Evidence map›Paper›PMID 39837562›Full record

ArticleBritish journal of clinical pharmacology2025

Risk of bias tools for medication adherence research: RoBIAS and RoBOAS.

Klarissa A Sinnappah, Dyfrig A Hughes, Sophie L Stocker, Daniel F B Wright, ESPACOMP the International Society for Medication Adherence

Abstract read
In one paragraph

Article in British journal of clinical pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Risk of bias tools for medication adherence research: RoBIAS and RoBOAS.British journal of clinical pharmacology · 2025
    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

5 authors.

Klarissa A SinnappahSchool of Pharmacy, University of Otago, Dunedin, New Zealand.ORCID https://orcid.org/0000-0002-6813-6022
Dyfrig A HughesCentre for Health Economics and Medicines Evaluation, Bangor University, Bangor, UK.ORCID https://orcid.org/0000-0001-8247-7459
Sophie L StockerSydney Pharmacy School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-2114-587X
Daniel F B WrightSydney Pharmacy School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0001-9313-9252
ESPACOMP the International Society for Medication Adherence

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsAn unbiased means of documenting medication-taking is important to ensure quality evidence about adherence research and to accurately identify individuals at risk of suboptimal adherence for the development of targeted and effective interventions. Guidance to assist researchers in the understanding of risk of bias when conducting or reviewing adherence research is currently not available. To address this gap, tools to identify and gauge the magnitude of important biases that may impact adherence research have been developed.

methodsThe Risk of Bias tool for Interventional Adherence Studies (RoBIAS) and the Risk of Bias tool for Observational Adherence Studies (RoBOAS) were constructed from a literature review of key adherence guidelines/frameworks, drafted initially through author consensus. The draft bias tools were piloted and evaluated with expert adherence researchers through an online survey platform to assess the internal consistency and agreement in responses, including gather "free text" feedback to improve the tool's utility.

resultsOf the 121 approached reviewers, only 20 out of the 30 reviewers who consented to participate completed the piloting of the tools. Both tools are structured around four domains relating to: (i) study design, (ii) randomization (RoBIAS tool) and confounding factors (RoBOAS tool), (iii) adherence outcome measurement, and (iv) data analysis. Each domain consists of items/statements, mapped to specific biases relevant to adherence research and study designs, including a domain-based ranking scale to determine the appropriate risk of bias judgement.

conclusionsThe tools are intended to have utility when systematically reviewing adherence research and to inform the design of future adherence studies.

Indexed as

Medication AdherenceResearch DesignBiasHumansObservational Studies as Topicbias in medical researchmedication adherencerisk of bias tools

Identifiers

PMID39837562
PMCPMC12035589

What OpenQuestion holds

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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.