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1.
Mil Psychol ; 35(5): 467-479, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37615559

RESUMO

Quitting Basic Military Training (BMT) is a problem in the Dutch Armed Forces. Previous research focused on physical factors. Yet, contemporary research focuses on psychosocial characteristics, study skills, and quality of life factors associated with recruits' intention to quit BMT. We combined several factors to identify the key factors affecting recruits' intentions to quit BMT. We also studied gender and rank position differences. Three hundred fifty-five recruits enrolled in BMT participated by completing a self-report questionnaire. Multiple regression analysis showed that being highly engaged with BMT, having a high sense of belonging, and being highly proactive resulted in lower intention to quit. Having a high sense of responsibility resulted in higher intention to quit BMT. For gender, significant differences were found in study skills and self-esteem. For rank positions, significant differences were found in several psychosocial characteristics, study skills, quality of life factors, and intention to quit; with officer rank recruits showing higher intentions to quit than noncommissioned officer rank recruits. These identified factors can be used to improve conditions for BMT recruits. It is further advised to investigate the origin of gender and rank position differences that affect associations between psychosocial characteristics, study skills, quality of life factors, and recruits' intention to quit, so that these differences can be minimized in the future.


Assuntos
Intenção , Militares , Humanos , Militares/educação , Qualidade de Vida , Habilidades para Realização de Testes , Análise Multivariada
2.
Appl Ergon ; 40(6): 1019-25, 2009 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-18823875

RESUMO

New driver support systems are developed and introduced to the market at increasing speed. In conditions of traffic congestion drivers may be supported by a "Congestion Assistant", a system that combines the features of a Congestion Warning System (acoustic warning and gas pedal counterforce) and a Stop & Go system (automatic gas and brake pedal during congestion). To gain understanding of the effects of driving with a Congestion Assistant on drivers, mental workload of drivers was registered under different conditions as well as acceptance of the system. Mental workload was measured by means of physiological registrations, i.e. heart rate, a secondary task and with the aid of subjective scaling techniques. Acceptance was measured with an acceptance scale. The study was carried out in an advanced driving simulator. Driving with the Congestion Assistant while in congestion potentially leads to decreased driver mental workload, whereas just before congestion starts, i.e. developing just noticeable, the system may add to the workload of the driver. Acceptance is generally high after experiencing the system, though not in all respects.


Assuntos
Inteligência Artificial , Atenção , Automação/instrumentação , Condução de Veículo , Cognição , Interface Usuário-Computador , Carga de Trabalho , Adulto , Atitude , Simulação por Computador , Coleta de Dados , Feminino , Frequência Cardíaca , Humanos , Masculino , Pessoa de Meia-Idade , Percepção , Inquéritos e Questionários , Análise e Desempenho de Tarefas
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