Social Skill Abilities and Demographic Correlates of Older Volunteers

Abstract

Older age is associated with reduced social networks while social skill abilities are important assets for older people to cope with these situations. To better understand older people’s social skill ability and important demographic correlates, the present cross-sectional survey research interviewed 1000 Taiwanese older volunteers from 73 community care centers. Findings of a mixed model indicated that education and serving area outweighed other demographic factors significantly correlated with older volunteers’ social skill ability. Latent class analyses further identified different latent ability groups for different education (high vs. low) or serving-area (urban vs. suburban) older volunteers. Specifically, low-education or suburban volunteers were correlated with disadvantageous social skill profiles. Notably, the suburban eclectic ability group exhibited a skill pattern signifying the risk of loneliness. Overall, the findings called for further investigation into the relationship between older people’s socioeconomic factors (e.g., education and serving area) and their social skill ability.

Keywords

latent class analysis older volunteering social skills socioeconomic status

What this paper adds

• The present study advanced current knowledge of older people’s social skill ability by exploring older volunteers’ social skill ability and their demographic correlates.

• Older volunteers’ social skill ability was found to substantially correlate with their socioeconomic demographic characteristics (e.g., education and serving area) rather than sociocultural factors (e.g., gender).

• Older volunteers featuring lower socioeconomic characteristics (e.g., lower education or suburban areas) tended to exhibit less advantageous social skill profiles or a skill pattern signifying potential loneliness risks.

Applications of study findings

• Older volunteers’ education and serving areas may serve as referent indicators for volunteer agencies to screen for older volunteers with potential social skills or loneliness risk issues.

• Older volunteers’ social skills were found to vary by their serving areas (urban/suburban), the training of older volunteers thus should be tailored according to the regional differences.

• The finding of this study calls for interventions targeting older adults with less advantageous socioeconomic characteristics to improve their social skill-relevant needs (e.g., interpersonal difficulties and loneliness).

Introduction

Aging has become a global issue due to the rapid growth of the aged population. Older age (particularly aged 65 or older) was associated with a gradual loss of social networks/significant others, decreased reciprocity in social relationships induced by poorer health conditions/frailty, and reduced social activities after retirement (Cohen-Mansfield & Parpura-Gill, 2007; Comi et al., 2022; Wrzus et al., 2013). Ineffective adaption to these situations might lead to social isolation or loneliness. Social skills are people’s assets to connect with others. Research has shown that better social skills are correlated with more satisfactory social interactions and people’s psychological well-being, such as better quality of life, life satisfaction, self-efficacy, hope, and happiness (Segrin & Taylor, 2007; Salavera & Usán, 2021). The social skills deficit vulnerability model (Segrin & Flora, 2000) posited social skills to be a protective factor for loneliness and that lower social skills increase people’s vulnerability to stress, resulting in their propensity to develop psychosocial problems (e.g., depression and loneliness). This has highlighted the importance of people’s social skill abilities in promoting psychosocial well-being and preventing negative psychosocial problems in old age.

Generally, social skills can be defined as a wide array of abilities allowing people to interact or communicate with others (Soto-Icaza et al., 2015). Riggio (1986) proposed a fine-grained definition of people’s social skill ability, which defined social skill ability to involve three types of abilities: the ability to decode (sensitivity), encode (expressivity), and regulate/control communication operating in non-verbal and social domains. This resulted in the following combinations of social skill ability: emotional sensitivity, emotional expressivity, social sensitivity, social expressivity, emotional control, social control, and social manipulation (Riggio, 1986). According to Riggio & Zimmerman (1991), expressive skills are particularly important in initiating social interaction as well as forming acquaintanceships. Sensitivity skills are critical for developing relationship bonds. Riggio & Zimmerman (1991) also highlighted the importance of “empathy” in maintaining ongoing relationships. Specifically, cognitive (perspective-taking) empathy involves skills in social sensitivity, social expressivity, and social control while emotional empathy involves emotional sensitivity and expressivity. Furthermore, people’s social problem-solving (coping) styles also reflect their social skill abilities. People might tend to solve problems on their own or might choose to seek help from others. Socially skilled persons are less distressed by relationships and are adept at avoiding the state of indebtedness, which could lead people to believe that help cannot be sought. Low socially skilled individuals, on the other hand, often incur interpersonal debts, which lead to rejections, and further lead to being discouraged to seek support (Riggio & Zimmerman, 1991).

Current evidence suggests that older people tend to exhibit poorer social skill ability, which is correlated with their declined communication skills caused by reduced cognitive ability (Murman, 2015), their decreased global social network due to life event changes (Fan et al., 2021; Wrzus et al., 2013), and their reduced social interactions due to mobility restrictions (Weijs-Perrée et al., 2015). As a result, social isolation or loneliness became a prevalent issue among the older population (Donovan & Blazer, 2020). Volunteering provides the opportunity for social participation, which is considered a useful strategy for improving older people’s social isolation (Crittenden, 2018). However, loneliness might not be readily improvable by solely increasing a person’s social participation. Loneliness is closely related to people’s perceived quality of interpersonal relationships (Jones et al., 1982; Mund & Johnson, 2021), while the foundation of a close interpersonal relationship relies much on a person’s social skill abilities.

People’s social skill ability was found to be correlated with certain demographic features such as gender (Salavera & Usán, 2021), age (Beadle & de la Vega, 2019), educational levels (Ünlü & Çeviker, 2022), and social contexts (Chapuis-de-Andrade & Esteves, 2017; Domenico-Grazziotin & Scortegagna, 2016). Despite social contexts may have a crucial impact on people’s social skills, limited information was known concerning what social demographic characteristics might be correlated with older people’s poorer social skills. Furthermore, research on social skills predominantly based on samples of children, adolescents, college students, or adults (Ben-Itzchak & Zachor, 2021; Lodder et al., 2016; Riggio, 1986; Riggio et al., 1993; Segrin & Taylor, 2007; Segrin & Flora, 2000; Yizengaw, 2021); scarce research was available for the older population (e.g., Domenico-Grazziotin & Scortegagna, 2016). To better understand the social skills of the older population, it is essential to investigate social skills and their demographic correlates based on samples of older adults.

To bridge this gap of knowledge, the present study aimed to investigate the social demographic correlates of social skills and the latent social skill profiles of Taiwanese older volunteers featuring these demographic characteristics. This study comprised two parts of the investigation. The first part of this study explored older volunteers’ demographic correlates of social skills, including gender, age, education, marital status, living arrangements, health condition/number of chronic diseases, and serving area, on their strengths of association with volunteers’ perceived social skill ability. After the significant demographic correlates were identified, an exploratory latent class analysis (ELCA) was utilized to further explore the latent social skill profiles of older volunteers featuring the identified demographic characteristics.

This study adopted five social skills elements and two coping styles discussed by Riggio (1986); Riggio et al. (1989); Riggio & Zimmerman (1991) to define volunteers’ social skill ability, including emotional sensitivity (the ability to decode the nonverbal communications of other people), social sensitivity (the ability to decode/understand the verbal communications of others), social expressivity (the ability to communicate or engage others in communication), social manipulation (the ability to influence/manipulate others in affecting the outcomes of specific social situations), cognitive empathy (non-emotional perspective taking), and self-reliant/help-seeking coping styles (self-reliant/help-seeking when encountering problems/difficulties) as social skills indicators. These skills were divided into basic and advanced (the ability in difficult social situations) skills by complexity (Table 1).

Table 1.

Social Skill Indicators.

Social skills (Abbreviations)	Items
Basic
Emotional sensitivity (ES)	Being able to observe and attend to the feelings of others.
Social sensitivity (SS)	Being able to listen to the thoughts/opinions of others.
Social expressivity (SE)	Being able to communicate/interact with others.
Cognitive empathy (empathy)	Being able to empathize the feelings of others.
Advanced
Self-reliance	Being able to problem solve on the spot when in service.
Help-seeking	Being able to seek help from people when confront with problems during service hours.
Social manipulation (SM)	Being able to manage/resolve conflicts when working in a team.

Note. The right column presented the seven items derived from the volunteer interpersonal skills sub-scale of the Older Volunteer Competency Scale (OVCS). The left column indicated the social skill constructs (and the abbreviations of the constructs) corresponded to the items on the right column. The items were divided into the basic and advanced skills by complexity.

The present study aims to address the following research questions: (1) What demographic variables were significantly correlated with the social skill ability of Taiwanese older volunteers? It was postulated that at least one demographic variable would show a substantial correlation with Taiwanese older volunteers’ social skill ability; (2) What latent social skill profiles can be identified among Taiwanese older volunteers featuring significant social skill demographic correlates? We hypothesized that different social skill profiles would be identified for older volunteers featuring different levels of demographic correlates (e.g., high vs. low education).

Methods

Design, Setting, and Participants

This study utilized a survey research design and collected research data based on face-to-face interviews with the research participants between April and September 2023. The sampling method involved two phases. Initially, based on the regional characteristics of the 7 areas of Kaohsiung City, 73 community centers were randomly sampled from the community center list of the senior citizens’ welfare division of the city government. After the study sites were determined, the research team contacted the study sites by phone to inquire their willingness to participate, and all sites agreed to participate in this study. The participants were systematically randomly sampled from the volunteer list of each site according to the size of community care centers. Based on the aforementioned sampling procedure, the present sample should be representative of older volunteers of the community care centers in the Kaohsiung area. The older volunteers provided services to the clients of the community care center (older people living in the community) including phone/home visits, on-site group activities, on-site monitoring of clients’ blood pressure/body temperature, general administrative activities, and service referrals. A total of 1000 older volunteers were systematically random-sampled from 73 community centers for further face-to-face interviews, and all participants received a small thank-you gift from the research team for their participation. The inclusion criteria of the participants were as follows: (1) older volunteers aged 65 and above; (2) having reading and writing ability in Chinese. The estimated sample power was .93, based on Zhang & Yuan (2018).

Ethical Considerations

This study was approved by the Institutional Review Board of a university hospital in a southern city of Taiwan. Written informed consent was obtained from the participants prior to the interview. All participants were informed about the content of this research and their rights to withdraw from this study at any time. The identities of participants were protected via assigning a corresponding ID number in the dataset to retain data confidentiality.

Data Collection

The Older Volunteer Competency Scale (OVCS) and a demographic survey were collected in this study. The demographic survey collected information on participants’ age, gender, marital status, education attainments, living arrangements, and the number of chronic diseases. The OVCS has 30 items, measuring volunteers’ perceived competency in three aspects of the community center work: (1) volunteer work knowledge (9 items), (2) volunteer service skills (8 items), and (3) volunteer interpersonal skills (13 items). The Likert scale was utilized on the scale items with item scores ranging from 0 to 10. The item scores measured volunteers’ perceived needed improvements in the three parts of volunteer abilities. Higher item scores represented more needed improvements. The content validity of the scale was established by domain experts based on focus group interviews (2 center directors, 2 volunteer work leaders, 2 nursing professionals, 2 social work professionals, and 2 experienced older volunteers who served in the field for a minimum of 3 years). The overall scale had a Cronbach’s alpha of .98 (coefficients of .96, .94, and .98 for the three subscales, respectively) and acceptable model-data fit as confirmed by factor analysis (χ² = 2.06, GFI = 0.93, RMSEA = 0.05, AGFI = 0.92, NFI = 0.96, CFI = 0.98, and IFI = 0.98). Due to the interpersonal subscale being the only subscale utilized in this study, more information concerning the items of the interpersonal subscale is provided in Table 1.

Data Analysis

In this study, we aimed to investigate which demographic variables were significantly correlated with older volunteers’ social skills. Considering the sample was derived from 73 community centers, a mixed-effects model was utilized to address this question. Furthermore, we hoped to better understand whether volunteers featuring different levels of the identified demographic correlates would exhibit different social skills in terms of the latent social skill profiles. Exploratory latent class analyses (ELCAs) were utilized to explore the latent skill patterns at different levels of the demographic correlates. The lme4 package (Bates et al., 2015) and the poLCA R package (Linzer & Lewis, 2011) were utilized to analyze the data. In the construction of the mixed-effects model, the demographic variables of the older volunteers (gender, age, education, marital status, living arrangements, number of chronic diseases, serving area [urban/suburban], and volunteer duration) were included in the model as fixed effects, and the units (73 community care centers) were included in the model as the random effect. Seven social skill items/indicators (Table 1) derived from the interpersonal sub-scale were reversely recorded (higher scores = better ability), and the item summation was utilized as the dependent variable in the mixed-effects model. After the significant demographic correlates were identified, ELCAs were conducted to explore the social skill profiles at different levels of the correlates. To illustrate, the education variable was divided into high and low (high: > 9^th grade, low: ≤ 9^th grade) for conducting the ELCA, so that the latent social skill groups can be identified for both high- and low-education groups.

The seven items derived from the interpersonal sub-scale were further utilized as social skill indicators in the LCA with the original item scores (ranged from 0 to 10) being further divided (recoded) into two levels by the middle category (sufficient ability = 2, insufficient ability = 1). The fit indicators utilized for determining the number of the latent social skill groups were Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), g², and the χ² values, with a lower value indicating a better fit. The BIC was utilized as the primary determination criterion. Descriptive statistics of means, standard deviations, and frequency on the demographic variables were reported to depict the characteristics of the older volunteers.

Results

Demographic Characteristics

The 1000 older volunteers had a mean age of 71.79 (SD = 4.93), were predominantly female (n = 808, 80.8%), had a higher than 9^th grade education (n = 519, 51.9%), married (n = 642, 64.2%), living with family (n = 852, 85.2%), volunteered in suburban areas (n = 560, 56%), and volunteered for an average of 136.01 months (SD = 102.69) in the local community care centers (Table 2).

Table 2.

Demographic Characteristics of the Older Volunteers (N = 1000).

Variable	M	SD	N	%
Age	71.79	4.93
Volunteering duration (months)	136.01	120.68
Number of chronic diseases	0.86	0.92
Gender
Female			808	80.8
Male			192	19.2
Marital status
Not married			358	35.8
Married			642	64.2
Educational level
≤9^th grade			481	48.1
>9^th grade			519	51.9
Living arrangements
Alone			148	14.8
With family			852	85.2
Serving area
Urban			440	44
Suburban			560	56

Demographic Correlates of the Social Skill Abilities

The findings of the mixed-effects model (Table 3) revealed that after adjusting for the contextual effect of the units (73 community centers) and the effects of other demographic variables in the model, older volunteers’ education attainments and serving area (urban vs. suburban) were the only two variables that demonstrated significant associations with the volunteers’ perceived social skill abilities (the sum score of the 7 indicators). Specifically, higher education and urban areas significantly correlated with older volunteers’ better social skill abilities.

Table 3.

Mixed-Effects Model Predicting Older Volunteers’ Social Skill Abilities.

Fixed effect	b	SE	p	95% CI
Intercept	53.91	10.00	<.001	34.29 to 73.54
Age	−0.07	0.12	.556	−0.30 to 0.16
Volunteering duration	0.01	0.01	.219	−0.00 to 0.02
Number of chronic diseases	0.05	0.57	.928	−1.07 to 1.17
Gender (female)	0.32	1.46	.824	−2.54 to 3.19
Marital status (married)	−0.07	1.23	.957	−2.47 to 2.34
Living with family	1.65	1.57	.292	−1.43 to 4.74
Education	1.01	0.44	.022	0.15 to 1.87
Serving area (suburban)	−9.21	3.14	.003	−15.37 to −3.06
Random effect	Variance
τ00 _units	143.73
σ²	247.21

Note. Dependent variable: the sum score of the seven social skill indicators (higher score = better ability). Continuous variables: age, education, volunteer duration, and number of chronic diseases. Dichotomous variables: gender, marital status (married/not married), living with family/living alone, and serving area (urban/suburban). τ00 _units = the units intercept (units indicate the 73 community centers). σ² = residual.

Latent Social Skill Groups

The model fit analysis identified three latent ability groups (high, moderate, and low ability) for both high- and low-education older volunteers (Table 4). As shown in Figure 1, both groups had the majority of people classified as high ability, followed by low and moderate ability. The main difference between high- and low-education older volunteers lays in the different social skill patterns of the moderate ability groups. The high-education, moderate ability group was less likely to endorse both coping styles (self-reliance and help-seeking) as well as the social manipulation skill, while the low-education, moderate ability group was only devoid of the help-seeking coping style. Furthermore, compared to the low-education group (n = 241, 60.7%), more people in the high-education group (n = 315, 50.1%) were classified in the high-ability group (being sufficient across all indicators). By contrast, compared to the high-education group (n = 122, 22.2%), more low-education older volunteers (n = 156, 32.4%) tended to be classified in the low-ability group (being insufficient across all indicators). The numbers of individuals classified in the moderate groups (being insufficient in parts of the indicators) were not substantially different for high- and low-education volunteers (n = 82, 15.8% vs. n = 84, 17.5%).

Table 4.

LCA Model Fit Information.

Number of latent groups	AIC	BIC	g ²	χ ²
High education
2	2454.40	2518.18	378.93	1385.68
3	2243.52	2341.31	152.05	223.59
4	2218.53	2350.34	111.06	124.61
Low education
2	2583.35	2645.98	315.18	783.17
3	2443.09	2539.14	158.92	187.13
4	2456.27	2585.72	156.10	188.66
Urban
2	2094.22	2155.52	289.29	842.27
3	1957.33	2051.32	136.39	171.60
4	1929.82	2056.51	92.88	107.03
5	1933.11	2092.49	80.17	96.85
Suburban
2	2919.84	2984.75	398.50	1070.61
3	2706.91	2806.46	169.57	207.44
4	2669.71	2803.87	116.37	123.09
5	2671.70	2840.49	102.37	110.32

Note. AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; g² = Likelihood ratio/deviance statistic; χ² = Chi-square goodness of fit. Bold fonts = the number of groups that showed the best fit of the data.

Figure 1.

Latent ability groups of the four demographic conditions. Note. This figure showed the latent social skill patterns under four demographic conditions (high/low education and urban/suburban). The x-axis indicates the 7 social skill indicators of this study: ES (emotional sensitivity), SS (social sensitivity), empathy, SE (social expressivity), SELF (self-reliant coping), HELP (help-seeking coping), and SM (social manipulation). The y-axis indicates the probability of being classified as sufficient ability (endorsing item scores of 2). Three latent ability groups were identified for the education conditions: high (higher probabilities of endorsing sufficiency across all indicators), moderate (moderate probabilities of endorsing sufficiency across all indicators), and low (low probabilities of endorsing sufficiency across all indicators). Apart from high and low ability groups, two additional latent groups were identified for urban/suburban volunteers, namely, basic (high probabilities of endorsing basic social skill indicators) and eclectic (high probabilities of endorsing mixed basic/advanced indicators) groups.

On the other hand, the model fit analysis further identified four latent ability groups for both urban and suburban older volunteers (Table 4). Older volunteers from urban or suburban areas both had the majority of people being classified in the high ability group (being sufficient across all indicators), followed by the basic ability group (being sufficient only at ES, SS, SE, and empathy), the low ability group (being insufficient across all indicators), and the eclectic ability group (being sufficient in mixed basic/advanced indicators). Different latent social skill patterns of the eclectic ability group were observed for urban and suburban volunteers. The urban eclectic group showed insufficiency in ES, SS, and empathy, while the suburban eclectic group showed insufficiency in SS, SE, empathy, and help-seeking coping styles (Figure 1).

Discussion

Demographic Correlates of Social Skill Abilities

In this study, we investigated the social skill abilities of Taiwanese older volunteers from the perspectives of demographic correlates as well as the latent social skill patterns associated with the significant demographic correlates. It was discovered that education and serving area (urban/suburban) were the only demographic variables significantly correlated with the volunteers’ perceived social skill abilities while non-significant findings were discovered for demographic variables, such as gender, age, marital status, cohabitation condition, and the number of chronic diseases. The non-significant demographic finding was particularly unexpected for the gender variable. Gender differences were often observed between men and women in regard to social networks/relationships. Women tended to receive more social support from smaller/closer social networks (Haines et al., 2008). Older women (in their 70s) were also reported to have larger social network sizes than older men (McLaughlin et al., 2010). Based on previous findings, we posited that female volunteers might show better social skill abilities since women were found by research as better socially engaged than their male counterparts. The present non-significant gender findings call for further exploration of gender and social skill differences in different cultures (Western vs. Asian) since research on this topic was often based on Western samples (e.g., McLaughlin et al., 2010).

Similar to the gender variable, demographic characteristics, such as older age, being single (not married), living alone, and poorer health (more chronic diseases), were also identified as significant correlates of both loneliness and social relations (Cohen-Mansfield et al., 2016; Kim & Lee, 2022; van den Broek, 2017). Older age was believed to increase people’s functional disability, thus impeding their social engagements (Guo et al., 2021). Marital status (e.g., divorced or separated) was found to have a significant impact on older men’s social networks (McLaughlin et al., 2010). Older people who lived alone were found to have less social support than those who lived with others (Chan et al., 2020). Despite a research-supported connection to people’s social relations, this study found none of these variables were significantly correlated with older volunteers’ perceived social skill abilities. One possible reason for the present non-significant demographic result could be due to the homogeneity of the research data, in that the present sample was predominantly female, married, and living with family. The lack of variability of the research data might lead to non-significant findings. However, it is also likely that older volunteers’ education and serving area (urban/suburban) were more strongly correlated with people’s social skill abilities than other demographic variables examined in this study (e.g., gender).

Furthermore, since volunteers’ serving areas were usually close to where they resided, the two demographic variables (education and serving area) constituted the volunteers’ socioeconomic status (SES) indicators. The present findings on volunteers’ education and serving area hence highlighted a strong correlation between people’s SES and their social skill abilities. This finding is consistent with the findings of recent research on SES and peoples’ social relations. Wang et al. (2023) discovered that people’s social relations were significantly influenced by their SES (as indicated by people’s rich/poor living areas). Based on analyzing the cell phone datasets, Wang et al. (2023) found that high SES individuals tended to have a variety of social relationships while low SES individuals showed a much smaller social circle. In the view of social learning theory, smaller social circles would reduce people’s social learning opportunities (Bandura, 1977) and possibly contribute to their poorer social skill abilities. In all, the present finding highlighted the necessity to attend to the social skill issue of low SES older adults in the community.

Latent Social Skill Patterns of Older Volunteers

The present study further identified similar latent ability groups (high, moderate, and low) for older volunteers with different education attainments. Findings revealed that higher education seemed to be an advantageous characteristic for better social skill abilities. Specifically, more highly educated volunteers were found to be classified as high ability (highest probabilities across all seven social skills indicators). By contrast, more low-educated volunteers (≤9^th grade) were found to be classified in the low-ability group (lowest probabilities on the seven indicators). Furthermore, since help-seeking was considered an adaptive social coping response (Riggio & Zimmerman, 1991), the moderate groups (moderate probabilities across indicators) of high/low educated volunteers both showed maladaptive response patterns (low in help-seeking). Another difference found between high- and low-educated moderate groups was their different skill patterns. Specifically, the high-educated moderate group showed lower capabilities (using the probability of 0.5 as the cutoff) in social manipulation skills and both styles of problem-solving (self-reliance and help-seeking), while the low-educated moderate group was only less capable of using the help-seeking coping style.

Furthermore, the LCA identified four latent groups (high, low, basic, and eclectic ability groups) for urban and suburban older volunteers. Both urban and suburban volunteers had most people being classified in the high ability group, followed by the low ability group, the basic ability group (only sufficient at basic skills including ES, SS, SE, and empathy), and the eclectic ability group (being sufficient in mixed basic/advanced indicators). The findings on proportions further revealed more suburban volunteers were classified as having low abilities than urban volunteers. Different patterns are also observed between urban and suburban eclectic groups. Urban volunteers were less capable of ES, SS, and empathy, while apart from SS and empathy, suburban volunteers were devoid of SE and help-seeking skills. As expressivity ability was considered as a skill for making initial contacts and sensitivity was considered as the skill for building deeper relationships (Riggio & Zimmerman, 1991), the social skill patterns of the urban eclectic group implied that this group might be more adept at making casual acquaintances rather than building close relationships.

It should also be noted that among the four demographic conditions examined in this study, the suburban eclectic group flagged a risk for loneliness due to its social skill patterns. The group was devoid of both SS and SE skills, which implied this group might have difficulty in building both superficial and deep relationships (Riggio & Zimmerman, 1991). Furthermore, according to the evolutionary theory of loneliness (Cacioppo & Cacioppo, 2018), in the absence of sufficient salutary social relationships (the loneliness condition), people would increase self-centeredness and become hypervigilant for social threats; this condition manifests in social behaviors, such as lacking empathy as well as exhibiting a tendency to avoid others (for self-preservation). The suburban eclectic group was the only group among the four featuring a lack of both cognitive empathy and the help-seeking coping style, which signified as the symptoms of loneliness. This finding highlighted a possibility of risk for loneliness among lower SES region older adults. Further investigations are warranted to confirm the present speculation.

Limitations

This study has some limitations. First, due to the cross-sectional nature of this study, causality relationships cannot be inferred from the research variables. Furthermore, the present findings were based on parts of the social skill elements proposed by Riggio (1986), which limited the investigations and the findings of the basic social skills. Future research is encouraged to adopt the complete set of social skill elements proposed by Riggio (1986) to investigate the social skill abilities of older adults. Lastly, this study identified a portion of suburban older volunteers as exhibiting a risk for loneliness; this postulation was based on the loneliness-associated social skill pattern delineated by the evolutionary theory of loneliness (Cacioppo & Cacioppo, 2018) but not the loneliness measurement per se. Further investigations on loneliness-associated social skill patterns based on valid loneliness measurements are warranted to verify this postulation.

Conclusions

Social skill abilities are people’s assets that help them to cope with age-related losses as well as promote positive psychological well-being. This study investigated the social skill abilities and their demographic correlates of 1000 Taiwanese older volunteers to better understand peoples’ social skill abilities in older age. The findings have several implications for practice (the program/intervention/policy) as well as for future research. First, the present finding indicated that volunteers’ education and serving area outweighed other demographics (e.g., gender) as the two most relevant demographic correlates of older volunteers’ social skill abilities. The finding suggested that older people’s SES has a substantial correlation with their social skill ability. Additional social skill training might be helpful to improve the social skills of older volunteers who have lower education or serve in suburban community care centers. Second, the findings also highlighted the need to further understand the social skill needs of older volunteers who have lower education or serve in suburban community care centers as well as to tailor appropriate training content. Third, this study identified a portion of suburban older volunteers to exhibit a social skill pattern signifying the risk of loneliness. The finding implied that older volunteerism may improve older people’s social participation; however, older volunteers featuring specific SES characteristics could have susceptibility to loneliness. Policymakers might need to consider this phenomenon in promoting strategies for improving issues of social isolation/loneliness among the older population. Future research is also warranted to further investigate this phenomenon as well as appropriate interventions for the situation. Lastly, the present research was based on a Taiwanese sample. The findings of this study may be more representative of relevant cultures (e.g., North East Asia) than of Western culture. Nonetheless, this study was one of the few research studies that has investigated older volunteers’ social skill demographic correlates and their corresponding latent social skill profile which provides important information for the promotion of the psychosocial well-being of the older population in society.

Footnotes

Acknowledgments

Sincere appreciation is directed by our group to the National Health Research Institutes (NHRIs) in Taiwan for funding this study (NHRI-EX113-11209PI), to the administrators and staff of 73 community care centers for their support and assistance, and to the 1000 older volunteers for their generous participation.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the National Health Research Institutes (NHRIs) in Taiwan (NHRI-EX113-11209PI).

Institutional Review Board Approval

The Institutional Review Board of Kaohsiung Medical University Chung-Ho Memorial Hospital approved this study (KMUHIRB-E(I)-20220056).

ORCID iDs

Szu-Yu Chen

Kuei-Min Chen

Chiang-Ching Chang

Frank Belcastro

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