Evidence map›Paper›PMID 39685094›Full record

ArticleHealthcare (Basel, Switzerland)2024

The Effects of Motivational Interviews About Activities of Daily Living on Physical Adjustment and Quality of Life in Elderly Total Knee Arthroplasty Patients: A Randomised-Controlled Trial.

Gizem Kubat Bakir, Sonay Göktas

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. 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. Guideline
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.

Gizem Kubat BakirSchool of Nursing, Maltepe University, Istanbul 34857, Turkey.ORCID 0000-0003-4294-0669
Sonay GöktasHamidiye Faculty of Nursing, University of Health Sciences, Istanbul 34668, Turkey.ORCID 0000-0002-8168-1287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In old age, knee osteoarthritis is a common disease that reduces mobility. Total knee arthroplasty (TKA) is, in fact, a very important surgery to treat severe knee osteoarthritis. This study aimed to analyse the effect of motivational interviewing (MI) on physical adjustment and quality of life among old patients after TKA. Self-assessment forms were applied before and after the intervention using the functional assessment form and SF-36 Quality of Life Questionnaire in both groups: the intervention group who received MI targeted at daily living activities and the control group who received usual care within a randomised controlled trial that included 70 participants. The results we obtained showed significantly higher functional capacity scores and QOLs among those who underwent MI than those who did not have this additional support, while showing strong adjusted mean differences between two interventions that indicate this effect size difference. There was a notable increase in SF-36 scores from 51.14 to 85.77 which was much higher than the control's rise from 45.97 to 59.46. Therefore, these findings suggest that many elderly people can greatly improve their health status after TKA with MI as it offers an opportunity for effective recovery during the post-operative period, especially among older adults. Therefore, it can be used as an efficient method included in standard routines after operations so that results are improved and patients' satisfaction levels also increased simultaneously too.

Indexed as

activities of daily livingmotivational interviewphysical adjustmentquality of life

Identifiers

PMID39685094
PMCPMC11641200

What OpenQuestion holds

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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.