Evidence map›Paper›PMID 36328237›Full record

ArticleOsong public health and research perspectives2022

Effects of medication adherence interventions for older adults with chronic illnesses: a systematic review and meta-analysis.

Hae Ok Jeon, Myung-Ock Chae, Ahrin Kim

Open access · diamondAbstract read
In one paragraph

Article in Osong public health and research perspectives, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

14 citing papers in PubMed, 15 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Hae Ok JeonDepartment of Nursing, Cheongju University, Cheongju, Korea.
Myung-Ock ChaeDepartment of Nursing, Cheongju University, Cheongju, Korea.
Ahrin KimDepartment of Nursing, Cheongju University, Cheongju, Korea.
Cheongju University · KR

Funding

National Research Foundation of Korea No. 2019R1G1A1008910
6 · The paper itself

Abstract

This systematic review and meta-analysis aimed to understand the characteristics of medication adherence interventions for older adults with chronic illnesses, and to investigate the average effect size by combining the individual effects of these interventions. Data from studies meeting the inclusion criteria were systematically collected in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The results showed that the average effect size (Hedges' g) of the finally selected medication adherence interventions for older adults with chronic illnesses calculated using a random-effects model was 0.500 (95% confidence interval [CI], 0.342-0.659). Of the medication adherence interventions, an implementation intention intervention (using face-to-face meetings and telephone monitoring with personalized behavioral strategies) and a health belief model-based educational program were found to be highly effective. Face-to-face counseling was a significantly effective method of implementing medication adherence interventions for older adults with chronic illnesses (Hedges' g=0.531, 95% CI, 0.186-0.877), while medication adherence interventions through education and telehealth counseling were not effective. This study verified the effectiveness of personalized behavioral change strategies and cognitive behavioral therapy based on the health belief model, as well as face-to-face meetings, as medication adherence interventions for older adults with chronic illnesses.

Indexed as

AgedChronic diseaseMedication adherenceMeta-analysisReview

Identifiers

PMID36328237
PMCPMC9633263
OpenAlexW4304588946

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.