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Record W3121931826 · doi:10.2196/22854

Comparison of Facebook, Google Ads, and Reddit for the Recruitment of People Who Considered but Did Not Obtain Abortion Care in the United States: Cross-sectional Survey

2021· article· en· W3121931826 on OpenAlexvenueno aff
Heidi Moseson, Alexandra Wollum, J Seymour, Carmela Zuniga, Terri‐Ann Thompson, Caitlin Gerdts

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsnot available
Fundersnot available
KeywordsAbortionSocial mediaAdvertisingCross-sectional studyMedicineFamily medicinePregnancyBusinessWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: In the United States, abortion access is restricted by numerous logistical, financial, social, and policy barriers. Most studies on abortion-seeking experiences in the United States have recruited participants from abortion clinics. However, clinic-based recruitment strategies fail to capture the experiences of people who consider an abortion but do not make it to an abortion clinic. Research indicates that many people search for abortion information on the web; however, web-based recruitment remains underutilized in abortion research. OBJECTIVE: This study aims to establish the feasibility of using Facebook, Google Ads, and Reddit as recruitment platforms for a study on abortion-seeking experiences in the United States. METHODS: From August to September 2018, we posted recruitment advertisements for a survey about abortion-seeking experiences through Facebook, Google Ads, and Reddit. Eligible participants were US residents aged 15-49 years who had been pregnant in the past 5 years and had considered abortion for a pregnancy in this period but did not abort. For each platform, we recorded staff time to develop advertisements and manage recruitment, as well as costs related to advertisement buys and social marketing firm support. We summarized the number of views and clicks for each advertisement where possible, and we calculated metrics related to cost per recruited participant and recruitment rate by week for each platform. We assessed differences across platforms using the chi-square and Kruskal-Wallis tests. RESULTS: Overall, study advertisements received 77,464 views in the 1-month period (from Facebook and Google; information not available for Reddit) and 2808 study page views. After clicking on the advertisements, there were 1254 initiations of the eligibility screening survey, which resulted in 98 eligible survey participants (75 recruited from Facebook, 14 from Google Ads, and 9 from Reddit). The cost for each eligible participant in each platform was US $49.48 for Facebook, US $265.93 for Google Ads, and US $182.78 for Reddit. A total of 84% (66/79) of those who screened eligible from Facebook completed the short survey compared with 73% (8/11) of those who screened eligible from Reddit and 13% (7/53) of those who screened eligible from Google Ads. CONCLUSIONS: These results suggest that Facebook advertisements may be the most time- and cost-effective strategy to recruit people who considered but did not obtain an abortion in the United States. Adapting and implementing Facebook-based recruitment strategies for research on abortion access could facilitate a more complete understanding of the barriers to abortion care in the United States.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.531
GPT teacher head0.600
Teacher spread0.069 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2021
Admission routes1
Has abstractyes

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