Abstract A19: [Advocate Abstract:] Survivors Teaching Students®: Educating Medical and other Health Professional Students about Ovarian Cancer
Bibliographic record
Abstract
Abstract “The goal of Survivors Teaching Students (STS) is for future physicians, nurse practitioners, nurses and physician assistants to be able to diagnose ovarian cancer when it is in its earlier, most treatable stages. Survivors Teaching Students is offered in 96 medical schools, 103 nursing schools, 13 Nurse Practitioner schools, 26 Physician Assistant schools, and 12 allied health programs across the United States. Active programs exist in 34 states, the District of Columbia, Virgin Islands, the United Kingdom and Canada. In 2015, the program educated 10,750 students, a 10% increase over the previous year. As of June, 2016, STS volunteers have already presented to approximately 6500 students in 35 states. More than 790 specially trained ovarian cancer survivors volunteer for this program. Each presentation includes a pre- and post-test to assess the student's knowledge about ovarian cancer detection, diagnostic procedures, symptoms, and risk factors, as well as the importance of referral to a gynecologic oncologist. Medical students' and nursing students' knowledge has increased by approximately 23% and 41% respectively during the presentations. Important facts about ovarian cancer: • Ovarian cancer is the most lethal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. • The majority of women are diagnosed when their ovarian cancer is in an advanced stage. • Currently, there is no reliable screening test for the early detection of ovarian cancer. • When detected in an early stage, the survival rates for ovarian cancer greatly improve. • Factors associated with an increased risk of ovarian cancer include a personal or family history of breast, colon, uterine or ovarian cancer, increasing age, never having been pregnant. • Factors associated with a decreased risk of ovarian cancer include using oral contraceptives, having and breastfeeding children, and having a tubal ligation or salpingectomy, hysterectomy or prophylactic removal of the ovaries. Ovarian cancer, even in its early stages, has symptoms: • Bloating • Pelvic or abdominal pain • Difficulty eating or feeling full quickly • Urinary symptoms (urgency or frequency) (Source: Ovarian Cancer Symptoms Consensus Statement - http://www.ocnapartners.org/wp-content/uploads/2013/01/Consensus.pdf) Women who have these symptoms more than 12 times during the course of one month should see a doctor, preferably a gynecologist-especially if the symptoms are new or unusual. Other symptoms have been commonly reported by women with ovarian cancer, including fatigue, indigestion, back pain, pain with intercourse, constipation and menstrual irregularities. However, these symptoms are not as useful in identifying ovarian cancer because they are found just as often in women who do not have the disease. If the symptoms suggest ovarian cancer, three tests should be performed: a complete pelvic exam, including a rectovaginal examination; a transvaginal ultrasound; and a CA-125 blood test. If ovarian cancer is suspected, the woman must be referred to a gynecologic oncologist. The focus of my work as an advocate and regional coordinator for STS includes survivor recruitment and training, outreach and collaboration to medical schools, and leadership of STS facilitators across the southeast United States. Locally in Charlotte, NC, I serve as facilitator and coordinator of Survivors Teaching Students through my role as Community Programs Manager for Lydia's Legacy, a 501(c)(3) non-profit whose mission is to raise awareness of gynecologic cancers through education and fund gynecologic cancer research through donation. Citation Format: Sarah Noonan. [Advocate Abstract:] Survivors Teaching Students®: Educating Medical and other Health Professional Students about Ovarian Cancer. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr A19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.452 | 0.171 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".