Hidden Workers in Aging Australia: Protocol of Intersectionality-Informed Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: Australians are living longer and are expected to remain in the workforce for longer; yet, many older adults struggle to secure employment despite being willing and able to work. A growing share of these individuals are "hidden workers," those underused in the labor market due to missed hours, long-term unemployment, or withdrawal from job seeking despite the capacity to work. This group reflects a global trend of aging yet underused workforces, and in Australia, they represent a significant proportion of the working-age population. Addressing the challenges of hidden workers is crucial, as their inclusion could help meet labor market demands, alleviate fiscal pressures of aging, and promote healthier, more equitable aging trajectories. OBJECTIVE: This intersectional mixed methods study has 3 overarching aims. First, to investigate how intersecting social identities (eg, age, gender, cultural background, health status, and caregiving responsibilities) shape hidden workforce participation and associated health outcomes among aging Australians. Second, to compare hidden workers with currently employed populations in order to identify health discrepancies between the 2 groups. Third, to explore the lived experiences of hidden workers, focusing on how intersecting and multiply disadvantaged identities impose additional burdens on employment outcomes and health status. Together, these aims will generate an integrated understanding of both structural and lived dimensions of hidden work, providing evidence to inform more equitable labor market and health policies. METHODS: This study uses an explanatory sequential mixed methods design to investigate the health, resources, and employment experiences of aging hidden workers in Australia. In phase 1, an online cross-sectional survey was administered to 1166 participants (696 hidden workers aged more than 45 years and 470 current workers), capturing variables on employment history, health, discrimination, workplace social capital, caregiving, and socioeconomic status. Validated instruments, including the Workplace Age Discrimination Scale, Intersectional Anticipated Discrimination Scale, and Workplace Social Capital Index, were incorporated to ensure reliability. Phase 2 will involve semistructured interviews with a purposive subsample (30 participants) identified from survey results, focusing on lived experiences of workforce exclusion and intersecting barriers. In phase 3, quantitative and qualitative findings will be integrated through triangulation and complementarity to provide a comprehensive understanding of hidden workers' challenges and assets, generating evidence to inform policy and stakeholder recommendations. RESULTS: As of September 2025, the online survey has been completed, phase 2 interviews are underway, and phase 3 integration is scheduled for completion by mid-2026. CONCLUSIONS: This study will generate the first intersectional evidence on the health and employment challenges of hidden aging workers in Australia. These insights will inform tailored policy interventions that can support re-engagement, reduce inequities in health and well-being, and strengthen workforce participation. Ultimately, the findings will contribute to addressing skills shortages while promoting social and economic inclusion of aging Australians. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/83401.
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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 | 0,014 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».