Using Facebook to Recruit Young Adult Veterans: Online Mental Health Research
Notice bibliographique
Résumé
BACKGROUND: Veteran research has primarily been conducted with clinical samples and those already involved in health care systems, but much is to be learned about veterans in the community. Facebook is a novel yet largely unexplored avenue for recruiting veteran participants for epidemiological and clinical studies. OBJECTIVE: In this study, we utilized Facebook to recruit a sample of young adult veterans for the first phase of an online alcohol intervention study. We describe the successful Facebook recruitment process, including data collection from over 1000 veteran participants in approximately 3 weeks, procedures to verify participation eligibility, and comparison of our sample with nationally available norms. METHODS: Participants were young adult veterans aged 18-34 recruited through Facebook as part of a large study to document normative drinking behavior among a large community sample of veterans. Facebook ads were targeted toward young veterans to collect information on demographics and military characteristics, health behaviors, mental health, and health care utilization. RESULTS: We obtained a sample of 1023 verified veteran participants over a period of 24 days for the advertising price of approximately US $7.05 per verified veteran participant. Our recruitment strategy yielded a sample similar to the US population of young adult veterans in most demographic areas except for race/ethnicity and previous branch of service, which when we weighted the sample on race/ethnicity and branch a sample better matched with the population data was obtained. The Facebook sample recruited veterans who were engaged in a variety of risky health behaviors such as binge drinking and marijuana use. One fourth of veterans had never since discharge been to an appointment for physical health care and about half had attended an appointment for service compensation review. Only half had attended any appointment for a mental health concern at any clinic or hospital. Despite more than half screening positive for current probable mental health disorders such as post-traumatic stress disorder, depression, anxiety, only about 1 in 3 received mental health care in the past year and only 1 in 50 received such care within the past month. CONCLUSIONS: This work expands on the work of other studies that have examined clinical samples of veterans only and suggests Facebook can be an adequate method of obtaining samples of veterans in need of care. TRIAL REGISTRATION: Clinicaltrials.gov NCT02187887; http://clinicaltrials.gov/ct2/show/NCT02187887 (Archived by WebCite at http://www.webcitation.org/6YiUKRsXY).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».