Evidence map›Paper›PMID 41583970›Full record

ArticleJournal of Korean gerontological nursing2023

Health-related quality of life for older patients with chronic low back pain: A structural equation modeling study.

Suin Lee, Eun-Ju Lee

Abstract read
In one paragraph

Article in Journal of Korean gerontological nursing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

2 authors.

Suin LeeAssistant Professor, Department of Nursing, Yeungjin University, Daegu, Korea.ORCID 0000-0001-8739-4433
Eun-Ju LeeAssociate Professor, Department of Nursing, Keimyung University, Daegu, Korea.ORCID 0000-0001-9637-1778

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to develop and validate a structural equation model for health-related quality of life in older patients with chronic low back pain. Methods: We selected social support, symptoms, fear-avoidance beliefs, functional disability, health perception, and health-related quality of life as the main variables based on Wilson and Cleary's model of health-related quality of life. A total of 211 participants aged ≥65 years who had been diagnosed with low back pain for more than three months were considered in this study. Data were collected from two hospitals in D Metropolitan City and A City, one public health center, and two senior citizen centers. We utilized SPSS/WIN 24.0 and R package 'plspm' (R Version 3.1.3) for data analysis. Results: The overall fit of the proposed hypothesized model was .53, which met the acceptable threshold, confirming the adequacy of the model's fit. Social support, symptoms, fear-avoidance beliefs, functional disability, and health perception were statistically significant variables in the health-related quality of life, and the explanatory power of these variables was 75.1%. Out of the 15 hypotheses in the model, 13 hypotheses were supported. Conclusion: The model showed 12 significant direct effects, one significant indirect effect, and 13 significant total effects (both direct and indirect). To enhance the health-related quality of life in older patients with chronic low back pain, alleviating fear-avoidance beliefs and functional disability is necessary and improving positive social resources such as social support and health perception is essential.

Indexed as

Chronic low back painHealth-related quality of lifeStructural equation modeling

Identifiers

PMID41583970
PMCPMC12384334

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.