| Objectives:1.To test the reliability and validity of Sub-Health Measurement Scale Version 1.0(SHMS V1.0),and to analyze its applicability in midwives in Fujian Province.2.To establish the mean norm,percentile norm and demarcation norm of SHMS V1.0 for midwives in Fujian Province.3.To clarify the level of sub-health among midwives in Fujian Province,and to explore the influencing factors of their physical,psychological and social sub-health.4.To construct the prediction model of sub-health among midwives in Fujian Province based on the demarcation norm,and to verify the feasibility and accuracy of the model.Methods:1.The first stage:In this study,all the midwives who met the selected conditions in46 midwifery medical institutions in Fujian Province were selected by stratified cluster random sampling from March to June 2019.Data were collected by general situation questionnaire,Sub-Health Measurement Scale Version 1.0,Maslach Burnout Inventory,Social Support Rating Scale,Pittsburgh Sleep Quality Index and Fatigue Scale-14.The applicability of SHMS V1.0 in midwives was determined by reliability and validity test;the score norm of SHMS V1.0 was established among midwives in Fujian Province by normal distribution method;statistical description,univariate analysis and multiple linear regression were used to analyze the level of physical,psychological,social sub-health and their influencing factors;the prediction model of sub-health among midwives was constructed through unconditional binary logistic regression.2.The second stage:The second stage of this study was an empirical study.Fifteen rest midwifery medical institutions in Fujian Province were selected through stratified cluster random sampling from July to August 2019.And the predictors were collected by the same questionnaire as the first stage and substituted into the midwife sub-health prediction model constructed in the first stage to test the prediction effect of the model.Results:1.In this study,900 questionnaires were distributed and 875 questionnaires were collected,with a recovery rate of 97.22%,of which 842 were valid,with an effective rate of 96.23%.2.Reliability and validity of SHMS V1.0:Cronbach’s a coefficient,split half coefficient and retest reliability of SHMS V1.0 were 0.908,0.813 and 0.804,respectively.The project analysis showed that the correlation coefficients between each item and its affiliated dimension,ranging from 0.619 to 0.890,were higher than those between the item and other dimensions.The correlation coefficients between each dimension and its affiliated sub-scale,ranging from 0.614 to 0.911,were higher than those between the dimension and other sub-scales.The correlation coefficients between each dimension and total scale ranged from 0.615 to 0.800.In confirmatory factor analysis,the first-order factor model and the second-order factor model for SHMS V1.0showed that all adaptation indexes reached the ideal values,suggesting that the scale had a good structural validity.The criterion validity analysis showed that the correlation coefficient between the score of SHMS V1.0 and FS-14 was-0.802,P<0.001,indicating that the criterion validity was good.3.Norm of SHMS V1.0 for midwives in Fujian Province:there was no statistical difference in the score of SHMS V1.0 among different age groups of midwives,and there was significant difference among different length of service in labor room.Therefore,the mean norm of SHMS V1.0 was formulated according to length of service in labor room:(58.83±12.11)for the midwives with≤10 years of service length in labor room,(56.56±11.78)for the midwives with 11～20 years of service length in labor room,and(63.69±10.96)for the midwives with≥21 years of service length in labor room.The optimal demarcation scheme for SHMS V1.0 was determined according to the normal distribution method and the correlation between the distribution of demarcation norm and the scores of SHMS V1.0,FS-14.Namely,[0,(?)-0.5s),[(?)-0.5s,(?)),[(?),(?)+0.5s),[(?)+0.5s,100]were classified as severe sub-health,moderate sub-health,mild sub-health,healthy,respectively.The corresponding bounds of SHMS V1.0 were[0,53],[53,59],[59,65],[65,100].The boundary value of physical sub-health were[0,52],[52,59],[59,66],[66,100];the boundary value of psychological sub-health were[0,49],[49,57],[57,64],[64,100];the boundary value of social sub-health were[0,54],[54,61],[61,67],[67,100].4.The average score of the sub-health among midwives was(58.66±12.07),and the average scores of physical,psychological and social sub-health were(59.00±14.31),(56.65±14.40)and(60.82±13.31)respectively.According to the demarcation norm,midwives with SHMS V1.0 score<65 were considered as sub-health;those with SHMS V1.0 score≥65 were considered as health.Consequently,the prevalence of midwives’sub-health was 68.88%,among which the prevalences of physical,psychological and social sub-health were 66.51%,69.36%and 67.81%,respectively.5.The multiple stepwise linear regression analysis showed that the influencing factors of physical sub-health among midwives were education background,length of service in labor room,frequency of irregular meals per week,types of adverse life events,types of occupational injury events,job satisfaction,job burnout and sleep quality(adjusted R~2=0.472,F=94.795,P<0.001);the influencing factors of midwives’psychological sub-health were frequency of irregular meals per week,duration of exercise per time,types of adverse life events,job satisfaction,job burnout,level of social support and sleep quality(adjusted R~2=0.470,F=107.470,P<0.001);the influencing factors of midwives’social sub-health were marital status,duration of each exercise,types of adverse life events,job satisfaction,job burnout,level of social support and sleep quality(adjusted R~2=0.369,F=71.298,P<0.001).6.According to the demarcation norm,midwives were classified as sub-health and health,which was treated as dependent variable.Unconditional binary logistic regression analysis showed that:the frequency of irregular meals per week,the duration of each exercise,the types of adverse life events,hospital nature,the length of service in the labor room,job satisfaction,job burnout,social support and sleep quality could predict the sub-health status of midwives.The goodness of fit test showed that the chi square value of Hosmer lemeshow test was 1.413,P=0.994;Cox&Snell R~2was 0.387,and nagelkeke R~2 was 0.544;the classification table suggested that the prediction accuracy of the model was 83.14%and Youden index was 58.36%.The area under the receiver operating characteristic curve(ROC)was 0.893,which indicated that the prediction effect of the model was good.7.A total of 15 midwifery medical institutions were investigated in the second stage,with 264 valid data,of which 70 were healthy and 194 were sub healthy.The predictors were substituted into the logistic regression model for midwife’s sub-health,which showed that the overall prediction accuracy of the model was 81.06%,and Youden index was 52.31%.Conclusions:1.SHMS V1.0 has good reliability and validity,which can be used to evaluate the sub-health status of midwives in Fujian Province.2.The establishment of mean norm,percentile norm and demarcation norm for SHMS V1.0 can provide reference for screening and evaluating the sub-health status of midwives in Fujian Province,and lay a theoretical foundation for further exploring the prevalence and influencing factors of sub-health among midwives.3.Most midwives in Fujian Province are in the state of sub-health,which is affected by demographic characteristics(education,marital status),life behavior(diet,physical exercise and adverse life events),occupational factors(hospital nature,length of service in labor room,occupational injury events,job satisfaction and burnout),social support and sleep quality.4.According to the prediction model,it does benefit to early detect and prevent sub-health of midwives.And it is important to take various measures such as regulatory action,hospital action,information communication and self-health promotion behavior to reduce the incidence of midwife’s sub-health,so as to improve the level of midwives’health and raise the quality of midwifery service... |
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