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目的:调查了解城市和农村籍(城乡)军人适应不良情况及其影响因素。方法:采用军人适应不良量表(MMMS)对随机整群抽取的不同年代入伍城乡官兵10 883例的适应不良情况进行测评,并分析其影响因素。结果:20世纪80年代与90年代城乡军人适应不良各因子分值差异不显著(P>0.05);而2000年以后城市籍军人适应不良各因子分值显著或非常显著高于农村籍军人(P<0.05,P<0.01)。Pearson相关分析结果显示,年代与行为问题、情绪障碍呈显著负相关(P<0.05),与人际关系不良、环境适应呈非常显著正相关(P<0.01);城乡与行为问题、情绪障碍和人际关系不良呈显著或非常显著负相关(P<0.05,P<0.01)。多元逐步回归分析结果显示,城乡进入军人适应不良各因子为因变量的回归方程(P<0.01),年代进入人际关系不良和环境适应为因变量的回归方程(P<0.01)。结论:2000年以后,城市籍军人适应不良发生率显著高于农村籍军人,军人适应不良与年代、城乡密切相关。
Objectives: To investigate and understand the maladjustments of urban and rural (urban and rural) military personnel and their influencing factors. Methods: The MMMS was used to evaluate the maladjustment of 10 883 enlisted soldiers in urban and rural areas randomly selected from random clusters and analyzed the influencing factors. Results: There was no significant difference in scores of various factors of maladjustment between urban and rural soldiers in the 1980s and 1990s (P> 0.05). After 2000, the scores of various maladjustments of urban males were significantly or very significantly higher than those of rural males <0.05, P <0.01). Pearson correlation analysis showed that there was a significant negative correlation between age and behavioral problems and mood disorders (P <0.05), and there was a significant positive correlation between age and behavior and environmental adaptation (P <0.01); urban-rural and behavioral problems, mood disorders and interpersonal Poor relationship was significant or very significant negative correlation (P <0.05, P <0.01). The results of multiple stepwise regression analysis showed that the factors of maladjustment among urban and rural residents were the regression equation of dependent variables (P <0.01), and the regression equation of interpersonal dysfunction and environmental adaptation as dependent variables (P <0.01). Conclusion: After 2000, the incidence of maladjustment by urban-area military personnel is significantly higher than that of rural-state military personnel. The maladaptation of military personnel is closely related to the age and urban-rural areas.