An ecological systems model of employee experience in industry-led autism employment programmes
Notice bibliographique
Résumé
Industry-led employment programmes have emerged to transition autistic people into employment and meet industry labour needs. However, theoretical research is limited in this area, often failing to appreciate the influence of the broader employment ecosystem. In this study, we interviewed 33 autistic employees ( n = 29 males, M age = 29.00 years) from two industry-led employment programmes regarding their experience of the programme’s supports, relationships and impact. We used qualitative content analysis to identify five themes: (1) working involves multiple job tasks that evolve as the employment context changes; (2) workplace relations are diverse and shaped by the type of work and the work environment; (3) workplace needs evolve as autistic individuals navigate the work environment; (4) developing a professional identity in the workplace through mastery and integration; and (5) recommendations for the development of supportive workplace environments for autistic individuals. We describe the way that factors within (e.g. training) and outside the two employment programmes changed and interacted over time to contribute to the participant’s work experience and professional identity. Building on ecological systems theory, our unique contribution to the literature is a new model capturing individual and workplace factors that contribute to the work experience of autistic people who participate in industry employment programmes. Lay Abstract We asked 33 autistic adults from two industry-led employment programmes about their experiences in the programmes. These are programmes started by companies to recruit and support autistic people in work. We also asked about their workplace supports, relationships and how they thought the programme had impacted their life. Understanding the experiences of people in these industry-led employment programmes is important as the information can help to improve the programmes and participants’ experiences. After reviewing the interviews, we found five themes that best described the employee’s experience: (1) working involves multiple job tasks that evolve as the employment context changes; (2) relationships in the workplace are diverse and are influenced by the type of work participants do and the work environment; (3) workplace needs change as the autistic employees learn to navigate their work environment; (4) autistic employees develop a professional identity in the workplace as they master work and feel more integrated in the workplace; and (5) recommendations for the development of supportive workplace environments for autistic people. We explored the way that aspects of the two employment programmes (e.g. training) and factors outside the programme changed with time and contributed to the participant’s experience. We developed a new model to capture individual and workplace factors that contribute to the experience of autistic people who participate in industry employment programmes.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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.
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