Evidence map›Paper›PMID 26107637›Full record

ReviewPloS one2015

Targeting Medication Non-Adherence Behavior in Selected Autoimmune Diseases: A Systematic Approach to Digital Health Program Development.

Trevor van Mierlo, Rachel Fournier, Michael Ingham

Open access · goldAbstract readReview
In one paragraph

Review in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 pooled it
5.9field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 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 2 institutions in 2 countries.

Trevor van MierloEvolution Health Systems Inc., 1266 Queen Street West, Suite 8, Toronto, Ontario, M6K 1L3, Canada; Research Associate, Henley Business School, University of Reading, Greenlands, Henley-on-Thames, Oxfordshire, RG9 3AU, United Kingdom.
Rachel FournierEvolution Health Systems Inc., 1266 Queen Street West, Suite 8, Toronto, Ontario, M6K 1L3, Canada; Research Associate, Henley Business School, University of Reading, Greenlands, Henley-on-Thames, Oxfordshire, RG9 3AU, United Kingdom.
Michael InghamJanssen Scientific Affairs LLC, 850 Ridgeview Dr., Horsham, Pennsylvania, 19044, United States of America.
University of Reading · GBRidgeview · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn's Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans.

objectiveDigital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies.

methodsGrounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn's Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence.

resultsOut of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%).

conclusionsThis study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Indexed as

Grounded TheoryAutoimmune DiseasesFemaleHealth Care CostsHealth PromotionHumansInternetMaleMedication AdherenceModels, TheoreticalPatient Education as TopicProgram DevelopmentQuality of LifeReminder SystemsRisk FactorsText Messaging

Identifiers

PMID26107637
PMCPMC4481109
OpenAlexW1913393683

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.