ArticleMaternal and child health journal2019
Primary Care Women's Health Screening: A Case Study of a Community Engaged Human Centered Design Approach to Enhancing the Screening Process.
Article in Maternal and child health journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- Co-development of a community pharmacy training regarding fentanyl and xylazine test strips.Exploratory research in clinical and social pharmacy · 2025Article
- Patients' comfort with and receipt of health risk assessments during routine dental visits: Results from the South Atlantic region of the US National Dental Practice-Based Research Network.Community dentistry and oral epidemiology · 2023Article
- Community engagement initiatives in primary health care to achieve universal health coverage: A realist synthesis of scoping review.PloS one · 2023Article
- The Application of Human-Centered Design Approaches in Health Research and Innovation: A Narrative Review of Current Practices.JMIR mHealth and uHealth · 2021Review
- "I'll tell you what's important to me…": lessons for women's health screening.BMC women's health · 2021Article
- May Measurement Month 2017-2019: A Community-Wide Opportunistic Blood Pressure Screening Campaign in Hong Kong.International journal of hypertension · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeTo apply a Human Centered Design (HCD) approach to co-designing a comprehensive women's health screening tool with community partners. DESCRIPTION: Evidenced-based health screenings for behaviors and risks are important tools in primary health care and disease prevention, especially for women. However, numerous barriers limit the effective implementation of comprehensive health screenings, and often lead to excluding important risks such as intimate partner violence (IPV). Utilizing a human centered design approach (HCD), Mountain Area Health Education Center (MAHEC, NC USA) developed a community co-designed 9-topic health screening for women. Key end-users were recruited to participate in the design process, including women who identified IPV as a health issue in their community, Spanish speaking women, domestic violence program organizers, and MAHEC staff. ASSESSMENT: A total of 21 participants collaborated during three design sessions on two specific goals: 1) creating a comprehensive women's health screening tool from the existing tools that were in use in our clinics at the time, and 2) incorporating IPV screening. Through the HCD sessions, participants highlighted the impact of what they termed "Triple T: time, trust and talk" on the effectiveness of women's health screening.
conclusionOur co-designed women's health screening tool is a first step towards addressing screening barriers from both primary care provider's and community women's perspectives. Future research will explore the facilitators of and barriers to implementing the tools in different primary care settings. Future work should also more systematically examine whether and how screening processes may reinforce or contribute to women's feelings of being stereotyped, and how screening processes can be designed to avoid stereotype threat, which has the potential to reduce the effectiveness of screenings intended to promote women's health.
Indexed as
Identifiers
31250241What OpenQuestion holds
Registered trials
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.