The problem of falls has been widely discussed in the geriatric field; however, this phenomenon also involves pediatric populations (Khambalia et al., 2006). Although most falls are of little consequences and most children fall many times in their lives without sustaining much more than a few cuts and bruises, nonfatal falls represent a significant burden on healthcare facilities around the world. The frequency of nonfatal falls, healthcare costs, and the significant risk of death (particularly as a result of head injuries) demand that the prevention of fall-related injuries becomes a vital focus of child safety efforts worldwide. In fact, pediatric falls could lead to an increase in overall length of stay, pain, disability, unanticipated treatment, and an increase in cost of care (Hunderfund, Sweeney, Mandrekar, Johnson, & Britton, 2011 ; Kothare et al., 2011). The Joint Commission National Patient Safety Goals identified inpatient fall as a significant patient safety risk recommending to assess and periodically reassess each patient’s risk for falling, including the potential risk associated with the patient’s medication regimen, and take action to address any identified risks. Since 2006, the organization has required hospitals to implement fall prevention programs and evaluate the efficacy of such programs (The Joint Commission, 2007). The World Health Organization reports that falls go beyond the resilience of a child’s body, making them the fourth largest cause of unintentional injury death for children (World Health Organization, 2008). These data suggest that falls remain a safety challenge that impacts on quality health care in inpatient pediatric population. However, the literature about how child's medical conditions and characteristics influence the risk of children’s falls in the hospital is very limited. Fall rates of inpatient children range from 2.5% to 3.0% per 1,000 patient days (Hill-Rodriguez et al., 2009). Recently, in a multicenter observational study, the pediatric inpatient fall prevalence was 0.84 per 1,000 patient days (Jamerson et al., 2014). However, the literature about how diagnosis and child’s characteristics influence the risk of children’s falls in the hospital is very limited. Previous studies reported that children with typical absence epilepsy are at risk for accidental injury, which may range from a small bite on the tongue to a broken bone (Graf, 2005 ; Harvey, Kramlich, Chapman, Parker, & Blades, 2010). Recently, Hill-Rodriguez et al. (2009) reported that pediatrics patients with diagnoses of neurological conditions including epilepsy showed a higher risk of falls. In addition, mobility impairments, orthopedic diagnosis, impaired gait, and sedating medications increased fall risk (Kingston, Bryant, & Speer, 2010 ; Razmus & Davis, 2012). On the contrary, no study has evaluated the risk of inpatient falls among children with neurodevelopmental conditions. Children with neurodevelopmental conditions can experience sensory processing problems, motor difficulties, or behavioral problems that may increase the risk of injury (Wirrell, 2006). Therefore, studies that investigate the risk of falls in children with neurodevelopmental conditions are needed. In addition, cognitive impairment has been identified as a fall risk factor among older adults (Dionyssiotis, 2012 ; Stewart Williams et al., 2015). Indeed, recent studies showed that cognition has a key role in the regulation of gait and balance in older adults (Amboni, Barone, & Hausdorff, 2013). These findings suggest that the motor and sensory systems are linked by higher-order neurological processes and cognition, which are required for planning movements, divided attention, and responding to changes within the environment. Although cognitive difficulties have been identified as risk factor in adults, studies evaluating this association in the pediatric population are missing.
Children characteristics such as age, gender, children’s developmental disability abilities, and environmental needs are related to inpatient pediatric falls. The findings for the higher incidence of inpatient falls with younger children have been noted by several studies (Cummings, 2006 ; McGreevey, 2005 ; Tung, Liu, Yang, Syu, & Wu, 2009). To date, studies investigating association between children’s gender and pediatric falls have produced equivocal results. Some studies reported that male children fall more frequently (Otters et al., 2005), and other studies report that female children fell more often compared to male children (Cooper & Nolt, 2007). Inpatient pediatric falls are related to children’s developmental abilities and environmental risks (Gaebler-Spira & Thornton, 2002). A 9-year longitudinal review of 205 inpatient charts showed the majority of falls were younger children who often fell from cribs (Lyons & Oates, 1993). Other common falls were children under 1 year who fell from gurneys and adolescents who fell while ambulating or performing activities in the bathroom (Cooper & Nolt, 2007).
Furthermore, the literature emphasizes the need for using hospital fall prevention initiatives and pediatric risk assessment tools. Falls prevention activities could prevent or reduce the overall number of falls by taking preventative measures (Tung et al., 2009). Identifying those children most at risk of falling is important in providing early and targeted intervention to reduce that risk, containing the use of resources and costs. Previous studies showed that fall risk assessment tools for adults were poor predictors of falls in the pediatric population (Aranda-Gallardo et al., 2013). There is a lack of pediatric-specific instruments that can be used with confidence as part of an effective falls prevention programs. However, risk assessment tools should involve both intrinsic (e.g., age, gender, and developmental status) and extrinsic factors (e.g., identifying fall risk, anesthesia, sedatives, and environmental factors). For this reason, in the current study we used the Humpty Dumpty Falls Scale (HDFS), already validated in pediatric studies (Hill-Rodriguez et al., 2009 ; Messmer, Williams, & Williams, 2013 ; Woods et al., 2006), that looks at both intrinsic (age, gender, diagnosis, and cognitive impairment) and extrinsic (environmental factors, response to sedation/anesthesia, and medication usage) factors.
Therefore, the aim of the current study was to investigate in-hospital falls among children with neurological or neurodevelopmental conditions in order to explore which children are at increased risk of falling and what are the predictors of inpatient falls among children with different conditions. Furthermore, we evaluated the association between child's characteristics such as age, gender, and intelligent quotient (IQ) and falls in children.
Research Design and Participants
A cross-sectional, correlational study design was used in this study. We selected an initial sample of 726 children, consecutively referred to the Scientific Institute for Research, Hospitalization and Health Care “Eugenio Medea-La Nostra Famiglia”–Unit for Severe Disabilities of Developmental Age and Young Adults (Brindisi, Italy), during the period between January 2013 and September 2016. All children were admitted to our pediatric neurorehabilitation unit for diagnosis or a comprehensive neurorehabilitation program. All hospitalized children are considered to be at high risk, and a fall prevention program, which is routinely applied in our hospital, was applied to all patients. The prevention program includes the training of each caregiver with regard to orientation in the hospital. In addition, a sticker indicating the high risk of falling is attached on the bed, pajamas, and the medical record of that patient.
Inclusion criteria were as follows: (1) admitted with neurological or neurodevelopmental conditions, (2) assessed IQ through standardized test, and (3) be between 12 month and 17 years of age. Exclusion criteria were the presence of any acute systemic disorder that would affect the patient’s general health status, causing severe malaise or any orthopedic problem not associated to diagnosis (e.g., amputation) that would increase the risk of fall. A total of 446 patients meeting the study inclusion criteria were recruited.
The patients were divided into two groups: the neurological group (epilepsy, cerebral palsy, developmental coordination disorder, ataxia, spinal muscular atrophy, muscular dystrophy, spastic paraparesis, gait abnormality, and neurofibromatosis) and the neurodevelopmental group (attention-deficit/hyperactivity disorder, autism spectrum disorder, global developmental delay, intellectual disability, speech and language disorders, tic disorder, and obsessive-compulsive disorder).
The study team defined a fall as an unplanned descent to the floor (or an extension of the floor, such as a trash can or other equipment) with or without injury to the patient (Agostini, Baker, & Bogardus, 2001). Injury severity level was assigned by investigators according to Schaffer et al. (2012). The severity category labeled “major” was defined to include injuries resulting in a fracture or sutures. “Moderate” injuries were classified as bleeding from any wound caused by the fall. “Minor” injuries were defined as children who obtained abrasions, bruises, reddened areas, contusions, and swelling or complaint of pain in the affected area. No ethics committee approval is necessary because the assessment of falls risk is included in the Falls Risk Management Plan of our Medical Center. However, personal data was protected by Data Protection Code-Legislative Decree No. 196/2003. All children were recruited in this study after obtaining written informed consent by their parents.
Demographic (age and gender) and clinical data (medication usage, falls in hospital, IQ) were collected to describe the sample. All data were collected during the week before the fall prevention program was implemented. We collected the number of falls while in hospital prior the beginning of the fall prevention program. IQ was assessed according to age through international standardized test such as Wechsler Intelligence Scale for Children-IV (Wechsler, 2003) and Wechsler Preschool and Primary Scale of Intelligence-III (Wechsler, 2002). Leiter International Performances Scale-Revised (Roid & Miller, 2011), alternatively to Wechsler Intelligence Scale for Children-IV, was used for children with speech and language impairment. The HDFS was completed and scored for each participant. The HDFS (Hill-Rodriguez et al., 2009) is a special screening tool developed for the assessment of risk of falling in children. The HDFS was developed by the Miami Children’s Hospital from a retrospective study of clinical criteria that accompanied falls in pediatric inpatients. The HDFS is composed of six categories including (a) age, (b) gender, (c) diagnosis, (d) cognitive impairment, (e) environmental factors, and (f) response to surgery/sedation/anesthesia and medication usage (Hill-Rodriguez et al., 2009). Patients are assigned values from 1 to 3 or from 1 to 4 for each parameter, depending on specific criteria for the parameter. Patients can score a minimum of 7 and a maximum of 23. The instrument indicates high risk at scores greater than 11, and patients scoring 7–11 are categorized as low risk. The HDFS Fall Risk score indicates whether the score obtained is less or greater than the cutoff of 12 (low score 7–11 = absent; high score >12 = present). The HDFS sensitivity was 0.85, the specificity was 0.24 with the positive predictive power at 0.53 and negative predictive power at 0.63; the overall percentage of patients correctly classified as to their risk of a fall was 59.3%. In the current study, the HDFS total mean scores were used as an indicator of “risk score.”
The mean, standard deviation (SD), and median values were calculated with descriptive statistics. The chi-square test (χ2) was used to compare dichotomous variables (gender, medication usage, falls in hospital, HDFS Fall Risk < or > of cutoff) between the neurological and neurodevelopmental groups. The χ2 enabled us to compare observed and expected frequencies of dichotomous variables objectively. Statistical significance in this case is due to difference between observed and expected frequencies. Both groups were compared with the independent sample t test for comparison of age, IQ, and HDFS total mean score. To determine factors associated with risk of children’s falls in the hospital, we have distinguished the statistical analysis for the neurological and neurodevelopmental groups. Analysis of variance test was used to evaluate the differences of the means of the HDFS total score among children included in different age groups (younger than 3 years, 3–6 years, 7–12 years, 13 years or older). In addition, Bonferroni correction was used to conduct the post hoc analysis. Independent continuous variables showing a p value of <.05 were included as predictors factors in a multiple linear regression analysis.
A p value of less than .05 was considered as statistically significant. For statistical processing, we used the data processing program the Statistical Package for Social Science version 20.0.
Sociodemographic characteristics of total, neurological, and neurodevelopmental groups are summarized in Table 1. Of the 446 patients, 66.8% (n = 298) were admitted with neurological conditions, whereas 33.2% (n = 148) were admitted with neurodevelopmental conditions. The neurological group included epilepsy (13.4%), cerebral palsy (21.8%), developmental coordination disorder (14.1%), ataxia (7.4%), spinal muscular atrophy (1%), muscular dystrophy (5.4%), spastic paraparesis (29.2%), gait abnormality (5%), and neurofibromatosis (2.7%). The neurodevelopmental group included attention-deficit/hyperactivity disorder (26.4%), autism spectrum disorder (20.9%), global developmental delay (25.7%), intellectual disability (16.8%), speech and language disorders (6.8%), tic disorder (2%), and obsessive-compulsive disorder (1.4%).
No statistical differences among the neurological and neurodevelopmental groups in age (p = .59) and gender (p = .21) were found. In the total sample, the mean HDFS total mean score was 13.5 (SD = 3.07), the mean IQ score was 67.4 (SD = 21.8), and the mean age was 7.01 (SD = 4.5).
There were no injuries classified as “major.” The 6% of the falls received medical or surgical treatment for their injuries and were classified as “moderate,” and the 94% of the falls were classified as “minor.”
Comparing Neurological and Neurodevelopmental Groups
We found statistically significant differences in HDFS total mean score (f = 17.8, p = .001), number of hospital falls (f = 8.5; p = .003), and age groups (f = 16.8; p = .001). The neurodevelopmental group (14.24 ± 3.1) showed higher HDFS total mean score compared the neurological group (13.2 ± 3.1). Falls in hospital are more frequent (p = .003) in the neurodevelopmental group (12.9%) compared with the neurological group (5.1%). The neurodevelopmental group was mainly characterized by children included in younger than 3 years (18.2%) and 3–6 years (47.2%) age groups, whereas the neurological group was mainly characterized by children included in 7–12 years (35.5%) and 13 years or older (16.4%) age groups.
Differences Within Neurological Group
Boys reported a higher percentage of high fall risk (p = .03) and HDFS total mean score (p < .001) compared with girls. Children undergoing polytherapy reported higher HDFS total mean score (p = 0.013) compared with children undergoing monotherapy. Children included in the age group of younger than 3 years showed higher HDFS total mean score compared with children included in the age group of 3–6 years (p < .001), 7–12 years (p < .001), and 13 years or older (p < .001); children included in the age group 3–6 years showed higher HDFS total mean score compared with children included in the age group 7–12 years (p = .001) and 13 years or older (p < .001). In addition, children included in the age group younger than 3 years (100%) and 3–6 years (83.9%) are more characterized by greater fall risk high prevalence of risk falls whereas children included in the age group 7–12 years (54.7%) and 13 years or older (45.3%) are more characterized by lower fall risk low prevalence of risk falls. Despite younger children (up to 6 years) having great fall risk than older children (>7 years), there was no significant difference in hospital falls between the age group. However, the actual falls happened the most in ages 3–6. Children with high risk of falls show a statistically significant lower IQ (p = .003) than children with low risk of falls. The differences within the neurological group are summarized in Table 2.
Differences Within Neurodevelopmental Group
Boys reported a higher HDFS total mean score (p = .013) compared with girls. Statistically significant differences between age groups were found in the number of falls in hospital (f = 27.6, p < .001), HDFS Fall Risk (f = 37.1, p < .001), and HDFS total mean score (f = 31.4, p < .001). In particular, children included in the age group of younger than 3 years were characterized by more falls in hospital (57.9%) and high prevalence of risk falls (100%), whereas children included in the age group of 3–6 years were characterized by high prevalence of risk falls (76%). In addition, children included in the age group of younger than 3 years showed higher HDFS total score compared with children included in the age group of 3–6 years (p < .001), 7–12 years (p < .001), and 13 years or older (p < .001); children included in the age group 3–6 years showed higher HDFS total score compared with children included in the age group 7–12 years (p < .001) and 13 years or older (p = .03). Children with high risk of falls show a statistically significant lower IQ (p = .005) than children with low risk of falls.
The differences within the neurodevelopmental group are summarized in Table 3.
Multiple Linear Regression and Correlation Between Children’s Age and IQ With HDFS Total Score
In the neurological group, HDFS total mean score correlates negatively with children’s age (r = −.554, p < .001) and IQ (r = −.197, p = .001). In the neurodevelopmental group, HDFS total mean score correlates negatively with children’s age (r = −.619, p < .001) and IQ (r = −.189, p = .022).
The results of correlational analysis are reported in Table 4. In both groups, age and IQ scores were added to the regression model to identify predictors of the HDFS total score. (Table 5). In the neurological group, adjusted R 2 = .31 indicates that age (β = −0.357; confidence interval [CI] [−0.409, −0.305]) and IQ (β = −0.24; CI [−0.035, −0.013]) explained 31% of the variance of the HDFS scores, whereas in the neurodevelopmental group, adjusted R 2 = .38 indicates that age (β = −0.531; CI [−0.409, −0.305]) and IQ (β = −0.168; CI [−0.035, −0.013]) explained 38% of the variance of the HDFS scores (Table 5).
In the current study, we investigated which individuals are at increased risk of falling and what the predictors of inpatient falls are comparing children with neurological and neurodevelopmental conditions. Several studies reported that the diagnosis of a neurological disease, especially epilepsy and seizures, was associated with an increased incidence of falls (Graf, 2005 ; Hill-Rodriguez et al., 2009). Other studies highlighted the need to use specific precaution or safety measures for children who are at high risk for falls, such as children with cerebral palsy (Alemdaroğlu et al., 2017 ; Tung et al., 2009). The great attention by literature studies on the risk of falls in children with neurological conditions may be explained by the fact that medical conditions characterizing the neurological group such as drop seizures, severe ataxia, diparesis, tetraparesis, hemiparesis, or use of ankle and foot orthosis are considered to have greater impact on the risk of falls (Khambalia et al., 2006 ; Norton, Nixon, & Sibert, 2004). In agreement with previous studies, we have found that children with neurological conditions such as epilepsy (7.5%), cerebral palsy (14.8%), or muscular dystrophy (6.4%) were identified as at increased risk of falls during hospitalization. However, results of the current study indicate that the neurodevelopmental group showed a higher HDFS total mean score and higher rate falls compared with the neurological group (Table 1). These findings highlight the importance of implementing falls prevention activities in children with psychopathologies, which may be less supervised and thus at increased risk. Furthermore, we have found a high prevalence of falls in children with attention-deficit/hyperactivity disorder (10.3%), autism spectrum disorder (9.7%), or global developmental delay (18.3%). The high prevalence of falls in children with global developmental delay may be due to the copresence of cognitive and motor impairments that might increase the risk of falls, whereas children with autism spectrum disorder or attention-deficit/hyperactivity disorder do not recognize their careless or impulsive actions as wrong and repeatedly display these actions (Lee, Kim, Lee, Lee, & Kim, 2015). These impulsive behaviors and decreased concentration and self-control may increase fall risk in these children. Further studies are required to investigate the association between in-hospital falls and neurodevelopmental conditions.
In the present study, we found that age, gender, and IQ are factors associated with the risk of falls.
As to age, Hill-Rodriquez et al. (2009) reported that most falls occurred in children younger than 3 years (37%) and 13 years and older (30%). Wood et al. (2006) reported that the most falls occur in children with a neurological impairment under 3 years and older than 12 years (Woods et al., 2006). In agreement with these studies, we found that most falls occurred in children younger than 3 years in both the neurological and neurodevelopmental groups. In contrast to earlier findings, however, no evidence of falls occurring in children older than 7 years was detected. About the children’s gender, it is unclear how gender has an influence on their fall risk. Although some studies reported that male children fall more frequently (McGreevey, 2005 ; Neiman, Rannie, Thrasher, Terry, & Kahn, 2011), one study reported that female children fell more often (55%) compared to male children (Cooper & Nolt, 2007), and no difference in gender risk was found in one study (Hill-Rodriguez et al., 2009). Our findings are consistent with studies that report a sample of male children who fell more often than female children in both neurological and neurodevelopmental groups.
Another important finding was the association between IQ and risk of children’s falls. So far, very little attention has been paid to the role of IQ on the risk of pediatric falls. We found that IQ correlates negatively with the risk of falling. This result suggests that cognitive impairment plays a major factor in pediatric falls. A possible explanation for this might be that falls may occur due to the child’s inability to understand the consequences of their actions. Therefore, cognitive abilities as influenced by both normal development and/or impairments may place children at risk for falls. Cognitive impairment can be a proxy for many possible factors associated with falls such as behavioral issues, lack of insight with resultant engagement in risk-taking activity, mobility deficits, and difficulty with performance of activities requiring divided attention. Research within homogeneous samples of children with cognitive disabilities can further help identify the underlying contributing factors and mechanisms that can enhance fall prevention interventions. These results, however, need to be interpreted with caution. In fact, the HDFS contained the cognitive impairment, and it may be the one reason why there was a strong correlation between the IQ and the risk of fall.
The generalizability of these results is subject to certain limitations. The present study was a cross-sectional, correlational study using a sample of fall events that did not include a comparative group of nonfallers. Although the HDFS captures some of the real risk of falling among hospitalized pediatric patients, further assessment tool with high specificity and high percentage of correctly classified risk of falls is necessary (Wiwanitkit, 2010). In addition, environmental risks such as location, activity at time of fall, and presence of parents or adults were not investigated.
Key Practice Points
- Neurological diseases are associated with an increased incidence of falls.
- Studies that investigate the risk of falls in children with neurodevelopmental conditions are lacking.
- A high prevalence of falls was also found in children with neurodevelopmental conditions.
- Fall prevention programs must be implemented in children with neurodevelopmental conditions.
In conclusion, in this study, we evaluated the incidence of falls among children with neurological or neurodevelopmental conditions and investigated associated child characteristics. The finding of the current study supports the significance of recommendations to identify and document falls in the hospitalized pediatric population. This study stresses the concept that the fall prevention programs must be implemented in children with neurodevelopmental conditions, not only in children with neurological conditions. In addition, we found that age, gender, and IQ are associated with the risk of inpatient falls. More research is needed, however, as to what the best preventive strategies for children are.
The authors thank the BIM (Brindisi IRCCS Medea) Falls Study Group for their contribution. The authors declare no conflict of interest.
Alemdaroğlu E., Özbudak S. D., Mandiroğlu S., Biçer S. A., Özgirgin N., & Uçan H. (2017). Predictive factors for inpatient falls
with cerebral palsy. Journal of Pediatric Nursing
, 32, 25–31. doi:10.1016/j.pedn.2016.08.005
Agostini J. V., Baker D. I., & Bogardous S. T. Jr. (2001). Prevention of falls in hospitalized and institutionalized older people. Markowitz A. J., Shojania K. G., Duncan B. W., McDonald K. M., & Wachter R. M. (Eds.), Making Health Care Safer: A Critical Analysis of Patient Safety Practices, (#43, pp.281–299)
. Rockville, Maryland: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services.
Amboni M., Barone P., & Hausdorff J. M. (2013). Cognitive contributions to gait and falls: Evidence and implications. Movement Disorders
, 28(11), 1520–1533. doi:10.1002/mds.25674
Aranda-Gallardo M., Morales-Asencio J. M., Canca-Sanchez J. C., Barrero-Sojo S., Perez-Jimenez C., Morales-Fernandez A., … Mora-Banderas A. M. (2013). Instruments for assessing the risk of falls in acute hospitalized patients: A systematic review and meta-analysis. BMC Health Services Research
, 13, 122. doi:10.1186/1472-6963-13-122
Cooper C. L., & Nolt J. D. (2007). Development of an evidence-based pediatric fall prevention program. Journal of Nursing Care Quality
, 22(2), 107–112. doi:10.1097/01.NCQ.0000263098.83439.8c
Cummings R. L. (2006). Creating a pediatric fall assessment tool
. In Paper presented at the 17th International Nursing Research Congress Focusing on Evidence-Based Practice
. Montreal, Quebec: Canada.
Dionyssiotis Y. (2012). Analyzing the problem of falls among older people. International Journal of General Medicine
, 5, 805–813. doi:10.2147/IJGM.S32651
Gaebler-Spira D., & Thornton L. S. (2002). Injury prevention for children
with disabilities. Physical Medicine and Rehabilitation Clinics of North America
, 13(4), 891–906.
Graf E. (2005). Examining inpatient pediatric falls: Understanding the reasons and finding the solutions. Joint Commission Perspectives on Patient Safety
, 54, 8.
Harvey K., Kramlich D., Chapman J., Parker J., & Blades E. (2010). Exploring and evaluating five paediatric falls assessment instruments and injury risk indicators: An ambispective study in a tertiary care setting. Journal of Nursing Management
, 18(5), 531–541. doi:10.1111/j.1365-2834.2010.01095.x
Hill-Rodriguez D., Messmer P. R., Williams P. D., Zeller R. A., Williams A. R., Wood M., & Henry M. (2009). The Humpty Dumpty Falls Scale: A case–control study. Journal for Specialists in Pediatric Nursing
, 14(1), 22–32. doi:10.1111/j.1744-6155.2008.00166.x
Hunderfund A. N., Sweeney C. M., Mandrekar J. N., Johnson L. M., & Britton J. W. (2011). Effect of a multidisciplinary fall risk
assessment on falls among neurology inpatients. Mayo Clinic Proceedings
, 86(1), 19–24. doi:10.4065/mcp.2010.0441
Jamerson P. A., Graf E., Messmer P. R., Fields H. W., Barton S., Berger A., … Lunbeck M. (2014). Inpatient falls
in freestanding children
's hospitals. Pediatric Nursing
, 40(3), 127–35.
Khambalia A., Joshi P., Brussoni M., Raina P., Morrongiello B., & Macarthur C. (2006). Risk factors for unintentional injuries due to falls in children
aged 0–6 years: A systematic review. Injury Prevention
, 12(6), 378–81.
Kingston F., Bryant T., & Speer K. (2010). Pediatric falls benchmarking collaborative. The Journal of Nursing Administration
, 40(6), 287–292. doi:10.1097/NNA.0b013e3181df10d9
Kothare S. V., Vendrame M., Sant J. L., Katz E. S., D'Ambrosio C., & Zarowski M. (2011). Fall-prevention policies in pediatric sleep laboratories. Journal of Clinical Sleep Medicine
, 7(1), 9–10.
Lee S. H., Kim K. S., Lee J. S., Lee J., & Kim S. D. (2015). Risk factors and incidence of falls among fifth- and sixth-grade children
in Seoul, South Korea. The Southeast Asian Journal of Tropical Medicine and Public Health
, 46(5), 924–938.
Lyons T. J., & Oates R. K. (1993). Falling out of bed: A relatively benign occurrence. Pediatrics
, 92(1), 125–7.
McGreevey M. (2005). Examining inpatient pediatric falls: Understanding the reasons and finding the solutions. Joint Commission Perspectives on Patient Safety
, 5, 2.
Messmer P. R., Williams P. D., & Williams A. R. (2013). A case–control study of pediatric falls using electronic medical records. Rehabilitation Nursing
, 38(2), 73–79. doi:10.1002/rnj.73
Neiman J., Rannie M., Thrasher J., Terry K., & Kahn M. G. (2011). Development, implementation, and evaluation of a comprehensive fall risk
program. Journal for Specialists in Pediatric Nursing
, 16(2), 130–139. doi:10.1111/j.1744-6155.2011.00277.x
Norton C., Nixon J., & Sibert J. R. (2004). Playground injuries to children
. Archives of Disease in Childhood
, 89(2), 103–108.
Otters H., Schellevis F. G., Damen J., van der Wouden J. C., van Suijlekom-Smit L. W., & Koes B. W. (2005). Epidemiology of unintentional injuries in childhood: A population-based survey in general practice. The British Journal of General Practice
, 55(517), 630–633.
Razmus I., & Davis D. (2012). The epidemiology of falls in hospitalized children
. Pediatric Nursing
, 38(1), 31–35.
Roid G. H., & Miller L. J. (2011). Leiter International Performance Scale-Revised (Leiter-R)
. Madrid, Spain: Psymtec.
Schaffer P. L., Daraiseh N. M., Daum L., Mendez E., Lin L., & Huth M. M. (2012). Pediatric inpatient falls
and injuries: a descriptive analysis of risk factors. Journal for Specialists in Pediatric Nursing
, 17(1), 10–18. doi: 10.1111/j.1744-6155.2011.00315.x
Stewart Williams J., Kowal P., Hestekin H., O'Driscoll T., Peltzer K., Yawson A. … SAGE Collaborators. (2015). Prevalence, risk factors and disability associated with fall-related injury in older adults in low- and middle-incomecountries: Results from the WHO Study on global AGEing and adult health (SAGE). BMC Medicine
, 13, 147. doi:10.1186/s12916-015-0390-8
Tung T. H., Liu M. C., Yang J. Y., Syu W. Y., & Wu H. P. (2009). Useful methods in preventing accidental falls from the bed in children
at the emergency department. European Journal of Pediatrics
, 168(11), 1323–1326. doi:10.1007/s00431-009-0928-x
Wechsler D. (2002). The Wechsler Preschool and Primary Scale of Intelligence
(3rd ed.). San Antonio, TX: The Psychological Corporation Canadian Journal of School Psychology.
Wechsler D. (2003). Wechsler Intelligence Scale for Children–Fourth Edition (WISC-IV)
. San Antonio, TX: The Psychological Corporation.
Wirrell E. C. (2006). Epilepsy-related injuries. Epilepsia
, 47(Suppl. 1), 79–86. doi:10.1111/j.1528-1167.2006.00666.x
Wiwanitkit V. (2010). Psychological plan for coping with swine flu outbreak. Journal for Specialists in Pediatric Nursing
, 15(4), 261. doi:10.1111/j.1744-6155.2010.00251.x
Woods M., Messmer P., Henry M., Salani D., Soto M., & Hill-Rodriguez D. (2006). Implementing a humpty dumpty fall scale for pediatric patients
. In Paper presented at the 17th International Nursing Research Congress Focusing on Evidence-Based Practice
. Montreal, Quebec: Canada.
Keywords:© 2018 Association of Rehabilitation Nurses.
Children; fall risk; inpatient falls; neurodevelopmental conditions; pediatric neurological conditions