Evidence map›Paper›PMID 42667038›Full record

ArticleMethodsX2026

The guided-research-garden method: A blended self-directed learning approach for enhancing evidence-based medicine research competencies

Rungrat Ponsawat, Worarat Pathumcharoenwattana, Chiroj Soorapanth

Abstract read
In one paragraph

Article in MethodsX, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rungrat PonsawatDepartment of Lifelong Education, Faculty of Education, Chulalongkorn University, Bangkok, 10330, Thailand.
Worarat PathumcharoenwattanaDepartment of Lifelong Education, Faculty of Education, Chulalongkorn University, Bangkok, 10330, Thailand.
Chiroj SoorapanthDepartment of Orthopaedics, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, 10300, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Development of medical education and training to enhance physicians' research competencies is challenging due to time constraints and heavy clinical workloads. This article presents the Guided-Research-Garden (GRG) method, which embeds our self-directed learning (SDL) program. The GRG method is designed to assist physicians in conducting evidence-based medical (EBM) research. The empathy maps and learning contracts are compiled as input data to analyse personalised learner preparedness. The mixed method was developed for the progression, which consists of individual analysis, program implementation, and rigorous learning assessment. The output data revealed crisp evidence of statistical improvement in students' academic achievement in gaining EBM research knowledge and skills. In summary, the GRG method provides a highly flexible and individualised pathway for developing EBM research skills needed in challenging clinical environments.A flexible, blended SDL program is precisely designed for physicians to flexibly manage typical time constraints and heavy clinical workloads in healthcare settings by improving scheduling flexibility.An integrative method combining non-formal education, SDL, and EBM research principles into a single coherent model.A learner-centred teaching approach that utilises empathy maps and personalised learning contracts to foster intrinsic motivation and the practical application of EBM research.

Indexed as

Blended learningEvidence-based medicineMedical educationNon-formal educationResearch competenciesSelf-directed learning

Identifiers

PMID42667038
PMCPMC13524449

What OpenQuestion holds

Textmetadata
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.