{
  "abstract": "This study aimed to evaluate healthcare professionals’ knowledge, attitudes, and practices (KAP) concerning the application of magnetic resonance imaging (MRI) in the diagnostic assessment of ovarian cancer. A cross-sectional survey was conducted at Tengzhou Central People’s Hospital between September 17 and October 17, 2025. A total of 838 questionnaires were collected, of which 656 were considered valid, yielding a questionnaire validity rate of 78.28%. The participant pool was predominantly female (73.9%), with a mean age of 39.09 ± 8.05 years. Most respondents held a bachelor’s degree (59.5%), worked as physicians (57.6%), and were employed in public tertiary hospitals (74.2%). The knowledge, attitude, and practice scores were 5.50 ± 1.28 (possible range: 0–9), 33.14 ± 4.36 (possible range: 8–40), and 17.31 ± 6.43 (possible range: 5–30), respectively. Structural equation modeling (SEM) with a weighted least squares mean- and variance-adjusted (WLSMV) estimator showed that knowledge had direct effects on attitude (β = 0.587, P < 0.001) and practice (β = 0.263, P = 0.001). Meanwhile, attitude had a direct impact on practice (β = 0.222, P < 0.001). Furthermore, knowledge indirectly affected practice through attitude (β = 0.130, P = 0.001). Gaps persist between favorable attitudes and insufficient knowledge and practice in MRI for ovarian cancer diagnosis, necessitating targeted education and training.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "Sheng Sun"
    },
    {
      "name": "Xiumei Ma"
    },
    {
      "name": "Jingyi Liu"
    },
    {
      "name": "Dongmei Dong"
    },
    {
      "name": "Baojing Li"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2e2xsseer8dg1.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-74599-w",
  "fulltext_url": null,
  "id": "2e2xsseer8dg1",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-74599-w",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2743|Ovarian cancer diagnosis and treatment"
    ]
  ],
  "openalex": "W7221193357",
  "pdf_url": "https://www.nature.com/articles/s41598-026-74599-w_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/2e2xsseer8dg1.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:24Z",
      "native_id": "10.1038/s41598-026-74599-w",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-74599-w"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2743|Ovarian cancer diagnosis and treatment",
      "subfield": "reproductive-child"
    }
  ],
  "title": "Knowledge attitudes and practices of healthcare professionals regarding magnetic resonance imaging for ovarian cancer diagnosis",
  "title_text": "Knowledge attitudes and practices of healthcare professionals regarding magnetic resonance imaging for ovarian cancer diagnosis",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:24Z",
  "url": "https://research.draconitic.com/paper/2e2xsseer8dg1",
  "venue": "Scientific Reports",
  "versions": []
}