ArticleBMJ open2013
Doctors' understanding of individualisation of drug treatments: a qualitative interview study.
Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- In-silico personalized protein-protein interaction networks prioritize candidate compounds for glioblastoma.PLoS computational biology · 2026Article
- Racial and ethnic minority patient participation in N-of-1 trials: perspectives of healthcare providers and patients.Personalized medicine · 2021Article
- Article
- We need to talk about purpose: a critical interpretive synthesis of health and social care professionals' approaches to self-management support for people with long-term conditions.Health expectations : an international journal of public participation in health care and health policy · 2017Review
- Individualized Integrative Cancer Care in Anthroposophic Medicine: A Qualitative Study of the Concepts and Procedures of Expert Doctors.Integrative cancer therapies · 2016Article
- Supporting the self-management of hypertension: Patients' experiences of using a mobile phone-based system.Journal of human hypertension · 2016Article
- We need more guidance on shared decision making.The British journal of general practice : the journal of the Royal College of General Practitioners · 2015Article
- Individualisation of drug treatments for patients with long-term conditions: a review of concepts.BMJ open · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore doctors' understanding of individualisation of drug treatments, and identify the methods used to achieve individualisation.
designIn this exploratory study, we used in-depth qualitative interviews with doctors to gain insight into their understanding of the term 'individualised treatments' and the methods that they use to achieve it.
participants16 general practitioners in 6 rural and 10 urban practices, 2 geriatricians and 2 clinical academics were recruited.
settingPrimary and secondary care in South West of England.
resultsUnderstanding of individualisation varied between doctors, and their initial descriptions of individualisation were not always consistent with subsequent examples of the patients they had treated. Understandings of, and methods used to achieve, individualised treatment were frequently discussed in relation to making drug treatment decisions. Few doctors spoke of using strategies to support patients to individualise their own treatments after the consultation.
conclusionsDespite its widespread use, variation in doctors' understanding of the term individualisation highlights the need for it to be defined. Efforts are needed to develop effective methods that would offer a structured approach to support patients to manage their treatments after consultations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.