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Record W3118742707 · doi:10.1016/j.invent.2021.100362

Recruiting participants for an international mHealth study via Facebook Ads: Experiences from the Untire App RCT

2021· article· en· W3118742707 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternet Interventions · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsnot available
FundersHorizon 2020European Commission
KeywordsmHealthContext (archaeology)Randomized controlled trialPsychological interventionSocial mediaIntervention (counseling)PsychologyScale (ratio)MedicineAdvertisingNursingComputer scienceBusinessWorld Wide WebSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: Social media recruitment via Facebook Ads seems to be a promising method for large-scale international trials examining the effectiveness of mHealth interventions. However, little is known about this method in terms of strategy, reach, and costs in the context of psycho-oncology. This paper presents the results of the recruitment strategy that was applied in the Untire app study and shows how many participants could be reached using advertisements (i.e., Ads) on Facebook, who participated, and what it cost. METHOD: The Untire app study is a randomized controlled trial targeted at cancer patients and survivors across four English-speaking countries (i.e., Australia, Canada, the U.K., and the U.S.A.). Reach was assessed by the number of people who were shown the Ads, who clicked on the Ads, and completed study assessments. Demographic characteristics were gathered from Facebook Ads Manager and from online study assessments to describe who was reached. Costs were assessed by the budget spent and the cost per click for Ads, for reaching the study's landing page, and for completing study assessments. To conduct a powered RCT, we needed 164 12-weeks assessments in both the intervention and the control group. RESULTS: From March till October 2018, we used 76 Ads, which were presented to 1.2 million people. 37.376 persons clicked on the study link in the Ads, resulting in 755 baseline completers. Most participants were female (92%), middle-aged (55.5 ± 9.79), and came from the U.K. (72%). The total Facebook advertisement costs from March till October 2018 were €17 k, resulting in an average cost of €0.45 per click on the Ads, €5.55 on average for a person reaching the study's landing page, and €14.89 on average per eligible participant. The costs for every baseline and 12-weeks completer were €22.42 and €47.69, respectively. DISCUSSION: Reaching participants for international mHealth studies in psycho-oncology via Facebook Ads has potential but is costly. The key to reducing costs lies in constant optimization and testing of Ads and refinement of target audience characteristics.

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.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.518
GPT teacher head0.554
Teacher spread0.036 · 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