The demographic, temporal, and regional dynamics of loneliness in long-term care in New Zealand: A secondary data analysis

doi:10.21203/rs.3.rs-8206728/v1

Download PDF

Research Article

The demographic, temporal, and regional dynamics of loneliness in long-term care in New Zealand: A secondary data analysis

https://doi.org/10.21203/rs.3.rs-8206728/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Objective(s)

The study aims to explore factors related to loneliness, its geographic distribution, and changes in its prevalence over time in long-term care facilities in New Zealand.

Methods

This study represents secondary data analysis of repeated cross-sectional data using the International Residential Assessment Instrument for Long-Term Care Facilities (interRAI LTCF) assessment collected from September 2015 to March 2023. Multivariable logistic regression was used to identify factors associated with loneliness in the current cohort, and chi-square analysis was used to test for changes in the prevalence of loneliness, stratified by ethnicity, over time as well as the significance of regional distribution between District Health Boards (DHB).

Results

In total, 494,052 records from the study period were analysed including 34,657 assessments from the most recent cohort. Of this cohort, respondents’ age group showed an inverse relationship with loneliness, females reported a higher prevalence than males, and Europeans had the highest prevalence while Pasifika had the lowest. Age group and ethnicity were also identified as predictors of loneliness in the regression model. Prevalence decreased significantly between 2016 to 2023 (7.71% vs 6.43%, p < 0.001); however, when stratified by ethnicity, only Europeans showed a significant change (7.88% vs 6.61%, p < 0.001). Differences in loneliness prevalence between DHBs were also significant (p < 0.001).

Conclusions

The study identified meaningful demographic and regional variation, and only the European population demonstrated a significant decline over the study period. Future research is needed to examine the effects of other confounding variables in these contexts.

loneliness

ethnicity

New Zealand

long-term care

temporal trend

While extensive research has studied the prevalence and factors of loneliness of older adults in New Zealand in a community context, comparatively little has been done in the way of analysis in an institutional setting and, to the best of the author’s knowledge, none have analysed loneliness after admission for long-term care residents in New Zealand on a large scale. Few studies have also researched the temporal changes in loneliness in this context internationally (Jansson et al., 2020). A systematic review and meta-analysis conducted in 2020 found international studies reported the prevalence of moderate and severe loneliness in long-term care ranged from 31%-100% and 9%-81%, respectively, varying widely depending on the method of assessment and nationality (Gardiner et al., 2020). Understanding country-specific trend in the prevalence of loneliness, associated factors, and regional distribution are crucial for directing policy intervention especially in New Zealand due to social and economic inequalities suffered by the indigenous Māori populations under colonialism. This research is also underpinned by New Zealand’s increasingly ageing and multi-ethnic population; the 2023 census revealed that 1 in 5 New Zealanders were aged 60 or above (Stats NZ, 2023a), and a third identified as an ethnicity other than European (Stats NZ, 2024b). Estimates also show the increased use of long-term care facilities with 47% of New Zealanders older than 65 predicted to access such facilities in their lifetime (Broad et al., 2015). Thus, this study aims to bridge an important gap in the current literature.

Studies widely report the many negative consequences that are associated with loneliness in older populations including higher rates of depression (Cacioppo et al., 2006; Lapane et al., 2022), anxiety (Lim et al., 2016), mortality (Luo & Waite, 2014), cognitive decline (Donovan et al., 2016), smoking, physical decline (Shankar et al., 2011), and potentially the onset of various forms of dementia (Sutin et al., 2018). Certain risk factors include visual impairment (Grow et al., 2015; Grow et al., 2009), number of and satisfaction with social relationships (Heylen, 2010), and widowhood (Yang & Gu, 2021). Individuals who report feelings of loneliness in long-term care are more likely to have an inferior quality of life, frailty, and suicidal thoughts (Cacioppo et al., 2006). The relationship between sociodemographic factors such as age, sex, and ethnicity and loneliness for older adults is inconclusive although studies generally identify a higher prevalence among females and those in older age groups (Dahlberg et al., 2021). Jamieson et al. (2017) found significant associations between loneliness and ethnicity in a home-care setting using interRAI data in New Zealand, and Bogati and Pirret (2021) found loneliness was associated with poor perceived health and fewer social networks in long-term care residents.

New Zealand was the first country to require the administration of the interRAI LTCF assessment nationwide across all aged-residential facilities in July 2015. The interRAI LTCF is a standardised and comprehensive tool that is composed of over 350 items which aims to assess the needs and characteristics of respondents including their social, functional, and clinical needs. Residents are assessed on admission and thereafter every 6 months by trained assessors, and information collected reflects observations made during the 3 days preceding the assessment. The assessment is used to inform care planning and monitor population-level changes, but it also offers a unique opportunity to systematically examine loneliness in long-term care at a national level.

The study is a retrospective secondary analysis of data created from routinely collected health-administrative data. This data, which has been de-identified and aggregated, was accessed using the Business Intelligence (BI) tool on interRAI New Zealand’s website (Data Visualisation | interRAI, n.d.).

2.1 Study Sample

The sample consisted of Māori, Pasifika, European, and Asian respondents from New Zealand who had taken an interRAI for Long-Term Care Facilities assessment anywhere between October 2015 and March 2023. The data werepresented in quarters of 3 months; two consecutive quarters were then combined to form a time interval for the purposes of this study. This was done to create a complete cross-sectional picture as residents were expected to complete an assessment every 6 months. The 4th quarter of 2022 and the first quarter of 2023 were then used to gain an understanding of the current cohort in long-term care, regional differences in loneliness prevalence, and demographic factors associated with it. For convenience, the period between September 2022 and March 2023 will be referred to as ‘2023’, and the period between October 2015 and March 2016 will be referred to as ‘2016’. The respondents were aged ≥ 65 at the time of the assessment. This yielded a total of 494,052 records, of which 34,657 were from the 2023 cohort, referred throughout the paper as the current cohort.

2.2 Data Collection

Respondents’ age group, self-identified ethnicity, sex, and the DHB where the assessment was taken were used for this study. Loneliness was identified through the question “says or indicates that he/she feels lonely” coded “yes/no”. The cohort size including lonely and non-lonely individuals was manually constructed from the ‘Outcome Scale’ on the BI tool which gave the responses of every individual across the study timeframe and could be further stratified to include the respondent’s age group, ethnicity, sex, and DHB; thus, we were able to derive the total number of each subgroup. The sample for individuals who reported feeling lonely was extracted separately through sub-selecting for the loneliness variable on the ‘Social and Wellbeing Measures’ section on the website. It then provided the aggregate number of lonely individuals across the study timeframe which could be filtered by age group, ethnicity, sex, and DHB.

2.3 Statistical Analysis

Descriptive analysis was performed to gain an understanding of the demographics of the current cohort; this is reported as percentages and frequencies. The significance of changes in loneliness over time, stratified by ethnicity, as well as regional differences in loneliness were investigated using chi-square tests. Finally, multivariable logistic regression analysis was used to find associations between age, sex and ethnicity and feelings of loneliness in the current cohort. Statistical significance was considered at p < 0.05.

3.1 Current Cohort Demographics

Of the 2023 cohort, 89% (30,886) identified as European, 5% (1,668) as Māori, 4% (1,386) as Asian and 2% (717) as Pasifika. Most respondents were women at 65% (22,384) and 35% (12,273) were men. Those 85 + constituted the largest age group at 53% (18,513) followed by those 75–84 at 34% (11,905) and 65–75 at 12% (4,239). These distributions are shown in Table 1.

Table 1
Demographic baseline and prevalence of loneliness among residents in long-term care in 2023.
	Total % (n)	% who are lonely (n)
Sex
Male	35 (12,273)	6 (760)
Female	65 (22,384)	7 (1,468)
Age
65–74	12 (4,239)	7 (292)
75–84	34 (11,905)	7 (815)
85+	53 (18,513)	6 (1,121)
Ethnicity
Europeans	89 (30,886)	7 (2,042)
Māori	5 (1,668)	5 (90)
Asian	4 (1,386)	5 (75)
Pasifika	2 (717)	3 (21)
Total	100 (34,657)	6 (2,228)

3.2 Current Cohort Loneliness

In this cohort, the oldest age group (85+) reported the lowest prevalence of loneliness (6%), while younger groups reported higher prevalence (75–84: 7%; 65–74: 7%). Europeans reported the highest prevalence of loneliness (7%) followed by Asian (5%) and Māori (5%) populations, while those identifying as Pasifika reported the lowest (3%). Females reported higher rates of loneliness (7%) than their male counterparts (6%). The overall rate of loneliness among the entire cohort was 6%.

Table 2 displays the results of the multivariable logistic regression analysis. Age group and ethnicity were found to be predictors of loneliness with younger cohorts (65–74: aOR = 1.23 [95% CI 1.07–1.41]; 75–84: aOR: 1.18 [95% CI 1.07–1.29]) and Europeans identified as having higher risk of loneliness, while Māori (aOR: 0.76 [95% CI 0.61, 0.95]) and Pasifika (aOR: 0.41 [95% CI 0.26, 0.63]) were less likely to report loneliness. Sex was not shown to be a significant predictor of loneliness.

Table 2
Multivariable logistic regression analysis of associated factors with loneliness.
	aOR (95% CI)	p value
Sex
Female	1.00
Male	0.92 (0.84–1.01)	0.083
Age
85+	1.00
75–84	1.18 (1.07–1.29)	0.003
65–74	1.23 (1.07–1.41)	< 0.001
Ethnicity
European	1.00
Māori	0.76 (0.61–0.95)	0.015
Asian	0.80 (0.63–1.01)	0.061
Pasifika	0.41 (0.26–0.63)	< 0.001
Note: CI: confidence interval; aOR: adjusted odds ratio

In 2023, rates of loneliness were highest in Wairarapa DHB at 8.7% (38) and lowest in West Coast DHB at 4.5% (8), and a significant association is noted (P < 0.001). The results are displayed in Table 3.

Table 3
Geographic distribution of loneliness prevalence by DHB in long-term care facilities in 2023.
New Zealand DHB	n	Lonely %	p value
Northland	1155	6.9	< 0.001
Waitemata	3705	6.3
Auckland	3342	5.4
Counties Manukau	2428	4.9
Waikato	2978	8.3
Lakes	720	6.4
Bay of Plenty	2019	7.2
Tairawhiti	306	6.5
Taranaki	1176	4.7
Hawke's Bay	1290	5.7
Mid Central	1573	8.1
Whanganui	526	6.8
Capital and Coast	1982	5.2
Hutt Valley	960	6.3
Wairarapa	438	8.7
Nelson Marlborough	1348	7.2
West Coast	178	4.5
Canterbury	5005	5.6
South Canterbury	543	8.1
Southern	2985	7.8

3.3 Changes over Time

As shown in Table 4, the overall prevalence of loneliness decreased significantly from 7.7% in 2016 to 6.4% in 2023 (p < 0.001). Across the four ethnicities included in this study, only Europeans showed a significant change (p < 0.001) in the same time period decreasing from 7.9% to 6.6%.

Table 4
Prevalence of loneliness for New Zealanders in long-term care aged ≥ 65 over time stratified by ethnicity.
	2016-Q1	2016-Q3	2017-Q1	2017-Q3	2018-Q1	2018-Q3	2019-Q1	2019-Q3	2020-Q1	2020-Q3	2021-Q1	2021-Q3	2022-Q1	2022-Q3	2023-Q1	p value
%European	7.88	7.45	7.55	7.22	7.02	6.78	6.66	6.90	6.91	6.77	6.82	6.65	6.80	6.64	6.61	< 0.001
%Māori	5.56	4.89	4.63	4.95	4.12	5.59	6.03	4.37	4.07	4.17	4.89	4.17	5.62	5.39	5.40	0.206
%Asian	7.04	7.02	6.50	5.97	7.03	7.18	7.57	8.51	7.47	6.85	7.15	7.44	6.58	6.69	5.41	0.530
%Pasifika	4.95	5.71	5.81	5.39	5.07	3.88	4.78	3.88	4.89	5.55	5.96	4.65	4.55	3.69	2.93	0.278
%Total	7.71	7.30	7.38	7.06	6.86	6.69	6.63	6.78	6.77	6.64	6.73	6.53	6.70	6.52	6.43	< 0.001
Note each time interval includes 2 quarters; the quarter displayed on the table represents the last of the two quarters

The purpose of this study was to provide an initial, exploratory view of loneliness in New Zealand’s long-term care facilities and its changes over time. Our study found that 6.43% of the latest cohort reported feelings of loneliness. Due to the heterogeneous nature of loneliness evaluation between studies and cohort composition, wide differences in prevalence are expected. This figure may in part reflect interRAI LTCF’s dichotomous treatment of loneliness and which only reflects residents’ state during a certain period. Even with this limitation, across international assessments, this still appears to be an extremely low value (Gardiner et al., 2020). A similarly low prevalence was reported among sampled long-term care residents in Auckland, New Zealand (Bogati & Pirret, 2021).

While we were unable to identify a significant association between loneliness and sex, it was more common in women than men. The literature suggests a complicated picture, but studies generally show a higher prevalence of loneliness for women; however, independent associations between sex and loneliness is often contradictory and dependent on the nature of analysis (Dahlberg et al., 2021; Jamieson et al., 2017).

Self-identified ethnicity was found to be a predictor of loneliness in our regression model. Māori and Pasifika respondents showed a significantly lower reported rate than Europeans. The observed ethnic distribution of loneliness could also be paralleled with a study by Jamieson et al. (2017) which found the highest prevalence of loneliness in home-care among Asians followed by Europeans and Māori, and then Pasifika; they also identified ethnicity as a factor of loneliness.

Studies have predominantly found age as having a positive or non-significant association with loneliness in older adults (Dahlberg et al., 2021). Our results showed the converse as we found younger age groups reported a significantly higher prevalence of loneliness than those 85+. However, research on this is not universal and certain studies do support our findings (Christina et al., 2005). A systematic review and meta-analysis by Gardiner et al. (2020) also found that studies with a lower mean age had a comparably higher prevalence of loneliness though this comes with some acute generalisation.

The results of this study show a statistically significant decrease in loneliness for Europeans and, likely as a result of their overwhelming makeup, the total cohort. Studies surrounding temporal trends of loneliness in older adults generally show a decreasing or unchanging relationship, contrary to popular perception (Jansson et al., 2020; Dykstra, 2009), which agrees with our findings. While the general decrease irrespective of ethnicity is encouraging, more work is needed to understand differences between ethnicities in this regard.

Significant regional differences in loneliness prevalence were also noted. Our study showed that Wairarapa DHB had the highest prevalence of loneliness which is consistent with findings from New Zealand’s home-care (Beere et al., 2019), and that West Coast DHB had the lowest prevalence. Interestingly, in the same year, Wairarapa and West Coast DHB also reported the highest and lowest percentage of long-term care facilities with vacancies, respectively, in New Zealand (Aged Care Funding and Service Models Review, 2018). This correspondence should be interpreted cautiously but may warrant future investigation.

The findings of this study help to provide insight into the prevalence, regional distribution, and associated demographic factors of loneliness in long-term care in New Zealand as well as its change over time. While the overall prevalence of loneliness reported was relatively low and found to have significantly decreased over time, this is likely an underestimation and the decrease was only reflected for Europeans. Efforts at intervention are still crucial to help mitigate and prevent loneliness’ adverse effects in old age.

4.1 Limitations

Several important limitations underlie the research that came as a consequence of using the BI tool. Potentially confounding factors such as participants’ cognitive and/or functional disabilities and mental health condition were not included in this study. These factors impact the generalisability of our findings. Another limitation was our inability to differentiate unique individuals; rather, we could only work with anonymised data. To ensure we were analysing unique individuals in our logistic regression analysis, we were only able to use the most recent cohort, providing a relatively small sample size for ethnic minority groups. There is also the possibility that the general decrease in loneliness was confounded by survivorship bias and/or a change in the cohort composition as we cannot determine the individuals we were analysing in each time interval. This means that while our temporal analysis was able to demonstrate that prevalence of loneliness decreased among those surveyed in long-term care facilities over time, we cannot make inference at the individual-level. The nature of the interRAI LTCF assessment, which treats loneliness as a dichotomous measure and reflects only the previous three days, may also result in an underestimation of the prevalence of loneliness in long-term care facilities. Finally, the cross-sectional nature of this research means no causal relationship can be determined.

This paper addresses an important gap in the understanding of loneliness in New Zealand’s long-term care facilities and aims to provide an initial framework for further research. Given the extensive literature on the adverse effects of loneliness at older ages, understanding its distribution is important for informing efforts to better support the wellbeing of residents in long-term care. Our study identified ethnicity and age group as predictors of loneliness. Those who were aged 65–74 and 75–84 were more likely to be lonely than their 85 + counterparts, contradicting much of the international literature. Europeans were also found to have higher risks of loneliness than those who identified as Māori or Pasifika. The change in prevalence of loneliness over time was significant, but when stratified by ethnicity, only Europeans showed a significant change. Finally, regional differences in loneliness between DHBs were identified as significant. Future research should aim to explore the effects of other confounding variables on loneliness in long-term care.

Informed Consent

Consent was not necessary for this study as it utilises secondary data available through interRAI New Zealand’s Data Visualisation tool. Informed consent for assessment is obtained by trained interRAI assessors.

Ethical Approval

This study involved secondary analysis of publicly available, fully anonymised and aggregated data, and therefore did not require ethics approval.

Funding

This study did not receive any funding.

Author Contribution

The author was responsible for the conception, design, data collection, analysis, interpretation, and writing of the manuscript.

Acknowledgement

I would like to recognise the generous time commitment Ulrich Bergler and Dr Tom Hawkins provided throughout the research process who were both patient and comprehensive in answering queries and helped guide the direction of research questions to no benefit of their own. I'm especially indebted to the help Ulrich Bergler provided during the early stages of this study and during the review process despite having absolutely no prior connection with the author. I’d like to additionally thank Dr Hawkins for reviewing the manuscript before submission.

Data Availability

All data used in this study could be found via the interRAI New Zealand's “Data Visualisation” tool using the following URL: https://www.interrai.co.nz/data-research-and-reporting/data-visualisation

Jansson, A. H., Savikko, N., Kautiainen, H., Roitto, H. M., & Pitkälä, K. H. (2020). Changes in prevalence of loneliness over time in institutional settings, and associated factors. Gerontology and Geriatrics, 89, 104043. https://doi.org/10.1016/j.archger.2020.104043
Gardiner, C., Laud, P., Heaton, T., & Gott, M. (2020). What is the prevalence of loneliness amongst older people living in residential and nursing care homes? A systematic review and meta-analysis. Age And Ageing, 49(5). https://doi.org/10.1093/ageing/afaa049
(2023). Census population, dwelling, and housing highlights | Stats NZ. Govt.nz. Published 2023. https://www.stats.govt.nz/information-releases/2023-census-population-dwelling-and-housing-highlights/
Stats, N. Z. (2023). Census population counts (by ethnic group, age, and Māori descent) and dwelling counts | Stats NZ. www.stats.govt.nz. Published 2024. https://www.stats.govt.nz/information-releases/2023-census-population-counts-by-ethnic-group-age-and-maori-descent-and-dwelling-counts/
Broad, J. B., Ashton, T., Gott, M., McLeod, H., Davis, P. B., & Connolly, M. J. (2015). Likelihood of residential aged care use in later life: a simple approach to estimation with international comparison. Australian and New Zealand Journal of Public Health, 39(4), 374–379. https://doi.org/10.1111/1753-6405.12374
Cacioppo, J. T., Hughes, M. E., Waite, L. J., Hawkley, L. C., & Thisted, R. A. (2006). Loneliness as a specific risk factor for depressive symptoms: Cross-sectional and longitudinal analyses. Psychology and Aging, 21(1), 140–151. https://doi.org/10.1037/0882-7974.21.1.140
Lapane, K. L., Lim, E., McPhillips, E., Barooah, A., Yuan, Y., & Dube, C. E. (2022). Health effects of loneliness and social isolation in older adults living in congregate long term care settings: A systematic review of quantitative and qualitative evidence. Gerontology and Geriatrics, 102(102), 104728. https://doi.org/10.1016/j.archger.2022.104728
Lim, M. H., Rodebaugh, T. L., Zyphur, M. J., & Gleeson, J. F. M. (2016). Loneliness over time: The crucial role of social anxiety. Journal of Abnormal Psychology, 125(5), 620–630. https://doi.org/10.1037/abn0000162
Luo, Y., & Waite, L. J. (2014). Loneliness and Mortality Among Older Adults in China. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 69(4), 633–645. https://doi.org/10.1093/geronb/gbu007
Donovan, N. J., Wu, Q., Rentz, D. M., Sperling, R. A., Marshall, G. A., & Glymour, M. M. (2016). Loneliness, depression and cognitive function in older U.S. adults. International Journal of Geriatric Psychiatry, 32(5), 564–573. https://doi.org/10.1002/gps.4495
Shankar, A., McMunn, A., Banks, J., & Steptoe, A. (2011). Loneliness, social isolation, and behavioral and biological health indicators in older adults. Health Psychology, 30(4), 377–385. https://doi.org/10.1037/a0022826
Sutin, A. R., Stephan, Y., Luchetti, M., & Terracciano, A. (2018). Loneliness and Risk of Dementia. The Journals of Gerontology: Series B, 75(7). https://doi.org/10.1093/geronb/gby112
Grow, S. J. L., Towers, A., Yeung, P., Alpass, F., & Stephens, C. (2015). The Relationship between Loneliness and Perceived Quality of Life among Older Persons with Visual Impairments. Journal of Visual Impairment & Blindness, 109(6), 487–499. https://doi.org/10.1177/0145482x1510900606
Grow, S. J. L., Alpass, F., Stephens, C., Economic, & Standing (2009). Health Status and Social Isolation among Visually Impaired Persons Aged 55 to 70 in New Zealand. Journal of Optometry, 2(3), 155–158. https://doi.org/10.3921/joptom.2009.155
HEYLEN L. The older, the lonelier? Risk factors for social loneliness in old age. Ageing and Society. (2010). ;30(7):1177–1196. https://doi.org/10.1017/s0144686x10000292
Yang, F., & Gu, D. (2021). Widowhood, widowhood duration, and loneliness among older adults in China. Social Science & Medicine, 283, 114179. https://doi.org/10.1016/j.socscimed.2021.114179
Dahlberg, L., McKee, K. J., Frank, A., & Naseer, M. (2021). A systematic review of longitudinal risk factors for loneliness in older adults. Aging & Mental Health, 26(2), 1–25. https://doi.org/10.1080/13607863.2021.1876638
Jamieson, H. A., Gibson, H. M., Abey-Nesbit, R., Ahuriri-Driscoll, A., Keeling, S., & Schluter, P. J. (2017). Profile of ethnicity, living arrangements and loneliness amongst older adults in Aotearoa New Zealand: A national cross-sectional study. Australasian Journal on Ageing, 37(1), 68–73. https://doi.org/10.1111/ajag.12496
Bogati, R., & Pirret, A. (2021). Loneliness among older people living in long-term care settings in a metropolitan city in Aotearoa New Zealand. Nursing Praxis Aotearoa New Zealand, 37(2), 24–34. https://doi.org/10.36951/27034542.2021.021
Data Visualisation | interRAI www.interrai.co.nz. https://www.interrai.co.nz/data-research-and-reporting/data-visualisation-2
Jansson, A. H. (2020). Loneliness of older people in long-term care facilities. Doctoral Dissertation. Department of General Practice and Primary Health Care, Faculty of Medicine, University of Helsinki. https://helda.helsinki.fi/handle/10138/319092.
VICTOR, C. H. R. I. S. T. I. N. A. R., & SASHA J. SCAMBLER, ANN, B. O. W. L. I. N. G. (2005). The prevalence of, and risk factors for, loneliness in later life: a survey of older people in Great Britain. Ageing and Society, 25(06), 357–375. https://doi.org/10.1017/s0144686x04003332
Dykstra, P. A. (2009). Older adult loneliness: myths and realities. European Journal of Ageing, 6(2), 91–100. https://doi.org/10.1007/s10433-009-0110-3
Beere, P., Keeling, S., & Jamieson, H. (2019). Ageing, loneliness, and the geographic distribution of New Zealand’s interRAI-HC cohort. Social Science & Medicine, 227, 84–92. https://doi.org/10.1016/j.socscimed.2018.08.002
Aged Care Funding and Service Models Review - Health New Zealand | Te Whatu Ora. Govt.nz. Published 2018. https://www.tewhatuora.govt.nz/for-health-professionals/clinical-guidance/specific-life-stage-health-information/health-of-older-people/aged-care-funding-and-service-models-review

No competing interests reported.

Download PDF

Reviews received at journal
28 Dec, 2025
Reviewers agreed at journal
08 Dec, 2025
Reviewers invited by journal
04 Dec, 2025
Editor assigned by journal
27 Nov, 2025
Submission checks completed at journal
27 Nov, 2025
First submitted to journal
25 Nov, 2025

You are reading this latest preprint version

The demographic, temporal, and regional dynamics of loneliness in long-term care in New Zealand: A secondary data analysis

Status:

Version 1

Abstract

Objective(s)

Methods

Results

Conclusions

1 Introduction

2 Methods

2.1 Study Sample

2.2 Data Collection

2.3 Statistical Analysis

3 Results

3.1 Current Cohort Demographics

3.2 Current Cohort Loneliness

3.3 Changes over Time

4 Discussions

4.1 Limitations

5 Conclusions

Declarations

Informed Consent

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1