Evidence map›Paper›PMID 21057975›Full record

ArticleJournal of genetic counseling2011

Genetic testing likelihood: the impact of abortion views and quality of life information on women's decisions.

Jessica L Wilson, Gail M Ferguson, Judith M Thorn

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Journal of genetic counseling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Presenting life with cystic fibrosis: a Q-methodological approach to developing balanced, experience-based prenatal screening information.Health expectations : an international journal of public participation in health care and health policy · 2015
    Article
  5. Article
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

3 authors at 1 institution in 1 country.

Jessica L WilsonDepartment of Psychology, Knox College, 2 East South Street, Box 120, Galesburg, IL 61401, USA.
Gail M Ferguson
Judith M Thorn
Knox College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Little is known about factors predicting the likelihood of choosing genetic testing in college aged women versus older women, including knowledge of quality of life (QOL) associated with a disorder. Using vignettes with female college students (Experiment 1: n=257, mean age=19.70 yrs) and female faculty/staff/alumni (Experiment 2: n (nulliparous)=83, mean age=30.20 yrs; n (mothers)=53, mean age=33.77 yrs), we examined the contribution of multiple factors to predicting genetic testing likelihood for cystic fibrosis. We investigated malleable situational factors (style of genetic risk presentation and providing QOL information including physical and social aspects) and stable dispositional factors (abortion views). Parity (i.e., prior births) was more influential in women's genetic testing likelihood than was age. Greater acceptability of abortion for oneself and self-assessed knowledge following QOL information were predictors of higher testing likelihood for college students. Greater acceptability of abortion for another person was a predictor for nulliparous women. Abortion views moderated the effect of predictors for nulliparous women and mothers. Findings encourage genetic counselors to utilize QOL information to promote informed decision making through genetic testing.

Indexed as

Abortion, InducedDecision MakingQuality of LifeAdultCystic FibrosisFemaleGenetic TestingHumansLikelihood Functions

Identifiers

PMID21057975
OpenAlexW1983915042

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.