Inconsistent Scores Research Articles

Examination of the Triarchic Assessment Procedure for Inconsistent Responding in six non-English language samples.

The Triarchic Assessment Procedure for Inconsistent Responding (TAPIR; Mowle et al., 2016) was recently developed to identify inattentiveness or comprehension difficulties that may compromise the validity of responses on the Triarchic Psychopathy Measure (TriPM; Patrick, 2010). The TAPIR initially was constructed and cross-validated using exclusively English-speaking participants from the United States; however, research using the TriPM has been increasingly conducted internationally, with numerous foreign language translations of the measure emerging. The present study examined the cross-language utility of the TAPIR in German, Dutch, Swedish, and Italian translations of the TriPM using 6 archival samples of community members, university students, forensic psychiatric inpatients, forensic detainees, and adolescents residing outside the United States (combined N = 5,404). Findings suggest that the TAPIR effectively detects careless responding across these 4 translated versions of the TriPM without the need for language-specific modifications. The TAPIR total score meaningfully discriminated genuine participant responses from both fully and partially randomly generated data in every sample, and demonstrated further utility in detecting fixed "all true" or "all false" response patterns. In addition, TAPIR scores were reliably associated with inconsistent responding scores from another psychopathy inventory. Specificity for a range of tentative cut scores for assessing profile validity was modestly reduced among our samples relative to rates previously obtained with the English version of the TriPM; however, overall the TAPIR appears to demonstrate satisfactory cross-language generalizability. (PsycINFO Database Record

Hand Posturing Is a Nonverbal Indicator of Catastrophic Thinking for Finger, Hand, or Wrist Injury.

Prior research documents that greater psychologic distress (anxiety/depression) and less effective coping strategies (catastrophic thinking, kinesophobia) are associated with greater pain intensity and greater limitations. Recognition and acknowledgment of verbal and nonverbal indicators of psychologic factors might raise opportunities for improved psychologic health. There is evidence that specific patient words and phrases indicate greater catastrophic thinking. This study tested proposed nonverbal indicators (such as flexion of the wrist during attempted finger flexion or extension of uninjured fingers as the stiff and painful finger is flexed) for their association with catastrophic thinking. (1) Do patients with specific protective hand postures during physical examination have greater pain interference (limitation of activity in response to nociception), limitations, symptoms of depression, catastrophic thinking (protectiveness, preparation for the worst), and kinesophobia (fear of movement)? (2) Do greater numbers of protective hand postures correlate with worse scores on these measures? Between October 2014 and September 2016, 156 adult patients with stiff or painful fingers within 2 months after sustaining a finger, hand, or wrist injury were invited to participate in this study. Six patients chose not to participate as a result of time constraints and one patient was excluded as a result of inconsistent scoring of a possible hand posture, leaving 149 patients for analysis. We asked all patients to complete a set of questionnaires and a sociodemographic survey. We used Patient Reported Outcomes Measurement Information System (PROMIS) Depression, Upper Extremity Physical Function, and Pain Interference computer adaptive test (CAT) questionnaires. We used the Abbreviated Pain Catastrophizing Scale (PCS-4) to measure catastrophic thinking in response to nociception. Finally, we used the Tampa Scale of Kinesophobia (TSK) to assess fear of movement. The occurrence of protective hand postures during the physical examination was noted by both the physician and researcher. For uncertainty or disagreement, a video of the physical examination was recorded and a group decision was made. Patients with one or more protective hand postures did not score higher on the PROMIS Pain Interference CAT (hand posture: 59 [56-64]; no posture: 59 [54-63]; difference of medians: 0; p = 0.273), Physical Function CAT (32 ± 8 versus 34 ± 8; mean difference: 2 [confidence interval {CI}, -0.5 to 5]; p = 0.107), nor the Depression CAT (48 [41-55] versus 48 [42-53]; difference of medians: 0; p = 0.662). However, having at least one hand posture was associated with a higher degree of catastrophic thinking (PCS scores: 13 [6-26] versus 10 [3-16]; difference of medians: 3; p = 0.0104) and a higher level of kinesophobia (TSK: 40 ± 6 versus 38 ± 6; mean difference: -2 [CI, -4 to -1]; p = 0.0420). Greater catastrophic thinking was associated with a greater number of protective hand postures on average (rho: 0.20, p = 0.0138). Protective hand postures and (based on prior research) specific words and phrases are associated with catastrophic thinking and kinesophobia, less effective coping strategies that hinder recovery. Surgeons can learn to recognize these signs and begin to treat catastrophic thinking and kinesophobia starting with compassion, empathy, and patience and be prepared to add formal support (such as cognitive-behavioral therapy) to help facilitate recovery. Level III, diagnostic study.

P264 Investigation of inconsistent score patients by using Lewis Score and CECDAI in Crohn’s disease

P264 Investigation of inconsistent score patients by using Lewis Score and CECDAI in Crohn’s disease

Improving text relatedness by incorporating phrase relatedness with word relatedness

AbstractText is composed of words and phrases. In the bag‐of‐words model, phrases in text are split into words. This may discard the semantics of phrases, which, in turn, may give an inconsistent relatedness score between 2 texts. Our objective is to apply phrase relatedness in conjunction with word relatedness on the text relatedness task to improve text relatedness performance. We adopt 2 existing word relatedness measures based on Google n‐gram and Global Vectors for Word Representation, respectively, and incorporate them differently with an existing Google n‐gram–based phrase relatedness method to compute text relatedness. The combination of Google n‐gram–based word and phrase relatedness performs better than Google n‐gram–based word relatedness alone, by achieving the higher weighted mean of Pearson's r, ie, 0.639 and 0.619, respectively, on the 14 data sets from the series of Semantic Evaluation workshops SemEval‐2012, SemEval‐2013, and SemEval‐2015. Similarly, the combination of GloVe‐based word relatedness and Google n‐gram–based phrase relatedness performs better than GloVe‐based word relatedness alone, by achieving the higher weighted mean of Pearson's r, ie, 0.619 and 0.605, respectively, on the same 14 data sets. On the SemEval‐2012, SemEval‐2013, and SemEval‐2015 data sets, the text relatedness results obtained from the combination of Google n‐gram–based word and phrase relatedness ranked 24, 3, and 31 out of 89, 90, and 73 text relatedness systems, respectively.

Training peer specialists with mental illness in motivational interviewing: A pilot study.

The objective of this study was to evaluate the effects of providing motivational interviewing (MI) training to peer specialists in the Veterans Affairs (VA) health-care system. Fourteen peer specialists at a local VA medical center received a 2-day workshop on MI and 2 monthly booster sessions afterward. A total of 55 therapy sessions between peer specialists and their peer service recipients were audio-recorded and independently rated on MI fidelity before the workshop and each month after the workshop for 3 months. Sessions were rated on fidelity scales assessing Fundamental MI Adherence and Competence, Advanced MI Adherence and Competence, and MI Inconsistent Adherence scales. One item was created for this study that assessed Sharing Lived Experiences. Repeated measures analysis was conducted to examine change in MI fidelity over time. Peer specialists had a significant decline in MI Inconsistent Adherence scale scores over time. Specifically, they showed reductions in providing unsolicited advice and emphasizing absolute abstinence. Peer specialists also showed a significant decline in the Sharing Lived Experience Adherence item score. There were no significant changes on MI Fundamental and Advance scale scores. Training peer specialists in MI is feasible and may lead to some change in practices, but comprehensive training and ongoing supervision is needed to incur and sustain changes. Guidance and assessment of how peer specialists share their lived experiences with fellow veterans may be needed to capitalize on their unique experiences and skill sets. (PsycINFO Database Record

The Assignment of American Society of Anesthesiologists Physical Status Classification for Adult Polytrauma Patients: Results From a Survey and Future Considerations.

The American Society of Anesthesiologists (ASA) physical status (PS) classification system assesses the preoperative health of patients. Previous studies demonstrated poor interrater reliability and variable ASA PS scores, especially in trauma scenarios. There are few studies that evaluated the assignment of ASA PS scores in trauma patients and no studies that evaluated ASA PS assignment in severely injured adult polytrauma patients. Our objective was to assess interrater reliability and identify sources of discrepancy among anesthesiologists and trauma surgeons in designating ASA PS scores to adult polytrauma patients. A link to an online survey containing questions assessing attitudes regarding ASA PS classification, demographic information, and 8 fictional trauma cases was e-mailed to anesthesiologists and trauma surgeons. The participants were asked to assign an ASA PS score to each scenario and explain their choice. Rater-versus-reference and interrater reliability, beyond that expected by chance, among respondents was analyzed using the Fleiss kappa analysis. A total of 349 participants completed the survey. All 8 cases had inconsistent ASA PS scores; several cases had scores ranging from I to VI and variable emergency (E) designations. Using weighted kappa (Kw) analysis for a subset of 201 respondents (101 trauma surgeons [S] and 100 anesthesiologists [A]), we found moderate (Kw = 0.63; SE = 0.024; 95% confidence interval, 0.594-0.666; P < .001) interrater-versus-reference reliability. The interrater reliability was fair (Kw = 0.43; SE = 0.037; 95% confidence interval, 0.360-0.491; P < .001). This study demonstrates fair interrater reliability beyond that expected by chance of the ASA PS scores among anesthesiologists and trauma surgeons when assessing adult polytrauma patients. Although the ASA PS is used in some trauma risk stratification models, discrepancies of ASA PS scores assigned to trauma cases exist. Future modifications of the ASA PS guidelines should aim to improve the interrater reliability of ASA PS scores in trauma patients. Further studies are warranted to determine the value of the ASA PS score as a trauma prognostic metric.

Electronic alert system for improving appropriate thromboprophylaxis in hospitalized medical patients: a randomized controlled trial

Background The use of thromboprophylaxis among acutely ill hospitalized medical patients remains inconsistent. Objective To improve thromboprophylaxis use by implementing a computer-based alert system combined with a Geneva Risk Score calculation tool in the electronic patient chart and order entry system. Patients/Methods Consecutive patients admitted to the general internal medicine wards of the University Hospital Bern, Switzerland were randomized to the alert group, in which an alert and the Geneva Risk Score calculation tool was issued in the electronic patient chart, or to the control group, in which no alert was issued. The primary endpoint was the rate of appropriate thromboprophylaxis during hospital stay. Results Overall, 1593 patients (alert group, 804; control group, 789) were eligible for analysis. The median age was 67 years (interquartile range, 53-79 years) and 47% were female. Appropriate thromboprophylaxis was administered to 536 (66.7%) patients from the alert group and to 526 (66.7%) patients from the control group. Among the 804 patients from the alert group, a total of 446 (55.5%) either had no score calculation by the physician in charge (n = 348) or had a calculated score result that was inconsistent with information from the patient chart (n = 98). Appropriate thromboprophylaxis was less often administered to patients with no score or an inconsistent score result than to 358 patients with a consistent score result (62.6% versus 71.8%). Conclusions The electronic alert (e-alert) system did not improve appropriate thromboprophylaxis, most likely because many e-alerts were ignored by ordering physicians. The use of appropriate thromboprophylaxis in the control group was higher than expected.

Detecting Inconsistent Responding on the Youth Psychopathic Traits Inventory-Short Form.

The Youth Psychopathic Traits Inventory-Short Form (YPI-S) is a convenient measure for assessing psychopathy in settings with constraints on resources. However, the YPI-S does not contain a means of detecting careless or random response styles. The present study describes the development and evaluation of an inconsistent responding scale for the YPI-S using five archival samples that vary in language (English, German, Italian, Dutch) and other participant characteristics (juvenile offenders, adolescent students). Inconsistency scores resulting from the new scale effectively distinguished genuine participant responses from randomly generated cases (area under the ROC curve [AUC] = .85-.90) and from cases in which 50% of original responses were replaced with random data (AUC = .75-.82). The associations between the YPI-S and theoretically relevant correlates were reduced among participants exceeding proposed cutoff scores for profile validity compared with associations among more consistent respondents.

Detecting the tipping points in a three-state model of complex diseases by temporal differential networks

BackgroundThe progression of complex diseases, such as diabetes and cancer, is generally a nonlinear process with three stages, i.e., normal state, pre-disease state, and disease state, where the pre-disease state is a critical state or tipping point immediately preceding the disease state. Traditional biomarkers aim to identify a disease state by exploiting the information of differential expressions for the observed molecules, but may fail to detect a pre-disease state because there are generally little significant differences between the normal and pre-disease states. Thus, it is challenging to signal the pre-disease state, which actually implies the disease prediction.MethodsIn this work, by exploiting the information of differential associations among the observed molecules between the normal and pre-disease states, we propose a temporal differential network based computational method to accurately signal the pre-disease state or predict the occurrence of severe disease. The theoretical foundation of this work is the quantification of the critical state using dynamical network biomarkers.ResultsConsidering that there is one stationary Markov process before reaching the tipping point, a novel index, inconsistency score (I-score), is proposed to quantitatively measure the change of the stationary processes from the normal state so as to detect the onset of pre-disease state. In other words, a drastic increase of I-score implies the high inconsistency with the preceding stable state and thus signals the upcoming critical transition. This approach is applied to the simulated and real datasets of three diseases, which demonstrates the effectiveness of our method for predicting the deterioration into disease states. Both functional analysis and pathway enrichment also validate the computational results from the perspectives of both molecules and networks.ConclusionsAt the molecular network level, this method provides a computational way of unravelling the underlying mechanism of the dynamical progression when a biological system is near the tipping point, and thus detecting the early-warning signal of the imminent critical transition, which may help to achieve timely intervention. Moreover, the rewiring of differential networks effectively extracts discriminatively interpretable features, and systematically demonstrates the dynamical change of a biological system.

Multiple common and rare variants of ABCG2 cause gout

ObjectivePrevious studies have suggested an association between gout susceptibility and common dysfunctional variants in ATP-binding cassette transporter subfamily G member 2/breast cancer resistance protein (ABCG2/BCRP), including rs72552713 (Q126X) and rs2231142...

Investigating Surface and Near-Surface Bushfire Fuel Attributes: A Comparison between Visual Assessments and Image-Based Point Clouds

Visual assessment, following guides such as the Overall Fuel Hazard Assessment Guide (OFHAG), is a common approach for assessing the structure and hazard of varying bushfire fuel layers. Visual assessments can be vulnerable to imprecision due to subjectivity between assessors, while emerging techniques such as image-based point clouds can offer land managers potentially more repeatable descriptions of fuel structure. This study compared the variability of estimates of surface and near-surface fuel attributes generated by eight assessment teams using the OFHAG and Fuels3D, a smartphone method utilising image-based point clouds, within three assessment plots in an Australian lowland forest. Surface fuel hazard scores derived from underpinning attributes were also assessed. Overall, this study found considerable variability between teams on most visually assessed variables, resulting in inconsistent hazard scores. Variability was observed within point cloud estimates but was, however, on average two to eight times less than that seen in visual estimates, indicating greater consistency and repeatability of this method. It is proposed that while variability within the Fuels3D method may be overcome through improved methods and equipment, inconsistencies in the OFHAG are likely due to the inherent subjectivity between assessors, which may be more difficult to overcome. This study demonstrates the capability of the Fuels3D method to efficiently and consistently collect data on fuel hazard and structure, and, as such, this method shows potential for use in fire management practices where accurate and reliable data is essential.

A Two-Step Latent Profile Method for Identifying Invalid Respondents in Self-Reported Survey Data

ABSTRACTInsincere respondents can have an adverse impact on the validity of substantive inferences arising from self-administered questionnaires (SAQs). The current study introduces a new method for identifying potentially invalid respondents from their atypical response patterns. The two-step procedure involves generating a response inconsistency (RI) score for each participant and scale on the SAQ and subjecting the resulting scores to latent profile analysis to identify classes of atypical RI respondent profiles. The procedure can be implemented post–data collection and is illustrated through a survey of school climate that was administered to N = 52,102 high school students. Results of this screening procedure revealed high levels of specificity and expected levels of concordance when contrasted with the results of traditionally used methods of screening items and response time. Contrasts between valid and invalid respondents revealed similar patterns across the three screening procedures when compared across external measures of academics and risk behaviors.

How Consistent Are the Best-Known Readability Equations in Estimating the Readability of Design Standards?

Research problem : Readability equations are widely used to compute how well readers will be able to understand written materials. Those equations were usually developed for nontechnical materials, namely, textbooks for elementary, middle, and high schools. This study examines to what extent computerized readability predictions are consistent for highly technical material—selected Society of Automotive Engineers (SAE) and International Standards Organization (ISO) Recommended Practices and Standards relating to driver interfaces. Literature review: A review of original sources of readability equations revealed a lack of specific criteria in counting various punctuation and text elements, leading to inconsistent readability scores. Few studies on the reliability of readability equations have identified this problem, and even fewer have systematically investigated the extent of the problem and the reasons why it occurs. Research questions: (1) Do the most commonly used equations give identical readability scores? (2) How do the scores for each readability equation vary with readability tools? (3) If there are differences between readability tools, why do they occur? (4) How does the score vary with the length of passage examined? Method : Passages of varying lengths from 12 selected SAE and ISO Recommended Practices and Standards were examined using five readability equations (Flesch-Kincaid Grade Level, Gunning Fog Index, SMOG Index, Coleman-Liau Index, and Automated Readability Index) implemented five ways (four online readability tools and Microsoft Word 2013 for Windows). In addition, short test passages of text were used to understand how different readability tools counted text elements, such as words and sentences. Results and conclusions: The mean readability scores of the passages from those 12 SAE and ISO Recommended Practices and Standards ranged from the 10th grade reading level to about 15th. The mean grade reading levels computed across the websites were: Flesch-Kincaid 12.8, Gunning Fog 15.1 SMOG 12.6, Coleman-Liau 13.7, and Automated Readability Index 12.3. Readability score estimates became more consistent as the length of the passage examined increased, with no noteworthy improvements beyond 900 words. Among the five readability tools, scores typically differed by two grade levels, but the scores should have been the same. These differences were due to how compound and hyphenated words, slashes, numbers, abbreviations and acronyms, and URLs were counted, as well other punctuation and text elements. These differences occurred because the sources for these equations often did not specify how to score various punctuation and text elements. Of the tools examined, the authors recommend Microsoft Word 2013 for Windows if the Flesch-Kincaid Grade Level is required.

Inconsistency Index for the Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ)

Abstract. The purpose of this study is the development of an index to assess inconsistency in the answers of Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ) in order to identify and discard inconsistent subjects in applied psychology, as clinical, forensics, or personnel selection. The procedure consists in the use of 10 pairs of highly correlated items in a wide sample of voluntary and anonymous subjects of both sexes (n = 5.644). We inserted random cases to the original data in order to obtain simulated scores of inconsistency and we established a cut-off criterion to discriminate between consistent and inconsistent subjects according to a 70 T Score. A score higher than 10 points discriminated the 3.7% of the subjects. Cronbach’s alpha average for facets was calculated by ZKA-PQ facets distributed in 8 (α: 0.79), 9–10 (α: 0.67), and above 10 points (α: .50) of the inconsistency index. The Feldt test indicates that alpha differences were significant. The inconsistency score did not affect the factorial structure of the ZKA-PQ. We discussed the utility of this index to identify inconsistent subjects with the ZKA-PQ, as, for instance, those with individual difficulties (a limited vocabulary, poor verbal comprehension, an idiosyncratic way of interpreting item meanings, carelessness, inattentiveness…).

Interrater reliability of Violence Risk Appraisal Guide scores provided in Canadian criminal proceedings.

Published research suggests that most violence risk assessment tools have relatively high levels of interrater reliability, but recent evidence of inconsistent scores among forensic examiners in adversarial settings raises concerns about the "field reliability" of such measures. This study specifically examined the reliability of Violence Risk Appraisal Guide (VRAG) scores in Canadian criminal cases identified in the legal database, LexisNexis. Over 250 reported cases were located that made mention of the VRAG, with 42 of these cases containing 2 or more scores that could be submitted to interrater reliability analyses. Overall, scores were skewed toward higher risk categories. The intraclass correlation (ICCA1) was .66, with pairs of forensic examiners placing defendants into the same VRAG risk "bin" in 68% of the cases. For categorical risk statements (i.e., low, moderate, high), examiners provided converging assessment results in most instances (86%). In terms of potential predictors of rater disagreement, there was no evidence for adversarial allegiance in our sample. Rater disagreement in the scoring of 1 VRAG item (Psychopathy Checklist-Revised; Hare, 2003), however, strongly predicted rater disagreement in the scoring of the VRAG (r = .58). (PsycINFO Database Record

Evaluating Transcription Factor Activity Changes by Scoring Unexplained Target Genes in Expression Data.

Several methods predict activity changes of transcription factors (TFs) from a given regulatory network and measured expression data. But available gene regulatory networks are incomplete and contain many condition-dependent regulations that are not relevant for the specific expression measurement. It is not known which combination of active TFs is needed to cause a change in the expression of a target gene. A method to systematically evaluate the inferred activity changes is missing. We present such an evaluation strategy that indicates for how many target genes the observed expression changes can be explained by a given set of active TFs. To overcome the problem that the exact combination of active TFs needed to activate a gene is typically not known, we assume a gene to be explained if there exists any combination for which the predicted active TFs can possibly explain the observed change of the gene. We introduce the i-score (inconsistency score), which quantifies how many genes could not be explained by the set of activity changes of TFs. We observe that, even for these minimal requirements, published methods yield many unexplained target genes, i.e. large i-scores. This holds for all methods and all expression datasets we evaluated. We provide new optimization methods to calculate the best possible (minimal) i-score given the network and measured expression data. The evaluation of this optimized i-score on a large data compendium yields many unexplained target genes for almost every case. This indicates that currently available regulatory networks are still far from being complete. Both the presented Act-SAT and Act-A* methods produce optimal sets of TF activity changes, which can be used to investigate the difficult interplay of expression and network data. A web server and a command line tool to calculate our i-score and to find the active TFs associated with the minimal i-score is available from https://services.bio.ifi.lmu.de/i-score.

Abnormal Ventricular and Aortic Wall Properties Can Cause Inconsistencies in Grading Aortic Regurgitation Severity: A Computer Simulation Study

Assessment of aortic regurgitation (AR) severity is often based on Doppler echocardiographic imaging. Hemodynamic responses to AR are influenced by the interplay among cardiovascular properties, including left ventricular (LV) and aortic tissue properties, that cannot be measured directly. The aim of this study was to investigate how both echocardiographic measures of AR severity and the hemodynamic consequences of AR are influenced by LV and aortic stiffness. AR was simulated using the CircAdapt computational model of the human cardiovascular system. Simulations were performed with normal LV and aortic stiffness, high LV stiffness, high aortic stiffness, and high LV and aortic stiffness. For each configuration of levels of stiffness, four AR severity grades were simulated by setting the effective regurgitant orifice area (ROA) of the aortic valve at 0, 0.05, 0.25, and 0.6cm2, representing no, mild, moderate, and severe AR, respectively. The regurgitant volume, regurgitant fraction (RF), and pressure half-time (PHT) were computed for each simulation giving an AR severity score (mild, moderate, or severe). Mean left atrial pressure was also calculated. Increasing ROA resulted in faster decay of diastolic flow velocity and larger regurgitant blood flow across the aortic valve. This caused shorter PHT and larger regurgitant volume and RF, all indicating higher AR severity. Increasing aortic stiffness resulted in a larger decline in diastolic aortic pressure, whereas increasing LV stiffness resulted in a larger rise in diastolic LV pressure. Hence, increasing LV and/or aortic stiffness led to faster decay of the transvalvular pressure gradient and, therefore, to faster decay of diastolic flow velocity across the aortic valve compared with normal stiffness with the same ROA. This faster decay led, on one hand, to a shorter PHT, indicating higher severity scores, and, on the other hand, to a lower RF, as less regurgitant blood volume traveled into the left ventricle, indicating lower severity scores. AR severity scores reflected mean left atrial pressure poorly when variations in tissue properties were present. Simulating altered AR hemodynamics caused by variations in cardiovascular tissue properties led to inconsistent severity scores when evaluating the severity using RF, regurgitant volume, and PHT. In this situation, pulmonary congestion is poorly reflected by AR severity as quantified by ROA, RF, and PHT. Cardiac and aortic tissue properties should therefore be taken into account to improve clinical assessment of AR severity.

Splenic artery embolization: technically feasible but not necessarily advantageous.

BackgroundThe spleen is the second most commonly injured organ in cases of abdominal trauma. Management of splenic injury depends on the clinical status of the patient and can include nonoperative management (NOM), splenic artery embolization (SAE), surgery (operative splenic salvage or splenectomy), or a combination of these treatments. In nonoperatively managed cases, SAE is sometimes used to control haemorrhage. However, the indications for SAE have not been clearly defined and, in some cases, the potential complications of the procedure may outweigh its benefits.Review of the literatureThrough review of the literature we address the question of when SAE is indicated in combination with NOM of splenic injury, and whether SAE may delay needed surgical treatment in some cases. This systematic review highlighted the use of imperfect and inconsistent scoring systems in the diagnosis of splenic injury, the lack of consensus regarding indications for SAE, and the potential for severe morbidities associated with this procedure. Based on current literature and evidence we provide a new, non-verified, decision algorithm.ConclusionsNOM+ SAE involves potential risks and operative management may be preferable to SAE for certain patients. To clarify current literature, we propose a new algorithm for blunt abdominal trauma that should be validated prospectively. New evidence-based protocols should be developed to guide diagnosis and management of patients with splenic trauma.Electronic supplementary materialThe online version of this article (doi:10.1186/s13017-016-0100-7) contains supplementary material, which is available to authorized users.

한국 청소년의 우울증상과 부모자녀관계

Objectives : The objective of this study was to compare the parent-child relationship of adolescents with depression and those without depression, by using Parent-Child Relationship Instrument (PCRI), Family Relationship Scale (FRS), and Parenting Attitude Test-Youth (PAT-Y). We also investigated the association between the parent-child relationship and depressive symptoms. Methods : Twenty-five adolescents with depression (age <TEX>$15.0{\pm}2.1years$</TEX>, 8 boys) and 24 adolescents without depression (age <TEX>$13.7{\pm}1.3years$</TEX>, 16 boys) completed the Adolescent-General Behavior Inventory (A-GBI), Adolescent-Mood Disorder Questionnaire (A-MDQ), Beck Depression Inventory (BDI), PCRI, and PAT-Y. The parents of subjects completed the Child Behavior Checklist, Parent-General Behavior Inventory 10-item Mania Scale (P-GBI-10M), Parent-Mood Disorder Questionnaire, and FRS. Independent t-tests, analysis of covariance, and partial correlation analysis were used. Results : The Intimacy (p=.002) and Respect (p=.029) scores of the PCRI were significantly higher in adolescents without depression compared to those with depression. The Intimacy scores of the PCRI showed negative correlation with the BDI and P-GBI-10M and the Strictness scores of the PCRI showed positive correlation with the A-GBI, A-MDQ, and BDI. The Inconsistency, Punishment, and Excessive Expectation scores of the PAT-Y showed positive correlation with the A-GBI and BDI scores. Conclusion : Our results suggest a possible association of the parent-children relationship and parenting attitude with adolescents' depressive symptoms.

A Practical Guide to Check the Consistency of Item Response Patterns in Clinical Research Through Person-Fit Statistics: Examples and a Computer Program.

Although there are many studies devoted to person-fit statistics to detect inconsistent item score patterns, most studies are difficult to understand for nonspecialists. The aim of this tutorial is to explain the principles of these statistics for researchers and clinicians who are interested in applying these statistics. In particular, we first explain how invalid test scores can be detected using person-fit statistics; second, we provide the reader practical examples of existing studies that used person-fit statistics to detect and to interpret inconsistent item score patterns; and third, we discuss a new R-package that can be used to identify and interpret inconsistent score patterns.