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JSLHR
Research Article
The Impact of Communication Impairments
on the Social Relationships of Older Adults:
Pathways to Psychological Well-Being
Andrew D. Palmer,
a
Paula C. Carder,
b
Diana L. White,
b
Gabrielle Saunders,
c
Hyeyoung Woo,
d
Donna J. Graville,
a
and Jason T. Newsom
e
Purpose: Social contact is known to be vital for older adults’
mental and physical health but, because communication
impairments often co-occur with other types of disability, it
is difficult to generalize about the relative impact of a
communication impairment on the social relationships of
older adults. Specific aims of the study were to examine
whether the severity of a communication impairment was
associated with a range of social measures and to examine the
association between these characteristics and psychological
well-being.
Method: Community-dwelling older adults ranging in age
from 65 to 94 were recruited for the study of Communication,
Health, Aging, Relationship Types and Support. The sample
included 240 participants with communication disorders arising
from a variety of etiologies including hearing impairment, voice
disorders, head and neck cancer, and neurologic disease,
as well as older adults without a communication disorder.
Results: Communication impairment was a significant
independent predictor for key characteristics of social
relationships, including the number of friends in the social
network, two types of social support, the frequency of
social participation, and social self-efficacy. Communication
impairment was also a significant predictor for higher levels
of loneliness and depression. In addition, two distinct
pathways between communication impairment and
psychological well-being were identified, with social self-
efficacy and reassurance of worth as mediators.
Conclusions: Even after controlling for age, gender, health,
and disability, communication impairment is a significant
independent predictor for key aspects of the social function
of older adults and demonstrates two distinct pathways to
loneliness and depression.
Supplemental Material: https://doi.org/10.23641/
asha.7250282
Communication forms the foundation of social
interaction (Heine & Browning, 2002). In older
adults, communication is central to the process
of successfully adjusting and adapting to the aging process,
being essential for living independently, pursuing personal
goals and interests, performing social roles and functions,
maintaining personal and familial relationships, making de-
cisions, and exercising control over quality of life and care
(Lubinski & Welland, 1997). Studies of communication in
normal aging have shown that the conversational skills of
normally aging older adults tend to remain well preserved,
even though the semantic content and syntactic structure of
language use change over the life course (Shadden, 1997).
With increasing age, however, there is an increase in the prev-
alence of conditions that may interfere with communication
(Yorkston, Bourgeois, & Baylor, 2010). Hearing impairment
is the most prevalent type of communication disorder na-
tionally and is the third most common chronic condition
of older adults (Wallhagen, 2002). The prevalence of hear-
ing impairment increases steadily with increasing age from
45% of those in their 60s to 89% of those aged 80 or more,
according to one estimate (Lin, Niparko, & Ferrucci, 2010).
The prevalence of other types of communication disorders
is less well known. Based on one large-scale survey of Medi-
care beneficiaries, it was estimated that 55% of all Medicare
beneficiaries (more than 16 million adults) had a communi-
cation impairment of some kind (Hoffman et al., 2005).
There is a significant body of evidence that the quan-
tity and quality of an individual’s social relationships are
a
NW Center for Voice & Swallowing, Department of Otolaryngology-
Head & Neck Surgery, Oregon Health & Science University, Portland
b
Institute on Aging, College of Urban and Public Affairs, Portland
State University, OR
c
National Center for Rehabilitative Auditory Research, Portland VA
Medical Center, OR
d
Department of Sociology, Portland State University, OR
e
Department of Psychology, Portland State University, OR
Correspondence to Andrew D. Palmer: palmeran@ohsu.edu
Editor-in-Chief: Julie Liss
Editor: J. Scott Yaruss
Received December 31, 2017
Revision received May 13, 2018
Accepted June 14, 2018
https://doi.org/10.1044/2018_JSLHR-S-17-0495
Disclosure: The authors have declared that no competing interests existed at the time
of publication.
Journal of Speech, Language, and Hearing Research •1–21 •Copyright © 2019 American Speech-Language-Hearing Association 1
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associated with better physical and mental health across
the life course (Holt-Lunstad, Smith, & Layton, 2010;
House, Landis, & Umberson, 1988). In studies of older
adults, psychological outcomes are associated not just
with the size of an individual’s social network but also with
its composition. The term social network refers to the web
of social relationships that surround an individual, as well
as the characteristics of those ties, and typically includes
relationships with friends, family members, neighbors, work
associates, or other important individuals in that person’s
life (Berkman & Glass, 2000). Studies of normal aging have
shown that changes in social relationships occur across the
life course. Stereotypical views had long depicted old age as
a time of social isolation and loss, but more recent research
indicates that this is not typical. According to “socioemotional
selectivity theory,”older adults typically choose to maintain
social relationships that are most rewarding and gradually
abandon those that are less so (Carstensen, Isaacowitz, &
Charles, 1999). As a result, the total number of social rela-
tions decreases with age, but the number of close social
relationships does not and social support remains stable un-
til very old age. The importance of the social network for
the psychological well-being of older adults is demonstrated
by the fact that individuals with restricted social networks
have the highest levels of depressive symptoms, particularly
if the network contains a paucity of friends (Fiori, Antonucci,
& Cortina, 2006).
To date, a number of different theoretical perspectives
have been used to account for the differences in the social
relationships of older adults, and there are several ways of
measuring and describing these relationships (van Tilburg
& Thomese, 2010). Based on their review of the literature,
Berkman, Glass, Brissette, and Seeman (2000) provide a
useful framework for organizing many of the relevant con-
cepts (see Figure 1). According to this framework, social
networks are embedded within the sociopolitical and cultural
context. Social networks are the structures that provide the
interpersonal connections through which a number of dif-
ferent “psychosocial mechanisms”known to be important
for health flow. These psychosocial mechanisms include the
provision of social support, social engagement, and attach-
ment, as well as access to resources and material goods.
These psychosocial mechanisms, in turn, affect the more
proximal “psychological pathways”to health, such as
loneliness and depression. Social networks are shaped by
multiple factors over the life course, including age, gen-
der, marital status, education, income, occupation, and per-
sonality (Allan, 1989; Burns & Farina, 1984; W. J. Dickens
& Perlman, 1981; Mugford & Kendig, 1987). Some authors
have argued that older adults may be able to compensate
for aging-related losses by actively managing their social
relationships in order to meet their emotional and physical
needs (M. M. Baltes & Carstensen, 1996; P. B. Baltes, 1997;
Carstensen et al., 1999; Lang & Carstensen, 1994). As a re-
sult, the effect of social relationships on well-being may
be mediated by individual-level variables such as control,
which means that some individuals may successfully man-
age their social network to retain access to social support
(Antonucci, 2001). This has been described as the “support
efficacy model”in which it has been hypothesized that
self-efficacy may help to explain the association between
social relationships and well-being (Antonucci & Jackson,
1987). As conceptualized by Bandura (1977), self-efficacy
is the conviction that one can successfully execute a specific
behavior in order to produce a desirable result. Since self-
efficacy perceptions are domain-specific, an individual can
have a high sense of self-efficacy for one type of activity
but a low sense of self-efficacy for another (Smith &
West, 2006). This is one characteristic of self-efficacy that
differentiates it from other personality traits, such as self-
confidence, self-esteem, and locus of control (Bandura,
1997; van der Bijl & Shortridge-Baggett, 2001). Conse-
quently, although general self-efficacy may also be impor-
tant, there is evidence to suggest that the ability to manage
social relationships and negotiate support needs may be
more strongly predicted by a domain-specific measure, such
as social self-efficacy (Bisconti & Bergeman, 1999). Social
self-efficacy has been defined as a belief in one’s ability to
deal effectively with others (Sherer et al., 1982). Although
it has not been studied widely, this characteristic has
been shown to be a significant predictor of mental health
in older adults. Fiori, McIlvane, Brown, and Antonucci
(2006) found social self-efficacy to be a partial mediator
of the relationship between social relationships and depres-
sive symptoms in a sample of older adults. Their study
suggests that older adults who are able to negotiate their
social support needs are less likely to become depressed as a
result. It is not known, however, whether older adults with
communication impairments are able to compensate for
their deficits and maintain their social network to access
social support in the same fashion, and the role of social
self-efficacy, in particular, has not been investigated.
Characteristics of the social network and the functions
that it performs can be measured in a number of ways.
In general, most authors distinguish between the terms
Figure 1. A conceptual framework for the impact of social networks
on health. Adapted with permission from Elsevier Science and
Technology Journals, “From Social Integration to Health: Durkheim
in the New Millennium,”L. F. Berkman, T. Glass, I. Brissette, & T. E.
Seeman, Social Science & Medicine, 51, Copyright © 2000;
permission conveyed through Copyright Clearance Center, Inc.
2Journal of Speech, Language, and Hearing Research •1–21
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loneliness and social isolation. Loneliness is generally
considered to be a subjective perception of inadequacy in
the nature of one’s social relationships, regardless of the
number or nature of one’s social contacts. In contrast, so-
cial isolation is a more objective measure that relates to
shortcomings in the size or quality of an individual’s social
network (de Jong Gierveld & Havens, 2004). Evidence sug-
gests that only a minority of community-dwelling older adults
is “severely”lonely or isolated, with typical estimates in
the region of 10% (Hawthorne, 2008; Victor, Scambler,
Bond, & Bowling, 2000). Risk factors for loneliness and iso-
lation include the loss of a partner, having no (surviving)
children, living alone, deteriorating health, and significant
negative life events. The risk of each of these characteris-
tics occurring increases over time, and consequently, lone-
liness and social isolation increase with advancing age
(Dugan & Kivett, 1994).
There are a number of ways that other aspects of an
individual’s social relationships can be defined and mea-
sured. Social support has been shown to buffer stress, pro-
mote better psychological well-being, and reduce the risk
of disability, morbidity, and mortality (Berkman & Glass,
2000; S. Cohen, 2004; Uchino, Cacioppo, & Kiecolt-Glaser,
1996). Social support is also associated with the risk of
hospitalization and institutionalization (Tobin & Kulys, 1981).
There are many definitions of social support and no one
model is universally accepted, but the term typically refers
to the different functions that social relationships may per-
form (Uchino, 2006). One of the most commonly cited is
Robert Weiss’s (1974) model of “social provisions”which
encompasses other widely used conceptualizations of social
support (Cutrona & Russell, 1987). According to Weiss, six
different social functions or provisions may be derived from
interactions with others. All six of these provisions are nec-
essary for an individual to feel adequately supported. Dif-
ferent provisions may be more or less important at different
points in the life-course and any individual may provide
more than one type of provision. As defined by Weiss, the
six social provisions are as follows: a) attachment (or “emo-
tional support”), which derives from a sense of empathy,
concern, and affection in meaningful personal relationships;
b) social integration (or “belonging support”), which derives
from membership in a group of individuals with similar
interests and concerns; c) reassurance of worth (or “esteem
support”), which refers to the sense that an individual’s
competence, skill, and value are recognized by others; d) re-
liable alliance (or “tangible support”), which refers to the
sense that others can be counted on to provide assistance in
a time of need; e) guidance (or “informational support”),
which refers to the provision of useful advice or information
by others; and f ) opportunity for nurturance (or “active sup-
port”), which refers to the sense that there are other people
who depend on the individual for their well-being. There is
some evidence that communication impairments may have
a deleterious impact on social support. Hearing impair-
ment has been shown to be associated with a significantly
increased need for social support from both formal and
informal supports in older community-dwelling adults
(Schneider et al., 2010). It has also been reported that the
presence of a hearing impairment is associated with de-
creased satisfaction with social support, suggesting that
older adults with hearing impairments may be less likely
to have their support needs met (Pachana, Smith, Watson,
McLaughlin, & Dobson, 2008).
To date, changes in social networks in individuals
with communication impairments have not been exten-
sively investigated (Lind et al., 2003). A number of studies
of individuals with conditions that occur in midlife to late
in life have shown the negative impact of these condi-
tions on an individual’s social network, such as in the case
of older adults with a hearing impairment and also in
those with aphasia (Davidson, Howe, Worrall, Hickson,
& Togher, 2008; Hilari & Northcott, 2006; Northcott,
Marshall, & Hilari, 2016; Weinstein & Ventry, 1982). These
findings suggest that the changes in the social networks of
older adults with communication impairments may be very
different from those observed in normal aging. In general,
studies of community-dwelling older adults have found
relatively weak associations between communication mea-
sures and social characteristics such as social network size
(Hickson, Worrall, Barnett, & Yiu, 1995; Lind et al., 2003).
For individuals with communication disorders, however, social
networks may diminish due to abandonment of former
friends (Parr, 2007) or due to avoidance of social situations and
activities in which trouble communicating may be experi-
enced, leading to social isolation (Hétu, Jones, & Getty, 1993).
In addition to the body of work related to the posi-
tive impact of social support and social networks on phys-
ical and mental health, there has been a growing interest
in negative social interactions. These types of interactions
include a variety of behaviors, such as lack of support
when needed, unwanted advice, intrusive behavior, criti-
cism, rejection, and neglect. Negative social interactions
have been found to have an adverse impact on physical
and mental health (Krause & Jay, 1991; Rook, 1998) and,
in some cases, may outweigh the benefits of positive inter-
actions (Newsom, Nishishiba, Morgan, & Rook, 2003; Okun,
Melichor, & Hill, 1990). There is good reason to suppose
that communication impairments may cause an increase in
negative social interactions. In progressive conditions, the
impact of worsening communication has been found to be
associated with a steady decline in the quality of intimate
relationships (Baikie, 2002; Carter et al., 1998). Similarly,
studies of couples in which one partner has a hearing im-
pairment have demonstrated poorer marital communica-
tion (Anderson & Noble, 2005; Heine, Erber, Osborn, &
Browning, 2002; Hétu et al., 1993; Preminger & Meeks,
2010; Scarinci, Worrall, & Hickson, 2008). Furthermore,
the use of hearing aids has been shown to benefit not just
individuals with hearing loss themselves but also their part-
ners and family members, resulting in greater social par-
ticipation, more interpersonal warmth, fewer communication
difficulties, decreased negative emotions, better emotional
stability, and decreased caregiver burden and distress
(Boi et al., 2012; Kochkin & Rogin, 2000; Tolson, Swan, &
Knussen, 2002).
Palmer et al.: Comm Impairments & Social Relationships of OAs 3
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Another area of research relates to the importance of
social participation. The World Health Organization (2002)
has targeted the enhancement of social participation by
older adults as part of its policy framework in addressing
concerns about population aging. With regard to the impact
of communication impairments on social participation, the
findings from previous research have been mixed. In one
study of community-dwelling older adults, communication-
related measures were not predictive of social participation
(Cruice, Worrall, & Hickson, 2005). This lack of an associa-
tion is in contrast to the findings from studies of individuals
with speech and hearing impairments, where associations
between communication impairment and participation
have been reported (Baylor, Yorkston, Bamer, Britton, &
Amtmann, 2010; Mulrow et al., 1990; Resnick, Fries, &
Verbrugge, 1997).
It is difficult to make general statements about the so-
cial impact of a communication impairment in older adults
based on the existing evidence. Communication impairments
often co-occur with other health problems and functional lim-
itations, including increased age, poorer health, and higher
levels of functional disability (Hoffman et al., 2005; Yorkston
et al., 2010). Consequently, it is hard to isolate the relative
contribution of the communication impairment itself from
co-occurring limitations (Bringfelt, Hartelius, & Runmarker,
2006; Kauhanen et al., 2000). In addition, most investigators
tend to study a single type of communication disorder in
isolation, and it is unclear whether the findings from one
population can be generalized to individuals with other types
of communication disorders. Some recent research has shown
that individuals with communication disorders of varying
etiologies may experience similar obstacles to social partici-
pation (Baylor, Burns, Eadie, Britton, & Yorkston, 2011;
Miller, Baylor, Birch, & Yorkston, 2017), suggesting that it
may be possible to look at more diverse samples than has
traditionally been attempted. In a previous investigation,
data from a nationally representative sample of older adults
were analyzed to determine whether there was an association
between communication impairment and a wide array
of social characteristics (Palmer, Newsom, & Rook, 2016).
Communication impairment was found to be significantly
associated with several aspects of social relationships even
after controlling for health, disability, and demographic
characteristics. Specifically, communication impairment
was a significant predictor of loneliness, fewer positive
social exchanges, smaller network size, and fewer social ac-
tivities. These findings must be interpreted with caution,
however. The prevalence of communication impairments
in the sample was relatively low, and the presence of a
communication impairment was based on combining the
scores from a number of communication-related survey
items rather than from a validated measure. Consequently,
these findings need to be confirmed and explored in
greater detail using a validated communication measure.
The framework described by Berkman et al. (2000)
was used to guide the investigation. In order to better
understand the potential impact of a communication impair-
ment, we sought to investigate whether there was evidence
for changes at the level of the structural components of
the social network itself, the “psychosocial mechanisms”of
social support, negative interactions, social participation,
and social self-efficacy and whether there was also an im-
pact on the “psychological pathways”of loneliness and
depression. Specifically, the current study was undertaken
to investigate the following questions:
1. Are communication impairments associated with the
social function of community-dwelling older adults,
even after controlling for health and demographic
factors? If so, are all aspects of social functioning
affected equally, or are some aspects of social rela-
tionships affected disproportionately?
2. Are communication impairments associated with
the psychological well-being of community-dwelling
older adults, even after controlling for health and
demographic factors?
3. Finally, if the model proposed by Berkman et al. (2000)
is correct, what social characteristics mediate the
relationship between communication impairments
and psychological well-being?
Method
Study Design
The goal of the current study was to provide detailed
information about the health, communication status, and
social relationships of a diverse sample of community-
dwelling older adults. Individuals with communication dis-
orders of various etiologies were recruited for the study. In
addition, healthy older adults and those with a range of
other medical and health problems were also included. As
discussed above, one of the limitations of previous research
studies of community-dwelling older adults is that healthier
individuals tend to be overrepresented, and the resultant
low incidence of communication disorders limits the sta-
tistical power of these studies to identify an effect. In con-
trast, in studies of patient populations, individuals with
communication disorders have poorer health and more
functional limitations, which makes it difficult to isolate
role of communication from the impact of health and dis-
ability. The goal of the current study was to recruit a sample
of individuals who varied widely in their functional and
physical abilities and also had a range of communication
abilities, from those with negligible or very mild alterations
in communication function to those with more severe defi-
cits. The diagnoses associated with communication impair-
ments were deliberately chosen to include those that might
result in no physical limitations at all (e.g., hearing impair-
ment and voice disorders) as well as those that may result in
a variety of physical alterations, such as amyotrophic lateral
sclerosis, multiple sclerosis, Parkinson’s disease (PD), and
stroke. In addition, it was anticipated that many of the
participants would have other health conditions common
to older adults (e.g., heart conditions, arthritis, diabetes)
that could result in functional limitations. By gathering
4Journal of Speech, Language, and Hearing Research •1–21
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informationonasamplewithmuch greater diversity, it
was hoped that the analysis would be better able to
determine whether communication impairments have
an independent effect on psychosocial outcomes and to
control for the relative impact of health and functional
impairments.
Although the term communication disorder is typically
used in the literature, the term communication impairment
was used for this study. As discussed above, changes in
communication occur in association with normal aging.
These tend to be less severe and less disruptive than those
associated with pathological conditions and therefore may
not be considered “disordered”per se but might still have
an impact on social relationships. The purpose of the cur-
rent study was to examine the impact of self-perceived
communication changes, regardless of etiology, type, or
categorization (i.e., normal/typical or pathological) on so-
cial relationships. Consequently, the term communication
impairment has been used throughout this investigation to
refer to a self-reported communication deficit, which may
or may not have been previously evaluated, whereas com-
munication disorder hasbeenusedtoindicateacondition
that has been diagnosed by a speech-language pathologist
or audiologist.
Sample Size and Power
The study was powered to address the primary objec-
tive, namely whether a communication impairment is an
independent predictor of psychosocial outcomes in a multi-
ple regression analysis. To achieve a power of 80% with a
significance level of .05, sample size was calculated for a
small, medium, and large effect size as defined by J. Cohen
(1988) with a single predictor and 10 covariates. Covari-
ates were assumed to account for 15% of the variance in
the model. In a previous investigation (Palmer et al., 2016),
communication impairment had an unstandardized beta
ranging from .04 to .13 with regard to seven psychosocial
outcomes of interest, suggesting an effect size ranging from
small to medium. The cumulative R
2
for the model as a
whole ranged from .05 to .21. It was estimated that a sam-
ple of approximately 100 participants would be sufficient
to address the primary research question.
Participants
The Communication, Health, Aging, Relationship
Types and Support study protocol was approved by both
Portland State University’s Human Subjects Research
Review Committee (PSU HSRRC 143059) and Oregon
Health and Science University’s Institutional Review Board
(OHSU IRB 10500). Potential participants were identi-
fied using a search of OHSU’s electronic medical record.
Two hundred older adults with communication disorders
resulting from a variety of etiologies were identified by this
means, including (a) benign voice disorders, (b) neurologic
disease, (c) head and neck cancer, and (d) hearing impair-
ment. A total of 200 individuals were targeted by this means,
50 in each group. Diagnosis codes from Centers for Disease
Control and Prevention’s clinical modification of the ninth
revision of the World Health Organization’s International
Classification of Diseases coding system (ICD-9) were being
used at this time. A complete list of the ICD-9 codes used
to identify participants is included in Supplemental Table S1.
The inclusion criteria for these participants were as follows:
being a native English speaker, living independently in the
community, being aged 65 or more, not having any con-
ditions known to cause significant cognitive impairment
and having adequate cognition for participation, being
currently cancer free or having completed cancer treatment
at least a year previously, having been evaluated by a
speech-language pathologist or audiologist at OHSU in
the previous year, and being diagnosed with a communi-
cation disorder originating in adulthood. The names of the
individuals identified from the electronic medical record
were assigned a random number, reordered numerically,
and then reviewed sequentially until a total of 50 eligible
individuals had been identified from each of the four cate-
gories. A total of 347 charts were reviewed in order to
identify 200 individuals who met eligibility criteria. In ad-
dition, 100 older adults without any of the above diagnoses
were also contacted for participation. The inclusion cri-
teria for these individuals were the same as those listed
above with the exception of the last two, that is, they had
not been evaluated by a speech-language pathologist or
audiologist in the previous year and had no history of a
communication disorder documented in the medical record.
These individuals had also been seen by physicians at
OHSU during the same period and were similarly assigned
a random number, reordered numerically, and reviewed
sequentially until a total of 100 patients meeting eligibility
criteria were identified. A total of 235 charts were reviewed
before 100 eligible participants were found. All 300 eligible
individuals identified by this means received the study
mailing, which consisted of a cover letter, an information
sheet, and a copy of the study survey.
In addition to the study mailing, participants were also
recruited through a variety of means to increase the likelihood
of obtaining an adequate response from a diverse sample.
This included recruiting additional individuals with the same
types of conditions listed above as well as older adults gen-
erally. Participants were recruited through ResearchMatch
(an online service that allows researchers to identify volun-
teers across the country that meet particular study criteria),
messages posted on listservs for American Speech-Language-
Hearing Association’s online forums and Special Interest
Groups, online support group forums for individuals with a
variety of medical conditions, and general online message
boards for older adults, and information about the study was
also posted on OHSU’s Research Opportunities web page.
Participants were allowed to complete the survey either over
the Internet or by mail.
By the response deadline, 145 of the 300 mailed sur-
veys had been returned, representing a response rate of
48%, and an additional 128 individuals had completed the
online survey. To ensure adequate cognition for the study,
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all participants completed three screening questions from
the Washington Group on Disability Statistics’(2011)
Extended Question Set on Functioning (Supplemental
Appendix S1, Section 1): “Q7. Do you have difficulty re-
membering or concentrating?”;“Q8.Howoftendoyou
have difficulty remembering?”;and“Q9. Do you have
difficulty remembering a few things, a lot of things, or al-
most everything?”Responses from individuals who reported
problems remembering “all of the time”(Q8), “a lot of
things”(Q9), or “almost everything”(Q9) were excluded.
Of the 273 responses, 33 were excluded for the following
reasons: self-reported age under 65 (n= 5), living outside
North America (n= 1), not living independently in the
community (n= 1), having trouble remembering almost
everything and /or all of the time (n= 5), having had a child-
hood communication disorder (n= 14), history of traumatic
brain injury (n= 5), being currently treated for cancer or
having been treated for cancer in the last year (n= 5), and
the survey being largely incomplete (n= 3). These catego-
ries were not mutually exclusive, and six individuals were
excluded for more than one reason. Data from the remain-
ing 240 individuals were used for the analysis.
Measures
Sociodemographic variables included standard assess-
ments of age, gender, marital status, education, and annual
household income, as used in previous national surveys
of older adults (Sorkin & Rook, 2004; Waite et al., 2007).
Self-rated health was measured using the commonly used
single item: “How would you describe your health at the
present time? Would you say it is excellent, very good, good,
fair or poor?”(0 = poor,4=excellent; Ware & Sherbourne,
1992). The number of comorbid health conditions was
assessed by asking participants, “Have you ever been told
by a doctor or other health professional that you have…”
any of the 12 common conditions (Manton, Stallard, &
Corder, 1998).
1
Functional limitations were measured with
15 questions that included activities of daily living (e.g., bath-
ing; Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963), instru-
mental activities of daily living (e.g., preparing own meals;
Lawton & Brody, 1969), upper extremity strength (e.g.,
grasping objects; Nagi, 1976), and mobility (e.g., climbing
stairs; Rosow & Breslau, 1966).
2
These measures have been
used in other previous national surveys of older adults such
as the National Long-Term Care Survey (Manton et al.,
1998), Later Life Survey of Social Exchanges (Sorkin &
Rook, 2004), and the National Social Life, Health, and Ag-
ing Project (Waite et al., 2007). One instrumental activity
of daily living item (telephone use) was excluded from the cal-
culation, as this relates to communication (Palmer et al.,
2016).
To date, there is no generally accepted scale for mea-
suring communication effectiveness across the spectrum
of speech and hearing disorders. After a review of available
published instruments, the Communicative Effectiveness
Index–Modified (CETI-M) was chosen (Supplemental Ap-
pendix S1, Section 1; Yorkston, Beukelman, Strand, &
Bell, 1999). The CETI-M is a 10-item scale that focuses on
social communication. The measure has been shown to
show strong associations between self-rated and partner-rated
assessments as well as between self-rated and objective mea-
sures of intelligibility (Ball, Beukelman, & Pattee, 2004)
and has been used in studies of individuals with amyotrophic
lateral sclerosis, PD, and other speech impairments (Halpern
et al., 2012; Joubert, Bornman, & Alant, 2011). Although it
has not been used in other populations, content validity for
this measure is supported by the fact that it has a number
of items similar to those in other widely used communica-
tion measures, including the Communicative Effectiveness
Survey (Donovan, Kendall, Young, & Rosenbek, 2008),
Hearing Handicap Inventory for the Elderly Screening Ver-
sion (Ventry & Weinstein, 1982), and Voice Handicap Index
Functional subscale (Jacobson et al., 1997). The CETI-M
asks respondents to rate the effectiveness of their communi-
cation in a variety of social situations using a 7-point scale
(1 = notatalleffective,7=very effective). As discussed above,
we elected to study older adults with a wide range of con-
ditions and disorders, and in the absence of a validated
screening tool that could be effectively used to divide the
sample into those with a communication disorder versus
those without, we elected to consider communication-
related changes as existing on a continuum with varying
degrees of severity, from those associated with typical
aging that might be relatively mild to those that were more
severe as a result of a pathological condition. Communica-
tion impairment, therefore, was operationally defined as an
individual’s perception of their degree of difficulty in
communicating across a range of social situations as rep-
resented by their mean score on the CETI-M, and this
score was used as a continuous variable throughout the
analysis.
A variety of published measures were used in the
study that have been previously validated for use with
older adults to assess social network size and composi-
tion, social support, social participation, and the frequency
of negative social interactions (see Table 1). Social self-
efficacy was assessed using the Social Self-Efficacy sub-
scale (Sherer et al., 1982), which consists of six items relating
to efficacy expectations at making friends and in social
situations (e.g., “I do not handle myself well in social
gatherings.”). During validation of this measure, scores
on the subscale were shown to be associated with (but
also substantially different from) other measures of per-
sonality, including locus of control, personal control,
social desirability, ego strength, interpersonal competence,
and self-esteem, which provided evidence of construct
validity. The six statements are rated on a 5-point scale
(0 = strongly disagree,4=strongly agree) and then summed
to provide a total score. The survey items for the Social
Self-Efficacy subscale and the other social measures used
in the study are available in Supplemental Appendix S1,
Section 2.
1
For a complete list, see Table 3.
2
For a complete list, see Table 5.
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Two measures were used to assess different aspects
of psychological well-being. Loneliness was assessed with
six items from the UCLA Loneliness Scale (UCLA-LS;
Russell, 1996), relating to feelings of isolation, companion-
ship, being known or understood, belonging to a group of
friends, and the meaningfulness of one’s relationships. Each
item was rated on a 5-point scale (0 = never,4=often),
and the six items are summed to obtain a total score. The
UCLA-LS is the most commonly used self-report loneliness
instrument for both clinicians and researchers and has
been widely used with older adults (A. P. Dickens, Richards,
Greaves, & Campbell, 2011; Luanaigh & Lawlor, 2008)
and in individuals with hearing impairments (Philp, Lowles,
Armstrong, & Whitehead, 2002; Poissant, Beaudoin, Huang,
Brodsky, & Lee, 2008). Of the many instruments which
have been used to identify depressive symptoms in adults,
the most widely used is the Center for Epidemiologic Studies
Depression Scale (CES-D; Radloff, 1977). A revised 9-item
version of the CES-D has been shown to be an efficient
method of screening for depression with good internal con-
sistency (Santor & Coyne, 1997) and suitable for use with
older adults (Wancata, Alexandrowicz, Marquart, Weiss, &
Friedrich, 2006). It has also been used to assess depression
in older adults with hearing impairments (Gopinath et al.,
2009; Kramer, Kapteyn, Kuik, & Deeg, 2002) and following
a stroke (Parikh, Eden, Price, & Robinson, 1989; Shinar
et al., 1986). The nine items relate to feelings of depression,
happiness, enjoyment, sadness, disrupted sleep, and trouble
concentrating during the preceding week and are rated on
a4-pointscale(0=rarely, 3=most or all of the time). The
scores from the nine items are then summed to provide a
total score. The survey items for both of the psychological
measures used in the study are available in Supplemental
Appendix S1, Section 3.
Data Analysis
Descriptive data were summarized for all of the
study variables, including mean, standard deviation, and
minimum and maximum values. Reliability analyses were
performed for each of the study measures, and internal
reliability was analyzed using Cronbach’s alpha. Standard
regression diagnostics were performed. Initial analyses
included bivariate correlations among all variables to inves-
tigate the first-order relationships. Research questions
were investigated using simultaneous ordinary least squares
Table 1. Published study instruments relating to social and psychological outcomes.
Instrument name (reference) Description Scoring, scaling, and interpretation
Social measures
Lubben Social Network
Scale–Revised
(Lubben et al., 2002)
An instrument designed to gauge social isolation
in older adults. The revised scale consists of
12 items relating to the size, closeness, and
frequency of contacts of a respondent’s social
network in 2 domains: Family (6 items) and
Friends (6 items). A total score from all 12 items
is also calculated.
Scores range from 0 to 30 on the Friends and
Family subscales and from 0 to 60 overall,
with higher scores indicating a bigger social
network.
Negative Interaction
Scale (Krause, 1995)
A 4-item scale that measures the frequency of
negative interactions, including demanding
behavior, criticism, intrusion, and taking
advantage.
Scores range from 0 to 12, with higher scores
indicating more frequent negative interactions.
Social Participation
Instrument (Bassuk
et al., 1999)
A 10-item scale that measures the frequency
of participation in 10 different types of leisure
and social activities over the course of the
previous month.
Social Participation–Number: A score ranging
from 0 to 10 was calculated by summing the
number of activities engaged in at least once
in the previous month. Social Participation–
Frequency: A mean score ranging from 0
to 5 (0 = never or almost never,5=daily)
was created by averaging all 10 items, with
higher scores indicating more frequent social
participation.
Social Provisions Scale
(Cutrona & Russell, 1987)
A 24-item scale of perceived social support with
regard to 6 separate social provisions, namely
Guidance, Reassurance of Worth, Social
Integration, Attachment, Nurturance, and
Reliable Alliance.
A combined score for each of the six subscales
(from 4 to 16) is calculated as well as a total
score (from 24 to 96), with higher scores
indicating higher levels of support.
Social Self-Efficacy
subscale (Sherer
et al., 1982).
A 6-item scale that measures an individual’s
belief in his or her ability to deal effectively
with other people.
Scores range from 0 to 24, with higher scores
indicating higher social self-efficacy.
Psychological measures
Center for Epidemiologic
Studies Depression Scale
(Santor & Coyne, 1997)
A 9-item version of the scale used to assess
psychological distress and depressive
symptomatology in adults.
Items are scored on a 4-point scale and summed
to produce a composite score from 0 to 27,
with higher scores indicating greater distress.
UCLA Loneliness Scale
(Russell, 1996)
A 6-item version of the scale used to measure
the frequency of feelings of loneliness and
social isolation.
Scores range from 6 to 24, with higher scores
indicating higher levels of loneliness.
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multiple regression. Analyses were performed using SPSS,
Version 21 (SPSS Inc., 2012).
Tests for mediation were conducted using the macro
for multiple mediation developed by Preacher and Hayes
(2008). Mediation is hypothesized as a causal chain in which
one variable affects a second variable, which, in turn,
affects the outcome of interest. This intervening variable
(the mediator) helps to account for the relationship between
the independent variable and the dependent variable. When
there is no direct effect between the independent and
dependent variables after controlling for the mediator, full
mediation is supported (see Figure 2). When the independent
variable has a direct effect on the dependent variable in
addition to the indirect effect, partial mediation is sup-
ported (see Figure 3). For a more detailed review of this
topic, the reader is referred to Baron and Kenny (1986).
Results
Participant Characteristics
The demographic and health data for all 240 study
participants are summarized in Table 2. The average age
of the study participants was 73 years (SD = 6.25) and
ranged from 65 to 94. Exactly half of the sample was male.
The majority of participants were retired (79%), had re-
ceived a college education (59%), and were married or had
a long-term partner (69%). The modal category for house-
hold income was between $25,000 and $50,000 annually
(32%). The sample was predominantly White (96%) and
non-Hispanic (99%). Slightly more than half of the sample
reported health that was “very good”or “excellent”(57%).
On average, participants reported that they had been diag-
nosed with 2.55 health conditions (SD = 1.72) from a list
of 12 health problems common in older adults. The total
number of health conditions from this list was used as a co-
variate in the regression analysis. As shown in Table 3, the
conditions most commonly reported were high blood pres-
sure/hypertension (52%), arthritis/rheumatism (45%), and
some type of cancer (41%). In addition to these conditions,
study participants were asked to identify any other medi-
cal conditions that they had been diagnosed with. This
question was used to provide additional descriptive infor-
mation about the study participants but was not used to
calculate the total number of comorbid health conditions.
As shown in Table 4, the other conditions most commonly
reported were hearing impairment (35%), head and neck
cancer (28%), prostate problems (22%), and PD (11%).
With regard to a list of 14 daily activities, on average study
participants reported having some kind of difficulty with
3.22 of those activities (SD =3.62,range0–14). The average
level of difficulty across all activities was 0.38 (SD = 0.52,
range 0–2.57) on a scale from 0 to 3 (0 = not difficult at all,
3=very difficult). As shown in Table 5, the participants
most commonly reported difficulty in climbing stairs
(51%); the ability to bend, kneel, or stoop (51%); and do-
ing work around the house/yard (39%). The average com-
munication score on the CETI-M was 50.94 (SD = 15.39),
and scores ranged from the minimum score (10) to the
maximum score (70). It appeared, therefore, that the study
recruitment strategy was successful in ensuring that the
respondents had a wide variety of communication abili-
ties.AsshowninTable6,respondents reported greatest
difficulty when having a conversation in a noisy envi-
ronment, communicating at a distance, or when speak-
ing in a group.
Association Between Communication
and Other Variables
Descriptive data for all of the social and psychologi-
cal measures of interest were summarized (see Table 7).
Values of Cronbach’s alpha ranged from .66 to .95 across
the study measures. Cronbach’s alpha is a measure of in-
ternal consistency, which gauges the degree to which a set
of items are interrelated. A high alpha coefficient value is
supportive evidence that the scale in question represents a
single underlying construct. Generally, values of Cronbach’s
alpha that are considered acceptable for research pur-
poses range from .70 to .90 (DeVellis, 2003; Nunnally &
Bernstein, 1994). Reliability estimates for Social Participa-
tion Instrument (Bassuk, Glass, & Berkman, 1999), the
Social Self-Efficacy subscale (Sherer et al., 1982), and the
Attachment subscale of the Social Provisions Scale (Cutrona
& Russell, 1987) fell slightly below the optimal value of .70
(DeVellis, 2003) but were considered adequate for the anal-
ysis. Communication scores were significantly correlated
with all of the other scales, with the exception of the Negative
Interaction Scale (Krause, 1995; see Table 8). The primary
communication measure (the CETI-M) is a previously vali-
dated measure for adults with communication disorders of
various kinds but has not been used in as heterogeneous a
population as in the current study. Evidence of criterion
validity of the CETI-M was provided by the fact that com-
munication scores were significantly associated with other
communication items on the survey. Communication scores
on the CETI-M were significantly worse in those who used
ahearingaid(M= 48.38, SD = 13.55) than those who did
not (M= 54.19, SD = 14.82), t(231) = 2.78, p= .006. Poorer
communication scores on the CETI-M were also associated
with increased difficulty in hearing (r=−.26, p< .001), in-
creased difficulty in communicating with others (r=−.57,
Figure 2. Full mediation.
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p< .001), and increased difficulty in using the telephone (r=
−.62, p< .001). Examination of the subset of the partici-
pants who had been seen at OHSU (n= 129) revealed that
scores on the CETI-M were significantly worse in those who
had a previously documented communication disorder
(M= 51.29, SD = 14.78) than those who did not (M=60.69,
SD = 9.34), t(127) = 3.66, p< .001.
Is Communication an Independent Predictor
of Characteristics of Social Relationships?
A series of multiple regressions was performed to ex-
amine the relationship between communication impairment,
social characteristics, and indices of psychological well-
being. In each model, communication was entered as the
primary predictor in addition to the following eight
covariates: age, gender, partnership status, education,
annual household income, self-rated health, number of
health conditions, and functional limitations. Communi-
cation effectiveness was a significant predictor for six of
the 14 aspects of social relationships examined, as shown in
Table 9.
For the Lubben Social Network Scale–Revised
(LSNS-R; Lubben, Gironda, & Lee, 2002), communica-
tion effectiveness was the only significant predictor for the
Friends subscale and predicted approximately 17% of the
variance, R
2
= .17, F(9, 165) = 3.84, p< .001. Poorer com-
munication was associated with significantly fewer friends
in the social network.
On the Social Participation Instrument (Cutrona &
Russell, 1987), the number of social activities participated
in during the previous month was significantly predicted
by communication effectiveness, the presence of a life
partner, and functional limitations. Individuals with better
communication abilities, fewer functional limitations, and
those with a life partner participated in a significantly
greater number of social activities. This model predicted
approximately 21% of the variance in the number of
Table 2. Demographic and health characteristics of participants.
Characteristic Category n(%)
Gender Male 118 (50.0)
Female 118 (50.0)
Partnership status Married/partnered 162 (69.2)
Single, widowed, separated, or divorced 72 (30.8)
Education High school or less 25 (10.7)
Associate/trade/vocational/some college 71 (30.3)
Four-year college degree or more 138 (59.0)
Annual household income Less than $25,000 27 (14.2)
Between $25,000 and $50,000 60 (31.6)
Between $50,000 and $75,000 33 (17.4)
Between $75,000 and $100,000 31 (16.3)
More than $100,000 39 (20.5)
Race White 210 (96.8)
Black/African American 2 (0.9)
Asian 1 (0.5)
Mixed race/Other 4 (1.8)
Ethnicity Non-Hispanic 225 (99.1)
Hispanic/Latino 2 (0.9)
Self-rated health Excellent 30 (12.6)
Very good 105 (43.9)
Good 73 (30.5)
Fair 29 (12.1)
Poor 2 (0.8)
Health conditions None 21 (8.8)
1–3 154 (64.4)
4–6 59 (24.7)
7–9 5 (2.1)
Functional limitations None 63 (28.6)
1–5 105 (47.7)
6–10 33 (15.0)
11–14 19 (8.6)
Note. Percentages are based on the number of responses for each item, excluding nonrespondents.
Figure 3. Partial mediation.
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social activities, R
2
= .21, F(9, 157) = 4.71, p< .001. Com-
munication effectiveness was also a significant independent
predictor for the frequency of social participation during
the previous month, together with female gender and the
presence of a life partner. These findings indicated that
women, those with a life partner, and those with better
communication abilities participated in social activities
significantly more often. This model predicted approximately
23% of the variance in the frequency of social participation,
R
2
= .23, F(9, 168) = 5.70, p< .001.
Communication effectiveness was a significant inde-
pendent predictor of two aspects of social support on the
Social Provisions Scale (SPS; Cutrona & Russell, 1987).
Functional limitations and communication effectiveness
were significant predictors for reassurance of worth or
“esteem support.”Poorer communication and more func-
tional limitations were associated with reduced reassurance
of worth. This model predicted approximately 21% of the
variance in reassurance of worth, R
2
=.21,F(9, 166) = 5.00,
p< .001. Communication effectiveness was the only variable
that was a significant predictor for social integration or
“belonging support,”indicating that poorer communication
was associated with significantly poorer feelings of social in-
tegration. This model predicted approximately 19% of the
variance in social integration, R
2
=.19,F(9, 166) = 4.27,
p< .001.
Finally, communication effectiveness was the only
variable that was a significant predictor for social self-
efficacy, indicating that poorer communication was
associated with significantly lower levels of social self-
efficacy. This model predicted approximately 15% of the
variance in social self-efficacy, R
2
= .15, F(9, 168) = 3.15,
p= .002.
Communication effectiveness was not a significant
predictor for the family social network, and no variable was
a significant predictor of the total social network (i.e., friends
and family networks combined) on the LSNS-R. Com-
munication effectiveness was not a significant predictor for
negative interactions on the Negative Interaction Scale
(Cutrona & Russell, 1987) for any of the other four subdo-
mains of social support (i.e., guidance, attachment, nurtur-
ance, reliable alliance) nor for total social support on the
SPS. The results for these regressions are available in Sup-
plemental Table S2.
Is Communication an Independent Predictor
of Psychological Well-Being?
Two regressions were performed relating to psycho-
logical function. In the first regression, loneliness was
the outcome of interest using the UCLA-LS. Only com-
munication effectiveness was a significant predictor, indi-
cating that poorer communication was associated with
higher levels of loneliness. This model predicted approxi-
mately 19% of the variance in loneliness, R
2
= .19, F(9, 168) =
4.41, p< .001. In the second regression, depression was
the outcome of interest using the CES-D. Four variables
were significant predictors for depression, namely age,
education, functional limitations, and communication
effectiveness. Being younger and having higher levels of
education, more functional limitations, and poorer com-
munication ability were significantly associated with
higher levels of depressive symptoms. This model predicted
approximately 20% of the variance in depression, R
2
=.20,
F(9, 162) = 9.90, p< .001.
Table 4. Other health conditions and procedures reported by at
least 1% of study participants.
Condition n(%)
Hearing impairment/hearing loss 84 (35.00)
Head and neck cancer 68 (28.33)
Prostate problems/surgery 53 (22.08)
a
Parkinson’s disease 27 (11.25)
Other neurologic disease
b
19 (7.92)
Cardiac or vascular issues/surgery 19 (7.92)
Gastrointestinal conditions
c
15 (6.25)
Reduced mobility and/or surgery of
lower limb (hip, knee, ankle, or foot)
12 (5.00)
Vision problems
d
10 (4.17)
Spasmodic dysphonia 7 (2.92)
Allergies/sinus problems 7 (2.92)
Osteoporosis 6 (2.50)
Chronic obstructive pulmonary disease 5 (2.08)
Laryngeal surgery 5 (2.08)
Thyroid problems 5 (2.08)
Cochlear implant 4 (1.67)
Depression 3 (1.25)
Miscellaneous injuries 3 (1.25)
Note. Categories are not mutually exclusive.
a
Percentage of whole sample. Problem present in 53/118 = 44%
of men.
b
Included ataxia, muscular dystrophy, myasthenia gravis,
multiple sclerosis, and primary lateral sclerosis.
c
Included Barrett’s
esophagus, dysphagia, gastroesophageal reflux disease, irritable
bowel syndrome, pancreatitis, and Sjogren’s syndrome.
d
Included
cataract, glaucoma, and macular degeneration.
Table 3. Health conditions reported by study participants in order
of frequency.
Condition n(%)
High blood pressure/hypertension 125 (52.30)
Arthritis/rheumatism 106 (45.11)
Any cancer 96 (40.85)
Kidney/bladder problems 41 (17.30)
Asthma 35 (14.83)
Diabetes 31 (13.14)
Heart attack/heart failure 27 (11.39)
Emphysema/chronic bronchitis 25 (10.59)
Stomach/intestinal ulcers 18 (7.63)
Stroke (or disability due to stroke) 16 (6.78)
Hip fracture 9 (3.81)
Liver disease 5 (2.13)
Note. Percentages are based on the number of responses for each
item, excluding nonrespondents.
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Do Social Variables Mediate the
Relationship Between Communication
and Psychological Well-Being?
Mediation is hypothesized as a causal chain in which
one variable affects a second variable, which, in turn,
affects the outcome of interest. When the hypothesis of
mediation by multiple potential mediators is entertained,
multiple mediation is an appropriate analytic strategy
for analyzing the relative contribution of each mediator
(Preacher & Hayes, 2008). By including several mediators
in a single model, researchers can determine the relative
magnitudes of the specific indirect effects associated with
all of the mediators. In other words, including several
mediators in the same model is one way to test a variety of
different theories about the relationship between the key
variables. Six different social characteristics were investi-
gated as potential mediators of psychological well-being,
based on the findings from the previous multiple regres-
sions, namely the Friends subscale of the social network
measure (the LSNS-R), the Reassurance of Worth and
Social Integration subscales of the social support measure
(the SPS), both measures of social participation (i.e., the
frequency of social participation and the number of social
activities engaged in) on the Social Participation Instrument,
and the Social Self-Efficacy Scale. First, each of these vari-
ables was entered as a potential mediator into a model with
communication as the independent variable and loneliness
as the outcome variable. The model also controlled for the
same eight covariates used previously. After testing each of
the social variables individually, all of those found to be
mediators were then entered into a model in which all of
the mediational variables were tested simultaneously (Shrout
& Bolger, 2002). After this process had been completed
with loneliness as the dependent variable, the same process
was then repeated for depression.
Results suggested that social self-efficacy partially
mediated the relationship between communication effec-
tiveness and loneliness. The indirect pathway for social
self-efficacy was the only one that remained statistically sig-
nificant (B=−0.016, SE = 0.008, 95% CI [−0.033, −0.003]).
Communication effectiveness was significantly associated
with loneliness after controlling for the mediators (B=−0.036,
SE =0.018,p= .049), consistent with partial mediation. The
indirect effect was tested using a bootstrap estimation ap-
proach, which indicated that the indirect coefficient was
Table 6. Communication scores on the Communicative Effectiveness Index–Modified (CETI-M) for all participants ordered from most to least
effective.
Item MSDRange
Having a conversation with familiar persons in a quiet environment 6.29 1.26 1–7
Having a conversation with strangers in a quiet environment 5.86 1.48 1–7
Having a conversation with a familiar person over the phone 5.79 1.70 1–7
Having a conversation with young children 5.55 1.72 1–7
Having a conversation while traveling in a car 5.34 1.70 1–7
Having a long conversation with someone (over an hour) 5.32 1.98 1–7
Having a conversation with a stranger over the phone 5.27 1.86 1–7
Speaking or having a conversation before a group 4.87 2.02 1–7
Having a conversation with someone at a distance 4.39 1.99 1–7
Having a conversation with someone in a noisy environment 4.02 1.89 1–7
CETI-M total score 50.94 15.39 10–70
Table 5. Functional limitations for all participants ordered from most to least difficult.
Activity Any difficulty (%) MSDRange
Climb 2 or 3 flights of stairs? 51.1 0.92 1.07 0–3
Bend, kneel, or stoop? 50.6 0.75 0.91 0–3
Do work around the house such as cleaning, laundry, yardwork, or shoveling snow? 38.6 0.65 0.95 0–3
Walk a quarter of a mile—about 3 city blocks? 34.7 0.69 1.06 0–3
Lift or carry something as heavy as 15 pounds (e.g., a full bag of groceries)? 30.5 0.53 0.91 0–3
Get in and out of bed or a chair? 25.8 0.36 0.69 0–3
Use the telephone? 25.7 0.47 0.91 0–3
Grasp or handle small objects (e.g., a door handle or coins)? 20.7 0.30 0.66 0–3
Travel independently by car or public transportation (e.g., by bus, train, or subway)? 17.0 0.29 0.74 0–3
Shop for food or household goods? 14.5 0.20 0.55 0–3
Prepare your own meals? 12.9 0.20 0.59 0–3
Bathe or dress yourself? 11.9 0.19 0.59 0–3
Manage your finances? 9.4 0.13 0.45 0–3
Take your medications or care for your health at home? 8.1 0.12 0.46 0–3
Feed yourself? 4.3 0.06 0.28 0–3
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significant (B=−0.042, SE =−0.079, 95% CI [−0.079,
−0.011]). Approximately 57% of the variance in loneli-
ness was accounted for by the predictors, R
2
= .571,
F(15, 147) = 13.032, p< .001. This model is illustrated
in Figure 4.
The same process was then repeated with depression
as the outcome of interest. When each of the possible
mediators was tested individually in a model containing
the eight covariates, the results supported full mediation
between communication effectiveness and depression for
three of the six variables examined, namely the Friends
subscale of the LSNS-R, the Reassurance of Worth sub-
scale of the SPS, and Social Self-Efficacy. Bootstrapping
results confirmed a significant indirect effect for all three
of these variables, and they were subsequently entered into a
model with communication effectiveness as the independent
variable, depression as the dependent variable, and the same
eight covariates. Results were consistent with full mediation.
Bootstrapping results indicated a significant indirect effect
for the model as a whole (B=−0.045, SE = 0.016, 95%
CI [−0.084, −0.017]). Reassurance of worth was a significant
mediator (B=−0.013, SE = 0.008, 95% CI [−0.039, −0.002]),
as well as social self-efficacy (B=−0.021, SE = 0.012, 95%
CI [−0.050, −0.002]). Communication effectiveness was no
longer a significant predictor of depression when the indirect
effect was accounted for supporting full mediation, as illus-
trated in Figure 5. Approximately 34% of the variance in
depression was accounted for by the predictors, R
2
= .342,
F(12, 159) = 6.881, p< .001.
Discussion
The findings from the current study support an asso-
ciation between communication impairments and several
important aspects of social relationships. Communication
impairment was associated with a significant reduction in
Table 8. Correlation among study measures.
Variable 2 3 4 5 6 7 8
1. Communicative Effectiveness (CETI-M) .285** .338** .029 .365** .366** −.389** −.258**
2. Social Network–Total (LSNS-R) .701** −.138* .543** .391** −.507** −.318**
3. Social Support–Total (SPS) −.290** .510** .432** −.679** −.488**
4. Negative Interactions Scale (NIS) −.014 −.169* .375** .344**
5. Social Participation–Frequency (SPI) .360** −.388** −.282**
6. Social Self-Efficacy −.533** −.385**
7. Loneliness (UCLA-LS) .605**
8. Depression (CES-D)
Note. CETI-M = Communicative Effectiveness Index–Modified; LSNS-R = Lubben Social Network Scale–Revised; SPS = Social Provisions
Scale; NIS = Negative Interaction Scale; SPI = Social Participation Instrument; UCLA-LS = UCLA Loneliness Scale; CES-D = Center for
Epidemiologic Studies Depression Scale.
*p< .05. **p< .01.
Table 7. Descriptive statistics for social and psychological measures.
Variable MSDRange
Social Network (LSNS-R)–Family subscale 18.07 5.94 0–30
Social Network (LSNS-R)–Friends subscale 16.13 5.66 0–27.60
Social Network (LSNS-R)–Total Score 34.23 9.79 0–57
Social Support (SPS)–Guidance subscale 13.98 2.06 5–16
Social Support (SPS)–Worth subscale 13.82 1.96 7–16
Social Support (SPS)–Social Integration subscale 13.50 2.19 6–16
Social Support (SPS)–Attachment subscale 13.42 2.32 4–16
Social Support (SPS)–Nurturance subscale 12.53 2.74 5–16
Social Support (SPS)–Alliance subscale 14.39 2.05 5–16
Social Support (SPS)–Total Score 81.69 10.31 43–96
Social Participation (SPI)–No. of Activities 7.54 1.99 1–10
Social Participation (SPI)–Frequency of Participation 1.93 0.73 0.2–4.40
Negative Interaction Scale 2.24 1.83 0–10
Social Self-Efficacy 14.56 3.66 2–24
Loneliness (UCLA-LS) 11.48 3.43 6–23
Depression (CES-D) 5.10 4.99 0–23
Note. LSNS-R = Lubben Social Network Scale–Revised; SPS = Social Provisions Scale; SPI = Social Participation Instrument; UCLA-LS =
UCLA Loneliness Scale; CES-D = Center for Epidemiologic Studies Depression Scale.
12 Journal of Speech, Language, and Hearing Research •1–21
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Table 9. Multiple regressions for social and psychological variables.
Predictor
Dependent variables
Social
Network–Friends
Social
Participation–
Number of
Activities
Social
Participation–
Frequency of
Participation
Social Support–
Reassurance
of Worth
Social Support–
Social Integration
Social
Self-Efficacy Loneliness Depression
BSEB βBSEBβBSEBβBSEB βBSEBβBSEB βBSEB βBSEB β
Age 0.069 0.069 .074 0.005 0.026 .015 0.006 0.009 .050 0.012 0.023 .038 0.052 0.028 .137 0.068 0.045 .114 −0.059 0.044 −.097 −0.115 0.056 −.150*
Gender 1.427 0.894 .124 0.450 0.320 .108 0.275 0.109 .188* 0.135 0.286 .036 0.168 0.345 .037 0.561 0.571 .077 −0.215 0.568 −.029 −0.320 0.714 −.034
Life partner −0.622 0.999 −.051 0.843 0.359 .191* 0.261 0.122 .168* −0.196 0.322 −.049 0.023 0.388 .005 0.598 0.640 .078 −0.720 0.637 −.091 −0.008 0.799 −.001
Annual income 0.203 0.378 .048 0.033 0.137 .021 0.014 0.046 .027 0.186 0.120 .135 0.170 0.145 .104 −0.303 0.239 −.115 0.029 0.239 .011 −0.130 0.299 −.038
Education −0.330 0.706 −.039 0.231 0.253 .074 0.012 0.086 .011 0.003 0.225 .001 −0.080 0.271 −.024 −0.235 0.448 −.043 0.501 0.446 .090 1.368 0.560 .196*
Self-rated health 0.593 0.631 .090 0.007 0.228 .003 0.033 0.077 .040 0.113 0.204 .052 0.467 0.246 .182 −0.123 0.407 −.029 0.083 0.401 .019 −0.235 0.509 −.043
Health conditions −0.292 0.271 −.089 −0.061 0.098 −.051 −0.046 0.033 −.111 0.060 0.087 .055 −0.011 0.105 −.009 −0.167 0.173 −.081 0.306 0.172 .144 0.265 0.217 .100
Functional
limitations
−0.660 1.020 −.062 −0.873 0.378 −.219* −0.235 0.123 −.173 −1.004 0.326 −.287** −0.578 0.393 −.139 −0.236 0.647 −.035 0.612 0.643 .089 2.228 0.808 .255**
Communication
effectiveness
1.079 0.332 .275** 0.264 0.121 .187* 0.115 0.040 .230** 0.245 0.106 .188* 0.258 0.129 .167* 0.929 0.209 .371*** −0.946 0.208 −.374*** −0.639 0.261 −.199*
R
2
.173 .212 .234 .213 .188 .145 .191 .196
*p< .05. **p< .01. ***p< .001.
Palmer et al.: Comm Impairments & Social Relationships of OAs 13
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the number of relationships with friends, a reduction in
certain aspects of social support, reduced social participa-
tion, and a decline in social self-efficacy. Communication
impairment was also a significant independent predictor of
greater loneliness and depression. Mediation analyses were
also used to investigate the relationship between communi-
cation and psychological well-being. Findings supported
two distinct pathways for loneliness and depression. Com-
munication was a significant predictor of loneliness after
controlling for social self-efficacy, consistent with partial
mediation. For depression, however, communication was
no longer a significant predictor after controlling for social
self-efficacy and reassurance of worth, consistent with full
mediation. Taken together, social self-efficacy and reassur-
ance of worth appear to be important in explaining the
connection between communication and psychological well-
being. To place the study findings in the context of the
framework outlined by Berkman and colleagues, it appears
that older adults with communication impairments differ
from their peers in a number of significant ways. Although
the family component of the social network may remain
stable, there is a disproportionate loss of friends, a reduction
in social integration and feelings of self-worth, a decline in
social participation, and, perhaps most importantly, a
reduction in the individual’s perception of their ability to
maintain current social relationships or to develop new
ones. Taken together, these changes have profound impli-
cations for mental health and well-being.
It had been anticipated that communication impair-
ment would be a significant predictor of overall social
network size, but this was not the case. Instead, the study
findings appeared to show that communication impair-
ment disproportionately affected relationships with friends.
The loss of friends was not a desired change in most cases,
however, as indicated by the reduction in the sense of so-
cial integration. These findings are consistent with previous
research into the impact of aphasia following a stroke,
which have demonstrated that older adults with aphasia
have smaller social networks with fewer friends (Davidson
et al., 2008; Hilari & Northcott, 2006). Previous research
on older adults with other kinds of disability has also
demonstrated that the presence of a disability is associ-
ated with an increase in the number of kin in the social net-
work and a smaller number of friends (Mugford & Kendig,
1987). Lind et al. (2003) similarly found that older adults
with both vision and hearing loss had a comparable number
of contacts with family members but a decrease in contact
with neighbors, friends, and acquaintances. Such findings are
not consistent with the changes in social networks described
by socioemotional selectivity theory, as demonstrated by
the fact that individuals with smaller social networks had
higher levels of loneliness and depression, suggesting that
smaller social networks were associated with lower levels of
satisfaction. It appears, therefore, that socioemotional se-
lectivity theory may describe the social changes associated
with normal aging but does not account for the changes in
social relationships of some older adults, such as those
with a disability. These findings reinforce the importance
of companionship for positive mental health. Previous re-
search has shown that family and friends frequently serve very
different functions in the lives of older people (Crohan &
Antonucci, 1989). In particular, friends seem to be par-
ticularly important for feelings of emotional well-being
and self-esteem (Johnson & Catalano, 1983; Lee, 1979;
Rook, 1987; Wood & Robertson, 1978), whereas family are
more important for providing practical and material as-
sistance that may be critical for delaying or preventing in-
stitutionalization (Tobin & Kulys, 1981).
Communication impairment was associated with a
reduction in the frequency of social participation as well as
a reduction in the number of social activities that the individ-
ual participated in on a regular basis. Despite the difficul-
ties that they experienced as a result of their communication
impairments, most participants continued to enjoy the
company of others and were active in a wide range of social
situations. In addition to family activities, they continued to
socialize with friends, volunteer, attend religious worship,
take classes, and attend group activities. The reduction in
social participation, therefore, appeared not to be the result
of lack of interest in social contact. The association between
communication impairment and social participation was
consistent with findings from our previous investigation
(Palmer et al., 2016) and, taken together, provide compelling
Figure 4. Illustration of the final model for loneliness with social
self-efficacy, partially mediating the relationship between communication
effectiveness and loneliness, controlling for demographic, health,
and disability characteristics.
Figure 5. Illustration of the final model for depression with reassurance
of worth and social self-efficacy, fully mediating the relationship
between communication effectiveness and depression, controlling
for demographic, health, and disability characteristics.
14 Journal of Speech, Language, and Hearing Research •1–21
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evidence that social participation is negatively affected by
communication impairment.
It had been hypothesized that communication im-
pairment would be an independent predictor of negative
social exchanges, but this was not the case. Communica-
tion impairments have been shown to have negative im-
pacts on personal relationships including declines in marital
intimacy and satisfaction as well as increases in frustration,
interpersonal strain, anger, resentment, and blame (Baikie,
2002; Carter et al., 1998; Hétu et al., 1993; Joubert et al.,
2011). It has been shown that older adults are more sus-
ceptible to the physiological impact of stress and will
work harder to avoid or prevent conflict in their interper-
sonal relationships (Charles, 2011). Older adults are known
to seek to insulate themselves from relationships that are un-
rewarding or problematic, as a result. In our previous in-
vestigation, there was no significant association between
communication impairments and negative interactions
(Palmer et al., 2016), and this finding was supported in the
current study. It has been shown that older adults who
experience negative social exchanges may be able to limit
their exposure to these types of interactions through social
withdrawal (Morgan, 1989). Hypothetically, then, the
avoidance of negative interactions might be one of the fac-
tors responsible for the reduction in aspects of the social net-
work and also reduced social participation. It is possible
that, in order to protect themselves from upsetting social in-
teractions, older adults with communication impairments
may place themselves at greater risk of social isolation.
Previous cross-sectional studies have found strong
associations between social support, communication impair-
ment, and well-being, suggesting a strong interconnection
between them (Blood et al., 1994; Frankel & Turner, 1983;
Oppegard et al., 1984). In the current investigation, com-
munication impairment was associated with lower levels
of two particular functions of social support, namely social
integration and reassurance of worth. The first of these,
social integration, relates to a sense of belonging, which is
derived from membership in a group of individuals with sim-
ilar interests, concerns, and/or recreational activity and is
most often provided by friends. The reduction in this type of
support is consistent with the fact that there was a significant
reduction in the contribution of friends to the overall social
network, as discussed above. The second aspect of social
support, reassurance of worth, has not been highlighted
in this type of analysis previously. The items on this sub-
scale asked respondents to agree or disagree with statements
about being regarded as competent and respected or admired
for their talents or abilities. Previous research has shown
that individuals with communication impairments feel less
confident in their own abilities and may also be treated as less
competent by others (Babbitt & Cherney, 2010; Marsiske,
Klumb, & Baltes, 1997). These findings are also consistent
with the qualitative study by Baylor et al. (2011) in which
participants described having to use alternate methods of
communication, adapt their method of communication,
rely on others to communicate for them, and ask for ac-
commodations from their communication partners. When
these strategies or accommodations were not effective, indi-
viduals tended to withdraw from a variety of social situa-
tions as well as life roles and positions of responsibility,
including those related to work, group membership, and
community involvement. As a result, Baylor’sparticipants
described feelings of isolation and marginalization, “like
a bystander,”“out of the loop,”and “ignored”and as
though they had lost their “sense of self ”(pp. 275–276).
These observations would be consistent with the findings
from the current study.
The significant relationship between communication
impairment and social self-efficacy is also a novel finding.
As conceptualized by Bandura (1977), self-efficacy is the
conviction that one can successfully execute the behavior
required to produce a desirable result. Models of successful
aging have highlighted the extent to which older adults
may adapt to changing circumstances in order to maintain
quality of life, such as by actively managing their social re-
lationships (M. M. Baltes & Carstensen, 1996; P. B. Baltes,
1997; Carstensen et al., 1999; Lang & Carstensen, 1994).
A key finding from the current investigation was that, of
the variables we examined, communication was the only
significant predictor of social self-efficacy. Kramer et al.
(2002) found that people with hearing impairments reported
more depressive symptoms, lower feelings of self-efficacy
and mastery, more loneliness, and a smaller social network
than their normally hearing peers. Ormel et al. (1997) found
that the presence of a hearing impairment was associated
with higher levels of physical and role disability and with
lower levels of mastery, self-efficacy, and social support.
In explaining this relationship, the authors suggested that
hearing impairments not only limit participation in various
kinds of activities but also lead to declines in the sense of
control, competence, and self-confidence, which, in turn,
cause increased distress, anxiety, and depression. Similar
findings have been reported by other researchers (Babbitt
& Cherney, 2010; Marsiske et al., 1997) and, coupled with
our findings, suggest that this is a process experienced
by older adults with a wide variety of communication
impairments.
Study Limitations
The study sample was predominantly White and
non-Hispanic and was less diverse than estimates for the
U.S. population, which limits the generalizability of the
findings. The study examined older adults with communi-
cation impairments due to a variety of voice, speech,
and hearing disorders but, because of the self-reported
nature of the study, deliberately excluded individuals with
cognitive and language disorders. As a result, the study
findings may not be representative of the experiences of
these groups. In addition, the study design deliberately
oversampled individuals with various communication dis-
orders in order to increase the statistical power of the anal-
ysis. Consequently, the data cannot be considered typical
of older adults generally and cannot be used to provide
estimates of incidence or prevalence. Comparisons of the
Palmer et al.: Comm Impairments & Social Relationships of OAs 15
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study data with other previously published studies, however,
demonstrate remarkable similarities (Anyanwu, Sharkey,
Jackson, & Sahyoun, 2011; Cutrona, 1986; Krause, 1995;
Wells, 2009). Furthermore, most individuals were recruited
through a medical center, support group, or organization
that provides information and access to resources. There-
fore, it is possible that the current study underestimates the
impact of communication impairments by underrepresent-
ing those who have not received appropriate care and
treatment for these problems. As the study was cross-sec-
tional, it is not possible to examine the extent to which
changes in social relationships are affected longitudinally
by factors occurring over the life course nor the ways
that communication impairments may vary in their im-
pact based on age of onset or duration. The fact that the
current study is cross-sectional also implies that causal re-
lationships between health, communication, social rela-
tionships, and well-being can only be inferred from the
study findings, as a longitudinal study would be needed
for such an analysis. In a recent longitudinal study of
individuals following a stroke, however, Northcott et al.
(2016) reported that aphasia was an independent risk
factor for a loss of friends from the social network, which
is consistent with the current study’s findings. In addition,
improvements in psychological well-being have been dem-
onstrated after a wide range of interventions for commu-
nication disorders (Baylor, Yorkston, Eadie, & Maronian,
2007; Boi et al., 2012; Hawkins, 2005; Heydebrand, Mauze,
Tye-Murray, Binzer, & Skinner, 2005; Liu et al., 1998;
Mulrow et al., 1990; Murry, Cannito, & Woodson, 1994),
which lend support to the hypothesis that the relationships
reported in the current study may be causal in nature.
Clinical Implications and Future Directions
Based on the study findings, a number of recommen-
dations can be made with regard to future research as
well as clinical practice. First, it appears feasible to con-
duct studies of older adults with a wide variety of com-
munication impairments, including those related to voice,
speech, and hearing disorders. Although most instruments
published to date are disorder specific, there has recently
been an interest in the development of participation-
based instruments that can be used across a variety of
disorders, such as the Communicative Participation Item
Bank (Baylor et al., 2013; Miller et al., 2017).
Second, the study supports the hypothesis that find-
ings from previous research regarding the impact of a
hearing impairment on the perceived competence and self-
confidence of older adults can be generalized to older
adults with communication impairments more generally.
Although improvements in psychological well-being have
been demonstrated after a wide range of interventions
for communication impairments, it is unclear whether as-
pects of social relationships are similarly responsive. Im-
proved communication alone does not automatically result
in improved participation in communicative situations
(Simmons-Mackie, 2000). Social and life participation
approaches to rehabilitation have been advocated for indi-
viduals with a wide variety of conditions, including
aphasia, hearing impairment, and traumatic brain injury
(Carson & Pichora-Fuller, 1997; Chapey et al., 2000;
Worrall & Hickson, 2003; Ylvisaker, Turkstra, & Coelho,
2005). The current study findings provide additional
justification for these approaches. Similarly, it has been
recommended that any interventional program for loneli-
ness and depression in older adults should target social
self-efficacy through cognitive restructuring or social skills
training (Cohen-Mansfield & Parpura-Gill, 2007), and the
current study provides justification for targeting social self-
efficacy directly in speech and hearing rehabilitation.
Third, the current study provides guidance for re-
searchers who are interested in investigating social outcomes.
It may have been assumed that all aspects of social rela-
tionships were affected by a communication disorder, but
the results from this study demonstrate that some aspects of
social relationships are affected more than others. This reali-
zation may help to explain why the findings from previous
studies may have been inconclusive. For future investiga-
tors, focusing on the aspects of social relationships highlighted
in this analysis may be more revealing.
Finally, the potential clinical implications of this re-
search are far-reaching. Given the wealth of evidence
documenting the importance of human relationships for
physical and mental health, the fact that communication
impairments are independently associated with poorer so-
cial relationships provides an important justification for
speech and hearing services. Based on the current study, it
is now possible to argue that these interventions are essential
for the long-term health and well-being of older adults.
Conclusion
The findings from this study support an association
between communication impairment and several important
aspects of social relationships in older adults. Even after
controlling for demographic characteristics, health, and
disability, communication impairment was a significant
independent predictor for fewer friends in the social net-
work, a reduction in certain components of social support,
and reduced social participation. Communication impairment
did not significantly predict overall levels of social support
but was significantly associated with lower levels of social
integration (network support) and reassurance of worth
(esteem support). Communication impairment also signifi-
cantly predicted higher levels of loneliness and depression
and reduced social self-efficacy. Evidence was found for
two distinct pathways between communication impairment
and psychological well-being. The impact of communica-
tion on loneliness was partially mediated through social
self-efficacy. The impact of communication on depression
was fully mediated through social self-efficacy and reas-
surance of worth. Taken together, these two characteris-
tics, namely social self-efficacy and reassurance of worth,
appear to be important in explaining the connection between
communication and psychological well-being.
16 Journal of Speech, Language, and Hearing Research •1–21
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Acknowledgments
The first author would like to acknowledge the support of
Paul Flint, Donna Graville, and the Department of Otolaryn-
gology at Oregon Health and Science University for providing
assistance and support during the completion of this work for his
doctoral dissertation, as well as all of the clinicians at the North-
west Center for Voice & Swallowing. The authors also thank
Margaret Neal, David Kinsella, and the faculty of the Urban
Studies Department, the Institute on Aging, and other depart-
ments at Portland State University that facilitated this research;
Jason Newsom, Dara Sorkin, and Karen Rook for allowing the
use of data from the Later Life Study of Social Exchanges for
preliminary work in this area; Katherine Yorkston and Carolyn
Baylor at the University of Washington for sharing their work
and ideas; staff at the National Association for the Deaf, National
Multiple Sclerosis Society, the National Spasmodic Dysphonia
Association, and Pat Wertz Sanders at WebWhispers, among
others, for publicizing the study; and, most importantly, all of
the study participants.
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