Evidence map›Paper›PMID 40697495›Full record

SynthesisInternational journal of health policy and management2025

Finding the Right Balance: Challenges in Optimising the Promise of Complexity Research for NCD Best-Buys Implementation and Adoption Comment on "Barriers and Opportunities for WHO 'Best Buys' Non-communicable Disease Policy Adoption and Implementation From a Political Economy Perspective: A Complexity Systematic Review".

Pragati B Hebbar, Upendra M Bhojani, Prashanth Nuggehalli Srinivas

Abstract readSystematic Review
In one paragraph

Synthesis in International journal of health policy and management, 2025. 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.

Pragati B HebbarCenter for Commercial Determinant of Health, Institute of Public Health Bengaluru, Bengaluru, India.ORCID 0000-0002-5410-4943
Upendra M BhojaniCenter for Commercial Determinant of Health, Institute of Public Health Bengaluru, Bengaluru, India.ORCID 0000-0002-9179-6248
Prashanth Nuggehalli SrinivasCentre for Health Systems, Institute of Public Health Bengaluru, Bengaluru, India.ORCID 0000-0003-0968-0826

Funding

DBT-Wellcome Trust India Alliance IA/CPHS/22/1/506533DBT-Wellcome Trust India Alliance IA/CRC/20/1/600007Wellcome Trust
6 · The paper itself

Abstract

There is a growing interest in complexity research. A recent systematic review by Loffreda et al attempted to study the barriers and opportunities for the adoption and implementation of the "best buys" for non-communicable diseases (NCDs) from a political economy perspective. In this commentary we take forward the discussion on the NCD best-buys by comparing the findings of the article with one of the risk factors of tobacco use and its control in India. We reflect on the challenges in actualizing the promise of research methods and approaches while studying such complex interventions like the NCD best buys. The balance of studying complexity while still keeping the findings translatable at country levels. Future research could potentially use a comparative lens focusing on either industry/government or actor behaviour across the different risk factors to facilitate cross learning, anticipate and pre-empt adverse policy decisions and implementation outcomes.

Indexed as

Health PolicyNoncommunicable DiseasesPolicy MakingPoliticsHumansIndiaRisk FactorsWorld Health OrganizationBest BuysComplexity ResearchNon-communicable DiseasesPolitical Economy AnalysisRealist Methods

Identifiers

PMID40697495
PMCPMC7617919

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.