Development and validation of a risk prediction model for sleep disorder in special operations forces during parachute training

Miao YU; Meisheng HUANG; Zaixiong DING; Yu CHEN; Tao JIANG

doi:10.16016/j.2097-0927.202301094

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Development and validation of a risk prediction model for sleep disorder in special operations forces during parachute training

Military Medicine | 更新时间：2026-01-09

- Development and validation of a risk prediction model for sleep disorder in special operations forces during parachute training
- Journal of Army Medical University Vol. 46, Issue 10, Pages: 1068-1074(2024)
- 作者机构：
  
  1.400037 重庆，陆军军医大学(第三军医大学)第二附属医院骨科
  2.650000 昆明，南部战区陆军第31636部队战勤科
  3.400038 重庆，陆军军医大学(第三军医大学)陆军卫勤训练基地军事医学地理学教研室
- 作者简介：
- 基金信息：
- DOI：10.16016/j.2097-0927.202301094
  CLC： E274.2;R338.63;R821.3
- Received：19 January 2023，
  
  Revised：2023-10-22，
  
  Published：30 May 2024
- 稿件说明：
移动端阅览
Miao YU, Meisheng HUANG, Zaixiong DING, et al. Development and validation of a risk prediction model for sleep disorder in special operations forces during parachute training[J]. Journal of Army Medical University, 2024, 46(10): 1068-1074.
DOI：

Miao YU, Meisheng HUANG, Zaixiong DING, et al. Development and validation of a risk prediction model for sleep disorder in special operations forces during parachute training[J]. Journal of Army Medical University, 2024, 46(10): 1068-1074. DOI： 10.16016/j.2097-0927.202301094.

摘要

目的

调查分析陆军某特种作战部队军人伞降训练期间发生睡眠障碍的影响因素，构建并验证预测模型。

方法

抽取2022年10-11月有伞降作业的特种作战军人349名作为研究对象，采用自制问卷、焦虑自评量表(Self-Rating Anxiety Scale

SAS)和匹兹堡睡眠质量指数(Pittsburgh Sleep Quality Index，PSQI)量表对其睡眠质量测评后记录基线资料，根据PSQI分值分为睡眠障碍组和非睡眠障碍组。按7∶3比例分为训练集和验证集。基于训练集，经单因素分析和多因素Logistic回归分析筛选出伞降训练军人睡眠障碍风险的影响因素，R语言绘制列线图，受试者工作特征曲线(recevier operating characteristic curve

ROC)评价模型区分度，校准曲线和Hosmer-Lemeshow拟合优度检验评价模型准确度，临床决策曲线DCA评价模型的有效性。利用验证集进行内部验证。

结果

共有325名特种作战伞降训练军人的数据有效，均为男性。PSQI总分为(4.26±3.30)分，结果提示62名(19.1%)存在睡眠障碍，睡眠障碍组中轻度睡眠障碍46名(14.1%)，中度睡眠障碍14名(4.3%)

重度睡眠障碍2名(0.6%)。训练集228名，单因素分析和多因素Logistic回归分析结果显示，跳伞次数(

: 0.390，95%

: 0.185~0.811)、吸烟(

: 2.980，95%

: 1.352~7.028)、焦虑状态(

: 3.280，95%

: 1.434~7.570)和慢性疼痛(

: 4.090，95%

: 1.952~8.690)是伞降训练军人睡眠障碍的独立影响因素。构建伞降训练军人睡眠障碍风险预测模型，绘制ROC曲线并计算曲线下面积(area under curve

AUC)为0.778，最佳阈值为0.163，特异度为63.6%，灵敏度为84.1%，区分度良好。校准曲线和Hosmer-Lemeshow拟合优度检验(

=8.789，

=0.456)显示模型准确度良好，临床决策曲线提示该预测模型具有较好的临床适用性。验证集97名内部验证该模型有效。

结论

特种作战伞降训练军人存在不同程度的睡眠问题。跳伞次数、吸烟、焦虑状态和慢性疼痛会加重睡眠障碍。

Abstract

Objective

To investigate the influencing factors for sleep disorder during parachute training in special operations forces from a unit of the army

and to develop and validate a prediction model.

Methods

A total of 349 special operations officers and soldiers undergoing parachute training from October to November 2022 were recruited as research objects. Self-made questionnaires

Self-Rating Anxiety Scale (SAS) and Pittsburgh Sleep Quality Index (PSQI) Scale were used to collect their baseline data and assess sleep quality. According to their PSQI score

the participants were divided into sleep disorder group and non-sleep disorder group

and then assigned into a training set (

=228) and a validation set (

=97) in a ratio of 7∶3. Based on the training set

univariate analysis and multivariate logistic regression analysis were used to screen out the factors influencing the risk of sleep disorders. Then R language was employed to draw a nomogram model

and receiver operating characteristic (ROC) curve was plotted to e

valuate the discrimination of the model. Calibration curve analysis and Hosmer-Lemeshow goodness-of-fit test were applied to evaluate the accuracy of the model

and decision curve analysis (DCA) was conducted to evaluate the validity of the model. The validation set was used for internal validation.

Results

There were totally 325 participants with valid data

and all of them were male. They had a total PSQI score of 4.26±3.30

and 62 of them (19.1%) had sleep disorders

including 46 (14.1%) of mild

14 (4.3%) of moderate

and 2 (0.6%) of severe sleep disorders. Based on the 228 participants in the training set

the results of univariate and multivariate logistic regression analyses showed the number of parachute jumping (

=0.390

95%

: 0.185~0.811)

smoking (

=2.980

95%

: 1.352~7.028)

anxiety state (

=3.280

95%

: 1.434~7.570)

and chronic pain (

=4.090

95%

: 1.952~8.690) were independent influencing factors of sleep disorder in these parachute officers and soldiers. A risk prediction model for sleep disorder was constructed

and the area under the curve (AUC) value was 0.778

with an optimal threshold of 0.163

a specificity of 63.6% and a sensitivity of 84.1%

with good discrimination. The quasi-curve and Hosmer-Lemeshow goodness-of-fit test (

Chi

-sqaure=8.789

=0.456) showed that the model had good accuracy

and the clinical decision curve indicated that the prediction model had good clinical applicability. The model was confirmed to be valid with internal verification based on the validation set of 97 participants.

Conclusion

Special operations forces with parachute training have different degrees of sleep disorders. Number of parachute jumping

smoking

anxiety and chronic pain will aggravate sleep disturbances.

关键词

Keywords

references

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