Systematic Assessment of Family Service Barriers to Support Youth Engagement with Health and Social Care

Abstract

Family characteristics and service barriers influence children’s access to health and social care. Systematic assessment of family service barriers may help practitioners in their efforts to support family engagement with needed services. To address this need, this study utilized data from a 12-week service navigation intervention to examine associations between family characteristics, service barriers, service need, and service access. Twenty-nine caregivers of youth under age 18 participated. Pre-test measures included a family demographic questionnaire, service barriers checklist, and family service plan. Post-test outcome measures were the type and number of services accessed in the family service plan. At baseline, participants reported an average of 10 barriers to care. The family characteristics, caregiver age, child age, and community group involvement, were associated with a greater number of service barriers. Over the course of the intervention, the service barrier “provider waitlists” was associated with an increased service access, while having a male child was associated with a decrease in service access. Results indicate families experience multiple service barriers and specific family characteristics influence service access. Systematic assessment of service barriers and consideration of family characteristics can assist practitioner efforts to support youth and family engagement with health and social care.

1. Introduction

The benefits of prevention and early intervention services to children’s health and well-being are well established [1,2], yet millions of families with children experience significant and persistent barriers accessing routine health care and social services each year. Socioeconomic status is an important marker of public health [3] and illustrates the scope of the problem. Recent data from the United States suggests 11.9 million children are living in poverty [4] and 4.3 million children are without health care coverage [5]. Low-income, rural, immigrant, and racial-, and ethnic-minority populations are particularly vulnerable to these challenges and the consequences are considerable [6]. Over the lifespan, health and social inequality are associated with increased risk of mental illness, family violence, morbidity, and early mortality [7,8,9].

Barriers to health and social care are complex, multidimensional, and community- and family-specific [10]. For low-income and racially minoritized families in the United States, lack of access to health and social care is due to several interconnected structural factors including racism, gender inequality, poverty, health care costs, and low family wages [11,12]. Recognition of the layered and complex nature of health care and social service access have led to the development of models of intervention designed specifically to reduce barriers and facilitate access to care. These brief, targeted models of service navigation originated in primary and specialty healthcare sectors [13,14], and have since expanded into early childhood_, community mental health, and child welfare settings [15,16,17]. Current research with service navigation programs is promising with respect to participant satisfaction and service engagement [18]; however, little is known about how family characteristics, service needs, and service barriers shape access to care, particularly in the context of prevention-oriented service navigation. Understanding how family characteristics, service needs, and barriers shape service access could inform future programs and services aimed at addressing the health, mental health, and social service needs of underserved children and families.

2. Materials and Methods

The current study utilizes data from a formative evaluation of a 12-session telephone and web-mediated model of prevention-oriented family navigation called “Navigate Your Way [19]”. The navigator model was designed to engage and support underserved families in accessing health care, mental health care, and social services for their children and family before problems required intensive or non-voluntary interventions. “Navigate Your Way” draws from theories of self-determination, empowerment, and social justice, self-advocacy, anti-oppressive practice, and person-centered care [19,20,21,22,23]. The primary navigation activities which encompass “Navigate Your Way” include (1) comprehensive assessment of the family system, prior and current family health care and social service utilization, and systematic assessment of service barriers, (2) collaboration with the primary caregiver to develop a family navigation service plan (i.e., identify, prioritize and strategize access for to up to three personalized health and social care services) on behalf of the youth and family, (3) weekly telephone and web-based support to provide support, problem solve, and facilitate service access, and (4) a closing assessment and discharge plan to assist the family after intervention conclusion. Navigation activities were conducted over a 12-week period, with major assessments conducted in weeks 1–12.

Navigators were graduate research assistants pursuing degrees in social work and marriage and family therapy. They were trained to conduct systematic assessments, engage in service research, provide parent education, conduct community outreach, problem solve, provide emotional and instrumental support, and monitor navigation plan progress. Weekly group supervision and fidelity monitoring were provided by the project’s principal investigator for the duration of the study. Primary outcomes from the formative evaluation identified significant increases in the number of services participants accessed during the 12-week period, reductions in children’s mental health difficulties, and reductions in the number of service barriers participants experienced [18]. This study builds on this research by investigating associations between the participating families’ characteristics, their service needs and barriers, and the services they accessed. The specific research questions guiding this study were (1) What were family service needs and barriers?, (2) What kinds of services did they access?, (3) Were participant characteristics associated with service barriers or service access?, and (4) Were service needs and barriers associated with service access?

Based on prior research into service barriers in child and adolescent mental health care [10], we hypothesized the presence of service barriers at multiple levels of the ecology (i.e., family, service provider, community, and health care system) would be associated with lower rates of service access. Based on prior research of health and social inequality [6], we also hypothesized race-based differences in the number of barriers participants would report and ultimately, the number of services they accessed. Finally, we employed social capital theory [24,25] to hypothesize a larger network of relational and institutional resources (i.e., older participants, larger households, presence of community connections, and presence of a social support system) would result in fewer service barriers and higher rates of service access during the study period.

2.1. Inclusion and Exclusion

To be eligible for participation, individuals must be the primary caregiver of a youth under age 18 and be experiencing significant or persistent barriers to connecting their children and family to health care and/or social services. Service barriers were broadly defined to include any condition or process internal or external to the family system which inhibited their ability to identify, access, or engage with health care or social services. Eligibility also required participants to speak English, have access to a telephone or the internet, and plan to reside in state where the research took place for the duration of their participation. To ensure participants were not receiving active navigation intervention components elsewhere during their participation in the study, families who were currently involved with a case management program, child protective services, or juvenile probation were excluded. Thirty-two caregivers enrolled, 29 completed the study. Two participants did not complete the pre-test assessment and one passively withdrew during participation for reasons unrelated to the project. The current study analyzes data from the 29 study completers.

2.2. Participant Characteristics

Participant characteristics included caregiver race, age, and gender; youth race, age, and gender; family household size, support network size, family community group involvement, religious affiliation, and tribal/immigration status. The majority of caregivers identified as racial and ethnic minority (55.2%, n = 17), reporting their race as White (44.8%, n = 13), Black (41.4%, n = 12), Multiracial (6.9%, n = 2), Asian/Pacific Islander (3.4%, n = 1), and East African (3.4%, n = 1). Youth race was reported as Black (37.9%, n = 11), White (31.0%, n = 9), Multiracial (20.7%, n = 6), Latino/a/e (3.4%, n = 1), and Asian/Pacific Islander (3.4%, n = 1). The race of one youth was not reported. The mean caregiver age was 38.6 (SD = 9.7) years, and the mean youth age was 10.1 (SD = 5.9) years. All but one caregiver identified as female (96.6%, n = 28). Youth gender was reported as female (65.5%, n = 19) and male (34.5%, n = 10). The mean household size was 3.5 (SD = 1.8) individuals. Caregivers reported an average of 1.1 (SD = 1.2) members in their social support network. Some caregivers reported involvement in community groups (27.6%, n = 8). Over half reported a religious affiliation (62.1%, n = 18). One participant reported immigration status (3.4%, n = 1).

2.3. Sampling Procedures

Recruitment was conducted through direct-to-consumer advertising (i.e., web, radio, social media) and community research partnerships which included an intermediate school district, a Head Start program, and a county department of human services. Caregivers self-referred to the research and written informed consent was obtained from all participants. Participants were incentivized for their participation, and could earn up to $100 dollars for completing all assessments during the 12-week period. Institutional Review Board approval and oversight was provided by the University of Minnesota, study #7787.

2.4. Measures

Pre-test and post-test measures were collected from the participant through telephone interviews with their family navigator. Data for the current study were collected from a selection of study measures which included a participant intake form, service barriers checklist, and family navigation service plan.

2.4.1. Participant Intake Form

The intake form was used to gather the demographic characteristics of the participants and their identified target child. Data included in the current study were parent race, age, and gender; child race, age, and gender; family religious affiliation, household size, support system size, and community group involvement.

2.4.2. Service Barriers Checklist

The service barriers checklist is a 23-item measure which was completed by the navigator after completion of the pre-test interview with the caregiver. The checklist is comprised of four constructs representing distinct categories of service barriers across family, logistical, provider, and system domains. Service barriers were summed for each category and for the measure overall. Service barriers could range from 0–23. The service barriers checklist demonstrated good reliability at pre-test assessment (Cronbach’s Alpha = 0.74). The family construct (9-items) included barriers related to individual family members and the family unit. Example items include cultural barriers, discrepancies among family members about the need for services, and ambivalence to engage with services. The family barriers construct demonstrated adequate reliability (Cronbach’s Alpha = 0.69), and was positively correlated to total (r = 0.82, p < 0.01) and provider barriers (r = 0.47, p < 0.01) but was not correlated to logistical or system level barriers. The logistical barriers construct (6-items) included items related to care coordination, planning, and service utilization. Example items include childcare challenges and transportation or commute challenges. The logistical barriers construct demonstrated weak reliability (Cronbach’s Alpha = 0.40). Logistical barriers were positively correlated to total barriers (r = 0.53, p < 0.01) but not family, provider, or system barriers. The provider barriers construct (6-items) included items related to actual and perceived difficulties with arranging care with a provider. Example items included confidentiality concerns and referral procedures. The provider barriers construct demonstrated adequate reliability (Cronbach’s Alpha = 0.65) and was positively correlated with total (r = 0.74, p < 0.01) and family barriers (r = 0.47, p < 0.01). The system barriers construct (2-items) included the lack of culturally sensitive services and lack of service options in the family’s geographic area. The system barriers construct demonstrated adequate reliability (Cronbach’s Alpha = 0.62) and was positively correlated with total barriers (r = 0.40, p < 0.05) but not provider, logistical, or family barriers.

2.4.3. Family Navigation Plan

The family navigation plan was used to guide the work between each participant and navigator. The plan was developed during the initial phone interview and completed over the course of intervention. Plans were family-specific and could target three health care and/or social service access goals. To assist the implementation of the family navigation plan, navigators worked with participants to articulate service plan objectives for each goal that were specific, measurable, relevant, and time bound. Weekly check-ins between the navigator and caregiver were used to determine goal completion. The Family Navigation Plan was updated with a completion note when a service was accessed. Participants could complete a total of 0–3 goals during study participation.

2.5. Analysis

Frequency and descriptive statistics were calculated for all study variables. Family characteristics included parent age, child age, parent race (0 = non-white, 1 = white), youth race (0 = white, 1 = non-white), number of people in household (count), number of people in support network (count), tribal/immigration status (0 = no, 1 = yes), community group involvement (0 = no, 1 = yes), and religious affiliation (0 = no, 1 = yes). Service barriers included total (range = 0–23), family (range = 0–9), logistical (range = 0–6), provider (range = 0–6), and system barriers (range = 0–2). Cronbach’s Alpha was used to examine the internal consistency of the service barrier checklist constructs. To test all three hypotheses, we developed a correlation matrix for binary and continuous variables. A Fisher’s exact test was used to examine service goal completion by service goal type.

3. Results

3.1. Service Barriers, Need, and Access

Families reported a variety of service barriers across family, logistical, provider, and system domains (

Table 1. Summary of participant identified service barriers.

Construct	M	SD	Range
Total Barriers	10.4	4.1	4–19
Family	4.6	2.2	1–9
Logistical	3.0	1.4	0–6
Provider	2.0	1.7	0–5
System	0.8	0.8	0–2
Item	%		N
Family Barriers
Lack of awareness about available service options	100.0		29
Lack of clarity about service needs	75.9		22
Attitudes toward help seeking/feelings of self-reliance	48.3		14
Attitudes toward available services	48.3		14
Lack of family support for engaging with services	48.3		14
Feelings of shame/stigma	44.8		13
Ambivalence/lack of motivation to engage services	41.4		12
Discrepancies among family about what to do	31.0		9
Cultural barriers	24.1		7
Logistical Barriers
Insurance/financial issues	86.2		25
Transportation/commute challenges	58.6		17
Lack of time	58.6		17
Work schedule	37.9		11
Other family obligations	34.5		10
Childcare challenges	27.6		8
Provider Barriers
Provider availability/waitlist/delays	51.7		15
Referral procedures	34.5		10
Provider competency	34.5		10
Specialist availability	34.5		10
Scheduling	34.5		10
Confidentiality concerns	6.9		2
System Barriers
Lack of service options in families geographic area	55.2		16
Lack of culturally sensitive services	20.7		6

). Families experienced an average of 10.4 (4.1) barriers to care. Most participants reported having insurance and financial issues (86.2%, n = 25) and a lack of clarity about their service needs (75.9%, n = 22). More than half of participants identified transportation/commute challenges (58.6%, n = 17), lack of time to engage services (58.6%, n = 17), and lack of services in their geographic area (55.2%, n = 16). The most identified family service need was connection to mental health care (28.7%, n = 25), followed by housing (12.6%, n = 11) and food security (10.3%, n = 9).

3.2. Family Characteristics and Service Barriers

No family characteristics were associated with total, family, or logistical barriers, however, participant age (r = 0.47, p = 0.01), child age (r = 0.36, p = 0.05), and community group involvement (r = 0.39, p = 0.04) was associated with increased provider barriers. Family community group involvement was associated with increased system barriers (r = 0.59, p < 0.01). At the item level, the number of people in the home was associated with lack of clarity about service needs (r = 0.38, p = 0.04). Older caregiver age (r = 0.43, p = 0.02) and community group involvement (r = 0.48, p = 0.01) were associated with lack of family support to engage with services. Older child age was associated with more negative attitudes towards available services (r = 0.49, p < 0.01). Families with a racial/ethnic minority child were associated with increased cultural barriers (r = 0.40, p = 0.04). Community group involvement was also associated with increased cultural barriers (r = 0.45, p = 0.02) and a lack of available services in their geographic area (r = 0.56, p < 0.01). Several participant characteristics were associated with logistical, provider, and system barriers. Older caregivers (r = 0.37, p = 0.05) and older children (r = 0.59, p < 0.01) were associated with an increase in referral procedure barriers. Older caregiver age was also associated with increased provider availability/waitlist/delay barriers (r = 0.40, p = 0.03).

3.3. Participant Characteristics, Service Barriers, and Service Access

Mean scores for the service barrier constructs were not associated with the number of services participants accessed, however one item level correlation emerged. Specifically, the barrier “provider lack of availability/waitlists/delays” (r = 0.43, p = 0.02) was associated with increased service access. For participant characteristics, caregivers of male children were associated with decreased service access (r = −0.72, p < 0.01). A post hoc exploration with a Fisher’s exact test showed that types of service needs differed based on child gender (p < 0.01), and that the type of service needs reported by the caregiver affected service access (p = 0.04). Regarding services accessed, 60% (n = 15) of participants in need of mental health care successfully accessed the service, 77.8% (n = 7) accessed food services, and 63.3% (n = 7) accessed housing supports. All goals related to health care (n = 6) were accessed, and 80% (n = 4) of employment/vocational services were accessed (

Table 2. Summary of participant reported service needs and services accessed.

	Needed		Accessed
	%	N	%	N
Mental health	28.7	25	60.0	15
Housing	12.6	11	63.6	7
Food security	10.3	9	77.8	7
Insurance	9.2	8	75.0	6
Transportation	9.2	8	50.0	4
Health care providers	6.9	6	100.0	6
Employment/vocational	5.7	5	80.0	4
Childcare	4.6	4	0.0	0
School	3.4	3	33.3	1
Diapers	3.4	3	33.3	1
Social skills	3.4	3	0.0	0
Financial support	2.3	2	0.0	0

Note: Service need was defined by type of goal indicated in Family Navigation Plan. A Fisher’s exact test of independence suggested differences in rates of service access by service need (p = 0.04).

).

4. Discussion

This study aimed to explore the relationship between family characteristics, service needs, service barriers, and service access, in the context of a prevention-oriented service navigation intervention study. Descriptively, results indicate that families most needed connection to mental health, housing, and food security services. Families experienced multiple barriers to care spanning multiple ecological domains. Common barriers included insurance and financial issues, transportation and commute challenges, a lack of services in their geographic area, and a lack of clarity of what services the family needed. Notably, all families experienced a lack of awareness of available services. This barrier has not been consistently identified in studies of health and social care navigation, and may be a valuable point for discussions with families once specific service needs have been established. Participants were successfully connected to health care, employment and vocational services, food security, and health insurance, but were not successfully connected to childcare, cash assistance, or social skills programs (e.g., youth group, positive youth development) programs.

Our first hypothesis was a greater number of service barriers would result in lower rates service access. This hypothesis was not supported. Mean total and domain-level service barriers were not correlated with the number of services accessed. Counterintuitively, at the item level, the presence of provider waitlist/delays were associated with increased access. This suggests the presence of waitlist barriers may be reflective of previous family efforts to seek out care and a readiness to engage with services.

With respect to family characteristics and service access, we hypothesized racial and ethnic minority participants would experience more service barriers and lower rates of service utilization. Results provide partial support for this hypothesis. Families with racial and ethnic minority youth experienced an increase in provider related cultural barriers, indicating a need for more culturally relevant and responsive services for families with children under age 18. Interestingly, there were no associations between racial and ethnic minority caregivers and increased barriers of any type. These findings may represent a commonality of barriers across racial groups, but could also be a function of our small sample size.

We also hypothesized older participant age, larger household size, greater community connections, and the presence of a support system would be associated with fewer service barriers and greater rates of service access. Findings did not support this hypothesis. In fact, older caregiver age was associated with an increase in provider barriers, an increase in referral procedure barriers, an increase in provider availability/waitlist/delay barriers, and a lack of family support to engage in services. This suggests families of older children and larger families may disagree about the need for services and experience more difficulty finding and accessing services in their communities. Families with previously established community connections also experienced an increase in provider and system-level barriers, including cultural barriers, lack of family support, and lack of services in their geographic area. Because this study was carried out during the COVID-19 pandemic, it is possible community connections the families previously relied on for help were overwhelmed or unavailable. Families with a larger household size also reported less clarity about their service needs, suggesting the presence of internal conflicts regarding what is needed and how to best move forward. This suggests whole-family navigation support may be needed to resolve disagreements, clarify service needs, and facilitate engagement with services.

This study revealed similarities and differences to past studies. Interestingly, except for child race and availability of culturally specific service providers, this study did not find a connection between caregiver race/ethnicity and the barriers families experienced. This contrasts with other research which suggests individuals who have low income or are racial and ethnic minorities experience greater barriers to care [6]. It is possible that this non-finding is a result of the small study sample size, but may also be due to a commonality of service barriers among rural, white, and racially diverse families. Study results do suggest an increase in barriers for older families and those who were engaged with their community. It is possible older caregivers could experience additional barriers accessing care since prevention-oriented programs and services tend to be targeted to new parents and parents of younger children. This would suggest families with older youth may need to be supported in ways that are different than families with young children. Our finding that community engagement was associated with increased barriers could be a function of timing the COVID-19 pandemic, when families could not engage with their community and receive supports in the ways done previously. Social capital theory contends social and institutional relationships are a critical human resource, and it is through organized social structures, mutual understanding, and network relationships that families acquire needed resources [25]. Because COVID-19 simultaneously disrupted the social networks of families and overwhelmed institutional resources, it is possible community-engaged families struggled to navigate challenges without the presence of supports they typically relied on.

Study results also provide implications for future navigation practice, policy, and research. In practice, navigators should systematically assess family service barriers, recognizing families may have similar needs but could experience different barriers to care. Navigators should also be prepared to take a whole-family approach to engagement and navigation, and to tailor their approach according to the developmental stage of the family, caregivers, and children. At the policy level, study results suggest a need to increase the accessibility and range of services available to families, including housing and concrete supports, as these services were difficult for all families to access due to limited community supply. Additionally, resources are needed in rural and racially diverse communities, as well as for families with older children. With respect to research, our analysis suggests service barriers varied based on service need and some family characteristics, which may suggest possible latent typologies of service barriers, service need, and service access. Future research should investigate the practical utility and predictive validity of the service barriers checklist, and consider how complex interrelated dynamics like family characteristics, service barriers, and specific service need contribute to service access over time.

Limitations

This study had several limitations that we aimed to minimize in the data analysis and interpretation process. First, this study took place in the middle of the COVID-19 pandemic. It is likely many participants who struggled to access services did not have the supports and resources that they used previously in their communities. Replication of the current study with a longer follow along period could help disentangle the effects of the COVID-19 pandemic on study findings. Second, our sample was small which limited statistical power and the types of analyses we could conduct. Our work could be replicated with a larger sample to examine the stability of findings, retest hypotheses, and explore other associations in a multivariate and latent variable modeling framework. Third, study participants received incentive payments for the duration of their participation in the 12-week study. Given that many participants were from a lower socio-economic background, payments for participant in the study could inadvertently influence their engagement with the navigators. In future research, incentive payments could be limited to major data collection intervals (e.g., pre- and post-test assessments) to reduce the potential for incentives to influence project engagement. Finally, we did not analyze the degree of intensity for barriers that families experienced, which could influence the strength and significance of associations from family characteristics to service barriers, and service barriers to service access.

5. Conclusions

The health care and social service needs of families are diverse, and the barriers they experience accessing care are complex, multidimensional, and interconnected. In this study a confluence of factors at the family and provider levels, alongside child and caregiver age and service need, shaped access to care. Systematic assessment of family characteristics and service barriers, such as those described in this study, can help inform personalized and developmentally sensitive approaches to navigation, which may help improve timely access to care. Continued investigation into these relationships may provide additional information to inform navigation programs, related services, and policies aimed at promoting service access and reducing health and social inequality.