Use of a Google Map Tool Embedded in an Internet Survey Instrument: Is it a Valid and Reliable Alternative to Geocoded Address Data?
Notice bibliographique
Résumé
BACKGROUND: Men who have sex with men (MSM) in the United States are at high risk for human immunodeficiency virus (HIV) and poor HIV related outcomes. Maps can be used to identify, quantify, and address gaps in access to HIV care among HIV-positive MSM, and tailor intervention programs based on the needs of patients being served. OBJECTIVE: The objective of our study was to assess the usability of a Google map question embedded in a Web-based survey among Atlanta-based, HIV-positive MSM, and determine whether it is a valid and reliable alternative to collection of address-based data on residence and last HIV care provider. METHODS: Atlanta-based HIV-positive MSM were recruited through Facebook and from two ongoing studies recruiting primarily through venue-based sampling or peer referral (VBPR). Participants were asked to identify the locations of their residence and last attended HIV care provider using two methods: (1) by entering the street address (gold standard), and (2) "clicking" on the locations using an embedded Google map. Home and provider addresses were geocoded, mapped, and compared with home and provider locations from clicked map points to assess validity. Provider location error values were plotted against home location error values, and a kappa statistic was computed to assess agreement in degree of error in identifying residential location versus provider location. RESULTS: The median home location error across all participants was 0.65 miles (interquartile range, IQR, 0.10, 2.5 miles), and was lower among Facebook participants (P<.001), whites (P<.001), and those reporting higher annual household income (P=.04). Median home location error was lower, although not statistically significantly, among older men (P=.08) and those with higher educational attainment (P=.05). The median provider location error was 0.32 miles (IQR, 0.12, 1.2 miles), and did not vary significantly by age, recruitment method, race, income, or level of educational attainment. Overall, the kappa was 0.20, indicating poor agreement between the two error measures. However, those recruited through Facebook had a greater level of agreement (κ=0.30) than those recruited through VBPR methods (κ=0.16), demonstrating a greater level of consistency in using the map question to identify home and provider locations for Facebook-recruited individuals. CONCLUSIONS: Most participants were able to click within 1 mile of their home address and their provider's office, and were not always able to identify the locations on a map consistently, although some differences were observed across recruitment methods. This map tool may serve as the basis of a valid and reliable tool to identify residence and HIV provider location in the absence of geocoded address data. Further work is needed to improve and compare map tool usability with the results from this study.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 tête enseignante, 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 ».