Evidence map›Paper›PMID 36123061›Full record

SynthesisBMJ open2022

Patient-reported outcome measures to detect intentional, mixed, or unintentional non-adherence to medication: a systematic review.

Mathumalar Loganathan Fahrni, Kamaliah Md Saman, Ali Saleh Alkhoshaiban, Faiza Naimat, Farzan Ramzan, Khairil Anuar Md Isa

Abstract readSystematic Review
In one paragraph

Synthesis in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Innovative Approaches to Enhance and Measure Medication Adherence in Chronic Disease Management: A Review.Medical science monitor : international medical journal of experimental and clinical research · 2024
    Review
  10. Article
  11. 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.

Mathumalar Loganathan FahrniFaculty of Pharmacy, Universiti Teknologi MARA, Puncak Alam Campus, Selangor, Malaysia mathumalar@gmail.com.ORCID 0000-0002-9042-4290
Kamaliah Md SamanFaculty of Pharmacy, Universiti Teknologi MARA, Puncak Alam Campus, Selangor, Malaysia.
Ali Saleh AlkhoshaibanUnaizah College of Pharmacy, Qassim University, Buraydah, Saudi Arabia.
Faiza NaimatFaculty of Pharmacy, Universiti Teknologi MARA, Puncak Alam Campus, Selangor, Malaysia.
Farzan RamzanDepartment of Primary Care and Public Health, Imperial College London, London, UK.ORCID 0000-0002-6861-2324
Khairil Anuar Md IsaFaculty of Health Sciences, Universiti Teknologi MARA, Puncak Alam Campus, Selangor, Malaysia.ORCID 0000-0001-6249-6476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo categorise patient-reported outcome measures (PROMs) into their propensity to detect intentional and/or unintentional non-adherence to medication, and synthesise their psychometric properties.

designSystematic review and regression analysis. ELIGIBILITY: Medication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded. DATA SOURCES: Using detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used. DATA ANALYSIS: Risk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses. OUTCOME MEASURES: Process domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence.

resultsPaper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by β=0.79 and β=0.34 units, respectively (R

conclusionsTen PROMs had

Indexed as

Medication AdherencePatient Reported Outcome MeasuresHumansPsychometricsReproducibility of ResultsSurveys and Questionnairesclinical auditprimary carepublic health

Identifiers

PMID36123061
PMCPMC9486224

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.