Evidence map›Paper›PMID 42749900›Full record

ArticleJournal of behavioral medicine2026

Military veterans and behavioral medicine: introduction to the special issue.

M Bryant Howren, Mark W Vander Weg

Abstract read
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In one paragraph

Article in Journal of behavioral medicine, 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

2 authors.

M Bryant HowrenVHA Office of Rural Health, Veterans Rural Health Resource Center, VA Iowa City Health Care System, Iowa City, IA, USA. matthew-howren@uiowa.edu.ORCID http://orcid.org/0000-0002-5863-3420
Mark W Vander WegVHA Office of Rural Health, Veterans Rural Health Resource Center, VA Iowa City Health Care System, Iowa City, IA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This special issue of the Journal of Behavioral Medicine highlights emerging research at the intersection of military veteran populations and behavioral medicine. Military service, while associated with numerous strengths and opportunities for growth, also exposes service members and veterans to a range of unique psychological, behavioral, social, and physical health challenges across the life course. Veterans may experience elevated rates of a variety of mental and behavioral health conditions, including posttraumatic stress disorder, chronic pain, sleep disturbances, substance use disorders, and suicide risk, as well as higher rates of common chronic health conditions such as asthma, cancer, chronic obstructive pulmonary disease, diabetes mellitus, and rheumatoid arthritis. The twenty articles included in this issue encompass empirical investigations, qualitative studies, intervention trials, systematic reviews, implementation studies, and expert consensus work involving diverse veteran populations and health care settings. Major themes include mental and behavioral health, suicide prevention, chronic illness self-management, chronic pain, telehealth and digital therapeutics, peer support, implementation science, and the transition from military to civilian life. Collectively, these contributions underscore the importance of addressing social and structural determinants of health, expanding access to evidence-based interventions, and leveraging innovative models of care to improve health outcomes among veterans and their families.

Indexed as

Behavioral medicineHealth behaviorImplementation scienceMental healthMilitary veteransTelemedicine

Identifiers

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.