The purpose of this study was to provide basic data on preschool children of accident prevention and to improve their health through a sound, safe living environment with safety education established through more systematic methods. Data were collected from 516 preschoolers from 4 to 6 years old using APP paper test which consists of a question and drawing. The children's general characteristics and accident proneness prospect were investigated. The relationship between the children's general characteristics and the accident proneness prospect were analyzed. The findings of the study are as follows: 1. The institution which children attended had a significant difference in accordance with the living safety(p=.015) and behavior character(p=.033). 2. The housing pattern in which children lived had a significant difference in accordance with the movement speed(p=.027). 3. The children's age had a significant difference in accordance with the living safety(p=.002), traffic safety(p=.001), the reasoning power(p=.000), movement speed(p=.00), movement stability(p=.000) and attentional power (p=.000). 4. The children's sex had a significant difference in accordance with the movement stability and behavioral character(p=.003, p=.008). 5. The children's past accidental experience had a significant difference in accordance with the behavior character(p=.001). 6. General assessment of the APP test had a significant difference in accordance with the children's age(p=.000) and children's past accidental experience(p=.020).
Accident Prevention ; Accident Proneness* ; Child ; Child, Preschool ; Education ; Housing ; Humans

OBJECTIVETo investigate the incidence of accident proneness and its influencing factors in rural children.

METHODSBy random cluster sampling, 1 560 children were enrolled from one rural area in Hunan Province, China, and were surveyed with self-designed general and injury questionnaires. Unconditional multivariate logistic regression analysis was used to explore the major risk factors for accident-prone children.

RESULTSOne hundred and forty-seven accident-prone children were screened out and the incidence of accident proneness was 9.42%. Univariate analysis showed that gender (P<0.01), academic record (P<0.01), left-behind status (P<0.05), family type (P<0.05), family economic status (P<0.01), guardian's gender (P<0.05), guardian's marital status (P<0.05), guardian's occupation (P<0.05), and family educational mode (P<0.05) were influencing factors for accident proneness in rural children. Multivariate logistic regression analysis further revealed that low grade (OR=3.683, 95%CI: 1.028-4.283) and very low grade (OR=2.099, 95% CI: 1.587-8.546) in academic record, poverty in family economic status (OR=2.353, 95% CI: 1.222-4.533), and indulgence or indifference (OR=1.914, 95% CI: 1.029-3.559) and fickleness (OR=4.153, 95% CI: 1.847-9.338) in guardian's educational mode were risk factors for accident proneness in rural children, while female gender (OR=0.539, 95% CI: 0.369-0.788) was a protective factor.

CONCLUSIONSLow academic record, poor family economy, and incorrect family education mode (indulgence or indifference and fickleness) would increase the incidence of accident proneness in rural children, but girls have less accident proneness than boys.

Accident Proneness ; Adolescent ; Child ; Female ; Humans ; Incidence ; Male ; Rural Population

The purpose of this study was to measure the effect of safety education program in preschool children for accident prevention and improve their health through more systematic method. Data were collected from 584 preschoolers(247 preschooler are assigned to experimental group and 337 preschoolers are assinged to control group) from 4 to 6 years old using APP paper test which consists of questions and drawings. To experimental group, safety education were done 4 times within the time of 30 minutes per 1 time using education books, drawings, OHP. The findings of this study are as follows: 1.There were significant difference in movement( X2=18.732, p=.0000), behavioral character( X2=27.785, p=.000), synthetic judgement( X2=12.02, p=0.002). So, safety education program have effect on preschooler. 2.In the accident proneness on preschooler between experimental group and control group according to general characteristics, it proved significant difference in the case of accident prevention education were done, reasoning power( X2=10.48, p=.005), movement speed( X2=7.341, p=.025) and behavioral character( X2=18.86, p=.000), in the case of housing pattern is private house(individual house, yard?), reasoning power( X2=6.683, p=.035), movement speed( X2=12.76, p= .002) and behavioral character( X2=12.24, p=.002), in the case of housing pattern is mixed-type, movement speed( X2=6.935, p= .031) and behavioral character( X2=10.816, p=.004), in the case of housing pattern is over six stories, movement speed( X2=7.543, p=.023), in the case of subjects' age is 4 years old, movement speed( X2=16.5, p= .000) and behavioral character( X2=12.18, p=.002), in the case of subjects' age is 5 years old, movement speed( X2=7.519, p= .023), watchfulness( X2=6.372, p=.041), behavioral character( X2=14.74, p=0.001) and synthetic judgement( X2=14.5, p=.001), in the case of subjects' sex is male, life safety( X2=6.406, p=.041), movment speed( X2=22.86, p= .000), behavioral character( X2=13.72, p= .001) and synthetic judgement( X2=13.82, p=.001), in the case of subjects' sex is female, reasoning power( X2=12.57, p=.002) and behavioral character( X2=13.16, p= .001), in the case of childrens have past accidental experience, traffic safety( X2= 6.683, p=.035), in the case of childrens have no past accidental experience, reasoning power( X2=8.384, p=.015), movement speed( X2=20.6, p=.000), behavioral character( X2 =25.1, p=.000) and synthetic judgement( X2 =10.79, p=.005), in the case of children's order is first, reasoning power( X2=11.15, p=.004), movement speed( X2=11.92, p= .003) and behavioral character( X2=7.003, p=.030), in the case of children's order is second, movement speed( X2=6.694, p= .035), behavioral character( X2=26.9, p= .000) and synthetic judgement( X2=14.3, p= .001), in the case of nuclear family, reasoning power( X2=8.777, p=.012), movement speed( X2=19.0, p=.000), behavioral character ( X2=26.4, p=0.000) and synthetic judgement ( X2=9.999, p=.007), in the case of mothers' school career is under high school graduate, life safety( X2=8.023, p=.018), movement speed( X2=10.99, p=.004) and behavioral character( X2=6.777, p=.034), in the case of mothers' school career is beyond college graduate, reasoning power( X2=6.717, p= .035), movement speed( X2=8.963, p=.011), behavioral character( X2=25.03, p=.000) and synthetic judgement( X2=15.19, p=.001), in the case of mothers' age ranged 31-34, movement speed( X2=12.29, p=.002) and behavioral character( X2=14.17, p=.001), in the case of mothers' age ranged 35-39, movement speed( X2=9.859, p=.007), behavioral character( X2=9.095, p=.011) and synthetic judgement( X2=7.810, p=.020), in the case of mothers' age is over 40, life safety( X2 =5.593, p=.025), in the case of mothers' job is full-time, traffic safety( X2=6.032, p=.049) and reasoning power( X2=8.502, p= .014), in the case of mothers' job is part- time., movement speed( X2=10.99, p=.004) and behavioral character( X2=7.895, p= .019), in the case of mothers have no job, movement speed( X2=6.410, p=.041), movement stability( X2=6.879, p=.032), behavioral character( X2=27.72, p=.000) and synthetic judgement( X2=18.11, p=.000). The difference of accident proneness between experimental group and control group according to general characterists, it also showed that there were significant difference in behaviorl character compared to other area.. From this findings, we can guess that safety education program change and guide preschoolers' behavioral character to desirable direction.
Accident Prevention ; Accident Proneness ; Child ; Child, Preschool ; Education* ; Female ; Housing ; Humans ; Male ; Mothers ; Nuclear Family ; Child Health

The purpose of this study was to provide basic data on preschool children for accident prevention and improve their health through sound, safe living enviornment with safety education estabilished through more systematic method. Data were collected from 300 preschoolers(150 preschooler are assigned to experimental group and 150 preschoolers are assinged to control group) from 4 to 6 years old using APP paper test which consists of questions and drawings. To experimental group, safety education were done 4 times within the time of 30 minutes per 1 time using education books, video, OHP, slide. The findings of this study are as follows: 1.There were significant difference in behavioral character between experimental group and control group( chi 2=11.690, p= 0.003). So, safety education have effect on the behavioral character of preschooler. 2. In the accident proneness on preschooler between experimental group and control group according to general characteristics, it proved significant difference in the case of accident prevention education were done, movement stability( chi 2=8.844, p=0.012) and behavioral character( chi 2=6.699, p=0.035), in the case of housing pattern is mixed-type, behavioral character( chi 2=10.37, p=0.006), in the case of subjects' age is 4 years old, watchfulness( chi 2=9.525, p=0.009), in the case of subjects' age is 5 years old, behavioral character( chi 2=7.324, p=0.026), in the case of children's order is second, behavioral character( chi 2=14.31, p=0.001), in the case of children's sex is boy, living safety( chi 2=7.981, p=0.018), movement speed ( chi 2=6.661, p=0.036), bihavioral character( chi 2=8.837, p=0.012), in the case of children's sex is girl, reasoning power( chi 2 =9.78, p=0.008), in the case of childrens have no past accidental experience, behavioral character( chi 2=9.862, p=0.007), in the case of nuclear family, movement speed( chi 2=6.341, p=0.042) and behavioral character( chi 2=9.326, p=0.009), in the case of mothers' age is under thirty behavioral character( chi 2=16.40, p=0.000), in the case of mothers' school career is under high school graduate, behavioral character( chi 2 =8.375, p=0.015), in the case of mothers' school career is beyond college graduate, reasoning power( chi 2=9.803, p=0.007) and behavioral character( chi 2=6.205, p=0.045), in the case of mothers' job is part time, movement speed( chi 2=10.99, p=0.004), in the case of mothers have no job, movement stability( chi 2=8.490, p=0.014) and behavioral character( chi 2=10.11, p=0.006). The difference of accident proneness between experimental group and control group according to general characterists, it also showed that there were significant difference in behaviorl character compared to other area.. From this findings, we can guess that safety education change and guide preschoolers' behavioral character to desirable direction.
Accident Prevention ; Accident Proneness* ; Child ; Child, Preschool ; Education* ; Female ; Housing ; Humans ; Male ; Mothers ; Nuclear Family ; Child Health

BACKGROUND: Workforce health is one of the primary and most challenging issues, particularly in industrialized countries. This article aims at modeling the major factors affecting accidents in the workplace, including general health, work-family conflict, effortereward imbalance, and internal and external locus of control. METHODS: A cross-sectional study was conducted in Esfahan Steel Company in Iran. A total of 450 participants were divided into two groups—control and case—and the questionnaires were distributed among them. Data were collected through a 7-part questionnaire. Finally, the results were analyzed using SPSS 22.0 and Amos software. RESULTS: All the studied variables had a significant relationship with the accident proneness. In the case group, general health with a coefficient of −0.37, work-family conflict with 0.10, effort-reward imbalance with 0.10, internal locus of control with −0.07, and external locus of control with 0.40 had a direct effect on occupational stress. Occupational stress also had a positive direct effect on accident proneness with a coefficient of 0.47. In addition, fitness indices of control group showed general health (−0.35), work-family conflict (0.36), effort-reward imbalance (0.13), internal locus of control (−0.15), and external locus of control (0.12) have a direct effect on occupational stress. Besides, occupational stress with a coefficient of 0.09 had a direct effect on accident proneness. CONCLUSION: It can be concluded that although previous studies and the present study showed the effect of stress on accident and accident proneness, some hidden and external factors such as workefamily conflict, effortereward imbalance, and external locus of control that affect stress should also be considered. It helps industries face less occupational stress and, consequently, less occurrence rates of accidents.
Accident Proneness ; Accidents, Occupational ; Cross-Sectional Studies ; Developed Countries ; Internal-External Control ; Iran ; Steel

OBJECTIVES: Obstructive sleep apnea syndrome (OSAS) has drawn increasing attention as medical community has become to be aware of its co-morbidities and complications, especially cardiovascular complications and excessive daytime sleepiness with accident proneness. As of now, polysomnography is the standard tool to diagnose sleep apnea and estimate the treatment validity. However, its being rather expensive and inconvenient, alternate diagnostic tools have been proposed including wrist actigraphy. So far, actigraphies have been adopted usefully to field-survey sleep apnea prevalence. In this study, we attempted in a sleep laboratory setting to assess the supplemental value of actigraphy in diagnosing OSAS. METHODS: This study was done at the Division of Sleep Studies, the Seoul National University Hospital. Thirty-seven clinically suspected cases of OSAS underwent the one-night polysomnography, simultaneously wearing an actigraphy on non-dominant wrist. We analyzed the data of 27 polysomnographically-proven OSAS patients (male: female 20: 7; age 47.6+/-12.9 years old; age range 23 to 72 years) with no other sleep disorders. We calculated RDI (respiratory disturbance index) from the polysomnography data and FI (fragmentation index) from the actigraphy data. Pearson correlation was calculated in order to compare FI with RDI and to evaluate the supplemental diagnostic value of the actigraphy. RESULTS: Mean total sleep time on polysomnography was 401.4+/-57.8 min (range of 274.0 to 514.1 min). Mean RDI was 21.7+/-20.4 /hour. Mean FI was 21.9+/-13.0 / hour. RDI and FI showed significant correlation (r=0.55, p< 0.01). CONCLUSIONS: Wrist actigraphy in OSAS patients generates a comparable outcome to polysomnography, in measuring the nocturnal sleep fragmentation. The actigraphy could be used supplementally in inpatients, outpatients, and field survey subjects, if polysomnography is unavailable or impossible. In follow-ups related with nasal CPAP (continuous positive airway pressure), upper airway surgery, and oral appliance in OSAS patients, the actigraphy might play a more dominant role in the future.
Accident Proneness ; Actigraphy* ; Female ; Follow-Up Studies ; Humans ; Inpatients ; Outpatients ; Polysomnography ; Prevalence ; Seoul ; Sleep Apnea Syndromes ; Sleep Apnea, Obstructive* ; Sleep Deprivation ; Sleep Wake Disorders ; Wrist