Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

Yuri Matsuzaki; Hiroki Okada; Maki Miyajima; Rika Hirayama; Risa Takashima

doi:10.1177/00469580251360650

. 2025 Aug 9;62:00469580251360650. doi: 10.1177/00469580251360650

Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

Yuri Matsuzaki ^1,², Hiroki Okada ¹, Maki Miyajima ¹, Rika Hirayama ¹, Risa Takashima ^1,^✉

PMCID: PMC12335655 PMID: 40782119

Abstract

Although social activity reduces loneliness levels, this relationship is not always consistent. Some older adults experience high loneliness despite active social participation. We aimed to clarify the characteristics of these individuals by focusing on their preference for solitude and satisfaction with and performance in valuable social and solitary activities. This cross-sectional survey included 3205 individuals aged ≥65 years and assessed loneliness, participation in social activities, preference for solitude, performance of valuable social and solitary activities, and depression. Participants were categorized into 3 groups based on the relationship between loneliness and social activity participation: higher social activity with a tendency toward loneliness, lower social activity without a tendency toward loneliness, and a correlated group. A one-way analysis of variance was conducted to clarify each group’s characteristics. Structural equation modeling was used to explore the structure underlying the discrepancy between loneliness and social activity. Older adults experiencing high loneliness despite active social engagement preferred solitude, had low performance of valuable social and solitary activities, and reported high depression. In the high loneliness despite social activity group, a higher preference for solitude was associated with a decreased performance of social activities valuable to the individual, leading to reduced performance of solitary activities valuable to the individual. These effects contributed to increased depression, further exacerbating the discrepancy between loneliness and social activity. Some older adults may experience little to no benefit from increasing social activities. Social activities that consider older adults’ solitude values could be more effective in addressing loneliness.

Keywords: loneliness, solitude, meaningful activity, personal factors, discrepancy

Highlights.

Some older adults are lonely despite frequent participation in social activities.
They preferred solitude and showed low performance in valuable activities.
Satisfaction with personally valuable activities is key to reducing loneliness.
Respect for solitude preference is important for interventions to reduce loneliness.
Enhancing satisfaction in solitary time may help reduce loneliness effectively.

Introduction

Loneliness is an important risk factor that adversely affects older adults’ physical and mental health.^1
-3 Active participation in social activities is widely recognized as an effective way to reduce loneliness among older adults, as numerous studies have demonstrated that increased social participation correlates with lower levels of loneliness.^4
-6 However, not all older adults benefit equally from social participation, as some continue to feel lonely despite being socially active.^7,8 This suggests that factors, such as the quality of social interactions, personal characteristics (eg, sex and cultural background), and the nature of social participation, may significantly impact loneliness itself.^7
-9

To explain the discrepancy in the relationship between participation in social activities and loneliness, we focused on individual preferences for solitude and the subjective aspect of social activities, specifically the performance of engaging satisfactorily in activities that are valuable to the individual. While loneliness is commonly defined as “a negative subjective experience of low quality and/or quantity of one’s social network,”¹⁰ recent studies have suggested that the quality of social interactions, rather than their quantity, might be more critical for understanding why some older adults feel lonely despite being socially active. Regarding services to combat loneliness, increasing the number of social networks and improving their quality is essential.¹¹ Furthermore, the quantity and quality of participation in social activities were closely related to loneliness.^12,13 However, research on how an individual’s preferences for solitude and subjective aspects of social activity cause a discrepancy in the relationship between the amount of participation in objective social activities and the subjective experience of loneliness has received little attention.

Older adults spend a higher proportion of their time alone than younger people¹⁴; this tends to decrease their participation in social activities. However, an aging paradox has been reported in which subjective well-being, which includes life satisfaction, is maintained in old age despite a decline in the frequency of participation in social activities and the experience of many losses, such as in physical functioning and social roles.^15,16 Therefore, even if people spend more time alone and engage in fewer social activities as they age, many remain adaptive. A concept that may explain this adaptability is the preference for solitude, a measure of orientation, such as preferring to be alone,^17,18 which can be described as the ability to spend time alone.¹⁸ Older adults who enjoy and perceive productivity during solitude maintain their subjective positive affect and life satisfaction.¹⁹ However, for those having a strong preference for solitude, maintaining a high level of social activity may lead to dissatisfaction or discomfort and decreased performance during social activities, which could, in turn, intensify feelings of loneliness.

In addition, even if the social and solitary activities are similar, they differ in how important they are to an individual.²⁰ Performance activities that align with unique values and interests in community life may provide greater meaning and fulfillment.²⁰ Middle-aged and older adults who can perform valuable activities that are important to them and can satisfactorily control and balance them with other activities exhibit better health-related quality of life²⁰ and subjective well-being.²¹ Therefore, the performance of valuable activities, both in social activities spent with others and solitary activities conducted alone, may have a significant impact on mental health, including loneliness.

Currently, loneliness interventions focus on increasing social participation and strengthening social networks. However, merely increasing social participation does not alleviate loneliness for all older adults.²² Some socially active older adults continue to experience significant loneliness, suggesting that traditional approaches may not fully address all underlying factors. In this study, we aimed to identify the characteristics of older adults experiencing high levels of loneliness despite high levels of social activity and explore new, tailored methods for reducing loneliness in those who cannot be effectively supported by existing strategies.

Methods

Participants

The survey was distributed on September 12, 2022, and responses were collected until October 14, 2022.We included 4069 older adults aged ≥65 years who lived in Town A, a typical suburban town in Japan. To minimize selection bias, we included all eligible older adults living in Town A, ensuring that every eligible resident had an opportunity to participate. We excluded individuals who were certified as requiring assistance in some or more of their daily activities, as they may have limitations in their ability to participate in social activities and their responses might not accurately reflect their own perceptions. Additionally, those who had been hospitalized for 3 months or longer were excluded because long-term hospitalization restricts social engagement. Furthermore, individuals residing in long-term care facilities located in other municipalities were excluded, as their living environment differs significantly from community settings in Town A. After applying these criteria, 3205 participants were enrolled from the initial 4069 eligible residents (847 required assistance, 12 hospitalized for 3 months or longer, and 5 lived in a long-term care facility outside Town A). Study descriptions and questionnaires were sent to participants via mail. The questionnaires were collected via return envelopes. In this mail survey research, participants were provided with a research information sheet detailing the purpose, methods, ethical considerations, and voluntary nature of participation in the study. Participants were asked to review this information before responding. Consent was deemed obtained upon submission of responses. This study was approved by the Ethical Review Committee of the institution. This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. The checklist was followed to ensure transparent and comprehensive reporting.²³

Survey Items

A self-administered questionnaire was used to collect participants’ basic attributes and key variables using well-established tools with validated reliability and validity: loneliness (Japanese version of the Short-form University of California, Los Angeles [UCLA] Loneliness Scale, 3rd edition), frequency of participation in social activities (Checklist for vivid social activities), preference for solitude (Japanese version of the Preference for Solitude Scale), performance of valuable social and solitary activities for the individual (Self-completed Occupational Performance Index [SOPI]), and depression (15-item Geriatric Depression Scale [GDS-15]).

Demographic Characteristics

We evaluated 8 basic attributes: age, sex, years of education, years of residence, family members living together, alcohol consumption, marital status, and current job status. Previous studies have evaluated the effects of age,²⁴ sex,^25,26 years of education,²⁶ years of residence,²⁷ family living together,²⁸ drinking,²⁹ marital status,³⁰ and current job¹³ on loneliness.

Loneliness

The Japanese version of the Short-Form UCLA Loneliness Scale (3rd edition) was used to assess loneliness.³¹ This scale, widely recognized in loneliness research, comprised 10 items, and responses were rated on a 4-point Likert scale that ranged from “1. always” to “2. sometimes,” “3. occasionally,” and “4. not applicable.” The higher the score, the higher an individual’s loneliness. A sample item is: “I feel that I have no companionship.” The 10-item format itself has demonstrated superior psychometric properties compared to other short forms.³²

Frequency of Participation in Social Activities

Participation in social activities was assessed via the validated checklist for vivid social activities developed by Ojima,³³ a tool specifically designed for evaluating Japanese older adults’ engagement in social activities. It comprised 21 items on social activities that older adults often engaged in, such as “socializing with neighbors” and “learning activities at a culture center.” Respondents were asked to choose between “1. sometimes or always” and “2. not.” A sample item is: “Interaction with neighbors.” The higher the score, the higher their amount of social participation.

Preference for Solitude

Preference for solitude, the degree to which people prefer to be alone, was assessed via the validated Japanese version of the Preference for Solitude Scale.¹⁹ This scale has been widely used in research on loneliness and comprises 17 items. Of the 17 items, 16 were evaluated, after one that had significant factor loadings in previous studies was excluded.¹⁹ A two-case method was used, and for each item, the response with a high and low preference for solitude was scored as 1 and −1, respectively. In each item, participants were asked to choose between two opposing statements, such as: “I enjoy being around people.” or “I enjoy being by myself.”

Performance of Social and Solitary Activities Valuable to the Individual

Performance of social and solitary activities valuable to the individual was assessed via a modified version of the SOPI.²⁰ To determine what constituted “valuable activities,” participants were asked, “Please imagine activities that are especially important in your life.” The SOPI assess an individual's sense of control over activities valuable to the individual, their ability to effectively balance these activities with other activities, and their satisfaction with performing these activities. Sample items included: “Are you able to decide for yourself when and how to perform those activities?” (control), “Are you able to balance the time and energy you spend on those activities according to your daily life?” (balance), and “Are you able to perform those activities with a sense of satisfaction?” (satisfaction). This scale was chosen because it allows for a subjective assessment of the performance of activities valuable to the individual in their daily lives. Since we aimed to analyze the characteristics of older adults who have discrepancies in the relationship between loneliness and frequency of participation in social activities, we evaluated the performance of (1) valuable activities in solitude and (2) valuable activities performed with others. The SOPI does not normally evaluate these 2 parameters separately; however, even if evaluated separately, the reliability of the SOPI is sufficiently ensured. Specifically, Cronbach’s alpha was .83 for solitary activities and .92 for activities performed with others, indicating strong internal consistency for both parameters.

Depression

To enhance generalizability, we included depression as an independent variable, given that the association between loneliness and depression has been demonstrated in previous studies.^34,35 Depression was assessed via the validated Japanese version of the GDS-15.^36,37 The GDS-15 is the most used screening test for geriatric depression worldwide. It comprises 15 short questions, and the respondents are asked to choose between “1. Yes” or “2. No.” A sample item is: “Are you basically satisfied with your life?” The higher the score, the more severe an individual’s depression.

Data Analysis

The UCLA Loneliness Scale and Checklist for Vivid Social Activities scores were converted into a Z-score. The difference between the 2 scores was used as the basis for the following groups: a group with a low frequency of participation in social activities and low loneliness (lower social activity tendency group; LST), a group with a moderate frequency of participation in social activities and loneliness (correlated social activity and loneliness group; CSL), and a group with a high frequency of participation in social activities and high loneliness (higher loneliness tendency group; HLT) (Figure 1). The cutoff value for the 3 groups was set at 0.75 standard deviation (SD), a more conservative standard than 0.5 SD, and widely reported as a minimally important amount for detecting health-related differences.^38,39 This threshold was intentionally chosen to provide a more stringent criterion, reflecting a more rigorous standard that exceeds the commonly used 0.5 SD.

This image is a scatter plot depicting the UCLA Loneliness Scale, the Checklist for Vivid Social Activities, and the HLT divided into three groups based on their scores. The plot displays 266 LST participants, 578 CSL participants, and 262 HLT participants, illustrating their tendencies towards social activity and loneliness. The LST group tends to participate less in social activities and experience less loneliness, the CSL group shows moderate tendencies in both aspects, and the HLT group is characterized by high social activity and high loneliness. — Method for dividing participants into 3 groups.

*Note.* Participants were divided into 3 groups by calculating the difference between the Z-scores of the UCLA Loneliness Scale and the Checklist for Vivid Social Activities. Lower social activity tendency group (LST, n = 266): Low frequency of participation in social activities and low loneliness. Correlated social activity and loneliness group (CSL, n = 578): Moderate frequency of participation in social activities and loneliness. Higher loneliness tendency group (HLT, n = 262): High frequency of participation in social activities and high loneliness. UCLA, University of California, Los Angeles.

SPSS for Windows (version 24; IBM Corp., Armonk, NY, USA) was used for all analyses. In this study, missing values ranged from 0% to 16.11% across the endorsement items. We identified missing basic attributes and examined the relationships between these attributes, the dependent variable, and primary outcomes: loneliness and the amount of participation in social activities. We used the Mann–Whitney U test and confirmed that, regarding primary outcomes, both the basic attributes and the dependent variable were Missing Completely at Random (MCAR). Given this MCAR assumption, we applied the mean imputation method to handle missing values. Recent studies have also affirmed the validity of the mean imputation method, particularly when dealing with MCAR data, highlighting its ability to preserve the general distribution and reduce potential bias in data analysis.^40,41

Comparative Analysis of LST, CSL, and HLT Characteristics

To characterize the three groups, a one-way analysis of variance (ANOVA) was conducted, with the Preference for Solitude Scale (preference for solitude), SOPI (performance of social and solitary activities valuable to the individual), and GDS-15 (depression) as the dependent variables, which were considered to be related to the discrepancy in the relationship between the amount of participation in social activities and loneliness. The Games–Howell test was used for multiple comparisons as some variables were not equally distributed.

Examination of the Influence of Basic Attributes on the Main Variable

Furthermore, for the 3 groups, we examined the confounding effects between preference for solitude, performance of social activities valuable to the individual, performance of solitary activities valuable to the individual, depression, and basic attributes. First, chi-squared (χ²) tests were conducted for sex, marital status, and current job status, and ANOVAs were conducted for age, years of education, years of residence, cohabitation with family, and alcohol consumption. Subsequently, a two-way ANOVA was conducted with a preference for solitude, performance of social and solitary activities valuable to the individual, and depression for the items that showed significant differences for these basic attributes. The significance level was set at p < .05.

Characteristics of Older Adults with High Loneliness Despite High Social Activity

To further explore the characteristics of older adults with a high amount of participation in social activities but high loneliness (HLT group), we employed structural equation modeling (SEM) to create a structured model that allowed for the simultaneous evaluation of both direct and indirect effects of various factors on the discrepancy in the relationship between social participation and loneliness in the HLT group. Previous studies have shown that the performances of both social and solitary activities that are meaningful to the individual are influenced by one’s preference for solitude.^17,18 Furthermore, declines in the performance of meaningful activities have been associated with increased depressive symptoms,⁴² and several studies have also demonstrated the bidirectional relationship between depression and loneliness.^34,35 Based on these findings, we developed and tested the following three models.

Model 1: Direct Effect Model

This model was constructed to test whether the discrepancy between social participation and loneliness can be explained by the direct effects of individual variables. It hypothesizes that each independent variable—preference for solitude, performance of social activities valuable to the individual, performance of solitary activities valuable to the individual and depression—directly affects the discrepancy.

Model 2: Stepwise Causal Model

After confirming in Model 1 that individual variables did not independently account for the discrepancy, Model 2 was constructed as a hypothesis-driven model informed by previous literature. It posits that preference for solitude affects the performance of both social and solitary activities valuable to the individual,^17,18 which then influences depression,⁴² ultimately contributing to the discrepancy between social participation and loneliness.^34,35

Model 3: Refined Model (Final Model)

Model 2 assumed indirect pathways from preference for solitude to the discrepancy via activity performance and depressive symptoms. In the event that some of the hypothesized paths in this model did not reach statistical significance, we constructed Model 3. Specifically, Model 3 was developed as a refined (final) model by removing the non-significant paths to enhance theoretical consistency.

To evaluate the structural validity of each model, we compared model fit indices, including the chi-square value (χ²; P > .05), comparative fit index (CFI ≥ 0.90), goodness of fit index (GFI ≥ 0.90), adjusted GFI (AGFI ≥ 0.90), and root mean square error of approximation (RMSEA < 0.08), based on standard recommendations.⁴³ These indices were used to determine the relative fit of the 3 models.

Results

Responses were received from 1106 participants (response rate: 34.5%). Table 1 presents the participants’ basic attributes.

Table 1.

Basic Attributes.

		LST	CSL	HLT
		Mean (SD)			p
Age (years)		76.37 (6.57)	75.40 (6.90)	75.17 (6.79)	0.086
Years of education		11.57 (2.40)	11.68 (2.36)	11.41 (2.46)	0.319
Years of residence		43.13 (19.87)	41.49 (21.69)	42.23 (21.69)	0.561
		n (%)			p
Sex	Males	112 (21.88)	259 (50.59)	141 (27.54)	0.014^*
	Females	154 (26.01)	318 (53.72)	120 (20.27)
	Others	0 (0)	0 (0)	1 (100)
Marital status	Single	4 (12.12)	17 (51.52)	12 (36.36)	0.012^*
	Married	173 (22.47)	405 (52.60)	192 (24.94)
	Separated or bereaved	88 (29.93)	151 (51.36)	55 (18.71)
Current job	White-collar	56 (27.45)	97 (47.55)	51 (25.00)	0.523
	White-collar	55 (23.81)	120 (51.95)	56 (24.24)
	Not working	144 (22.71)	345 (54.42)	145 (22.87)
Family living together	Living alone	77 (29.28)	130 (49.43)	56 (21.29)	0.452
	Living couple only	141 (22.60)	326 (52.24)	157 (25.16)
	Two generations living	30 (18.29)	93 (56.70)	41 (25.00)
	Three generations living	15 (42.86)	18 (51.43)	2 (5.71)
	Others	3 (17.65)	9 (52.94)	5 (29.41)
Drinking	Every day	54 (26.09)	106 (51.21)	47 (22.71)	0.941
	Sometime	49 (21.97)	116 (52.02)	58 (26.01)
	Hardly	39 (20.63)	105 (55.56)	45 (23.81)
	Not	124 (25.62)	249 (51.45)	111 (22.93)

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Note. A chi-square (χ²) test was conducted for sex, marital status, and current job; ANOVA was conducted for other basic attributes. CSL = Correlated social activity and loneliness group (n = 578); HLT = Higher loneliness tendency group (n = 262); SD = standard deviation; LST = Lower social activity tendency group (n = 266).

P < .05.

LST (266 respondents) was defined as a group with a low level of participation in social activities and a low level of loneliness. CSL (578 respondents) was defined as a group with a correlated level of participation in social activities and loneliness. HLT (262 respondents) was defined as a group with a high level of participation in social activities and high loneliness.

Comparative Analysis of LST, CSL, and HLT Characteristics

Multiple comparisons among the 3 groups revealed that the HLT and CSL groups were significantly more likely to prefer solitude than the LST group (Table 2). Hence, those who preferred to be alone and needed and enjoyed solitude had higher levels of loneliness, although their participation in social activities was higher.

Table 2.

Amount of Participation in Social Activities and Factors Affecting the Discrepancy Between Loneliness.

		Mean (SD)
		LST	CSL	HLT	F	p	Games–Howell
Preference for solitude (Preference for Solitude Scale)^*		0.61 (6.64)	1.43 (6.91)	2.61 (7.39)	14.692	<0.01	LST≪CSL, HLT
Performance of activities valuable to the individual (SOPI)^**	performance of solitary activity	11.75 (2.50)	11.09 (2.40)	10.55 (2.55)	16.047	<0.01	LST≫CSL> HLT
	performance of social activities	10.76 (3.49)	10.05 (3.35)	8.86 (3.52)	20.773	<0.01	LST> CSL≫HLT
Depression (GDS-15)^***		2.42 (2.17)	3.56 (2.91)	4.87 (3.59)	49.758	<0.01	LST≪CSL≪HLT

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Note. LST = Lower social activity tendency group (n = 266); CSL = Correlated social activity and loneliness group (n = 578); HLT, Higher loneliness tendency group (n = 262); SOPI, Self-completed Occupational Performance Index; GDS-15, 15-item Geriatric Depression Scale; SD, standard deviation.

The higher the score on preference for solitude, the more solitude is needed, the more solitude is enjoyed, leading to more productive solitude.

^**

The higher the score, the more controlled, balanced, and satisfactory the participation in activities valuable to the individual.

^***

The higher the depression score, the higher the depressive tendency; >, <; P < .05, ≫, ≪; P < .01

Furthermore, the LST, CSL, and HLT groups, in that order, had predominantly higher scores regarding performance of social and solitary activities valuable to the individual (Table 2). Therefore, those who tended to have high performance of activities valuable to the individual, whether solitary or social activity, had lower levels of loneliness, even though their participation in social activities was lower.

The HLT, CSL, and LST groups, in that order, had predominantly higher scores regarding depression (Table 2). Hence, those with a high level of participation in social activities and loneliness were more likely to have depression.

Examination of the Influence of Basic Attributes on the Main Variable

This study examined whether the preference for solitude, performance of social and solitary activities valuable for the individual, and depression were influenced by basic attributes. χ² test revealed differences among the 3 groups in marital status (P = .012); however, the 2-way ANOVA revealed no interactions of preference for solitude, performance of social and solitary activities valuable to the individual, and depression.

Characteristics of Older Adults with High Loneliness Despite High Social Activity

To clarify the characteristics of older adults who experienced high levels of loneliness despite high levels of social activity (HLT group), we employed SEM to analyze how the quality of social activities contributed to the discrepancy in the relationship between participation in social activities and loneliness. First, correlations between variables were explored (Table 3), followed by the construction and comparison of 3 models (Models 1-3).

Table 3.

Mean, Standard Deviations (SD), and Inter-Correlations among Key Observed Variables in HLT.

	Mean	SD	2	3	4	5
1. Discrepancy between participation in social activities and loneliness	1.33	0.49	0.08	−0.10	−0.13^*	0.15^*
2. Preference for solitude	2.61	7.39		0.03	−0.13^*	0.09
3. Performance of solitary activities valuable to the individual	10.55	2.55			0.31^**	−0.34^**
4. Performance of social activities valuable to the individual	8.86	3.52				−0.19^**
5. Depression	4.87	3.48

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Note. HLT = higher loneliness tendency group (n = 262); SD = standard deviation.

P < .05. ^** P < .01

Model 1 (Direct Effect Model)

In Model 1, we analyzed whether each independent variable (preference for solitude, performance of social activities valuable to the individual, performance of solitary activities valuable to the individual, and depression) had an influential effect on the discrepancy between participation in social activities and loneliness (Figure 2).

Add detailed information about the study, purpose, and context of the SEM Model 1 diagram. — Model 1 (direct effect model).

*Note.* SEM Model 1 examines whether each independent variable directly influences the discrepancy between participation in social activities and loneliness among older adults with high loneliness despite high social activity (HLT group, n = 262). CFI = comparative fit index; AGFI = adjusted GFI; GFI = goodness of fit index; RMSEA = root mean square error of approximation; SEM = structural equation modeling.

Although the correlation analysis revealed significant associations between some variables (eg, performance of social activities and depression) and loneliness, SEM results showed that none of the independent variables had significant direct effects on the discrepancy. This suggested that the discrepancy could not be fully explained by simple direct effects.

Model 2 (Stepwise Causal Model)

Based on the findings of Model 1, Model 2 was developed to test a theoretical structure incorporating indirect effects derived from previous research (Figure 3). Specifically, a preference for solitude was hypothesized to influence the performance of both social and solitary activities that are valuable to the individual. These, in turn, would affect depression and ultimately contribute to the discrepancy between social participation and loneliness.

The image is a diagram illustrating a structural equation model (SEM) that examines the relationships between an individual's preference for solitude, their engagement in social and solitary activities, depression, and the conflict between loneliness and social activity. — Model 2 (Stepwise Causal Model).

SEM Model 2 examines the influence of preference for solitude on the performance of both social and solitary activities, as well as the subsequent impact on depression and the discrepancy between loneliness and social activity among older adults with high loneliness despite high social activity (HLT group, n = 262). CFI = comparative fit index; AGFI = adjusted GFI; GFI = goodness of fit index; RMSEA, root mean square error of approximation; SEM = structural equation modelling.

*P < .05; **P < .01; ***P < .001

However, SEM results indicated that this model did not meet the criteria for acceptable fit: χ²(5) = 33.078, P = .000, CFI = 0.586, GFI = 0.953, AGFI = 0.858, RMSEA = 0.147. Additionally, the path from preference for solitude to performance of solitary activities (P = .689) and the path from performance of social activities to depression (P = .092) were not statistically significant.

Model 3: Refined model (final model)

To enhance theoretical consistency and model fit, Model 3 was constructed by removing the non-significant the paths from Model 2 and introducing a new path from performance of social activities to performance of solitary activities (Figure 4).

Depicts SEM Model 3 detailing relationships among solitude preference, social and solitary activities performance, depression, and loneliness-societal activities discrepancy in older adults (n=262). Statistically significant correlations (p<.05, p<.01, p<.001) are highlighted. — Model 3: Refined model (final model).

SEM Model 3 examines the relationships among preference for solitude, performance in both social and solitary activities, depression, and the discrepancy between loneliness and social activity among older adults with high loneliness despite high social activity (HLT group, n = 262). CFI, comparative fit index; AGFI, adjusted GFI; GFI, goodness of fit index; RMSEA, root mean square error of approximation; SEM, structural equation modeling.

*P < .05. **P < .01. ***P < .001

As a result, all paths became significant, and the model demonstrated good fit: χ²(6) = 10.056, P = .122, CFI = 0.940, GFI = 0.985, AGFI = 0.963, RMSEA = 0.051.

According to this model, in the HLT group, a higher preference for solitude was associated with lower performance of social activities valuable to the individual, which subsequently reduced performance of solitary activities valuable to the individual. This decline in performance led to increased depression, which in turn amplified the discrepancy between participation in social activities and loneliness.

Discussion

In this study, we aimed to clarify the characteristics of older adults who experienced high levels of loneliness despite high levels of social activity. We conducted a survey of older, community-dwelling adults and investigated the influence of preference for solitude and performance of social and solitary activities valuable to the individuals on the discrepancy between loneliness and social activities. Results of the ANOVA revealed that older adults in the HLT group, who experienced high loneliness levels despite high levels of social activity, preferred solitude and exhibited low performance of satisfactorily engaging in social and solitary activities valuable to individuals. Furthermore, they had high levels of depression.

Prior research on older adults has suggested that older adults tend to view their time in solitude as the time that they could control and were more likely to choose solitude at their own discretion.^14,44 These facts indicate that solitary time does not necessarily amplify loneliness in older adults and may even have positive effects. Considering that the HLT group, which experienced high loneliness levels despite high levels of social activity, was the group that showed the strongest preference for solitude among the 3 groups. It is possible that the HLT group engages in a greater amount of social activity than what aligns with their preferences. The finding that older adults in the LST group, characterized by low loneliness levels despite low levels of social activity, exhibited satisfactory performance in solitary activities. This suggests that the LST group may have better control over their time spent in solitude than the HLT group.

The SEM results similarly suggest that the HLT group may lack control over their time spent in solitude. The HLT group is likely to engage in social activities beyond their preference for solitude. The SEM findings revealed that a higher preference for solitude was associated with lower performance of valuable social activities and further impacted the performance of solitary activities. For individuals in the HLT group who strongly prefer solitude, it is easy to imagine that exceeding the optimal level of social activity depletes their time and energy, even when engaging in performance of valuable activities with others. Therefore, for the HLT group, it is natural that individuals who prefer solitude cannot satisfactorily perform valuable activities with others. Consequently, they may not be able to allocate sufficient time and energy to solitary activities, resulting in unsatisfactory performance of those activities. Interestingly, SEM clearly demonstrated that satisfaction with solitary activities, rather than satisfaction with social activities with others, is a more proximal factor in exacerbating the discrepancy between depression and/or loneliness and social activity. Older adults inherently tend to spend more time in solitude than younger individuals.¹⁴ It may be unsurprising that satisfaction with social activities influences satisfaction with solitary activities and that solitary activities are a closer determinant of the worsening discrepancy between depression and/or loneliness and social activity than activities with others. Indeed, engaging in activities valuable to the individual has been shown to function as a protective factor against depression.⁴⁵

Furthermore, this study revealed that ultimately depression contributes to the discrepancy between social activity and loneliness in the HLT group. While the bidirectional relationship between loneliness and depression has been extensively studied and well-documented in the literature,^2,46 the findings of this study suggest that depression significantly influences the relationship between social activity and loneliness.⁴ This finding indicates that, for older adults in the HLT group, the stronger their depression, the more social activities may paradoxically amplify their loneliness. Although this result might be expected for the HLT group, characterized by high loneliness levels despite high levels of social activity, it underscores the importance of providing social activities tailored to individual preferences for solitude. Rather than uniformly recommending increased social engagement, making accommodations to consider individual preferences for solitude can enable individuals to better control their social activities, leading to greater satisfaction with their participation.

Moreover, combining interventions aimed at improving the performance of solitary activities may offer a novel approach to addressing loneliness, which has often been difficult to overcome. Most previous studies on loneliness have focused on relationships with others, social engagement, and social activities with others.^12,13,47 Few studies have considered the performance of solitary time and activities. Our findings suggest that addressing loneliness requires attention to whether individuals can perform both social and solitary activities satisfactorily. Effective interventions in these areas may have the potential to lead to the development of countermeasures for reducing loneliness tailored to individual lifestyles.

Limitations

This study has some limitations. First, it was conducted in a single town in Japan, which may have limited the generalizability of the results. However, the fact that the entire survey was conducted in one town made it possible to prevent sample errors. Additionally, the aging rate for individuals aged 65 years and older in Japan is 37.7%,⁴⁸ which aligns with nearly half of the municipalities in the country. This demographic pattern likely reflects the trends observed in many other regions of Japan. Japan, with the highest aging rate in the world, is already facing challenges that other countries are likely to encounter as their populations age.⁴⁹ However, given that Japan's aging rate is notably higher than that of many other countries, further research in diverse regions is essential to strengthen the generalizability of these findings. Second, this was a cross-sectional study. While our results suggest that personal orientation and the way one spends one’s time alone are related to loneliness, they do not indicate a causal relationship. Therefore, future longitudinal studies should examine this causal relationship. Third, we examined the factors behind discrepancies in social activity and loneliness in the HLT via SEM. However, the SEM model could explain only a small part of the discrepancies. Nevertheless, we found that an individual’s preference and time alone, which have not been focused on until now, were some factors behind the discrepancies, which is a significant finding. Further research should explore the complex involvement of additional factors in this discrepancy. Fourth, this study did not include data on personality traits, such as introversion, neuroticism, agreeableness, and openness to experience. These traits may influence the relationship between preference for solitude, performance of social and solitary activities, and depression. Therefore, future studies should include personality assessments to further elucidate the complex interactions between personal characteristics, social participation, and loneliness. Finally, the sample size was not determined using a priori power analysis. Instead, we included all eligible older adults residing in Town A to maximize representativeness and minimize selection bias. While this comprehensive approach enhances the external validity of our findings, it may limit the precision of effect size estimates.

Conclusion

This study found that older adults who experienced high loneliness levels despite high social activity often exhibited a strong preference for solitude. Our findings suggest that addressing loneliness requires more than merely increasing the frequency of social activity; it is crucial to understand individuals’ internal values and preferences for solitude. Furthermore, enhancing the satisfaction of time spent solitary, rather than solely on social activities with others, may serve as a foundation for a novel approach to reducing loneliness.

Although this study has limitations, it offers valuable insights into the complex relationship between loneliness and social activity and provides a foundation for a more comprehensive approach to older adults’ mental health. Future research should include older adults from diverse backgrounds. To develop strategies to address loneliness, it is necessary to respect each older adult’s individual values regarding solitude and tailor approaches to meet their specific needs.

Supplemental Material

sj-docx-1-inq-10.1177_00469580251360650 – Supplemental material for Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

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Supplemental material, sj-docx-1-inq-10.1177_00469580251360650 for Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study by Yuri Matsuzaki, Hiroki Okada, Maki Miyajima, Rika Hirayama and Risa Takashima in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

sj-docx-2-inq-10.1177_00469580251360650 – Supplemental material for Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

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Supplemental material, sj-docx-2-inq-10.1177_00469580251360650 for Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study by Yuri Matsuzaki, Hiroki Okada, Maki Miyajima, Rika Hirayama and Risa Takashima in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Acknowledgments

This study was conducted with the cooperation of the Community Comprehensive Support Center of Hidaka Town, Hokkaido, Japan. We would like to thank Ishizaka Nami, Iwabuchi Yumeno, Kimura Hirari, and Yamashita Ikumi for their help in data collection. We would also like to thank Editage (www.editage.jp) for the English language editing.

Footnotes

ORCID iDs: Yuri Matsuzaki Inline graphic https://orcid.org/0000-0003-2127-7028

Hiroki Okada Inline graphic https://orcid.org/0000-0002-7844-9321

Maki Miyajima Inline graphic https://orcid.org/0000-0002-0861-781X

Rika Hirayama Inline graphic https://orcid.org/0009-0009-6171-0085

Risa Takashima Inline graphic https://orcid.org/0000-0002-2480-1983

Ethical Considerations: This study was approved by the Ethical Review Committee of the Faculty of Health Sciences, Hokkaido University (No. 22-45) on August 29, 2022.

Consent to Participate: In this mail survey research, participants were provided with a research information sheet detailing the purpose, methods, ethical considerations, and voluntary nature of participation in the study. Participants were asked to review this information before responding. Consent was deemed obtained upon submission of responses.

Author Contributions: Conceptualization: R. Takashima and Y. Matsuzaki; Data curation: Y. Matsuzaki; Formal analysis: H. Okada and Y. Matsuzaki; Funding acquisition: Y. Matsuzaki; Investigation: Y. Matsuzaki; Methodology: R. Takashima, Y. Matsuzaki, M. Miyajima, and H. Okada; Project administration: R. Takashima. Resources: [Not provided]. Software: [Not .provided]. Supervision: R. Takashima; Validation: R. Takashima and H. Okada; Visualization: Y. Matsuzaki, H. Okada, and R. Takashima; Writing – original draft: Y. Matsuzaki; Writing – review and editing: R. Takashima, Y. Matsuzaki, H. Okada, M. Miyajima, and R. Hirayama

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the JSPS KAKENHI Grant Number JP21K21179.

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

Data Availability Statement: The datasets generated and/or analyzed during the current study are not publicly available due to ethical considerations and participant confidentiality. However, the data are available from the corresponding author upon reasonable request.

Supplemental Material: Supplemental material for this article is available online.

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Supplementary Materials

sj-docx-1-inq-10.1177_00469580251360650 – Supplemental material for Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

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[bibr1-00469580251360650] 1. Cacioppo S, Capitanio JP, Cacioppo JT. Toward a neurology of loneliness. Psychol Bull. 2014;140(6):1464-1504. doi: 10.1037/a0037618. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr2-00469580251360650] 2. Golden J, Conroy RM, Bruce I, et al. Loneliness, social support networks, mood and well-being in community-dwelling elderly. Int J Geriatr Psychiatry. 2009;24(7):694-700. doi: 10.1002/gps.2181. [DOI] [PubMed] [Google Scholar]

[bibr3-00469580251360650] 3. Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: a meta-analytic review. PLoS Med. 2010;7(7):e1000316. doi: 10.1371/journal.pmed.1000316. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr4-00469580251360650] 4. Zhao L, Wu L. The association between social participation and loneliness of the Chinese older adults over time—the mediating effect of social support. Int J Environ Res Public Health. 2022;19(2):815. doi: 10.3390/ijerph19020815. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr5-00469580251360650] 5. Dahlberg L, Andersson L, Lennartsson C. Long-term predictors of loneliness in old age: results of a 20-year national study. Aging Ment Health. 2018;22(2):190-196. doi: 10.1080/13607863.2016.1247425. [DOI] [PubMed] [Google Scholar]

[bibr6-00469580251360650] 6. Xu W, Hu H. Social participation and loneliness in older adults: the moderating role of views of social change. Asia Pac J Soc Work Dev. 2024. doi: 10.1080/29949769.2024.2420896 [DOI] [Google Scholar]

[bibr7-00469580251360650] 7. Victor CR, Yang K. The prevalence of loneliness among adults: a case study of the United Kingdom. J Psychol. 2012;146(1-2):85-104. doi: 10.1080/00223980.2011.6138758 [DOI] [PubMed] [Google Scholar]

[bibr8-00469580251360650] 8. Zhang W, Liu L, Tang F, Dong X. Social engagement and sense of loneliness and hopelessness: findings from the PINE Study. Gerontol Geriatr Med. 2018;4:2333721418778189. doi: 10.1177/2333721418778189 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr9-00469580251360650] 9. Olawa BD, Idemudia ES. Gender differences in the associations between forms of social engagements and loneliness in a sample of Nigerian older adults: a cross-sectional survey. Psychol Stud (Mysore). 2020;65(4):370-380. doi: 10.1007/s12646-020-00579-3 [DOI] [Google Scholar]

[bibr10-00469580251360650] 10. European Commission. Defining loneliness. Accessed May 25, 2025. https://joint-research-centre.ec.europa.eu/scientific-activities-z/loneliness/defining-loneliness_en

[bibr11-00469580251360650] 11. Liebmann M, Pitman A, Hsueh YC, Bertotti M, Pearce E. Do people perceive benefits in the use of social prescribing to address loneliness and/or social isolation? A qualitative meta-synthesis of the literature. BMC Health Serv Res. 2022;22(1):1264. doi: 10.1186/s12913-022-08656-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr12-00469580251360650] 12. Green LR, Richardson DS, Lago T, Schatten-Jones EC. Network correlates of social and emotional loneliness in young and older adults. Pers Soc Psychol Bull. 2001;27(3):281-288. doi: 10.1177/0146167201273002 [DOI] [Google Scholar]

[bibr13-00469580251360650] 13. Luhmann M, Hawkley LC. Age differences in loneliness from late adolescence to oldest old age. Dev Psychol. 2016;52(6):943-959. doi: 10.1037/dev0000117 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr14-00469580251360650] 14. Larson RW. The solitary side of life: an examination of the time people spend alone from childhood to old age. Dev Rev. 1990;10(2):155-183. doi: 10.1016/0273-2297(90)90008-R [DOI] [Google Scholar]

[bibr15-00469580251360650] 15. Baltes PB, Baltes MM. Psychological perspectives on successful aging: the model of selective optimization with compensation. In: Baltes PB, Baltes MM, eds. Successful Aging: Perspectives from the Behavioral Sciences. Cambridge University Press; 1990:1–34. doi: 10.1017/CBO9780511665684.003 [DOI] [Google Scholar]

[bibr16-00469580251360650] 16. Mroczek DK, Kolarz CM. The effect of age on positive and negative affect: a developmental perspective on happiness. J Pers Soc Psychol. 1998;75(5):1333-1349. doi: 10.1037/0022-3514.75.5.1333 [DOI] [PubMed] [Google Scholar]

[bibr17-00469580251360650] 17. Burger JM. Individual differences in preference for solitude. J Res Pers. 1995;29(1):85-108. doi: 10.1006/jrpe.1995.1005 [DOI] [Google Scholar]

[bibr18-00469580251360650] 18. Long CR, Averill JR. Solitude: an exploration of benefits of being alone. J Theory Soc Behav. 2003;33(1):21-44. doi: 10.1111/1468-5914.00204 [DOI] [Google Scholar]

[bibr19-00469580251360650] 19. Toyoshima A, Kusumi T. Examining the relationship between preference for solitude and subjective well-being among Japanese older adults. Innov Aging. 2022;6(1):igab054. doi: 10.1093/geroni/igab054 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr20-00469580251360650] 20. Imai T, Saito S. Measuring the quality of participation in activities in everyday life: developing the Self-completed Occupational Performance Index (SOPI). Jpn Occup Ther Res. 2010;29(3):317-325. doi: 10.11477/MF.6003900943 [DOI] [Google Scholar]

[bibr21-00469580251360650] 21. Kishita R, Nagaki K, Ishizuki C, Miyaguchi H. The relationship between subjective well-being, activity participation status, and basic attributes in community-dwelling older adults. Jpn Occup Ther Res. 2021;40(1):34-41. doi: 10.32178/JOTR.40.1_34 [DOI] [Google Scholar]

[bibr22-00469580251360650] 22. Donovan NJ, Blazer D. Social isolation and loneliness in older adults: review and commentary of a National Academies report. Am J Geriatr Psychiatry. 2020;28(12):1233-1244. doi: 10.1016/j.jagp.2020.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr23-00469580251360650] 23. von Elm E, Altman DG, Egger M, et al. ; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. PLoS Med. 2007;4(10):e296. doi: 10.1371/journal.pmed.0040296 [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr24-00469580251360650] 24. Yang F, Zhang J, Wang J. Correlates of loneliness in older adults in Shanghai, China: does age matter? BMC Geriatr. 2018;18:300. doi: 10.1186/s12877-018-0994-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[bibr25-00469580251360650] 25. Takagi E, Saito Y, Chan A. Gender differences in the association between social relationships and loneliness among older adults in Singapore. J Popul Res. 2020;37(3):243-263. doi: 10.1007/S12546-020-09242-0 [DOI] [Google Scholar]

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Characteristics of Older Adults Experiencing High Loneliness Despite Active Social Participation: A Cross-Sectional Study

Yuri Matsuzaki, MSc

Hiroki Okada, PhD

Maki Miyajima, PhD

Rika Hirayama, MSc

Risa Takashima, PhD

Abstract

Highlights.

Introduction

Methods

Participants

Survey Items

Demographic Characteristics

Loneliness

Frequency of Participation in Social Activities

Preference for Solitude

Performance of Social and Solitary Activities Valuable to the Individual

Depression

Data Analysis

Figure 1.

Comparative Analysis of LST, CSL, and HLT Characteristics

Examination of the Influence of Basic Attributes on the Main Variable

Characteristics of Older Adults with High Loneliness Despite High Social Activity

Model 1: Direct Effect Model

Model 2: Stepwise Causal Model

Model 3: Refined Model (Final Model)

Results

Table 1.

Comparative Analysis of LST, CSL, and HLT Characteristics

Table 2.

Examination of the Influence of Basic Attributes on the Main Variable

Characteristics of Older Adults with High Loneliness Despite High Social Activity

Table 3.

Model 1 (Direct Effect Model)

Figure 2.

Model 2 (Stepwise Causal Model)

Figure 3.

Model 3: Refined model (final model)

Figure 4.

Discussion

Limitations

Conclusion

Supplemental Material

Acknowledgments

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

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RESOURCES

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