How Should Providers Prepare for Pediatric Exams Systematic Review
Introduction
The World Health System defines child maltreatment as abuse and neglect that is directed at children nether 18 years former. Child maltreatment constitutes all forms of physical corruption, sexual abuse, emotional abuse, and fail that results in actual or potential harm to a child'due south wellness or survival (Globe Health Organization, 2020). In cases of child abuse, only children with injuries or in a life-threatening state of affairs are referred for medical treatment. All the same, child abuse does not necessarily present consistent symptoms and signs. Almost abusers or caregivers tend to deny or refuse to provide a child'due south medical history, which overshadows the crucial bespeak and misleads judgments on the presence of kid abuse, making related diagnoses and treatments more difficult. Without immediate identification and intervention, the risk of repeated maltreatment in children experiencing corruption increases, leading to physical and mental trauma that may be life-threatening (Oral et al., 2008).
Healthcare providers such as community and hospital medical staffs often encounter maltreated children in their professional settings. The characteristics of abuse differ across cases. In some cases, children who have experienced corruption exhibit just mild or insignificant symptoms such as bruises (Mimasaka et al., 2010). Healthcare professionals often apply medical histories, exhibited symptoms, and observations of interactions betwixt the child and his or her caregivers to determine the presence of corruption.
Existing screening tools for child corruption may be used by a wide range of professionals in various settings. Some tools accept been designed based on parents' or children'due south self-reported corruption (Saini et al., 2019), whereas others rely on the objective results of imaging examinations (Flom et al., 2016) or on physical and medical history analyses (Berger et al., 2016). Furthermore, community assessments of child corruption largely rely on parental statements, parental behavior, caring experiences, and straight observations to assess the state of a child and the home environment (van der Put et al., 2017). An efficient screening tool may assist healthcare providers to effectively identify potential cases of child corruption. Hoytema van Konijnenburg et al. (2013) reviewed the related literature and explored the employ of physical examinations to screen child abuse in hospitals and communities. Their findings showed that 0.8%–13.5% of children are screened for kid abuse. However, that study did non acquit a sensitivity and specificity analysis. Moreover, physical examination lonely is insufficient for screening child abuse cases. Because the difficulty in identifying child corruption, healthcare providers must pay greater attention to details and be more than sensitive in detecting cases of potential or actual abuse to systematically and efficiently screen suspected cases in busy clinical settings. The use of screening tools that offer high sensitivity and cover common injuries and features of child corruption has been shown to increase the rate of detection of kid abuse from less than iii% to 34% (Louwers et al., 2012).
An efficient screening tool that covers both risk factors and identification elements of child abuse volition enable healthcare workers to identify child abuse effectively, while reducing the burden of judgment and evaluation and lowering the chance of overlooking cases. Furthermore, the early on detection of child abuse will allow the provision of appropriate assistance, foreclose further abuse, and reduce long-term negative effects (Salinas-Miranda et al., 2015). A recent systematic literature review by Saini et al. (2019) analyzed 52 screening tools for kid abuse. This review included just instruments that measured whatever form of child abuse in manufactures published in English. The review found that virtually of the existing screening tools use self-reported and retrospective questionnaires and that they mainly explore child corruption cases occurring before eighteen years old. The significance of this review is that information technology examined the quality of the screening tools using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist, wherein only viii of the screening tools were establish to have a moderate or loftier quality of show. However, this systematic literature review is mainly applicative to assessing the abuse experience of victims and is less appropriate for infants and young children who are unable to limited themselves or for assessments conducted in time-sensitive emergencies. Moreover, it did not include screening tools designed for utilise in healthcare settings. Hoft and Haddad (2017) as well conducted a systematic literature review of existing screening tools and guidelines for identifying kid abuse. The study analyzed nine screening tools, which included a questionnaire completed by parents on the risk of kid abuse and sexual exploitation, a adventure assessment questionnaire completed past the medical staff on physical and sexual abuse screening tools, and a questionnaire on the scale of potential child neglect evaluated past preschool professionals. Although the review by Hoft and Haddad examined different types of screening tools, it did not evaluate or compare the quality of each tool. Therefore, information technology was not possible to identify the effectiveness of each analyzed tool.
Healthcare covers a broad range of services from the management of astute medical units to health promotion and administration in communities. Thus, the suitability of a screening tool for child abuse varies depending on the context in which information technology is used. Healthcare workers—even those in acute intendance hospitals—confront multiple difficulties when using screening tools for kid abuse. For example, emergency rooms (ERs), pediatric intensive intendance units, outpatient departments, and customs and homecare services may, respectively, use different screening tools based on their unique contexts. Rumball-Smith et al. (2018) used the Escape tool to construct a screening tool to find kid corruption in children nether 13 years old using electronic medical records in the ERs of 13 hospitals. Their results showed that the reporting charge per unit was considerably college when the screening tool was used (1.iii% vs. 0.4%; odds ratio [OR] = 2.90, 95% confidence interval [CI; one.67, v.02]) and that the reporting rate for positive cases was significantly higher than that for negative cases (l% vs. 0.3%; p < .0001).
Rigorous screening tools appropriate for utilize in the healthcare surroundings may help healthcare providers to find child abuse early besides as reduce their workload, improve piece of work efficiency, and increase conviction and job satisfaction (Carson, 2018). To this end, this written report was designed to identify the current screening tools used by healthcare providers to detect child corruption, place the assessment content used in these tools, and evaluate the reliability and quality of these tools using a systematic literature review. The findings volition be used to advise the well-nigh appropriate, reliable, and validated screening tools for child abuse that may be used in various segments of the healthcare manufacture. The inquiry questions of this study were as follows: (a) What screening tools are used by healthcare providers to detect child abuse? (b) How should screening tools for detecting child abuse be evaluated? and (c) What are the psychometric properties of child abuse screening tools?
Methods
This systematic review was constructed based on Preferred Reporting Items for Systematic Review and Meta-Analysis (Moher et al., 2009). In addition, the COSMIN checklist (Prinsen et al., 2018) was used to conduct the literature review, and the Grading of Recommendation, Cess, Evolution, and Evaluation (GRADE; Schünemann et al., 2017) was adopted to form the quality of bear witness to evaluate the measurement backdrop and formulate results and recommendations.
Search Strategy
This systematic review included an extensive search of relevant domestic and international publication databases, including Airiti Library, PubMed, MEDLINE, CINAHL, Instruction Resource Information Center, Cochrane Library, Embase, and OpenGray. An extensive literature search was conducted for all full-text articles published before Oct 2019 to canvass the most comprehensive range possible. The Boolean logic operator "OR" was used for joint sets of synonyms and "AND" for keyword conjugations. These operators were used in combination and separately during the keyword search. The search keywords included the post-obit: ("child*abuse [MeSH]," "kid*maltreatment," "child fail," or "calumniating head trauma") and ("instrument," "screening," "measurement," "scale," or "questionnaire") and ("health intendance").
Inclusion Criteria
The screening tools identified in this systematic review were required to meet the following iii inclusion criteria: (a) have equally their chief objective the evaluation of victims who had been abused either physically (including abusive caput trauma), sexually, or emotionally or had been subjected to neglect; (b) be applicative to children less than 18 years old; and (c) exist designed for apply by healthcare professionals such as medical staff in ERs, pediatric wards, and community healthcare units. Furthermore, the reviewed articles were required to have been published in either Chinese or English.
Exclusion Criteria
Review articles, commentaries, editorials, and skillful stance articles were excluded from consideration.
Search Outcome
Publications were offset screened independently by two researchers based on their titles and abstracts, and duplicate publications were deleted. Publications that used screening tools for the objective evaluation of children younger than 18 years old and those used by healthcare professionals at hospitals and communities were selected. Finally, 23 publications met the inclusion criteria, and xv screening tools were selected for further analysis. The literature search in this written report was based on the Preferred Reporting Items for Systematic Review and Meta-Analysis argument (refer to the menstruum diagram presented in Figure 1).
Systematic review: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart
Quality Appraisal
Ii researchers reviewed all selected publications independently using the COSMIN checklist (Prinsen et al., 2018), which includes nine measurement backdrop, including internal consistency, reliability, measurement error, content validity, construct validity, hypothesis testing, cross-cultural validity, criterion validity, and responsiveness. The quality of publications was classified as inadequate, doubtful, acceptable, and very good. The GRADE approach was adopted for evaluating the quality of testify (Schünemann et al., 2017). Publications were further graded as not serious, serious, very serious, and undetected with reference to risk of bias, inconsistency, imprecision, indirectness, and publication bias. Furthermore, the quality of evidence was classified as high, moderate, low, and very low. If at that place were divergent opinions in the process of quality cess, a final determination was reached after belongings discussions with a third reviewer.
Results
Study Selection
Twenty-iii publications, which used xv different screening tools, met the inclusion criteria. The applicable subjects, assessment items, and reliability and validity of the identified tools are presented in Tables 1 and 2. The included tools assessed the following forms of child abuse: physical abuse (northward = 6); corruption-related head trauma (northward = 3); physical abuse and neglect (northward = 2); child abuse and neglect (n = 1); physical and sexual abuse (n = i); physical abuse, emotional abuse, and neglect (n = 1); and sexual abuse (northward = 1). These tools were mainly adult in the Us or in European countries, with seven developed in the United states, four in holland, 2 in the United Kingdom, and one each in Spain and South korea.
Table 1 - Clarification of Selected Studies That Examined Child Corruption Screening Instruments
| Study | Musical instrument | Inclusion Criteria (Children) | Form of Child Abuse | Sample Size | No. of Items | Scoring/Cutoff Point | Sensitivity | Specificity | AUC | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| % | 95% CI | % | 95% CI | % | 95% CI | |||||||
| ane. Berger et al. (2016; The states) | PIBIS | < 1 y in the emergency department (ED) | Abused head trauma | 1,040 | 4 | A 5-bespeak calibration that assessed (a) abnormality on dermatologic examination (2 points), (b) historic period ≥ 3.0 months (1 signal), (c) caput circumference > 85th percentile (i bespeak), and (d) serum hemoglobin level < 11.ii chiliad/dl (ane point)/cutoff point: total score of two points | 93.3 | [89.0, 96.3] | 53.0 | [49.3, 57.1] | 83.0 | [80.0, 86.0] |
| two. Chang et al. (2004; United States) | DIPCA | < 3 y identified by External Injury Codes (E-codes) in the range of 967.0–967.9 | Physical abuse | 11,919 | 6 | A 15-point scale with (a) one signal for fracture of base of operations or vault of skull; (b) 2 points each for contusion of heart, rib fracture, intracranial haemorrhage, multiple burns, or age of i–3 y; and (c) six points for age of 0–1 y/cutoff signal: total score of three points | 72.5 | 89.1 | 86.0 | |||
| 3. Chang et al., (2005; The states) | SIPCA | < 14 y identified based on ICD-9, Clinical Modification codes 800–959 | Physical abuse | 58,558 | 6 | A fifteen-signal scale with (a) ane point for fracture of base or vault of skull; (b) two points each for contusion of middle, rib fracture, intracranial bleeding, multiple burns, or age of 1–3 y; and (c) 6 points for age of 0–one y/cutoff point: total score of three points | 86.6 | eighty.5 | 89.0 | |||
| iv. Cowley et al. (2015; United Kingdom) | PredAHT | < 3 y with an intracranial injury in the pediatric intensive intendance unit (PICU) | Abused head trauma | 198 | vi | Yes/no questions/cutoff betoken of iii points | 72.3 | [60.4, 81.seven] | 85.vii | [78.8, 90.7] | 88.0 | [82.3, 92.6] |
| 5. Ezpeleta et al. (2017; Spain) | INTOVIAN | < 3 y in public health centers | Concrete abuse, emotional corruption, neglect | 219 | 9 | Yes/no questions/cutoff point of at to the lowest degree one point | – | – | ||||
| 6. Hymel et al. (2014; United States) | Four-variable CPR | < 3 y for intensive care of head injuries | Driveling head trauma | 291 | 4 | Yeah/no questions/cutoff point of at least 1 point | 96.0 | [xc.0, 99.0] | 43.0 | [35.0, fifty.0] | 78.0 | |
| 7. Kemp et al. (2018; United kingdom) | Burn-Tool | < 16 y with a burn in the pediatric ED | Physical abuse, burn | 1,327 | 7 | Integer scores ranging from 0 to 3 points/cutoff betoken: total score of three points | 87.five | [61.7, 98.4] | 81.five | [77.1, 85.four] | 87.0 | [83.0, 90.0] |
| eight. Louwers et al. (2014; Netherlands) | Escape | < 18 y who visited the ED | Concrete abuse | 38,136 | 6 | Yes/no questions/cutoff indicate of at least 1 bespeak | lxxx.0 | [67.0, 89.0] | 98.0 | |||
| 9. Paek et al. (2018; South korea) | FIND | < fourteen y who visited the ED with injuries | Concrete corruption, neglect | 3,855 | 8 | Yes/no questions/cutoff point of at least 1 point | – | – | ||||
| x. Pierce et al. (2010; United States) | TEN-4 BCDR | < 4 y with abusive or accidental trauma in the PICU | Physical abuse, bruises | 95 | ane | Bruising on the torso, ear, or neck for a child aged less than 4 y, and bruising in whatever region for an infant aged less than 4 months | 97.0 | 84.0 | ||||
| xi. Schols et al. (2019; Netherlands) | ERPANS | < one y assessed during a home visit of families | Physical abuse, neglect | 1,257 | 31 | 4-indicate response format ranging from 0 (never observed or reported) to 3 (very often observed or reported)/cutoff indicate: total score of 1 bespeak | – | – | ||||
| 12. Shakil et al. (2018; The states) | PedHITSS | <12 y in clinic completed by parents | Concrete abuse, sexual abuse | 422 | v | five-point Likert scale (0 = never, 1 = rarely, 2 = sometimes, 3 = fairly often, or 4 = frequently)/cutoff indicate: total score of 1 betoken | 85.0 | [81.0, 89.0] | ||||
| 13. Sittig et al. (2011; Netherlands) | SPUTOVAMO-R | < 7 y with physical injury in the ED | Physical abuse | 5,000 | 6 | Yeah/no questions/cutoff point of at to the lowest degree 1 point | – | – | ||||
| 14. van der Put et al. (2017; Netherlands) | IPARAN | < ane y assessed during a home visit of families | Kid corruption, fail | 4,692 | 16 | four-point response scale (always, often, sometimes, never) or a yes/no option Each item is assigned a score between 0 and two/cutoff indicate of at least 1 betoken | 66.seven | 77.iv | 72.0 | [59.3, 84.7] | ||
| fifteen. Wells et al. (1997; U.s.a.) | SASA | < fifteen y with risk of sexual corruption based on the tool completed by parents in a clinic | Sexual corruption | 121 | 12 | Yeah/no questions/cutoff point: full score of 3 points or more than | 90.9 | 88.five | ||||
Note. "INTOVIAN" was a European Committee-funded projection proper noun. AUC = surface area nether curve; y = years; PIBIS = Pittsburgh Infant Brain Injury Score; DIPCA = Diagnostic Index for Concrete Kid Abuse; SIPCA = Screening Index for Physical Kid Corruption; PredAHT = Predicting Abusive Head Trauma; CPR = Clinical Prediction Rule; BuRN-Tool - Burns Risk assessment for Neglect or corruption Tool; FIND = Finding Musical instrument for Nonaccidental Deeds; TEN-4 BCDR = Body, Ear, and Neck Bruising Clinical Determination Rule; ERPANS = Early Risks of Physical Abuse and Fail Scale; PedHITSS = Pediatric Hurt-Insult-Threaten Scream-Sex screening tool; SPUTOVAMO-R = acronym consisting of the get-go letters of the question in Dutch; IPARAN = Identification of Parents At Risk for kid Abuse and Neglect; SASA = Symptoms Associated with Sexual Abuse; ICD-ix = International Nomenclature of Diseases-ninth Edition.
Tabular array 2 - COSMIN Checklist for Evaluating the Methodological Quality of Private Studies That Utilized Kid Abuse Screening Instruments
| Written report | Instrument | Internal Consistency | Reliability | Measurement Error | Content Validity | Structural Validity | Hypotheses Testing | Criterion Validity | Responsive-ness | Cross-Culture Validity |
|---|---|---|---|---|---|---|---|---|---|---|
| Berger et al. (2016) | PIBIS | Very good | NA | Adequate | Adequate | NA | Adequate | Adequate | Very good | NA |
| Chang et al. (2004) | DIPCA | Acceptable | NA | NA | NA | NA | Adequate | Adequate | Very good | NA |
| Chang et al. (2005) | SIPCA | Very good | NA | NA | Acceptable | NA | Acceptable | Adequate | Very good | NA |
| Cowley et al. (2015) | PredAHT | Adequate | NA | Adequate | NA | NA | Adequate | Adequate | Very good | NA |
| Ezpeleta et al. (2017) | INTOVIAN | Very good | Adequate | NA | Adequate | NA | Adequate | NA | NA | NA |
| Hymel et al. (2014) | 4-variable CPR | Adequate | NA | Adequate | Adequate | NA | Adequate | NA | Doubtful a | NA |
| Kemp et al. (2018) | Fire-Tool | Very good | NA | Acceptable | Acceptable | NA | Acceptable | NA | Very good | NA |
| Louwers et al. (2014) | Escape | Very good | NA | Adequate | Adequate | NA | Adequate | Adequate | Very practiced | NA |
| Paek et al. (2018) | Find | Adequate | NA | Doubtful b | Acceptable | NA | Adequate | Doubtful c | NA | NA |
| Pierce et al. (2010) | TEN-iv BCDR | Adequate | NA | Adequate | NA | NA | Adequate | Adequate | Acceptable | NA |
| Schols et al. (2019) | ERPANS | Very good | Adequate | Adequate | Acceptable | Adequate | Acceptable | NA | NA | NA |
| Shakil et al. (2018) | PedHITSS | Very good | Very good | Acceptable | Adequate | Acceptable | Adequate | Adequate | Adequate | NA |
| Sittig et al. (2011) | SPUTOVAMO-R | Very good | NA | NA | Adequate | NA | Adequate | Adequate | NA | NA |
| van der Put et al. (2017) | IPARAN | Very adept | NA | NA | Acceptable | NA | Acceptable | Very good | Doubtful a | NA |
| Wells et al. (1997) | SASA | Adequate | Adequate | NA | Na | NA | Adequate | Very proficient | Adequate | NA |
Note. Methodological quality: inadequate, doubtful, adequate, very practiced, and not applicable (NA). "INTOVIAN" was a European Commission-funded project name. PIBIS = Pittsburgh Infant Encephalon Injury Score; DIPCA = Diagnostic Index for Physical Child Abuse; SIPCA = Screening Index for Physical Kid Abuse; PredAHT = Predicting Calumniating Caput Trauma; CPR = Clinical Prediction Rule; BuRN-Tool = Burns Take a chance assessment for Fail or abuse Tool; Detect = Finding Instrument for Nonaccidental Deeds; TEN-four BCDR = Torso, Ear, and Neck Bruising Clinical Determination Rule; ERPANS = Early on Risks of Concrete Corruption and Neglect Scale; PedHITSS = Pediatric Hurt-Insult-Threaten Scream-Sexual activity screening tool; SPUTOVAMO-R = acronym consisting of the kickoff messages of the question in Dutch; IPARAN = Identification of Parents At Risk for child Abuse and Fail; SASA = Symptoms Associated with Sexual Abuse. aLower specificity and AUC. b Unexplained or missing data. c Evaluation by emergency medicine board-certified doc without gold standard.
Population Characteristics
Of the 15 kid corruption screening tools identified in the included manufactures, 8 targeted children who had sought medical attention with injury and three targeted all children who had sought medical attention. The tools used in these studies included the Pittsburgh Baby Brain Injury Score (PIBIS), INTOVIAN (a European Commission-funded project proper noun), and Escape (Berger et al., 2016; Ezpeleta et al., 2017; Louwers et al., 2014). The remaining four studies that utilized cocky-report tools to assess gamble of child abuse were the Early Risks of Concrete Abuse and Neglect Calibration (ERPANS), Pediatric Hurt-Insult-Threaten Scream-Sex (PedHITSS) screening tool, Identification of Parents At Run a risk for child Corruption and Neglect (IPARAN), and Symptoms Associated with Sexual Abuse (SASA; Schols et al., 2019; Shakil et al., 2018; van der Put et al., 2017; Wells et al., 1997). These cocky-report tools were designed to exist used past parents to provide descriptions of either their parental behavior or their observations of their child's behavioral problems. Eleven studies provided descriptions of child characteristics, including mean ages of less than 1 year (n = seven), one–4 years (n = 2), and v–viii years (n = 2).
Screening Tools
Healthcare providers mainly provide care in hospital and community settings. When an abused kid is sent to the hospital, healthcare providers will deport physical examinations and tests using medical devices to evaluate whether that kid'due south symptoms are related to abuse. In addition, when conducting family unit visits in the community, there is also the opportunity to assess the caregiver'south parenting and environs to facilitate the early detection of abused children. To identify the fundamental factors of child abuse, the assessment items and methods of the child abuse screening tools include questions on the symptoms of abuse and on whether the child is in a high-risk environs. On the basis of the assessment items, the screening tools of the selected studies were classified into three major categories. Those in the first category involved an objective assessment of the consistency of the mechanism and severity of injury as determined through a physical examination and review of the kid's medical history besides as its ceremoniousness with the child's development and abilities. In this category, interviews and concrete examinations such equally visual inspections to check for bruising and burns/scalds were used as the basis for assessing whether the mechanism of injury was consistent with the kid'south developmental stage. Of the 15 tools identified in this review, five were in this category, including INTOVIAN for assessing physical abuse, emotional abuse, and neglect (Ezpeleta et al., 2017); the Burns Risk assessment for Fail or abuse Tool (Burn-Tool) for assessing burns (Kemp et al., 2018); the Torso, Ear, and Neck Bruising Clinical Conclusion Rule (TEN-four BCDR) for assessing bruising (Pierce et al., 2010); and Escape and SPUTOVAMO-R (acronym consisting of the outset letters of the question in Dutch) for assessing physical abuse (Louwers et al., 2014; Sittig et al., 2011).
Tools in the 2d category involved the employ of biochemical tests and precision imaging in add-on to interviews and physical examinations for determining the mechanism of injury. Examinations included x-ray imaging for detecting skull or long bone fractures, computed tomography imaging for detecting intracranial hemorrhaging, fundoscopic examination for detecting retinal hemorrhaging, the measurement of head circumference, and the measurement of serum hemoglobin level. Among the 15 tools identified in this review, half dozen belonged to this category, including PIBIS, Predicting Abusive Caput Trauma (PredAHT), and the four-variable Clinical Prediction Rule (CPR) for assessing calumniating head trauma (Berger et al., 2016; Cowley et al., 2015; Hymel et al., 2014); the Screening Index for Physical Child Corruption (SIPCA) and Diagnostic Index for Physical Child Corruption (DIPCA) for assessing physical abuse (Chang et al., 2004, 2005); and Finding Instrument for Nonaccidental Deeds (FIND) for assessing physical abuse and neglect (Paek et al., 2018).
Tools in the third category involved assessing the risk of child corruption through parental self-reporting on physical and mental health problems, parenting and disciplining methods, and kid-related emotional and behavioral issues. Among the fifteen tools identified in this review, four were in this category, including ERPANS for assessing physical corruption and neglect (Schols et al., 2019), PedHITSS for assessing concrete and sexual abuse (Shakil et al., 2018), IPARAN for assessing kid corruption and neglect (van der Put et al., 2017), and SASA for assessing sexual abuse (Wells et al., 1997).
Except for ERPANS, which comprises 31 items (Schols et al., 2019), and the TEN-4 BCDR, which comprises ane item (Pierce et al., 2010), the remaining thirteen tools contain betwixt four and 16 items. Aye/no questions were used in viii tools, a 4- or five-point Likert scale was used in three tools, and a weighted scoring system was used in four tools.
Most of the reviewed publications (n = 11) did not state whether training was required before using the associated screening tool. Nevertheless, basic medical and nursing knowledge was conspicuously a necessary although unstated prerequisite, as professional noesis is required to determine the level of consistency betwixt physical examination and medical history results. Screening tool grooming methods and content were elucidated in 4 publications, as follows: SPUTOVAMO-R: description of ways to place kid corruption and the method for filling out the SPUTOVAMO-R class; SASA: description of how structured interviews and data collection were performed; and ERPANS and IRAPAN: description of the grooming required to identify the diverse forms of child abuse, assessment methods, and means to ameliorate the communication techniques and relationship building skills of parents.
Quality of Studies
The COSMIN checklist (Prinsen et al., 2018) was used to assess the measurement quality of the child corruption screening tools identified in this review. As presented in Table 2, none of the tools accomplished a rating of "adequate" or above on whatever of the nine measurement properties. In terms of measurement error, the FIND received a "hundred-to-one" rating, as the article did not provide an explanation for missing data. Regarding benchmark validity, no gold standard was presented with which to confirm kid corruption cases using the iv-variable CPR, BuRN-Tool, or ERPANS. For the Find, evaluation past a board-certified emergency medicine physician was stated as the criterion for confirming child abuse cases. With reference to responsiveness, neither sensitivity nor specificity analysis was performed for the INTOVIAN, Detect, ERPANS, and SPUTOVAMO-R, whereas the four-variable CPR and IPARAN exhibited depression sensitivity or area under curve (AUC) values. The values for either AUC (72.0%–89.0%) or sensitivity (66.seven%–97.0%) and specificity (53.0%–98.0%) were reported for eleven tools, whereas internal consistency (Cronbach's blastoff = .79–.83) was reported for two tools. Cantankerous-cultural validity could not be evaluated for any of the tools, as all were used in a single country setting simply. A comparison of the number of "adequate" and "very good" ratings of the screening tools revealed that the PedHITSS earned the highest number (8 ratings), followed by PIBIS, Escape, and ERPANS (6 ratings each).
The quality of evidence of the screening tools was evaluated using GRADE (Schünemann et al., 2017). As shown in Table 3, the quality of evidence was rated as "loftier" in three tools (the PIBIS, Escape, and PedHITSS), "moderate" in nine tools, and "low" in three tools. In addition, a "serious" rating was assigned considering the following factors affecting the certainty of evidence were observed: (a) risk of bias, that is, subject inclusion criteria were non stated for the PredAHT and INTOVIAN, and no gold standard for confirming child abuse cases was provided for the four-variable CPR, BuRN-Tool, and FIND; and (b) imprecision, that is, sensitivity or specificity assay was not performed for the INTOVIAN, FIND, ERPANS, and SPUTOVAMO-R; a 95% CI for sensitivity or specificity was not provided for the DIPCA, SIPCA, TEN-4 BCDR, and SASA; and depression sensitivity and specificity values or AUC values were exhibited by IPARAN and the four-variable CPR. Publication bias could non be evaluated, equally all tools were used in the published written report only.
Table 3 - GRADE Summary of Findings on Screening Tools for Child Abuse
| Study | Musical instrument | Risk of Bias | Indirectness | Inconsistence | Imprecision | Publication Bias | Certainty of Evidence |
|---|---|---|---|---|---|---|---|
| Berger et al. (2016) | PIBIS | Not serious | Not serious | Not serious | Not serious | Undetected | High |
| Chang et al. (2004) | DIPCA | Not serious | Not serious | Non serious | Serious a | Undetected | Moderate |
| Chang et al. (2005) | SIPCA | Non serious | Not serious | Not serious | Serious a | Undetected | Moderate |
| Cowley et al. (2015) | PredAHT | Serious b | Not serious | Not serious | Not serious | Undetected | Moderate |
| Ezpeleta et al. (2017) | INTOVIAN | Serious b | Not serious | Not serious | Serious a | Undetected | Depression |
| Hymel et al. (2014) | Four-variable CPR | Serious c | Not serious | Not serious | Serious d | Undetected | Low |
| Kemp et al. (2018) | Burn-Tool | Serious c | Not serious | Not serious | Not serious | Undetected | Moderate |
| Louwers et al. (2014) | Escape | Non serious | Not serious | Not serious | Non serious | Undetected | High |
| Paek et al. (2018) | FIND | Serious e | Not serious | Non serious | Serious a | Undetected | Low |
| Pierce et al. (2010) | X-four BCDR | Non serious | Not serious | Not serious | Serious a | Undetected | Moderate |
| Schols et al. (2019) | ERPANS | Not serious | Not serious | Not serious | Serious a | Undetected | Moderate |
| Shakil et al. (2018) | PedHITSS | Not serious | Not serious | Not serious | Not serious | Undetected | High |
| Sittig et al. (2011) | SPUTOVAMO-R | Not serious | Not serious | Non serious | Serious a | Undetected | Moderate |
| van der Put et al. (2017) | IPARAN | Non serious | Not serious | Not serious | Serious d | Undetected | Moderate |
| Wells et al. (1997) | SASA | Non serious | Not serious | Non serious | Serious a | Undetected | Moderate |
Note. Evidence quality: not serious, serious, very serious, and undetected. "INTOVIAN" was a European Commission-funded project name. Grade = Grading of Recommendation, Assessment, Development, and Evaluation; PIBIS = Pittsburgh Infant Brain Injury Score; DIPCA = Diagnostic Index for Physical Child Abuse; SIPCA = Screening Index for Physical Kid Abuse; PredAHT = Predicting Calumniating Head Trauma; CPR = Clinical Prediction Rule; Burn-Tool = Burns Risk assessment for Neglect or abuse Tool; Notice = Finding Musical instrument for Nonaccidental Deeds; 10-4 BCDR = Torso, Ear, and Cervix Bruising Clinical Determination Dominion; ERPANS = Early on Risks of Physical Abuse and Neglect Scale; PedHITSS = Pediatric Hurt-Insult-Threaten Scream-Sex screening tool; SPUTOVAMO-R = acronym consisting of the first letters of the question in Dutch; IPARAN = Identification of Parents At Take a chance for child Abuse and Neglect; SASA = Symptoms Associated with Sexual Corruption. a Studies were insufficient to provide screening validity for AUC, or sensitivity and specificity without 95% CI. b Subjects without inclusion criteria. c Gold standard criteria for the diagnosis of child corruption do not exist. d Provide screening validity for lower AUC, or sensitivity and specificity. eastward Evaluation by emergency medicine board-certified physician.
Applicable Settings and Replicability of the Screening Tools
Of the 15 screening tools, two (the ERPANS and IRAPAN) were used during newborn home visits to assess whether parents were at a high risk of abusing their children, two (the DIPCA and SIPCA) were used in hospital settings to confirm child abuse using diagnosis codes, three (the PedHITSS, INTOVIAN, and SASA) were used for assessment purposes at outpatient clinics, five (the PIBIS, Burn down-Tool, Find, Escape, and SPUTOVAMO-R) were used during triage in emergency departments, and three (the PredAHT, four-variable CPR, and Ten-4 BCDR) were used in pediatric intensive care units.
Give-and-take
The systematic literature review conducted in this report identified xv screening tools used by healthcare providers to assess child abuse. Although all of the tools covered one or more forms of abuse, none encompassed all types of abuse. Two thirds of the tools (due north = 10) screened for a specific course of abuse, with nine tools designed to screen for concrete corruption (including three tools targeted toward calumniating caput trauma) and one tool designed to screen for sexual abuse. Furthermore, xiv of the 15 tools addressed physical abuse, and just one tool (INTOVIAN) addressed emotional abuse.
Physical abuse is the most common course of child abuse encountered in clinical practice (Solis-Garcia et al., 2019). As the mechanisms of concrete abuse related injuries are clearly observable and may serve as identification indicators, tools designed to screen for concrete abuse account for the greatest proportion of kid abuse screening tools. When a child who has experienced concrete harm or encountered a life-threatening situation is taken to a medical institution for handling, rapid screening by medical staff is essential for subsequent intervention and the prevention of further damage. Therefore, it is imperative for healthcare providers to prioritize the assessment of child abuse. The Escape tool was the near commonly used child-abuse assessment tools identified in this review (Louwers et al., 2012). With loftier sensitivity and specificity of lxxx%–100% and 98.0%–98.3%, respectively, the Escape tool has been used in several studies conducted in dissimilar countries, including Iran (Dinpanah & Akbarzadeh Pasha, 2017), the United states of america (Carson, 2018; Rumball-Smith et al., 2018), and kingdom of the netherlands (Louwers et al., 2012, 2014; Moll, 2014). Certain tools are designed to assess maltreatment using observations of specific injuries. For example, PIBIS assesses the crusade of abusive head trauma, BuRN-Tool assesses the cause of burns, and Ten-4 BCDR assesses the cause of bruises to confirm whether they are attributable to accidents or intentional harm.
Among the assessment tools identified in this article, only a pocket-sized number (n = iv) assessed neglect or emotional abuse. However, neglect is the nearly normally reported grade of maltreatment, accounting for 60.viii%–75.9% of all reported cases of kid maltreatment (Administration for Children and Families, 2020; Chang et al., 2016). The assessment of fail requires the consideration of multiple aspects and signs such every bit the needs of the child, parenting abilities, and family and environmental factors. However, considering of the paucity of available assessment tools, clinical personnel often rely on past experience or intuition to make related judgments (Horwath, 2007). In a previous study, health professionals with experience in the field of pediatrics were found to be significantly more competent than personnel with experience in other subspecialties in identifying cases of child abuse (p < .001; Sathiadas et al., 2018). Given the difficulty of conducting standardized assessments of subjective intuition, the limited number of medical personnel who possess professional knowledge/extensive feel in pediatrics, and the lack of assessment tools and standards, healthcare providers tend to written report child abuse cases based on feel or intuition. This results in inconsistencies and increased brunt in the conclusion of neglect or nonneglect by hospitals and social welfare units. Therefore, the development of show-based standardized neglect cess tools to facilitate systematic assessment and judgment is necessary.
The lack of obvious injury in cases of emotional abuse and the traditional Asian concept that scolding is a reasonable form of subject often lead to the failure of children to recognize child abuse and to rationalize the abusive behavior inflicted past abusers. In turn, this affects the uncovering of abuse events (Wang et al., 2018) and complicates the assessment of emotional abuse. However, as emotional abuse ofttimes coexists with other forms of abuse (Clarkson Freeman, 2014), emotional abuse assessment tools such as INTOVIAN may be used to meantime appraise physical abuse, emotional abuse, and neglect (Ezpeleta et al., 2017). By performing a comprehensive assessment of various forms of abuse, future negative consequences of emotional abuse such equally mental illnesses, substance abuse, feet, and emotional disorders may be prevented (Schoemaker et al., 2002).
The sensitivity and specificity of cess tools are of vital importance, as adopting tools that lack high sensitivity and specificity may upshot in imitation-positive or false-negative cases, which not only increases the assessment burden of kid protective services workers and may necessitate judicial investigation to confirm individual cases (O'Donohue et al., 2018) only too may issue in missed opportunities for intervention. In this study, most of the identified tools (n = 12) achieved a "moderate" rating or in a higher place for certainty of evidence. The values of AUC (72.0%–89.0%) or of sensitivity (66.7%–97.0%) and specificity (53.0%–98.0%) were reported for 11 tools, with 70% and lxx% of these 11 tools reporting sensitivities and specificities greater than 80%, respectively. Therefore, more one-half of the screening tools had high sensitivity and specificity levels related to detecting child abuse. The internal consistency or face validity was reported for ii of the tools. As reliability and validity testing was not performed for the remaining two tools, their validity remains unclear and their quality could not be evaluated.
At nowadays, no single screening tool is applicable to all healthcare settings, every bit all tools require appropriate settings and adequate professional person knowledge to exist used properly. Almost of the cess tools examined in this study (n = 13) were utilized in medical institutions (emergency departments, pediatric intensive care units, and outpatient clinics), whereas 2 were designed to be completed by community nurses using the responses of parents during dwelling visits to assess whether parents were at a loftier run a risk of abusing their children. Other objective cess tools such equally the Family Map Inventories-Adverse Childhood Experiences may too exist used by customs nurses during home visits to facilitate the screening of high-gamble families and support subsequent intervention efforts (McKelvey et al., 2016).
All of the screening tools used by infirmary healthcare providers were focused on physical abuse and sexual abuse. It is recommended to use Escape and PedHITSS, with AUC values of 99.2%, and 85%, respectively (Dinpanah & Akbarzadeh Pasha, 2017, Shakil et al., 2018). However, if a child with a brain injury or fracture acquired by corruption is examined by ten-ray, computed tomography browse, magnetic resonance imaging, or ophthalmoscope, the mechanism of injury tin exist confirmed. It is recommended to use PIBIS, DIPCA, and SPICA, which earned AUC values of 83%, 86%, and 89%, respectively (Berger et al., 2016, Chang et al., 2004, 2005). The results of equipment-aided medical examinations help healthcare providers ostend objective evidence of child abuse. However, although equipment-aided examinations tin increase the ability of healthcare professionals to identify kid abuse, only a few abuse types, for instance, physical and sexual abuse, may exist identified in this manner. Moreover, the requisite equipment is non easily accessible or universally available such as in customs or medical-dispensary settings. Therefore, valid screening tools must showroom loftier sensitivity and specificity characteristics.
Through the use of standardized, easily comprehensible, and valid tools to assess child abuse, healthcare providers can perform consistent assessments without omitting key items, which facilitates decision making related to the identification of child abuse cases. This is especially beneficial for novice medical personnel with express or no pediatric experience, as a high level of acceptance of cess tools leads to a lower perceived clinical burden and increased validity in child corruption screening (Louwers et al., 2012; Mullen et al., 2018). Given the highly complex nature of child corruption, assessment tools may non simply be used in preliminary screenings but also be used to promote timely intervention measures.
This study differs from previous studies in the highlighting of the significance of using objective assessment measures to identify child abuse. Nonetheless, nigh publications reviewed in the present article did not land whether grooming was required for these cess tools and did not compare the screening results of different healthcare providers. Therefore, the target user of these tools may require farther attending and training. By attending advisable training sessions, medical personnel may become skillful in using assessment tools and improve their assessment capabilities (Schols et al., 2019). It is hoped that, past combining high-quality cess tools with professional person preparation and abilities, early on intervention and preventive measures may be implemented to protect children from violence to improve overall kid health and welfare.
Limitations
As this systematic review included manufactures published in either English or Chinese only, there may exist relevant articles on assessment tools published in other languages that were omitted from this review. Moreover, the integrity of the identified tools could not be analyzed, as most were used in single studies merely and many tools were not analyzed for sensitivity and specificity. Furthermore, our ability to assess the evidence and quality of a number of the tools was limited because reliability and validity testing results were not provided. Future studies should be designed to compare different cess tools to promote the timely identification of child abuse cases. Furthermore, most of the studies examined in this systematic review focused simply on assessments of children who had sought medical attending or were living in communities. Future assessment efforts may too be extended to school children to further determine the validity of these tools.
Conclusions
In this systematic literature review, fifteen tools used by healthcare providers to appraise child abuse were identified. Every bit the assessment items included in the screening tools were classified into different categories, this report found that the tools were distributed disproportionately. Most were designed to assess physical corruption and achieved moderate to high levels of testify quality, rendering them suitable for utilise by medical personnel in hospital and community settings. Even so, as research on the use of these tools in clinical exercise is limited, further practical experience is required to ostend their reliability and validity to assist in the early conclusion by healthcare providers of kid abuse cases.
Acquittance
This research was funded past National Cheng Kung University Hospital (NCKUH-10905025).
Author Contributions
Report formulation and pattern: JYF
Information drove: CJC, YWC, HYC
Data analysis and interpretation: CJC, YWC, HYC
Drafting of the article: CJC
Critical revision of the article: CJC, JYF
References
Administration for Children and Families. (2020). Kid abuse, neglect data released. https://www.acf.hhs.gov/media/press/2020/child-abuse-neglect-data-released
- Cited Here
Berger R. P., Fromkin J., Herman B., Pierce Chiliad. C., Saladino R. A., Flom Fifty., Tyler-Kabara E. C., McGinn T., Richichi R., Kochanek P. Thousand. (2016). Validation of the Pittsburgh infant brain injury score for abusive head trauma. Pediatrics, 138(1), Article e20153756. https://doi.org/10.1542/peds.2015-3756
- Cited Here
Carson S. M. (2018). Implementation of a comprehensive programme to improve child concrete abuse screening and detection in the emergency department. Journal of Emergency Nursing, 44(6), 576–581. https://doi.org/10.1016/j.jen.2018.04.003
Chang D. C., Knight V., Ziegfeld S., Haider A., Warfield D., Paidas C. (2004). The tip of the iceberg for child abuse: The disquisitional roles of the pediatric trauma service and its registry. The Periodical of Trauma and Acute Surgery, 57(6), 1189–1198. https://doi.org/10.1097/01.TA.0000145076.05111.E1
- Cited Here
Chang D. C., Knight V. Grand., Ziegfeld S., Haider A., Paidas C. (2005). The multi-institutional validation of the new screening index for physical child corruption. Journal of Pediatric Surgery, forty(i), 114–119. https://doi.org/10.1016/j.jpedsurg.2004.09.019
Chang Y. C., Huang J. L., Hsia Southward. H., Lin K. L., Lee E. P., Chou I. J., Hsin Y. C., Lo F. Southward., Wu C. T., Chiu C. H., Wu H. P.; Prevention, Protection Against Kid Abuse, Neglect (PCHAN) Study Group. (2016). Kid protection medical service demonstration centers in approaching child abuse and neglect in Taiwan. Medicine (Baltimore), 95(44), Article e5218. https://doi.org/x.1097/md.0000000000005218
- Cited Here
Clarkson Freeman P. A. (2014). Prevalence and relationship between agin childhood experiences and child behavior amongst young children. Babe Mental Health Journal, 35(6), 544–554. https://doi.org/10.1002/imhj.21460
Cowley L. East., Morris C. B., Maguire Due south. A., Farewell D. Yard., Kemp A. M. (2015). Validation of a prediction tool for abusive head trauma. Pediatrics, 136(2), 290–298. https://doi.org/10.1542/peds.2014-399
Dinpanah H., Akbarzadeh Pasha A. (2017). Potential child abuse screening in emergency department; a diagnostic accuracy study. Emergency (Tehran, Iran), 5(one), Article e8.
- Cited Here
Ezpeleta L., Pérez-Robles R., Fanti K. A., Karveli V., Katsimicha East., Nikolaidis G., Hadjicharalambous 1000. Z., Hatzinikolaou K. (2017). Evolution of a screening tool enabling identification of infants and toddlers at hazard of family unit abuse and neglect: A feasibility written report from 3 Southward European countries. Child: Care, Health and Development, 43(1), 75–80. https://doi.org/10.1111/cch.12416
Flom L., Fromkin J., Panigrahy A., Tyler-Kabara E., Berger R. P. (2016). Evolution of a screening MRI for infants at hazard for calumniating head trauma. Pediatric Radiology, 46(4), 519–526. https://doi.org/x.1007/s00247-015-3500-z
Hoft Thou., Haddad L. (2017). Screening children for abuse and neglect: A review of the literature. Journal of Forensic Nursing, 13(1), 26–34. https://doi.org/10.1097/JFN.0000000000000136
Hoytema van Konijnenburg E. Yard., Teeuw A. H., Sieswerda-Hoogendoorn T., Leenders A. G., van der Lee J. H. (2013). Bereft bear witness for the use of a physical examination to detect maltreatment in children without prior suspicion: A systematic review. Systematic Reviews, 2, Article No.109. https://doi.org/10.1186/2046-4053-2-109
- Cited Here
Horwath J. (2007). The missing assessment domain: Personal, professional person and organizational factors influencing professional judgements when identifying and referring child neglect. The British Journal of Social Work, 37(8), 1285–1303. https://doi.org/ten.1093/bjsw/bcl029
Hymel 1000. P., Armijo-Garcia V., Foster R., Frazier T. Northward., Stoiko M., Christie L. M., Harper Northward. Southward., Weeks K., Carroll C. L., Hyden P., Sirotnak A., Truemper Due east., Ornstein A. East., Wang Yard.; Pediatric Brain Injury Research Network (PediBIRN) Investigators. (2014). Validation of a clinical prediction dominion for pediatric abusive head trauma. Pediatrics, 134(6), e1537–e1544. https://doi.org/10.1542/peds.2014-1329
Kemp A. M., Hollén L., Emond A. M., Nuttall D., Rea D., Maguire S. (2018). Raising suspicion of maltreatment from burns: Derivation and validation of the Burn-Tool. Burns, 44(2), 335–343. https://doi.org/10.1016/j.burns.2017.08.018
Louwers East. C., Korfage I. J., Affourtit Chiliad. J., Ruige M., van den Elzen A. P., de Koning H. J., Moll H. A. (2014). Accuracy of a screening instrument to identify potential child abuse in emergency departments. Child Abuse & Neglect, 38(7), 1275–1281. https://doi.org/x.1016/j.chiabu.2013.11.005
Louwers E. C., Korfage I. J., Affourtit M. J., Scheewe D. J., van de Merwe Thousand. H., Vooijs-Moulaert A. F., van den Elzen A. P., Jongejan M. H., Ruige K., Manai B. H., Looman C. West., Bosschaart A. Northward., Teeuw A. H., Moll H. A., de Koning H. J. (2012). Effects of systematic screening and detection of child corruption in emergency departments. Pediatrics, 130(3), 457–464. https://doi.org/x.1542/peds.2011-3527
McKelvey L. M., Whiteside-Mansell 50., Conners-Burrow N. A., Swindle T., Fitzgerald South. (2016). Assessing agin experiences from infancy through early on babyhood in home visiting programs. Kid Abuse & Neglect, 51, 295–302. https://doi.org/10.1016/j.chiabu.2015.09.008
- Cited Here
Mimasaka Southward., Ohtani M., Kuroda N., Tsunenari S. (2010). Spectrophotometric evaluation of the historic period of bruises in children: Measuring changes in bruise color as an indicator of child physical abuse. The Tohoku Journal of Experimental Medicine, 220(two), 171–175. https://doi.org/ten.1620/tjem.220.171
Moher D., Liberati A., Tetzlaff J., Altman D. Thou.; PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, half dozen(7), Article e1000097. https://doi.org/10.1371/journal.pmed.1000097
- Cited Here |
- PubMed
Moll H. A. (2014). Screening on child abuse in Europe. Athenaeum of Disease in Childhood, 99, A18–A19. https://doi.org/x.1136/archdischild-2014-307384.58
Mullen S., Quinn-Scoggins H. D., Nuttall D., Kemp A. M. (2018). Qualitative analysis of clinician experience in utilising the BuRN Tool (Burns Risk assessment for Neglect or corruption Tool) in clinical practice. Burns, 44(7), 1759–1766. https://doi.org/10.1016/j.burns.2018.03.013
O'Donohue W., Cummings C., Willis B. (2018). The frequency of simulated allegations of child sexual abuse: A disquisitional review. Journal of Child Sexual Corruption, 27(5), 459–475. https://doi.org/x.1080/10538712.2018.1477224
Oral R., Yagmur F., Nashelsky M., Turkmen Thousand., Kirby P. (2008). Fatal abusive head trauma cases: Effect of medical staff missing milder forms of physical abuse. Pediatric Emergency Care, 24(12), 816–821. https://doi.org/ten.1097/PEC.0b013e31818e9f5d
Paek S. H., Jung J. H., Kwak Y. H., Kim D. K., Ryu J. G., Noh H., Kyong Y. Y., Kang Y. J. (2018). Development of screening tool for child abuse in the Korean emergency department: Using modified Delphi study. Medicine (Baltimore), 97(51), Commodity e13724. https://doi.org/10.1097/Doc.0000000000013724
- Cited Here
Pierce M. C., Kaczor Grand., Aldridge S., O'Flynn J., Lorenz D. J. (2010). Bruising characteristics discriminating physical kid abuse from accidental trauma. Pediatrics, 125(1), 67–74. https://doi.org/x.1542/peds.2008-3632
Prinsen C. A. C., Mokkink Fifty. B., Bouter L. Grand., Alonso J., Patrick D. L., de Vet H. C. Westward., Terwee C. B. (2018). COSMIN guideline for systematic reviews of patient-reported outcome measures. Quality of Life Inquiry, 27(5), 1147–1157. https://doi.org/10.1007/s11136-018-1798-iii
Rumball-Smith J., Fromkin J., Rosenthal B., Shane D., Skrbin J., Bimber T., Berger R. P. (2018). Implementation of routine electronic health record-based child abuse screening in general emergency departments. Child Abuse & Neglect, 85, 58–67. https://doi.org/10.1016/j.chiabu.2018.08.008
Saini S. M., Hoffmann C. R., Pantelis C., Everall I. P., Bousman C. A. (2019). Systematic review and critical appraisement of kid corruption measurement instruments. Psychiatry Inquiry, 272, 106–113. https://doi.org/10.1016/j.psychres.2018.12.068
Salinas-Miranda A. A., Salemi J. L., King L. M., Baldwin J. A., Berry E. 50., Austin D. A., Scarborough K., Spooner 1000. K., Zoorob R. J., Salihu H. K. (2015). Agin childhood experiences and wellness-related quality of life in adulthood: Revelations from a community needs assessment. Health & Quality of Life Outcomes, xiii, Article No. 123. https://doi.org/x.1186/s12955-015-0323-4
- Cited Here |
- PubMed
Sathiadas M. Thou., Viswalingam A., Vijayaratnam K. (2018). Child abuse and fail in the Jaffna district of Sri Lanka—A study on knowledge mental attitude practices and behavior of wellness intendance professionals. BMC Pediatrics, 18(1), Commodity No. 152. https://doi.org/10.1186/s12887-018-1138-3
- Cited Here |
- PubMed
Schoemaker C., Smit F., Bijl R. V., Vollebergh W. A. (2002). Bulimia nervosa post-obit psychological and multiple child abuse: Support for the self-medication hypothesis in a population-based cohort report. International Journal of Eating Disorders, 32(4), 381–388. https://doi.org/10.1002/eat.10102
Schols Yard. Due west. A., Serie C. M. B., Broers Northward. J., de Ruiter C. (2019). Factor analysis and predictive validity of the Early Risks of Physical Corruption and Neglect Scale (ERPANS): A prospective study in Dutch public youth healthcare. Child Abuse & Neglect, 88, 71–83. https://doi.org/10.1016/j.chiabu.2018.10.011
- Cited Hither
Schünemann H. J., Wiercioch W., Brozek J., Etxeandia-Ikobaltzeta I., Mustafa R. A., Manja Five., Brignardello-Petersen R., Neumann I., Falavigna M., Alhazzani Due west., Santesso N., Zhang Y., Meerpohl J. J., Morgan R. L., Rochwerg B., Darzi A., Rojas Grand. Ten., Carrasco-Labra A., Adi Y., Akl E. A. (2017). Grade Bear witness to Decision (EtD) frameworks for adoption, adaptation, and de novo development of trustworthy recommendations: GRADE-ADOLOPMENT. Journal of Clinical Epidemiology, 81, 101–110. https://doi.org/ten.1016/j.jclinepi.2016.09.009
Shakil A., Day P. Yard., Chu J., Wood S. B., Bridges K. (2018). PedHITSS: A screening tool to observe childhood abuse in clinical settings. Family Medicine, 50(x), 763–769. https://doi.org/10.22454/FamMed.2018.778329
Sittig J. S., Uiterwaal C. South., Moons K. G., Nieuwenhuis E. E., van de Putte E. G. (2011). Kid abuse inventory at emergency rooms: Concatenation-ER rationale and design. BMC Pediatrics, 11, Commodity No. 91. https://doi.org/x.1186/1471-2431-eleven-91
Solis-Garcia G., Maranon R., Medina Munoz Yard., de Lucas Volle Due south., Garcia-Morin Grand., Rivas Garcia A. (2019). Child corruption in the Emergency section: Epidemiology, management, and follow-up. Register of Pediatrics (Barcelona), 91(1), 37–41. https://doi.org/10.1016/j.anpedi.2018.09.013
- Cited Hither
van der Put C. E., Bouwmeester-Landweer Chiliad. B. R., Landsmeer-Beker E. A., Wit J. M., Dekker F. W., Kousemaker N. P. J., Baartman H. E. M. (2017). Screening for potential child maltreatment in parents of a newborn babe: The predictive validity of an Instrument for early identification of Parents At Risk for child Abuse and Neglect (IPARAN). Kid Corruption & Fail, 70, 160–168. https://doi.org/ten.1016/j.chiabu.2017.05.016
- Cited Hither
Wang F., Wang M., Xing Ten. (2018). Attitudes mediate the intergenerational transmission of corporal punishment in Prc. Child Abuse & Neglect, 76, 34–43. https://doi.org/10.1016/j.chiabu.2017.10.003
- Cited Here
Wells R., McCann J., Adams J., Voris J., Dahl B. (1997). A validational study of the structured interview of Symptoms Associated with Sexual Abuse (SASA) using three samples of sexually abused, allegedly abused, and nonabused boys. Child Corruption & Neglect, 21(12), 1159–1167. https://doi.org/10.1016/s0145-2134(97)00091-4
Keywords:
child abuse; screening tool; healthcare provider
Source: https://journals.lww.com/jnr-twna/Fulltext/2022/02000/Screening_Tools_for_Child_Abuse_Used_by_Healthcare.11.aspx
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