they serve (Brownstein et al. 2011). CHWs are individuals who provide interpretation and translation services, culturally appropriate health education and information, assistance to people to get needed care, informal counseling and guidance on health behaviors, advocacy for individual and community health needs, and some direct services such as first aid and blood pressure screening. These align well with behaviors that have been identified as kin keeping. Thus, CHWs are well-acquainted with the notion of behaviors aimed to foster collective action. However, CHWs may not play this role in their families of origin. Further, CHWs are commonly employed to address disparities in health service access as part of health department or health system outreach. Thus, testing kin keeping as a concept to be capitalized on to expand the reach of genomic translation with CHWs has potential to inform future interventions. We focused on African American CHWS because our research team had ongoing funding to work with experienced CHWs in local communities to disseminate a family history of cancer risk assessment tool.

Family history tools offer a context for kin keeping scale development

Family health history (FHH) assessments are a well-established approach used to characterize genetic, environmental, and behavioral risk factors shared among family members. FHH can identify those who may carry genetic mutations that greatly increase risk for inherited cancer syndromes (Pyeritz 2012; Guttmacher et al. 2004; Rose et al. 2004; Lucassen et al. 2001; DeLancey et al. 2008; Centers for Disease Control Prevention 2015). Traditionally, FHH information has been collected by health professionals as part of medical visits. However, a variety of barriers (e.g., patient’s incomplete knowledge of their health histories, and provider time limits) are commonly cited as reason for not collecting FHH information during office visits (Valdez et al. 2010; Yoon et al. 2002; Qureshi and Kai 2008; Claassen et al. 2010; McBride et al. 2005; deHeer et al. 2017; Koehly et al. 2018; Ochs-Balcom et al. 2015; Ouakrim et al. 2014; Veldwijk et al. 2016). Noting these barriers, a wide array of tools and initiatives have been developed and promoted nationally. These FHH tools provide a framework for families to have conversations about shared risk outside of clinical settings and when facilitated by kin keepers or kin keeping behaviors could broaden dissemination of high-risk screening to the public (Smith et al. 2018; United States Preventive Task Force 2013, 2018, 2016).

Study 1: development and validation of the kin keeping scale

Methods for development and validation of the kin keeping scale

In the following section, we describe the multi-step process we used to develop a kin keeping scale. First, our methodological approach to scale development involved four steps: item development using concept analysis and content validity, scale development among a national sample, scale evaluation using exploratory factor analysis, and scale reduction.

Step 1: item development using concept analysis and content validity approaches

First, we identified concepts and completed a concept analysis based on an informal review of existing kin keeping literature. Key sources included literature from sociology, nursing, and public health that have previously defined kin keeping and related behaviors (Rosenthal 1985; Brown and DeRycke 2010; Braithwaite et al. 2017; Leach and Braithwaite 1996). Six dimension of kin keeping (caregiving, compassion, celebrations, communication, connectedness, coordination) were identified and discussed with four experts in sociological methods, kin keeping, and family communication via phone and email. We then incorporated the feedback and finalized the definitions (Saylor 2013).

We completed two rounds of content validity checks in collaboration with three experts using the content validity index score (Polit and Beck 2006). Three measures of content validity were assessed: content validity of an individual item (I-CVI), content validity of the overall scale (S-CVI), and mean expert proportion relevant. This process involved having the experts review the questions and then rate each question on a Likert scale (1 = not relevant, 2 = somewhat relevant, 3 = quite relevant, 4 = highly relevant). The scores were based on level of agreement that the question captured an aspect of kin keeping. Scores and notes were reviewed to assess whether there were inconsistencies in how individuals understood certain questions or where they were confused. We conducted two rounds of expert review to achieve appropriate content validity index scores among experts.

We next completed cognitive assessment with eight African American community members. These individuals served as “judges” to evaluate face validity of the scale items, an important component of content validity. These end users were engaged in cognitive interviews to assess whether they regarded the construct to be a good measure of kin keeping. The cognitive interviews involved a verbal probe technique (a cognitive interviewing technique where the interviewer asks a series of probing questions designed to elicit expanded thinking and think-aloud process; the participant is asked to freely describe what comes to mind as they complete a task) (Beatty and Willis 2007). In this step, individuals were asked to verbalize their responses as they attempted to answer the item on the scale. After completing this step, item wording was updated to incorporate the feedback, resulting in the initial set of 35 items.

Step 2: scale development among a national sample

During this step, we engaged a Survey Monkey Audience to collect data from a panel of nationally representative (age and geography) African American adults around the USA. We calculated raw and standardized measures for each dimension and the total scale using Cronbach’s alpha to assess reliability for each dimension and the total scale.

Step 3: scale evaluation using exploratory factor analysis

We next used an iterative approach to conduct exploratory factor analysis and item reduction. This approach is common since this is completely new scale development (Dilorio 2005). All scale evaluation analyses were completed in SAS v 9.4 with all possible cases used in analyses (< 5% missingness). To begin, we used a variance-covariance matrix with ML estimation, orthogonal rotation, and specified six factors based on a table of specification since we had a good understanding of the six dimensions likely to be present in the kin keeping scale (Watkins 2018; Costello and Osborne 2019; Browne 2001). Eigenvalues greater than 1 were retained and factor patterns assessed (Dilorio 2005). After assessing the first EFA, we then ran a model with five factors/dimensions. Correlations were assessed in this model.

Step 4: scale reduction

After identifying a 15-item scale, we conducted scale reduction procedures to identify the most parsimonious number of items required to maintain reliability and goodness of fit parameters. A shortened scale could reduce respondent burden and enable increase family research feasibility. We examined various models and removed items based on both statistical and theoretical features. Model fit was assessed using a variety of indicators that included the comparative fit index (CFI) (good fit > 0.95), adjusted goodness of fit index (AFGI) (good fit > 0.95), root mean square error of approximation (RMSEA) (good fit < 0.06), and standardized root-mean-square residual (SRMR) (good fit < 0.08) (Kline 2015).

Results for development and validation of the kin keeping scale

Step 1: item development using concept analysis and content validity approaches

We found low ratings in the initial round of content validity assessment, but achieved an appropriate rating for each of these areas after the second round: content validity of individual items = 0.85, content validity of overall scale = 0.69, and mean expert proportion relevant = 0.85 (Table 1) (Polit and Beck 2006; Beatty and Willis 2007). A 35-item scale with 6 domains (factors) was developed at the conclusion of the item development step (Supplemental Materials, Table 3).

Table 1.

Expert content validity

Measure of content validity Round 1 Round 2
Content validity of individual items (I-CVI) 0.67 0.85
Content validity of overall scale (S-CVI) 0.41 0.69
Mean expert proportion relevant 0.65 0.85
Open in a new tab

Content Validity of Individual Items (S-CVI): proportion of content experts giving items a relevance rating of 3 or 4; Content Validity of Overall Scale (S-CVI): content validity of overall scale; Mean Expert Proportion Relevant: promotion of items on a scale that achieves a relevance rating of 3 or 4 by all experts

Step 2: scale development among a national sample

A total of 312 individuals responded to the survey (54.1% female, 33.6% age 45–60, 37.9% married, 31.1% graduating from college, and 48.9% household income of less than $49,999 per year). In this initial testing, both the raw and standardized Cronbach’s alpha scores for the total dimensions performed well for the full sample and each individual dimension of kin keeping (Table 2).

Table 2.

Cronbach’s alpha scores for 35-item scale

Dimension Questions Raw Standardized
Caregiving 1–5 0.69 0.69
Compassion 6–10 0.86 0.89
Celebrations 11–17 0.82 0.83
Communication 18–22 0.89 0.89
Connectedness 23–29 0.75 0.76
Coordination 30–35 0.86 0.87
Total 0.95 0.95
Open in a new tab

In the first iteration, and consistent with the initial 35-item scale, we specified six factors and all 35 items were included. The EFA results accounted for 95.0% of the total variance in kin keeping. The results suggested the removal of eight items (1, 2, 3, 14, 15, 16, 17, and 25) due to poor loading (< 0.04) and/or inconsistent loading across multiple factors. The EFA results showed that no items met the factor loading criteria for the sixth factor (i.e., no loadings > 0.40). Thus, we dropped these items and completed EFA with the remaining 27 items. This EFA accounted for 100% of the variance in kin keeping. Based on these results, one additional item was removed (item 4) due to statistical and conceptual criteria. The final EFA included 15 items with five factors with three items loading onto each factor. Table 3 includes the factor means, item means, initial eigenvalues, and rotated factor loadings for the 15-item scale. Model fit indices were as follows: CFI = 0.97, AFGI = 0.89, RMSEA = 0.06, SMRM = 0.05.

Table 3.

15-item kin keeper scale statistics

Dimension and item Mean SD α Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
Caregiving 3.62 0.92 0.81
KK5 3.42 1.15 0.69
KK6 3.89 1.01 0.53 0.42
KK7 3.54 1.09 0.57 0.30
Compassion 3.97 0.99 0.88
KK8 3.97 1.07 0.74
KK9 4.01 1.18 0.79
KK10 3.93 1.05 0.68
Celebration 3.04 1.13 0.85
KK11 3.53 1.20 0.55 0.33 0.32
KK12 3.09 1.31 0.78
KK13 2.52 1.35 0.79
Communication 3.86 0.98 0.91
KK18 3.97 1.05 0.69
KK19 3.91 1.09 0.79
KK20 3.69 1.09 0.66 0.35
Connectedness 3.12 1.03 0.86
KK21 3.08 1.20 0.69
KK22 3.10 1.14 0.71
KK23 3.18 1.15 0.64
Kin keeping scale total 3.35 0.75 0.93
Open in a new tab

N = 312. SD standard deviation, α Cronbach’s alpha; bold font for EFA factor loading indicates the scale on which item loaded. Factor loading for values less than 0.3 are not reported in the table

To reduce the scale, we found that a 9-item scale with three factors accounted for 100% of the variance in kin keeping. The dimensions of caregiving and connection were removed. This scale provided high overall strong reliability (alpha = 0.91, and for each of the dimensions ranging from 0.88 to 0.91). Table 4 includes factor means, item means, initial eigenvalues, and rotated factor loadings for the 9-item scale. It also had good model fit (CFI = 0.97, AFGI = 0.89, RMSEA = 0.09, SMRM = 0.06).

Table 4.

9-item kin keeper scale statistics

Dimension and item Mean SD α Factor 1 Factor 2 Factor 3
Compassion 3.97 0.99 0.88
KK8 3.97 1.07 0.79
KK9 4.01 1.18 0.82
KK10 3.93 1.05 0.69
Celebration 3.04 1.13 0.85
KK11 3.53 1.20 0.31 0.38 0.59
KK12 3.09 1.31 0.94
KK13 2.52 1.35 0.72
Communication 3.86 0.99 0.91
KK18 3.97 1.05 0.31 0.75
KK19 3.91 1.09 0.88
KK20 3.69 1.09 0.33 0.74
Kin keeping total 3.36 0.75 0.91
Open in a new tab

N = 312. SD standard deviation, α Cronbach’s alpha; bold font for EFA factor loading indicates the scale on which item loaded. Factor loading for values less than 0.3 are not reported in the table

Study 2: supposition testing: assessment of kin keeping as a role (structural functional perspective) or behavior (behavioral perspective)

We posed suppositions of associations that would indicate that the developed kin keeping measure was assessing a specific family role or a set of behaviors possible for broader family involvement.

Methods to conduct supposition testing

Data were collected among a sample of 52 self-identified African American CHWs. Recruitment took place via email through state and national list servs of CHWs and included a PDF flyer about the study. Eligible CHWs, self-identified as African American, were 18 years or older, had some contact with biological family members in the past year, and spoke English.

Eligible CHWs completed a FCH tool that required the participant to complete a family pedigree. A member of the study team reviewed the pedigree and prepared materials to collect network information using the Colored Eco-Genetic Relationship Map (CEGRM) method, a personal/ego-network data collection approach to gather family network data (Peters et al. 2006; Kenen and Peters 2001). This includes elicitation of family information in a pedigree form and social network analysis using colors and shapes. Following the CEGRM method, participants viewed their prepopulated pedigree using screen sharing via videoconference. Together the participant and study team member discussed any missing information (e.g., family members, demographics, or cancer history for family members). The sociogram was then used to elicit information about social exchanges to better understand the overall structure of networks (Hogan et al. 2005). The research staff guided the participant to place symbols on their pedigree. These symbols represent meaningful social exchanges within the family network, including information services, tangible exchanges, emotional interactions, and members who block or disseminate cancer information (Peters et al. 2006; Kenen and Peters 2001).

We assessed sociodemographics, including age, gender, race, highest grade, household income, and marital status. Kin keeping was assessed using the shortened 9-item kin keeping scale. Family network structures included measures of density, degree or size of family, average age of network members, and proportion of network members who were female. Family network social support constructs included proximity, number of family members engaged in family health history collection, information services, tangible exchanges, emotional interactions, disseminators, and blockers as reported by the CHW. We also asked CHWs to self-report how well they thought they did in completing their family health information (subjective completeness). All aspects of this study were approved by the Emory University IRB prior to beginning recruitment (Emory IRB, IRB00108824). For the purposes of these analyses, we considered p < 0.10 to indicate association. We adopted this more liberal significance level due to the preliminary nature of our suppositions.

Results of supposition testing

Description of participants

CHWs who participated (n = 52) were on average age 45.3 (SD = 12.85); the majority were female (82.7%). All participants reported some college or higher education (19.2% some college, 55.8% college graduate, and 25.0% postgraduate). Most reported a household income of less than $75,000 (73.1%). Approximately one-third were married (34.6%) and one-third were single (32.7%). Self-rated kin keeping (9-item kin keeping scale) was relatively high (M = 4.18, Range = 1–5; SD = 0.57.

Assessment of kin keeping as a role

We identified two sets of associations, one to indicate that kin keeping might best be considered a role, as originally conceptualized in the literature—that is, one person in the family holds the role of kin keeper (Table 5). Aligned with the structural-functional perspective, we would expect to see socio-demographic profile comprising female gender, older age, and being married being positively associated with the kin keeping scale. We also expected that CHWs who subjectively rated themselves to have high levels of dissemination skills or as being very accurate in their collection of family history would also score high on the kin keeping scale. Lastly, consistent with prior research taking a kin keeper role perspective, we expected CHWs who reported their family to have greater closeness (i.e., higher density), and being larger in size and more days of contact with each family member would also score higher on kin keeping.

Table 5.

Assessment of KK as a role or behavior

Association with 9-item KKS KK as a Role KK as a Behavior
Mean STD B p-value
Sociodemographics
  Age 45.31 12.85 0.01 0.17 X
Gender (N, %)
  Female 43 82.69 0.37 0.09* X
Marital status (N, %)
  Married 18 34.62 ref ref X
  Living as married 1 1.92  − 0.46 0.45
  Divorced 12 23.08  − 0.19 0.38
  Widowed 4 7.69  − 0.27 0.42
  Single, never married 17 32.69  − 0.28 0.17
Family network structures
  Density 7.84 2.30 0.17  < 0.0001* X
  Degree/size 23.09 5.82 0.02 0.22 X
Family network social support
  Proximity 0.27 0.17 1.23 0.02 X
  Information services 0.26 0.25 0.99 0.005* X
  Tangible exchanges 0.13 0.10 1.54 0.082* X
  Emotional interactions 0.30 0.28 0.71 0.02 X
  Disseminators 0.17 0.17 0.55 0.31 X
  Number engaged in FCH collection 0.07 0.14 0.31 0.65 X
  Subjective rating of FCH collection 0.87 0.17  − 0.04 0.34 X
Open in a new tab

*p < 0.10 considered significant

For supposition set 1, kin keeping as a role, we found no association of age (B = 0.01, p = 0.17), or marital status (p > 0.05) with kin keeping; only gender was marginally and positively associated (B = 0.37, p = 0.09). We also found no significant association of being a self-identified disseminator (B = 0.55, p = 0.31), larger family network (B = 0.02, p = 0.22), or subjective assessment of family history collection (B =  − 0.04, p = 0.35) with kin keeping.

However, we found that greater perception of family closeness (i.e., network density) was positively associated with the kin keeping (B = 0.17, p < 0.0001). CHWs who reported greater frequency of contact with each family member (i.e., proximity) also scored higher on kin keeping (B = 1.226, p = 0.0162).

Assessment of kin keeping as a modifiable behavior

We posited a second set of associations that would indicate kin keeping might be treated as a modifiable set of behaviors. We expected to see significant positive associations of numbers of family tangible support behaviors with kin keeping. Specifically, we expected that reporting more individuals in the network who share cancer and health information (i.e., information services), more individuals in the network who may be asked to come to a health appointment (i.e., tangible exchanges), more individuals who would share feelings with about cancer (i.e., emotional interactions), and more people in the family engaged in family cancer history collection would be associated with more kin keeping.

For supposition set 2, kin keeping as a behavioral skill, we found no association of the number of reported family members involved in health care visits (i.e., tangible exchanges) (B = 1.5439, p = 0.0817) or the number of individuals engaged in family cancer history collection (B = 0.3046, p = 0.6475) with kin keeping. We found that CHWs who reported having more individuals in the family network who share cancer information (i.e., information services) (B = 0.99376, p = 0.0047) and more who share feelings about cancer (i.e., emotional interactions) scored higher in kin keeping (B = 0.7075, p = 00186).

Discussion

The concept of kin keeping has been explored for over a decade, largely being conceptualized as a family role that has potential for extending health promotion into family systems. Indeed, exploration of this has shown that there may be individuals within families, predominantly women, who play this role. Unfortunately, to date there has been no quantitative measure of kin keeping that could be used to explore this distinction. To this end, we engaged in a rigorous process and developed a reliable and valid 15-item kin keeping measure that could be shortened to 9 items while retaining sound psychometrics.

Our findings are mixed with respect to kinkeeping being conceptualized as a role. We found that female gender was marginally and positively associated with the 9-item kin keeping scale as was reported closeness among the family network (i.e., density) and having more frequent contact with family members (i.e., proximity) (Rosenthal 1985; Wellman and Wortley 1989). However, rating one’s self as a “disseminator” of cancer or genetic information in the family was not associated with level of reported kin keeping. Network size also was not associated with kin keeping. This is a bit surprising as the structural functionalist perspective would suggest that larger family size should prompt the need for a family connector role if retention of family closeness is a goal. Subjective ratings of accuracy at collecting a family history also were not associated with kin keeping. These latter findings support the notion that individuals may not be reliably able to self-identify as kin keepers. If interventions aim to engage family members who play the role of kin keeper, they might consider using a network approach to collect the perspectives of multiple family members to identify the kin keeper.

Additionally, we explored an expanded conceptualization of kinkeeping and found preliminary support that it may be viewed as a set of transactional behaviors that multiple family members can play. As hypothesized, more health information exchanges (i.e., information services) and more relatives who would be available to assist with doctors’ appointments and other needs (i.e., tangible exchanges) were associated with greater kin keeping. However, having more individuals engaged in family health history collection was not associated with greater kin keeping. Taken together, these findings suggest that families that more frequently share health information and rely on each other for health-related support may share kin keeping responsibilities. This suggests that multiple family members could be activated to exchange inherited risk information.

If replicated, this new conceptualization opens up the possibility for further research to develop and evaluate family-wide interventions to promote kin keeping. Rather than relying on one individual as the gatekeeper of family health information, as the field has traditionally done, interventions to promote communication about inherited risk could target the family system, and encourage shared responsibility for hereditary risk communication (Baroutsou et al. 2021; Zhao et al. 2022), specific mechanism through which kin keeping behaviors’ active (or disuade) information sharing could also be explored.

Our findings are the first to test the conceptual distinction between kin keeping as a role played by one member versus behaviors that many could take on. While the findings provide partial support for kin keeping being conceptualized as both, additional research is needed to build on our findings. In the ideal, future studies would focus on a larger and more heterogenous sample including other professions such as social workers and nursing, incorporate prospective assessments, and consider engaging multiple family members in self evaluation of kin keeping and that of other family members.

This preliminary study has several limitations worth noting. The sample size of 52 was relatively small and likely limited our power to detect associations. The sample of CHWs was selected to ensure that the concept of kin keeping would be particularly relevant. However, this also meant that the distribution of kin keeping was skewed toward higher kin keeping overall. This also may have limited power to detect associations. As a cross-sectional investigation, we are not able to infer any directionality to the associations and so kin keeping could be the cause and not the result of support behaviors. Future testing of the scale can support full CFA in different contexts and target populations, including other health professions and even online communities. This expansion could help broaden the scope of our sample and help delineate aspects of kin keeping amenable to intervention.

Despite these limitations, the development of the kin keeping scale was a critical step to help advance research about the role of kin keeping in information sharing and health decision-making among family networks. This is the first measure designed to quantify family-building behaviors that could be mobilized to promote health. Ultimately, the scale could be used to operationalize kin keeping in various theoretical models and frameworks, guide intervention development to encourage or train for kin keeping behaviors, and test suppositions about kin keeping and its role in family health promotion generally.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 56 KB) (56.1KB, docx)

Author contribution

CGA and CMM conceptualized the project, CGA secured funding for the project, CGA and CH completed the data collection, CGA and WA completed the data analysis, CGA and CMM completed the initial writing of the manuscript, all authors contributed to editing, and all authors reviewed the final manuscript.

Funding

Caitlin G. Allen received funding K00CA253576. Cam Escoffery has support from U48DP006377 and P30CA138292.

Data Availability

Data are available upon reasonable request to the corresponding author.

Declarations

We comply with the ethical standard of the Journal of Community Genetics.

Conflict of interest

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Ake JF, Lin J, Wilkinson AV, Koehly LM. Motivating Mexican American adults to share family history with healthcare providers. Prev Med Rep. 2021;22:101384. doi: 10.1016/j.pmedr.2021.101384. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Baroutsou V, Underhill-Blazey ML, Appenzeller-Herzog C, Katapodi MC (2021) Interventions facilitating family communication of genetic testing results and cascade screening in hereditary breast/ovarian cancer or lynch syndrome: a systematic review and meta-analysis. Cancers (Basel) 13(4) [DOI] [PMC free article] [PubMed]
  3. Bastian LA, Fish LJ, Peterson BL, et al. Assessment of the impact of adjunctive proactive telephone counseling to promote smoking cessation among lung cancer patients' social networks. Am J Health Promot: AJHP. 2013;27(3):181–190. doi: 10.4278/ajhp.101122-QUAN-387. [DOI] [PubMed] [Google Scholar]
  4. Beatty PC, Willis GB. Research synthesis: the practice of cognitive interviewing. Public Opin Q. 2007;71:287–311. doi: 10.1093/poq/nfm006. [DOI] [Google Scholar]
  5. Braithwaite DO, Bach BW, Hosek A, Wolf BM. Constructing family: a typology of voluntary kin. J Soc Pers Relat. 2010;27(3):388–407. doi: 10.1177/0265407510361615. [DOI] [Google Scholar]
  6. Braithwaite DO, Marsh JS, Tschampl-Diesing CL, Leach MS. "Love needs to be exchanged:" a diary study of interaction and enactment of the family kinkeeper role. West J Commun. 2017;81(5):601–618. doi: 10.1080/10570314.2017.1299881. [DOI] [Google Scholar]
  7. Brown LH, DeRycke SB. The kinkeeping connection: continuity, crisis and consensus. J Intergener Relatsh. 2010;8(4):338–353. [Google Scholar]
  8. Browne MW. An overview of analytic rotation in exploratory factor analysis. Multiv Behav Res. 2001;36(1):111–150. doi: 10.1207/S15327906MBR3601_05. [DOI] [Google Scholar]
  9. Brownstein JN, Hirsch GR, Rosenthal EL, Rush CH. Community health workers "101" for primary care providers and other stakeholders in health care systems. J Ambul Care Manag. 2011;34(3):210–220. doi: 10.1097/JAC.0b013e31821c645d. [DOI] [PubMed] [Google Scholar]
  10. Buchanan AH, Lester Kirchner H, Schwartz MLB, et al. Clinical outcomes of a genomic screening program for actionable genetic conditions. Genet Med: Off J Am Coll Med Genet. 2020;22(11):1874–1882. doi: 10.1038/s41436-020-0876-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Centers for Disease Control and Prevention (2014) Tier 1 Genomics Applications and their Importance to Public Health. https://www.cdc.gov/genomics/implementation/toolkit/tier1.htm. Accessed
  12. Centers for Disease Control Prevention (2015) Leading causes of death by race/ethnicity, all Females-United State. https://www.cdc.gov/women/lcod/index.htm. Accessed
  13. Chivers Seymour K, Addington-Hall J, Lucassen AM, Foster CL. What facilitates or impedes family communication following genetic testing for cancer risk? A systematic review and meta-synthesis of primary qualitative research. J Genet Couns. 2010;19(4):330–342. doi: 10.1007/s10897-010-9296-y. [DOI] [PubMed] [Google Scholar]
  14. Claassen L, Henneman L, Janssens AC, et al. Using family history information to promote healthy lifestyles and prevent diseases; a discussion of the evidence. BMC Public Health. 2010;10:248. doi: 10.1186/1471-2458-10-248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Costello AB, Osborne J (2019) Best pr Best practices in explor actices in exploratory factor analysis: four or analysis: four recommendations for getting the most from your analysis. Pract Assess
  16. deHeer H, de la Haye K, Skapinsky K, Goergen A, Wilinson A, Koehly LM. Let's Move: a randomized trial of the impact of family health history on encouragement and co-engagement in physical activity of Mexican-origin parents and their children. Health Educ Behav: Off Publ Soc Publ Health Educ. 2017;44(1):141–152. doi: 10.1177/1090198116644703. [DOI] [Google Scholar]
  17. den Heijer (2011) Psychological distress in women at risk for hereditary breast cancer: the role of family communication and perceived social support, Psycho Oncology - Wiley Online Library [DOI] [PubMed]
  18. DeLancey JO, Thun MJ, Jemal A, Ward EM. Recent trends in Black-White disparities in cancer mortality. Cancer Epidemiol Biomark Prev: Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2008;17(11):2908–2912. doi: 10.1158/1055-9965.EPI-08-0131. [DOI] [PubMed] [Google Scholar]
  19. Dilorio CK (2005) Measurement in Health Behavior: Methods for Research and Evaluation. Wiley Professional, References and Trade. John Wiley & Sons, 336
  20. Donenberg GR, Kendall AD, Emerson E, Fletcher FE, Bray BC, McCabe K. IMARA: A mother-daughter group randomized controlled trial to reduce sexually transmitted infections in Black/African-American adolescents. PLoS ONE. 2020;15(11):e0239650. doi: 10.1371/journal.pone.0239650. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Dotson WD, Douglas MP, Kolor K, et al. Prioritizing genomic applications for action by level of evidence: a horizon-scanning method. Clin Pharmacol Ther. 2014;95(4):394–402. doi: 10.1038/clpt.2013.226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. EGAPP Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives. Genet Med: Off J Am Coll Med Genet. 2009;11(1):35–41. doi: 10.1097/GIM.0b013e31818fa2ff. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Feeney BC, Collins NL. A new look at social support: a theoretical perspective on thriving through relationships. Pers Soc Psychol Rev. 2015;19(2):113–147. doi: 10.1177/1088868314544222. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Gaff CL, Clarke AJ, Atkinson P, et al. Process and outcome in communication of genetic information within families: a systematic review. Eur J Hum Genet: EJHG. 2007;15(10):999–1011. doi: 10.1038/sj.ejhg.5201883. [DOI] [PubMed] [Google Scholar]
  25. Guttmacher AE, Collins FS, Carmona RH. The family history–more important than ever. N Engl J Med. 2004;351(22):2333–2336. doi: 10.1056/NEJMsb042979. [DOI] [PubMed] [Google Scholar]
  26. Hammarstrom G. The construct of intergenerational solidarity in a lineage perspective: a discussion on underlying theoretical assumptions. J Aging Stud. 2005;19(1):33–51. doi: 10.1016/j.jaging.2004.03.009. [DOI] [Google Scholar]
  27. Hogan B, Carrasco JA, Wellman B. Visualizing personal networks: working with participant-aided sociograms. Field Methods. 2005;19(2):116–144. doi: 10.1177/1525822X06298589. [DOI] [Google Scholar]
  28. House JS, Landis KR, Umberson D. Social relationships and health. Science (New York, NY) 1988;241(4865):540–545. doi: 10.1126/science.3399889. [DOI] [PubMed] [Google Scholar]
  29. Kenen R, Peters J. The Colored, Eco-Genetic Relationship Map (CEGRM): a conceptual approach and tool for genetic counseling research. J Genet Couns. 2001;10(4):289–309. doi: 10.1023/A:1016627426430. [DOI] [PubMed] [Google Scholar]
  30. Kingsbury N, Scanzoni J (2016) Sourcebook of family theories and methods: a contextual approach
  31. Kline RB. Principles and practice of structural equation modeling. New York: Guilford publications; 2015. [Google Scholar]
  32. Koehly L, McBride CM. Genomic risk information for common health conditions: Maximizing kinship-based health promotion. In: Tercyak K, editor. Handbook of Genomics and Family. New York: Springer; 2010. pp. 407–436. [Google Scholar]
  33. Koehly LM, Peterson SK, Watts BG, Kempf KK, Vernon SW, Gritz ER. A social network analysis of communication about hereditary nonpolyposis colorectal cancer genetic testing and family functioning. Cancer Epidemiol Biomark Prev: Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2003;12(4):304–313. [PubMed] [Google Scholar]
  34. Koehly LM, Peters JA, Kuhn N, et al. Sisters in hereditary breast and ovarian cancer families: communal coping, social integration, and psychological well-being. Psychooncology. 2008;17(8):812–821. doi: 10.1002/pon.1373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Koehly LM, Peters JA, Kenen R, et al. Characteristics of health information gatherers, disseminators, and blockers within families at risk of hereditary cancer: implications for family health communication interventions. Am J Public Health. 2009;99(12):2203–2209. doi: 10.2105/AJPH.2008.154096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Koehly LM, Persky S, Spotts E, Acca G. Social and behavioral science priorities for genomic translation. Transl Behav Med. 2018;8(1):137–143. doi: 10.1093/tbm/ibx052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Koerner AF, Schrodt P. An introduction to the special issue on family communication patterns theory. J Fam Commun. 2014;14(1):1–15. doi: 10.1080/15267431.2013.857328. [DOI] [Google Scholar]
  38. Lareau A, Rao AH. Intensive family observations: a methodological guide. Sociol Methods Res. 2020;51(4):1–54. doi: 10.1177/0049124120914949. [DOI] [Google Scholar]
  39. Leach MS, Braithwaite DO. A binding tie: supportive communication of family kinkeepers. J Appl Commun Res. 1996;264:200–216. doi: 10.1080/00909889609365451. [DOI] [Google Scholar]
  40. Lewis MA, Rook KS. Social control in personal relationships: impact on health behaviors and psychological distress. Health Psychol. 1999;18(1):63–71. doi: 10.1037/0278-6133.18.1.63. [DOI] [PubMed] [Google Scholar]
  41. Lewis MA, McBride CM, Pollak KI, Puleo E, Butterfield RM, Emmons KM. Understanding health behavior change among couples: an interdependence and communal coping approach. Soc Sci Med. 2006;62(6):1369–1380. doi: 10.1016/j.socscimed.2005.08.006. [DOI] [PubMed] [Google Scholar]
  42. Lucassen A, Watson E, Harcourt J, Rose P, O'Grady J. Guidelines for referral to a regional genetics service: GPs respond by referring more appropriate cases. Fam Pract. 2001;18(2):135–140. doi: 10.1093/fampra/18.2.135. [DOI] [PubMed] [Google Scholar]
  43. McBride CM, Baucom DH, Peterson BL, et al. Prenatal and postpartum smoking abstinence a partner-assisted approach. Am J Prev Med. 2004;27(3):232–238. doi: 10.1016/j.amepre.2004.06.005. [DOI] [PubMed] [Google Scholar]
  44. McBride CM, Persky S, Wagner LK, Faith MS, Ward DS. Effects of providing personalized feedback of child's obesity risk on mothers' food choices using a virtual reality buffet. Int J Obes. 2013;37(10):1322–1327. doi: 10.1038/ijo.2013.87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nguyen AM, Cleland CM, Dickinson LM, et al. Considerations before selecting a stepped-wedge cluster randomized trial design for a practice improvement study. Ann Fam Med. 2022;20(3):255–261. doi: 10.1370/afm.2810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Nycum G, Avard D, Knoppers BM. Factors influencing intrafamilial communication of hereditary breast and ovarian cancer genetic information. Eur J Hum Genet: EJHG. 2009;17(7):872–880. doi: 10.1038/ejhg.2009.33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Ochs-Balcom HM, Jandorf L, Wang Y, et al. "It takes a village": multilevel approaches to recruit African Americans and their families for genetic research. J Community Genet. 2015;6(1):39–45. doi: 10.1007/s12687-014-0199-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Ouakrim DA, Boussioutas A, Lockett T, Hopper JL, Jenkins MA. Cost-effectiveness of family history-based colorectal cancer screening in Australia. BMC Cancer. 2014;14:261. doi: 10.1186/1471-2407-14-261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Peters JA, Hoskins L, Prindiville S, Kenen R, Greene MH. Evolution of the colored eco-genetic relationship map (CEGRM) for assessing social functioning in women in hereditary breast-ovarian (HBOC) families. J Genet Couns. 2006;15(6):477–489. doi: 10.1007/s10897-006-9042-7. [DOI] [PubMed] [Google Scholar]
  50. Peters JA, Kenen R, Hoskins LM, et al. Unpacking the blockers: understanding perceptions and social constraints of health communication in hereditary breast ovarian cancer (HBOC) susceptibility families. J Genet Couns. 2011;20(5):450–464. doi: 10.1007/s10897-011-9370-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Peters JA, Kenen R, Hoskins LM, Glenn GM, Kratz C, Greene MH. Close ties: an exploratory Colored Eco-Genetic Relationship Map (CEGRM) study of social connections of men in Familial Testicular Cancer (FTC) families. Hered Cancer Clin Pract. 2012;10:2. doi: 10.1186/1897-4287-10-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Peterson SK. The role of the family in genetic testing: theoretical perspectives, current knowledge, and future directions. Health Educ Behav: Off Publ Soc Publ Health Educ. 2005;32(5):627–639. doi: 10.1177/1090198105278751. [DOI] [PubMed] [Google Scholar]
  53. Polit DF, Beck CT. The content validity index: are you sure you know what's being reported? Critique and recommendations. Res Nurs Health. 2006;29(5):489–497. doi: 10.1002/nur.20147. [DOI] [PubMed] [Google Scholar]
  54. Pyeritz RE. The family history: the first genetic test, and still useful after all those years? Genet Med: Off J Am Coll Med Genet. 2012;14(1):3–9. doi: 10.1038/gim.0b013e3182310bcf. [DOI] [PubMed] [Google Scholar]
  55. Qureshi N, Kai J. Informing patients of familial diabetes mellitus risk: how do they respond? A cross-sectional survey. BMC Health Serv Res. 2008;8:37. doi: 10.1186/1472-6963-8-37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Rose PW, Murphy M, Munafo M, Chapman C, Mortensen N, Lucassen A. Improving the ascertainment of families at high risk of colorectal cancer: a prospective GP register study. Br J Gen Pract: J Royal Coll Gen Pract. 2004;54(501):267–271. [PMC free article] [PubMed] [Google Scholar]
  57. Rosenthal CJ. Kinkeeping in the Familial Division of Labor. J Marriage Fam. 1985;47(4):965–974. doi: 10.2307/352340. [DOI] [Google Scholar]
  58. Sarason I, Sarason B. Social support: mapping the construct. J Soc Pers Relatsh. 2009;26(1):113–120. doi: 10.1177/0265407509105526. [DOI] [Google Scholar]
  59. Saylor R. Concepts, measures, and measuring well: an alternative outlook. Sociol Methods Res. 2013;42(3):354–391. doi: 10.1177/0049124113500476. [DOI] [Google Scholar]
  60. Smith RA, Andrews KS, Brooks D, et al. Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening. CA: Cancer J Clin. 2018;68(4):297–316. doi: 10.3322/caac.21446. [DOI] [PubMed] [Google Scholar]
  61. Srinivasan S, Won NY, Dotson WD, Wright ST, Roberts MC. Barriers and facilitators for cascade testing in genetic conditions: a systematic review. Eur J Hum Genet: EJHG. 2020;28(12):1631–1644. doi: 10.1038/s41431-020-00725-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Thompson T, Seo J, Griffith J, Baxter M, James A, Kaphingst KA. "You don't have to keep everything on paper": African American women's use of family health history tools. J Community Genet. 2013;4(2):251–261. doi: 10.1007/s12687-013-0138-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Thompson T, Seo J, Griffith J, Baxter M, James A, Kaphingst KA. The context of collecting family health history: examining definitions of family and family communication about health among African American women. J Health Commun. 2015;20(4):416–423. doi: 10.1080/10810730.2014.977466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. United States Preventive Task Force (2013) Lung Cancer: Screening. https://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFinal/lung-cancer-screening. Accessed
  65. United States preventive Task Force (2016) Colorectal Cancer: Screening. https://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFinal/colorectal-cancer-screening2?ds=1&s=colorectal. Accessed
  66. United States Preventive Task Force (2018) Cervical Cancer: Screening https://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFinal/cervical-cancer-screening2. Accessed
  67. Valdez R, Yoon PW, Qureshi N, Green RF, Khoury MJ. Family history in public health practice: a genomic tool for disease prevention and health promotion. Annu Rev Public Health. 2010;31:69–87. doi: 10.1146/annurev.publhealth.012809.103621. [DOI] [PubMed] [Google Scholar]
  68. Veldwijk J, Lambooij MS, Kallenberg FG, et al. Preferences for genetic testing for colorectal cancer within a population-based screening program: a discrete choice experiment. Eur J Hum Genet: EJHG. 2016;24(3):361–366. doi: 10.1038/ejhg.2015.117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Watkins M (2018) Exploratory factor analysis: a guide to best practice J Black Psychol 44(3)
  70. Wellman B, Wortley S. Brothers' keepers: situating kinship relations in broader networks of social support. Sociol Perspect. 1989;32(3):273–306. doi: 10.2307/1389119. [DOI] [Google Scholar]
  71. Williams KP. Kin keeper a family-focused cancer prevention model for African-American women. J Hum Behav Soc Environ. 2008;15(2–3):291–305. [Google Scholar]
  72. Williams KP, Mabiso A, Jackson TL, Lawshe DC, Maurer J. Breast cancer and cervical cancer control program enrollees inform the kin keeper curriculum. J Cancer Educ: Off J Am Assoc Cancer Educ. 2009;24(4):257–260. doi: 10.1080/08858190902972939. [DOI] [PubMed] [Google Scholar]
  73. Williams KP, Mullan PB, Todem D. Moving from theory to practice: implementing the kin keeper cancer prevention model. Health Educ Res. 2009;24(2):343–356. doi: 10.1093/her/cyn026. [DOI] [PubMed] [Google Scholar]
  74. Wiseman M, Dancyger C, Michie S. Communicating genetic risk information within families: a review. Fam Cancer. 2010;9(4):691–703. doi: 10.1007/s10689-010-9380-3. [DOI] [PubMed] [Google Scholar]
  75. Yoon PW, Scheuner MT, Peterson-Oehlke KL, Gwinn M, Faucett A, Khoury MJ. Can family history be used as a tool for public health and preventive medicine? Genet Med: Off J Am Coll Med Genet. 2002;4(4):304–310. doi: 10.1097/00125817-200207000-00009. [DOI] [PubMed] [Google Scholar]
  76. Zhao J, Guan Y, McBride CM. A systematic review of theory-informed strategies used in interventions fostering family genetic risk communication. Patient Educ Couns. 2022;105(7):1953–1962. doi: 10.1016/j.pec.2022.03.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale of Perceived Social Support. J Pers Assess. 1990;55(3–4):610–617. doi: 10.1207/s15327752jpa5503&#x00026;4_17. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 56 KB) (56.1KB, docx)

Data Availability Statement

Data are available upon reasonable request to the corresponding author.

Articles from Journal of Community Genetics are provided here courtesy of Springer

RESOURCES