Development and Testing a Volunteer Screening Tool for Assessing Community Health Volunteersʼ Motives at Recruitment and Placement in Western Kenya
Notice bibliographique
Résumé
Introduction:In times of inadequate resources and rising public demand, social service organizations rely on volunteers to meet needs.In the current human resource for health crisis in Africa there is urgent need for community health volunteers (CHVs).Studies have highlighted problems of high attrition rates leading to high replacement training costs among CHVs.There is need for careful selection of volunteers that can serve long-term, once trained.This study was done to develop a volunteer assessment framework for recruitment of CHVs.The framework is based on identification intrinsic motives for volunteering that have been shown to be associated with long volunteer service.Methods: The assessment tool was developed by searching literature for theory based constructs and assessment items associated with volunteering.These constructs and items were synthesized into a proposed assessment framework.The framework was subjected to face content and construct validation in West Kenyan context in phase 1 of the study.The validated framework was tested for ability to differentiate between long serving volunteers and nonvolunteers matched by gender, age and residence.The 2 groups were presented with test items and asked to record their agreement on a scale of 1 to 5 on the reasons why people volunteer.Results: From literature we identified functional, role identity, and social exchange as theories underpinning volunteering.From these theories we identified 8 constructs to include in a proposed volunteer assessment framework.We tested the framework and although all the eight constructs satisfied internal consistency test only 5: altruism, materialism, social adjustment, esteem enhancement and career development were statistically significantly more associated with either volunteers or non-volunteers.Therefore, only these were included on the final volunteer assessment framework, for identification of long serving volunteers in the local context. Conclusion:We propose a volunteer assessment tool with the 5 constructs and 25 assessment items for identification and recruitment of CHVs, with motives consistent with long-term volunteer service.The final framework consists of altruistic (altruism, social adjustment, esteem enhancement) or egoistic (material gain and career development) constructs with 25 assessment statements.The frame work would able to identify individuals with altruistic motives to include and those with egoistic tendencies to exclude during a volunteer recruitment exercise.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».