Evidence map›Paper›PMID 27540286›Full record

ArticleClinical interventions in aging2016

The social network index and its relation to later-life depression among the elderly aged ≥80 years in Northern Thailand.

Myo Nyein Aung, Saiyud Moolphate, Thin Nyein Nyein Aung, Chitima Katonyoo, Songyos Khamchai, Pongsak Wannakrairot

Abstract read
In one paragraph

Article in Clinical interventions in aging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Social Support for Thai Adults with Type 2 Diabetes: A Case-Control Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024
    Article
  15. Article
  16. Article
  17. Article
  18. Social Support and Symptoms of Depression in Late Life: Bidirectional Associations over Time.International journal of environmental research and public health · 2022
    Article
  19. Social Frailty and Meaningful Activities among Community-Dwelling Older Adults with Heart Disease.International journal of environmental research and public health · 2022
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Myo Nyein AungFaculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Saiyud MoolphateDepartment of Public Health, Chiang Mai Rajabhat University, Chiang Mai, Thailand.
Thin Nyein Nyein AungDepartment of Public Health, Juntendo University School of Medicine, Tokyo, Japan.
Chitima KatonyooDepartment of Public Health, Chiang Mai Rajabhat University, Chiang Mai, Thailand.
Songyos KhamchaiChiang Mai Provincial Health Office, Chiang Mai, Thailand.
Pongsak WannakrairotFaculty of Medicine, Chulalongkorn University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHaving a diverse social network is considered to be beneficial to a person's well-being. The significance, however, of social network diversity in the geriatric assessment of people aged ≥80 years has not been adequately investigated within the Southeast Asian context. This study explored the social networks belonging to the elderly aged ≥80 years and assessed the relation of social network and geriatric depression.

methodsThis study was a community-based cross-sectional survey conducted in Chiang Mai Province, Northern Thailand. A representative sample of 435 community residents, aged ≥80 years, were included in a multistage sample. The participants' social network diversity was assessed by applying Cohen's social network index (SNI). The geriatric depression scale and activities of daily living measures were carried out during home visits. Descriptive analyses revealed the distribution of SNI, while the relationship between the SNI and the geriatric depression scale was examined by ordinal logistic regression models controlling possible covariants such as age, sex, and educational attainment.

resultsThe median age of the sample was 83 years, with females comprising of 54.94% of the sample. The participants' children, their neighbors, and members of Buddhist temples were reported as the most frequent contacts of the study participants. Among the 435 participants, 25% were at risk of social isolation due to having a "limited" social network group (SNI 0-3), whereas 37% had a "medium" social network (SNI 4-5), and 38% had a "diverse" social network (SNI ≥6). The SNI was not different among the two sexes. Activities of daily living scores in the diverse social network group were significantly higher than those in the limited social network group. Multivariate ordinal logistic regression analysis models revealed a significant negative association between social network diversity and geriatric depression.

conclusionRegular and frequent contact with various social contacts may safeguard common geriatric depression among persons aged ≥80 years. As a result, screening those at risk of social isolation is recommended to be integrated into routine primary health care-based geriatric assessment and intervention programs.

Indexed as

Interpersonal RelationsSocial SupportActivities of Daily LivingAged, 80 and overCross-Sectional StudiesDepressionFamilyFemaleFriendsGeriatric AssessmentHumansLogistic ModelsMaleQuality of LifeThailandagingChiang Maicommunitygerontologypsychogeriatricssociology of agingSoutheast Asia

Identifiers

PMID27540286
PMCPMC4982492

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.