Staying in the Loop: Quality of Family-Paid Caregiver Communication & Influences on Resident Mental Health in Long-Term Care

Abstract

Background:

Considerable research has examined communication dynamics among family members and staff in nursing homes (NHs) and has demonstrated that better communication is associated with more optimal mental health outcomes in both family caregivers and paid caregivers. However, the literature on how communication dynamics influence mental health in long-term care residents is limited, and it has yet to be determined how communication impacts residents across care contexts, such as assisted living facilities (ALFs). The purpose of this study is to examine family caregivers’ perceptions of communication with paid caregivers and its influence on long-term care resident outcomes and to compare how results differ across care settings (NHs versus ALFs).

Methods:

Data were drawn from a subsample of the National Health and Aging Trends Study (NHATS) and the National Study on Caregiving (NSOC). The sample consisted of 142 NHATS participants residing in long-term care (n=93 ALF residents; n=49 NH residents) with an eligible family caregiver who participated in the NSOC. Family caregivers’ perceived quality of communication was assessed via questions regarding the frequency, availability, and helpfulness of communication with paid caregivers. Resident mental health was assessed via measures of positive and negative affect, depressive symptoms, and anxiety.

Results:

Across the total sample, greater availability of communication between paid and family caregivers was associated with lower depressive symptoms and negative affect in residents. When examining how these relationships varied across care setting, communication was a stronger predictor of fewer depressive symptoms among residents in ALF settings.

Conclusions:

Study findings provide insights into how interpersonal dynamics between family and paid caregivers influence resident mental health and underscores the importance of enhanced communication among all members of the primary care team – that is, paid caregivers, residents, and their family members.

The growing older adult population is heavily reliant on long-term care options for optimal quality of care and to alleviate stress and burden on family caregivers. Estimates show nearly 70% of adults aged 65+ will need long-term care services and supports at some point.¹ Despite the critical role that long-term services play in providing a comprehensive continuum of care to medically complex older adults, institutional-level barriers – including understaffing, lack of time/training protocols, high workload, employee turnover, and staff dissatisfaction – can impact a myriad of processes that impede the ability to establish consistent lines of communication with family members. Further, ineffective communication can hinder the provision of high-quality care and adversely impact well-being, mood, and quality of life of long-term care residents.^{2, 3}

The terms ‘Person-Centered’ and ‘Family Centered’ care have been described as a ‘movement’ and a ‘cultural change’ in the long-term care industry aimed at shifting from a hospital-like, task-oriented approach to more individualized care in which relationships represent a critical marker of care quality.⁴ Although these terms have gained prominence, family caregivers are often left out of the communication loop despite remaining involved in care after their care-recipient transitions to residential care.^5–8 Successful person-centered care is contingent on collaborations with family, staff, and residents; positive and consistent communication dynamics are a prerequisite for developing trust with paid caregivers assuming care tasks originally fulfilled by family members.⁹ Research has shown that poor communication with and information received from paid caregivers is a looming concern among family caregivers of nursing home (NH) residents.^{5, 10, 11} This is unfortunate, given that family members possess deep knowledge about residents’ personal history and may be attuned to concerns with residents’ health and well-being prior to paid staff becoming aware and, thus, can contribute a rich background to help individualize care plans and maximize quality of care.⁵

Research in NHs has also shown that effective family-paid caregiver communication is dependent on frequent, high-quality interactions characterized by shared goals and knowledge, with the inclusion of family caregivers as members of the primary care team.^{12, 13} Improving communication in long-term care can facilitate improved care coordination and optimize quality of care and quality of life for residents,^{14, 15} and may also mitigate caregiving-related strain among family members.¹⁶

Most of the literature examining interpersonal dynamics in long-term care has been limited to NHs, and a surprisingly little amount of work examines communication on resident outcomes. Most work focuses on staff and family outcomes, largely limited by staff/family proxy reports to evaluate resident outcomes. Despite its limitations, both quantitative and qualitative research has concluded that effective communication is an essential indicator of care quality within long-term care settings, and is also associated with better resident outcomes, including better end-of-life outcomes, and greater family satisfaction.^{6, 17–21} Additional research is needed to better elucidate the relationship between family-paid caregiver communication and its influence on resident well-being, specifically mental health.

Although evidence suggests that better communication enhances patient-centered care, much this research has been limited to NHs. Despite the increasing demand on both assisted living facilities (ALFs) and NHs, little empirical work has examined differences in communication dynamics and its associations in residents across NHs and ALFs.

The demand for ALFs as a residential care option has continually increased as a popular, and perhaps more desirable, alternative to NHs. In 2020, there were approximately 1.3 million NH residents and nearly 1 million older adults were residing in ALFs.²² ALFs have evolved to provide a wide-ranging continuum of care, including dementia-specific services and specialized care for residents with diverse functional needs.^{23, 24} Prior work comparing general differences in resident characteristics across ALFs and NHs is mixed. Some have reported no differences among ALF and NH residents regarding mortality, depression, behavioral symptoms, and social withdrawal,²⁵ while others suggest better quality of life among ALF residents.²¹ In the context of communication, one study of family and staff in ALFs found that poorer interpersonal dynamics influence both paid (i.e., burnout, depression) and family (i.e., burden) caregiver outcomes,¹⁶ but its impact on resident mental health remains to be examined.

Enhancing knowledge on perceived communication dynamics will help to delineate a currently lacking conceptual framework of communication between residents, families, and paid caregivers in long-term care. Further, ascertaining family caregivers’ perceived communication quality with paid caregivers across care settings could allow for the development of targeted interventions to enhance communication tailored to care context and setting. However, to maximize the ability for interventions to be efficacious in real-world settings, further investigation is warranted into how family caregivers perceive communication with paid caregivers, how perceptions of communication affect residents’ mental health, and how such perceptions differ across care settings. Thus, the purpose of this study is to characterize and explore the influence of family caregivers’ perceptions of communication with paid caregivers on long-term care resident mental health (i.e., depressive symptoms, anxiety, positive and negative affect) and to examine how these relationships vary based on care-setting (NHs versus ALFs).

Method

Secondary data were used from round 7 of the National Health and Aging Trends Study (NHATS)^26–28 collected in 2017 and linked caregiver self-report data from the National Study on Caregiving (NSOC-III),^{29, 30} an NHATS companion study. Both the NSOC and NHATS datasets are publicly available and do not contain individual identifier information, therefore this study is considered exempt by the Institutional Review Board of the primary institution of the study’s principal investigator/first author of this paper. Funded by the National Institute on Aging (NIA;U01AG32947), the NHATS examines functioning in a national sample of Medicare beneficiaries aged 65+. The NSOC is a telephone-based survey of unpaid caregivers identified by eligible Medicare beneficiaries who participated in the NHATS study (NIA;R01AG054004).

Participants

The current study included NHATS participants in long-term care (NH, ALF) and their eligible caregiver with a completed NSOC interview. Eligible NHATS participants included were those who transitioned to residential care following their initial NHATS interview and either a) resided in an ALF (n=337, 5.34%) or b) NH (n=112, 1.77%) and c) had an eligible non-paid caregiver who participated in the NSOC-III. There were a total of 449 NHATS participants in residential care during round 7 of the interview, 313 of whom had a caregiver eligible to participate in the NSOC. Of those 313 patients and caregivers, 231 caregivers had completed the NSOC. Additionally, participants without any communication variables were excluded from the analyses (n = 89; 38.5%). Thus, the final analytic sample comprised 142 long-term care residents (n=93 living in ALFs; n=49 living in NHs) and caregivers with complete data for the NHATS and NSOC interviews, respectively. Chi-square tests were conducted to examine whether having a caregiver who participated in the NSOC (n=231), versus those without (n = 218), was associated with differences in gender, race/ethnicity, or age of the care recipient. Having a caregiver participate in the NSOC was not associated with gender or race/ethnicity, but those with a caregiver who participated in the NSOC included more individuals in the older age category (85+) compared to those who did not (X²=5.44, df=1, p=.02).

Measures

Participant Characteristics

Demographics.

Participants reported on their background/demographic characteristics including age, gender, race/ethnicity, education, socioeconomic status, and type of care setting the care-recipient currently resides.

Resident Cognition.

Cognition was assessed using eight items measuring orientation to dates and names (e.g., name correct day, month, year). Responses were coded as 1=correct or 0=incorrect, with scores ranging from 0–8 (Cronbach’s α=.62).

Communication

Three constructs assessed caregivers’ perceived quality of communication received by paid caregivers regarding care-recipients’ care and condition. Communication Frequency was measured with one item asking participants to report their frequency of communication with paid caregivers over the past year, with response options including 1=often to 3=rarely. Perceived Availability of Communication was assessed via three items assessing perceived availability of communication around support received by paid caregivers. Items included: “How often did the provider listen to what you had to say?”; “How often did the provider ask if you needed help managing [care-recipient’s] health treatments?”; and “How often did the provider ask if you understood [care recipient’s] health treatments?” with four response options (1=always to 4=never). Responses for the three items were summed to form a composite variable representing perceived availability of communication (Cronbach’s α=.62). Perceived Helpfulness of Communication was assessed with one item asking caregivers to rate the extent to which communication with paid caregivers were perceived as helpful in caring for the care-recipient, with four response options ranging from 1=a lot to 4=not at all. Scores were reverse coded for each variable so that higher values indicate higher levels of frequency, availability, and helpfulness of communication.

Resident Mental Health

Positive and Negative Affect.

Four items were used to assess positive and negative affect in residents.^{31, 32} Participants were presented with four items comprising two positive (“Cheerful”; “Full of Life”) and two negative (“Upset”; “Bored”) adjectives. Participants rated the frequency to which they felt that way in the last month on a 5-point Likert scale ranging from 1=every day to 5=never. Two summed variables were created, one representing positive affect (Cronbach’s α=.92) and one representing negative affect (Cronbach’s α=.96). Variables were recoded so that higher scores indicate higher levels of positive/negative affect.

Depressive Symptoms.

Depressive symptoms experienced in the last month were assessed via two-item Patient Health Questionnaire (PHQ-2).³³ Residents were asked to report how often they 1) had little interest or pleasure in doing things and 2) felt down, depressed, or hopeless. Responses were recorded on a four-point Likert scale with options ranging from 1=not at all to 4=nearly every day. Responses were summed, with higher scores indicating greater frequency of depressive symptoms (Cronbach’s α=.65).

Anxiety.

The two-item Generalized Anxiety Disorder scale (GAD-2)³⁴ asked residents to report how often in the last month they felt 1) nervous, anxious, or on edge and 2) were unable to stop or control worrying. Response options included a four-point Likert scale ranging from 1=not at all to 4=nearly every day. Responses were summed to form a composite variable, with higher scores indicating greater frequency of anxiety symptoms (Cronbach’s α=.76).

Data Analysis Plan

Descriptive statistics and frequency distributions were computed for key study variables and to screen for missing data and normality. Pearson’s correlations were conducted to examine the bivariate associations among the predictor variables (i.e., frequency, availability, and perceived helpfulness of communication with paid caregivers) and resident mental health outcome variables. To reduce the number of predictor variables to obtain a more parsimonious model, only predictors correlated with resident mental health variables were included in subsequent analyses.

To examine the predictive validity of the communication variables on the mental health outcomes after controlling for relevant sociodemographic variables, we conducted a three-block hierarchical regression for each outcome (positive affect, negative affect, depressive symptoms, and anxiety). Resident and family caregiver characteristics were entered in Blocks 1 and 2, respectively, and the three communication variables described above were entered in Block 3.

Independent samples t-tests were conducted to assess differences in aspects of communication and resident outcomes based on care-setting (ALF versus NH). Then, two separate-three block hierarchical regressions were run, similar to that described above, with relevant resident and covariate characteristics in Blocks 1 and 2, respectively, and aspects of communication in Block 3 predicting resident mental health outcomes. To examine subgroup differences in the strength of the effects of aspects of communication on resident outcomes in NH and ALFs, separate analyses were conducted by care setting (ALF versus NH) on resident mental health. The similarity of regression coefficients across the models were compared via a Z test to evaluate differences in the magnitude of unstandardized regression coefficients.^{16, 35} Analyses were conducted with IBM SPSS Statistics, Version 28.0.³⁶ Listwise deletion was used to deal with missing data. No weighting procedures were adopted for the present analyses.

Results

Tables 1 and 2 present descriptive statistics and Pearson’s correlations, respectively, among key study variables. The three communication variables were significantly correlated with one another (rs range from .22 to .52). Additionally, communication availability was positively associated with positive affect (r =.24, p<.05), and negatively associated with negative affect (r=−.24, p<.05) and depressive symptoms (r=−.21, p<.05). Communication frequency was negatively associated with depressive symptoms (r=−.19, p<.05).

Table 1.

Descriptive Statistics for Key Study Variables.

	Range in data	% missing	Total (N= 142)	ALF (n = 93)	NH (n = 49)	t or X2	df	p
			M (SD)	M (SD)	M (SD)
Communication Frequency	1–3	0.0	1.77 (0.73)	1.85 (0.77)	1.61 (0.64)	1.85	140	0.066
Communication Availability	2–11	0.0	5.83 (2.19)	5.89 (2.14)	5.71 (2.30)	0.46	140	0.647
Communication Helpfulness	1–4	0.7	1.67 (0.84)	1.76 (0.88)	1.49 (0.74)	1.84	139	0.069
Positive Affect	1–10	44.4	6.67 (1.67)	6.72 (1.44)	6.42 (1.44)	0.57	77	0.57
Negative Affect	2–10	43.7	3.43 (1.82)	3.47 (1.88)	3.17(1.47)	0.53	78	0.597
Depressive Symptoms	1–8	0.7	3.79 (1.89)	3.42 (1.70)	4.52 (2.04)	−3.41	139	<.001
Anxietya	1–8	2.1	3.42 (1.81)	3.15 (1.54)	3.94 (2.16)	−2.22	70.57	0.03
CR cognition	0–8	28.9	3.72 (2.54)	4.11 (2.48)	2.15 (2.18)	4.12	99	0.001
Caregiver age	23–93	3.5	64.15 (9.65)	64.67 (10.33)	63.11 (8.15)	1.88	135	0.373
			%
CR Gender (Female)		6.3	68.3	67.9	81.6	2.98	1	0.085
CR Age (65–84 years)		0.0	17.6	17.2	18.4	0.03	1	0.863
CR Race (White)		0.0	85.9	90.3	77.6	4.33	1	0.038
Caregiver gender (Female)		0.0	73.9	76.3	69.4	0.81	1	0.369
Caregiver race (White)		3.5	83.8	91.2	78.7	4.15	1	0.042

Note. CR= care recipient; ALF= Assisted Living Facility; NH= Nursing Home

^{a =}Levene’s test of equality of variances is significant; reported statistics are for equal variances not assumed.

Table 2.

Correlation Matrix (Ns range from 76–142)

	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1. Positive affect	--
2. Negative affect	−.55**	--
3. Depressive symptoms	−.59**	.56**	--
4. Anxiety	−.50**	.60**	.65**	--
5. Communication frequency	.14	.01	−.19*	−.15	--
6. Communication availability	.24*	−.24*	−.21*	−.07	.22**	--
7. Communication helpfulness	.12	−.02	−.13	−.05	.34**	.52**	--
8. CR Age (1 = 65–84; 2=85–90+)	.32**	−.20	−.02	−.01	−.07	.09	.04	--
9. Gender (1= male; 2= female)	−.17	.09	.12	.08	−.06	.04	−.11	−.01	--
10. CR race/ethnicity (1=White; 2= POC)	−.25*	.27*	−.05	−.02	−.04	.02	−.03	−.13	.11	--
11. Type of care setting (0=ALF; 1=NH)	−.07	−.06	.28**	.21*	−.16	−.04	−.15	−.02	.15	.18*	--
12. Orientation to date and names	−.16	−.04	−.16	−.06	.04	.01	.05	−.11	−.17	.06	−.31**	--
13. Caregiver age	−.09	−.03	−.02	.14	−.04	.08	.05	.23**	−.23**	−.13	−.08	.10	--
14. Caregiver gender (1= male; 2= female)	.09	−.17	−.08	−.15	−.12	−.02	−.06	−.06	.02	.06	−.08	−.04	−.17*	--
15. Caregiver race/ethnicity (1=White; 2=POC)	−.33**	.34**	.00	−.04	−.11	−.00	−.07	−.16	.13	.94**	.17*	.06	−.16	.03

Note. CG= caregiver; CR = care recipient; ALF= Assisted Living Facility; NH= Nursing Home; POC= Person of Color.

^*p < .05,

^**p < .01

Perceived Communication and Resident Mental Health

To examine the communication variables on resident mental health, after controlling for relevant covariates, 3-block hierarchical regression analyses were conducted for each of the outcomes (positive affect, negative affect, depressive symptoms, and anxiety). Block 1 included care recipient attributes (e.g., type of care setting, cognitive status), Block 2 included caregiver attributes (e.g., age, gender), and Block 3 included the three communication variables. Predictors were retained for Block 1 and 2 for each outcome only if they demonstrated significant zero-order correlations with the respective outcome (Table 2). Care recipient race/ethnicity was strongly correlated with caregiver race/ethnicity (r=.94, p <.01). Thus, only caregiver race/ethnicity was included in the models.

The standardized coefficients of the predictors from the final block (Block 2 or 3 depending on whether both care recipient and caregiver attributes were retained) of the model for each dependent variable are presented in Table 3. Results show that more optimal communication availability was negatively associated with depressive symptoms (β=−.20, p <.05) and negative affect (β=−.29, p <.05), after controlling for care recipient and caregiver attributes. The R² change for the final block was significant only for the model in which depressive symptoms was the outcome variable (F=2.85, p<.05).

Table 3.

Standardized Coefficients (βs) and Change Statistics from the Final Block in the Hierarchical Regression Models Predicting Psychosocial Outcomes.

	Positive affect	Negative affect	Depressive symptoms	Anxiety
Block 1
CR Age (1 = 65–84; 2=85–90+)	.23*	-	-	-
Type of care setting (1=ALF; 2=NH)	-	-	.26 *	.19*
Block 2
CG race/ethnicity (1=White; 2=POC)	−.26*	.33*	-	-
Block 3
Communication frequency	.10	.02	−.13	−.12
Communication availability	.17	−.29*	−.20*	−.07
Communication helpfulness	−.05	.11	.05	.05
Change statistics
R2 change	.040	.069	.055	.018
F change	1.09	1.986	2.851	.856
df1	3	3	3	3
df2	69	70	135	133
p	.36	.12	.04	.47

Note. CR = care recipient; CG = caregiver; ALF= Assisted Living Facility; NH= Nursing Home; POC= Person of Color

^*p < .05

Differences between ALF and NH Residents

Independent samples t-tests were conducted to examine differences between communication and resident outcomes in ALFs and NHs (see Table 1). Residents of ALFs and NHs did not differ significantly on the communication variables, but NH residents reported significantly higher levels of depressive symptoms and anxiety compared to those residing in ALFs.

To examine whether perceptions of different aspects of communication differentially influenced resident mental health between NH and ALF care settings, regression analyses (Table 4) were run separately for each subgroup. Differences in the magnitude of the unstandardized coefficients across the two groups were then assessed.

Table 4.

Standardized Coefficients (βs) from the Final Block in the Hierarchical Regression Models Predicting Mental Health Outcomes for the Subgroups of Assisted Living Facility Residents and Nursing Home Residents

	Depressive Symptoms			Anxiety
	ACF	NH	Z	ACF	NH	Z
	n = 92	n = 48		n = 91	n = 47
Communication frequency	−.23*	.05	−1.17	−.19	−.05	−0.36
Communication availability	−.25*	−.22	−0.02	−.12	−.03	−0.31
Communication helpfulness	.03	.12	−0.49	.03	.11	−0.44

Note. ALF= Assisted living facility; NH = Nursing home

^*p < .05

Z values of ≥ 1.96 are indicative of a significant difference between the magnitude of the unstandardized coefficients. When the sample is divided into two subsamples of ALF and NH residents, the sample size for the NH group (n=11) was too small to examine difference in predictors of positive affect and negative affect. Communication frequency and communication availability significantly predict depressive symptoms, but only within the ALF subgroup, such that higher frequency and availability of communication was associated with lower depressive symptoms. Inspection of Z values in Table 4 show that there are no significant differences in the magnitude of the unstandardized coefficients between the two groups.

Discussion

Mental health is associated with quality of life, physical health, and functional status in long-term care.^37–42 Depression is particularly pervasive among residents, with prevalence estimates ranging from 25–50%,^{39, 41, 43–45} and is associated with increased morbidity, mortality, suicidality, family burden, and healthcare utilization.^{39, 44, 45} Experiences that are common in long-term care residents (e.g., adapting to a new environment, loss of prior networks, deteriorating health) are risk factors for poor mental health and other adverse outcomes.^{39, 45} Despite offering distinct philosophies of care, it is unclear how mental health varies across care settings, namely NHs and ALFs. When comparing ALF and NH residents generally, some have noted better quality of life and lower depression and anxiety in ALFs,^{21, 46} while others found similar rates of depression across ALF and NHs.^{25, 46}

High quality family-centered care is contingent on successful collaborative efforts between all care team members, including family caregivers, to promote tailored and personalized care provision, which can subsequently improve patients’ health. The benefits of good communication on both family and paid caregiver outcomes are well-established.^{6, 17–21} However, research examining resident outcomes in the context of family-paid caregiver communication has been methodologically limited, but this work does demonstrate that better communication is related to better resident quality of life as rated by family and staff.^{6, 17, 18, 20, 21} Thus, building on prior work, the current study examined how perceived communication dynamics in long-term care settings between family and paid caregivers influence resident mental health.

Results showed that, across care settings, more optimal communication was associated with better resident outcomes. Specifically, greater availability of communication between paid and family caregivers was associated with lower depressive symptoms and negative affect in residents. When examining how these relationships vary across care setting, communication was a stronger predictor of fewer depressive symptoms among residents in ALF settings compared to NH settings, although magnitudes of the coefficients did not significantly differ. Nonetheless, study findings provide insight into the influence of perceived communication dynamics on resident well-being, warranting further investigation on this topic.

The premise of family-centered care recognizes that care provision occurs within the context of dynamic interactions between patients, family, and staff,^{4, 47} even when patients reside outside of the home. Family members are a source of crucial emotional and practical support, and their continued involvement after transitioning to a residential facility can create continuity for residents to their personal history and improve quality of life.⁴⁸ Along with supporting residents’ physical and psychosocial needs, family caregivers are in a unique position to understand, articulate, communicate, and advocate on their care-recipient’s behalf. Thus, open lines of communication between family and paid caregivers is a mechanism that facilitates tailored care plans to maximize residents’ quality of care and mental health.

Consistent, transparent, and open communication among all members of the primary care team (i.e., resident, family caregiver, paid caregiver) is associated with greater satisfaction in residents, family, and staff.^{3, 49} However, a major disconnect between research and practice remains. Despite documented benefits of better interpersonal dynamics in long-term care, family caregivers are often left with pressing needs for information and guidance about their family members’ care and condition, which can exacerbate distress.^{5, 10, 11} Further, the inadequate communication pipelines disadvantage the entire care team, as important information regarding the resident may not reach all caregivers.¹¹ Family caregivers in the long-term care system are generally responsible for initiating and maintaining communication with paid caregivers, but institutional level barriers (e.g., high patient caseload) make it difficult to communicate with staff.^{5, 9} Enhancing communication is a central tenant of person-centered care, emphasizing that effective care requires mutual and collaborative power-sharing relationships, while considering the emotional, social, and health needs of patients. In a report examining ways to better engage family caregivers in care settings, one of the most pressing recommendations was the need for enhanced provider education (e.g., evidence-based training curricula for staff on family-centered care) to ensure high-quality care delivery.⁵⁰ Similarly, long-term care settings could facilitate more streamlined communication, for example by allocating staff to serve as liaisons to communicate with families, having detailed information about the resident’s history in electronic health records to increase paid caregivers’ knowledge, and/or leveraging technology-based forums (e.g., embedding data fields for family caregivers to ask questions in patient portals; hosting regularly scheduled virtual office hours to connect with staff).¹⁰ Optimal communication is contingent on transparent access to information beyond medical status and formal and informal means of communication can bridge the information gap between paid and family caregivers.⁹ However, additional research is needed on the perceived impacts of communication to better elucidate how enhanced communication dynamics can improve mental health outcomes and subsequently, quality of care.

This study should be considered in the context of its limitations. The cross-sectional analyses do not allow for the assessment of causality, and future work should examine communication quality from the perspectives of residents, paid caregivers, and family caregivers longitudinally to explore how perceptions of communication change and influence the care-recipient over time. Additionally, some of the measures used exhibited low reliability (α’s ranging from .62–.96), likely due to some measures comprising only two items. Future work should use more comprehensive and reliable measures. Further, a limited number of NHATS participants resided in long-term care. Nursing home residents were only eligible to participate if they were community-dwelling in the initial sampling rounds and transitioned to residential care in subsequent rounds of data collection. Relatedly, statistics indicate that in the United States there are more residents in NHs than in ALFs (approximately 1.3 million versus 1 million respectively⁵¹). As such, the sample distribution (of which 65% of the participants resided in ALFs) does not reflect the population distribution. Thus, further work is needed on larger, more representative samples of long-term care residents to gain a better understanding of the association between family-paid caregiver communication and resident outcomes. Finally, more in-depth assessments of communication dynamics are needed to better understand the aspects that are essential for the provision of high-quality care.

Overall, this study offers important insights into the influence of family-paid caregiver communication on resident mental health, such that more optimal perceptions of communication was associated with better resident mental health. Results, therefore, highlight the need for consistent, transparent, and supportive two-way communication to share information concerning residents, as well as for enhanced provider education and personalized care plans that engages family members, to maximize quality of care and quality of life in long-term care residents.

Key Points.

• In long-term care settings, greater availability of communication between family and paid caregivers was associated with fewer depressive symptoms residents.

• Family caregivers’ reports of greater availability of communication with paid caregivers were associated with lower negative affect in residents.

• When comparing nursing homes versus assisted living facilities, more optimal communication was associated with fewer depressive symptoms among residents in assisted living facilities.

Why Does This Matter?

The associations between more optimal communication between family and paid caregivers and better resident mental health in long-term care settings highlight the need for consistent, transparent, and supportive two-way communication between family and paid caregivers to improve quality of care and quality of life in long-term care residents.