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Record W1966114939 · doi:10.3389/fpsyg.2015.00523

Recruitment strategies should not be randomly selected: empirically improving recruitment success and diversity in developmental psychology research

2015· article· en· W1966114939 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGeneralizability theoryPsychologyDiversity (politics)Social psychologyEthnic groupScripting languageApplied psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Psychological and developmental research have been critiqued for the lack of diversity of research samples. Because differences in culture, race, and ethnicity can influence participant behavior, limited diversity limits the generalizability of the findings. These differences may also impact how participants behave in response to recruitment attempts, which suggests that recruitment itself may be leveraged to increase sample diversity. The goal of the current study was to determine what factors, within a recruitment interaction, could be leveraged to increase success and diversity when recruiting families with children for developmental research. Study 1 found three factors influenced success: (1) recruitment was more successful when other potential participants were also interested (i.e., recruiters were busy), (2) recruiters of particular races were more successful than recruiters of other races, and (3) differences in success were related to what the recruiter said to engage the potential participant (i.e., the script). The latter two factors interacted, suggesting some recruiters were using less optimal scripts. To improve success rates, study 2 randomly assigned scripts to recruiters and encouraged them to recruit more vigorously during busy periods. Study 2 found that two factors influenced success: (1) some scripts were more successful than others and (2) we were more successful at recruiting non-White potential participants than White participants. These two interacted, with some scripts being more successful with White and other scripts being more successful with non-White families. This intervention significantly increased recruitment success rate by 8.1% and the overall number of families recruited by 15.3%. These findings reveal that empirically evaluating and tailoring recruitment efforts based on the most successful strategies is effective in boosting diversity through increased participation of children from non-White families.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.503
GPT teacher head0.483
Teacher spread0.020 · 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