Evidence map›Paper›PMID 28229306›Full record

ArticleTranslational behavioral medicine2017

Behavioral and Social Sciences at the National Institutes of Health: adoption of research findings in health research and practice as a scientific priority.

William T Riley

Abstract read
In one paragraph

Article in Translational behavioral medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

1 author.

William T RileyOffice of Behavioral and Social Sciences Research, National Institutes of Health, Bethesda, MD, USA. wiriley@mail.nih.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The National Institutes of Health's Office of Behavioral and Social Sciences Research (OBSSR) recently released its Strategic Plan for 2017 to 2021. This plan highlights three scientific priorities: (1) improve the synergy of basic and applied behavioral and social sciences research, (2) enhance and promote the research infrastructure, methods, and measures needed to support a more cumulative and integrated approach to behavioral and social sciences research, and (3) facilitate the adoption of behavioral and social sciences research findings in health research and in practice. This commentary focuses on the challenges and opportunities to facilitate the adoption of research findings in health research and in practice. In addition to the ongoing NIH support for dissemination and implementation (D&I) research, we must address transformative challenges and opportunities such as better disseminating and implementing D&I research, merging research and practice, adopting more rigorous and diverse methods and measures for both D&I and clinical trials research, evaluating technological-based delivery of interventions, and transitioning from minimally adaptable intervention packages to planned adaptations rooted in behavior change principles. Beyond translation into practice and policy, the OBSSR Strategic Plan also highlights the need for translation of behavioral and social science findings into the broader biomedical research enterprise.

Indexed as

Behavioral ResearchNational Institutes of Health (U.S.)ResearchSocial SciencesGoalsHumansInformation DisseminationStrategic PlanningUnited StatesBehavioral and social sciences researchClinical research methodologyClinical translationDissemination and implementation researchImplementation sciencePlanned adaptationPractice adoption

Identifiers

PMID28229306
PMCPMC5526815

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.