Evidence map›Paper›PMID 40308371›Full record

ArticleWomen's health reports (New Rochelle, N.Y.)2025

Tailoring Chronic Disease Interventions to Meet Specific Needs of Women: A Case Example of a Hypertension Program.

Caroline A Dancu, Julie Schexnayder, Hayden B Bosworth, Allison Lewinski, Abigail Shapiro, Tiera Lanford, Courtney White Clark, Bevanne Bean-Mayberry, Leah L Zullig, Jennifer M Gierisch and 1 more

Abstract read
In one paragraph

Article in Women's health reports (New Rochelle, N.Y.), 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

11 authors.

Caroline A DancuSan Francisco School of Nursing, University of California, San Francisco, California, USA.
Julie SchexnayderUniversity of Alabama School of Nursing, Birmingham, Alabama, USA.
Hayden B BosworthDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Allison LewinskiDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Abigail ShapiroDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Tiera LanfordDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Courtney White ClarkDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Bevanne Bean-MayberryCenter for the Study of Healthcare Innovation, Implementation & Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.
Leah L ZulligDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Jennifer M GierischDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.
Karen M GoldsteinDurham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Women have a unique risk profile for cardiovascular disease (CVD) due to underlying sociocultural and biological determinants. Current CVD prevention and treatment interventions, however, largely remain agnostic to the influences of an individual's sex assigned at birth or gender identity. This study describes a process for tailoring existing evidence-based interventions to the biological and sociocultural determinants of health for women. Methods: This study adapted the Team-supported, Electronic Health Record (EHR)-leveraged, Active Management (TEAM) CVD preventative care intervention designed for telehealth-based remote hypertension (HTN) care in rural Veterans. Tailoring choices were informed by a 12-month process including a focused literature review, qualitative interviews with women's health experts, and feedback from providers and women Veterans on existing intervention materials. Results: Literature review and qualitative interview findings informed the modification of patient- and provider-facing TEAM materials. Patient-facing material modifications included the addition of information relevant to sex-specific CVD risk factors, addressing gender-related barriers to CVD risk reduction, and including diverse visual representation and inclusive language. Provider-facing materials were modified through a new EHR template to comprehensively address sex-specific CVD risk factors. These changes resulted in individualized care plans to better address gaps in HTN management among women. Conclusion: Tailoring existing evidence-based interventions is an achievable and practical strategy to incorporate the sociocultural and biological determinants of CVD health specific to women. This approach could be used to adapt other programs and interventions designed to address health conditions that occur among both men and women but which are sensitive to important biological and sociocultural determinants. These findings highlight the broad discourse on sex- and gender-sensitive health care interventions and advocate for the integration of these interventions into routine clinical practice.

Indexed as

cardiovascular risksex- and gender-tailoringVeterans

Identifiers

PMID40308371
PMCPMC12040593

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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.