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使用职业信息网络对美国陆军军事职业专长进行分类。

Classifying U.S. Army Military Occupational Specialties using the Occupational Information Network.

作者信息

Gadermann Anne M, Heeringa Steven G, Stein Murray B, Ursano Robert J, Colpe Lisa J, Fullerton Carol S, Gilman Stephen E, Gruber Michael J, Nock Matthew K, Rosellini Anthony J, Sampson Nancy A, Schoenbaum Michael, Zaslavsky Alan M, Kessler Ronald C

机构信息

Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, University of British Columbia, 620B-1081 Burrard Street, Vancouver, BC V6Z 1Y6.

Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI 48104.

出版信息

Mil Med. 2014 Jul;179(7):752-61. doi: 10.7205/MILMED-D-13-00446.

Abstract

OBJECTIVES

To derive job condition scales for future studies of the effects of job conditions on soldier health and job functioning across Army Military Occupation Specialties (MOSs) and Areas of Concentration (AOCs) using Department of Labor (DoL) Occupational Information Network (O*NET) ratings.

METHODS

A consolidated administrative dataset was created for the "Army Study to Assess Risk and Resilience in Servicemembers" (Army STARRS) containing all soldiers on active duty between 2004 and 2009. A crosswalk between civilian occupations and MOS/AOCs (created by DoL and the Defense Manpower Data Center) was augmented to assign scores on all 246 O*NET dimensions to each soldier in the dataset. Principal components analysis was used to summarize these dimensions.

RESULTS

Three correlated components explained the majority of O*NET dimension variance: "physical demands" (20.9% of variance), "interpersonal complexity" (17.5%), and "substantive complexity" (15.0%). Although broadly consistent with civilian studies, several discrepancies were found with civilian results reflecting potentially important differences in the structure of job conditions in the Army versus the civilian labor force.

CONCLUSIONS

Principal components scores for these scales provide a parsimonious characterization of key job conditions that can be used in future studies of the effects of MOS/AOC job conditions on diverse outcomes.

摘要

目的

利用美国劳工部(DoL)职业信息网络(O*NET)评级,得出工作条件量表,用于未来研究工作条件对陆军军事职业专长(MOSs)和集中领域(AOCs)的士兵健康及工作效能的影响。

方法

为“陆军评估军人风险与复原力研究”(Army STARRS)创建了一个综合行政数据集,其中包含2004年至2009年期间所有现役士兵。对民用职业与MOS/AOCs之间的交叉对照表(由劳工部和国防人力数据中心创建)进行了扩充,以便为数据集中的每个士兵在所有246个O*NET维度上打分。使用主成分分析来总结这些维度。

结果

三个相关成分解释了大部分O*NET维度方差:“体力需求”(方差的20.9%)、“人际复杂性”(17.5%)和“实质复杂性”(15.0%)。尽管与民用研究大致一致,但发现了一些与民用结果的差异,这反映出陆军与民用劳动力在工作条件结构方面可能存在的重要差异。

结论

这些量表的主成分得分提供了关键工作条件的简洁描述,可用于未来关于MOS/AOC工作条件对各种结果影响的研究。

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本文引用的文献

1
The O*Net Jobs Classification System: A Primer for Family Researchers.
Fam Relat. 2006 Oct;55(4):461-472. doi: 10.1111/j.1741-3729.2006.00415.x. Epub 2006 Sep 7.
2
Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective.
Multivariate Behav Res. 2013 Jan;48(1):28-56. doi: 10.1080/00273171.2012.710386.
3
Design of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).
Int J Methods Psychiatr Res. 2013 Dec;22(4):267-75. doi: 10.1002/mpr.1401.
4
Associations of occupational attributes and excessive drinking.
Soc Sci Med. 2013 Sep;92:35-42. doi: 10.1016/j.socscimed.2013.05.023. Epub 2013 Jun 4.
7
Suicide risk by military occupation in the DoD active component population.
Suicide Life Threat Behav. 2013 Jun;43(3):274-8. doi: 10.1111/sltb.12013. Epub 2013 Jan 24.
8
Cardiovascular disease and risk factors in law enforcement personnel: a comprehensive review.
Cardiol Rev. 2012 Jul-Aug;20(4):159-66. doi: 10.1097/CRD.0b013e318248d631.
10
Occupation attributes relate to location of atrophy in frontotemporal lobar degeneration.
Neuropsychologia. 2010 Oct;48(12):3634-41. doi: 10.1016/j.neuropsychologia.2010.08.020. Epub 2010 Aug 26.

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