A comparison of different measures of the proportion of explained variance in multiply imputed data sets.

The proportion of explained variance is an important statistic in multiple regression for determining how well the outcome variable is predicted by the predictors. Earlier research on 20 different estimators for the proportion of explained variance, including the exact Olkin-Pratt estimator and the Ezekiel estimator, showed that the exact Olkin-Pratt estimator produced unbiased estimates, and was recommended as a default estimator. In the current study, the same 20 estimators were studied in incomplete data, with missing data being treated using multiple imputation. In earlier research on the proportion of explained variance in multiply imputed data sets, an estimator called R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ was shown to be the preferred pooled estimator for regular R 2 $$ {R}^2 $$ . For each of the 20 estimators in the current study, two pooled estimators were proposed: one where the estimator was the average across imputed data sets, and one where R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ was used as input for the calculation of the specific estimator. Simulations showed that estimates based on R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ performed best regarding bias and accuracy, and that the Ezekiel estimator was generally the least biased. However, none of the estimators were unbiased at all times, including the exact Olkin-Pratt estimator based on R ̂ SP 2 $$ {\hat{R}}_{\mathrm{SP}}^2 $$ .

Role of knowledge and reasoning processes as predictors of resident physicians' susceptibility to anchoring bias in diagnostic reasoning: a randomised controlled experiment.

BACKGROUND: Diagnostic errors have been attributed to reasoning flaws caused by cognitive biases. While experiments have shown bias to cause errors, physicians of similar expertise differed in susceptibility to bias. Resisting bias is often said to depend on engaging analytical reasoning, disregarding the influence of knowledge. We examined the role of knowledge and reasoning mode, indicated by diagnosis time and confidence, as predictors of susceptibility to anchoring bias. Anchoring bias occurs when physicians stick to an incorrect diagnosis triggered by early salient distracting features (SDF) despite subsequent conflicting information. METHODS: Sixty-eight internal medicine residents from two Dutch university hospitals participated in a two-phase experiment. Phase 1: assessment of knowledge of discriminating features (ie, clinical findings that discriminate between lookalike diseases) for six diseases. Phase 2 (1 week later): diagnosis of six cases of these diseases. Each case had two versions differing exclusively in the presence/absence of SDF. Each participant diagnosed three cases with SDF (SDF+) and three without (SDF-). Participants were randomly allocated to case versions. Based on phase 1 assessment, participants were split into higher knowledge or lower knowledge groups. MAIN OUTCOME MEASUREMENTS: frequency of diagnoses associated with SDF; time to diagnose; and confidence in diagnosis. RESULTS: While both knowledge groups performed similarly on SDF- cases, higher knowledge physicians succumbed to anchoring bias less frequently than their lower knowledge counterparts on SDF+ cases (p=0.02). Overall, physicians spent more time (p<0.001) and had lower confidence (p=0.02) on SDF+ than SDF- cases (p<0.001). However, when diagnosing SDF+ cases, the groups did not differ in time (p=0.88) nor in confidence (p=0.96). CONCLUSIONS: Physicians apparently adopted a more analytical reasoning approach when presented with distracting features, indicated by increased time and lower confidence, trying to combat bias. Yet, extended deliberation alone did not explain the observed performance differences between knowledge groups. Success in mitigating anchoring bias was primarily predicted by knowledge of discriminating features of diagnoses.

Neurobiological correlates of antisociality across adolescence and young adulthood: a multi-sample, multi-method study.

BACKGROUND: Antisociality across adolescence and young adulthood puts individuals at high risk of developing a variety of problems. Prior research has linked antisociality to autonomic nervous system and endocrinological functioning. However, there is large heterogeneity in antisocial behaviors, and these neurobiological measures are rarely studied conjointly, limited to small specific studies with narrow age ranges, and yield mixed findings due to the type of behavior examined. METHODS: We harmonized data from 1489 participants (9-27 years, 67% male), from six heterogeneous samples. In the resulting dataset, we tested relations between distinct dimensions of antisociality and heart rate, pre-ejection period (PEP), respiratory sinus arrhythmia, respiration rate, skin conductance levels, testosterone, basal cortisol, and the cortisol awakening response (CAR), and test the role of age throughout adolescence and young adulthood. RESULTS: Three dimensions of antisociality were uncovered: 'callous-unemotional (CU)/manipulative traits', 'intentional aggression/conduct', and 'reactivity/impulsivity/irritability'. Shorter PEPs and higher testosterone were related to CU/manipulative traits, and a higher CAR is related to both CU/manipulative traits and intentional aggression/conduct. These effects were stable across age. CONCLUSIONS: Across a heterogeneous sample and consistent across development, the CAR may be a valuable measure to link to CU/manipulative traits and intentional aggression, while sympathetic arousal and testosterone are additionally valuable to understand CU/manipulative traits. Together, these findings deepen our understanding of the fundamental mechanisms underlying different components of antisociality. Finally, we illustrate the potential of using current statistical techniques for combining multiple datasets to draw robust conclusions about biobehavioral associations.

Effectiveness of an online self-help program, expert-patient support, and their combination for eating disorders: Results from a randomized controlled trial.

OBJECTIVE: Many individuals with an eating disorder do not receive appropriate care. Low-threshold interventions could help bridge this treatment gap. The study aim was to evaluate the effectiveness of Featback, a fully automated online self-help intervention, online expert-patient support and their combination. METHOD: A randomized controlled trial with a 12-month follow-up period was conducted. Participants aged 16 or older with at least mild eating disorder symptoms were randomized to four conditions: (1) Featback, a fully automated online self-help intervention, (2) chat or email support from a recovered expert patient, (3) Featback with expert-patient support and (4) a waiting list control condition. The intervention period was 8 weeks and there was a total of six online assessments. The main outcome constituted reduction of eating disorder symptoms over time. RESULTS: Three hundred fifty five participants, of whom 43% had never received eating disorder treatment, were randomized. The three active interventions were superior to a waitlist in reducing eating disorder symptoms (d = -0.38), with no significant difference in effectiveness between the three interventions. Participants in conditions with expert-patient support were more satisfied with the intervention. DISCUSSION: Internet-based self-help, expert-patient support and their combination were effective in reducing eating disorder symptoms compared to a waiting list control condition. Guidance improved satisfaction with the internet intervention but not its effectiveness. Low-threshold interventions such as Featback and expert-patient support can reduce eating disorder symptoms and reach the large group of underserved individuals, complementing existing forms of eating disorder treatment. PUBLIC SIGNIFICANCE STATEMENT: Individuals with eating-related problems who received (1) a fully automated internet-based intervention, (2) chat and e-mail support by a recovered individual or (3) their combination, experienced stronger reductions in eating disorder symptoms than those who received (4) usual care. Such brief and easy-access interventions play an important role in reaching individuals who are currently not reached by other forms of treatment.

Cost-effectiveness of three internet-based interventions for eating disorders: A randomized controlled trial.

OBJECTIVE: The primary aim was assessing the cost-effectiveness of an internet-based self-help program, expert-patient support, and the combination of both compared to a care-as-usual condition. METHOD: An economic evaluation from a societal perspective was conducted alongside a randomized controlled trial. Participants aged 16 or older with at least mild eating disorder symptoms were randomly assigned to four conditions: (1) Featback, an online unguided self-help program, (2) chat or e-mail support from a recovered expert patient, (3) Featback with expert-patient support, and (4) care-as-usual. After a baseline assessment and intervention period of 8 weeks, five online assessments were conducted over 12 months of follow-up. The main result constituted cost-utility acceptability curves with quality-of-life adjusted life years (QALYs) and societal costs over the entire study duration. RESULTS: No significant differences between the conditions were found regarding QALYs, health care costs and societal costs. Nonsignificant differences in QALYs were in favor of the Featback conditions and the lowest societal costs per participant were observed in the Featback only condition (€16,741) while the highest costs were seen in the care-as-usual condition (€28,479). The Featback only condition had the highest probability of being efficient compared to the alternatives for all acceptable willingness-to-pay values. DISCUSSION: Featback, an internet-based unguided self-help intervention, was likely to be efficient compared to Featback with guidance from an expert patient, guidance alone and a care-as-usual condition. Results suggest that scalable interventions such as Featback may reduce health care costs and help individuals with eating disorders that are currently not reached by other forms of treatment. PUBLIC SIGNIFICANCE STATEMENT: Internet-based interventions for eating disorders might reach individuals in society who currently do not receive appropriate treatment at low costs. Featback, an online automated self-help program for eating disorders, was found to improve quality of life slightly while reducing costs for society, compared to a do-nothing approach. Consequently, implementing internet-based interventions such as Featback likely benefits both individuals suffering from an eating disorder and society as a whole.

The diagnostic process from primary care to child and adolescent mental healthcare services: the incremental value of information conveyed through referral letters, screening questionnaires and structured multi-informant assessment.

BACKGROUND: A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined. AIMS: To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians' remote evaluations in predicting mental health disorders. METHOD: Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed. RESULTS: Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value. CONCLUSIONS: Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary-secondary care interface should now be quantified in prospective studies.

Enhancement of Room Temperature Ethanol Sensing by Optimizing the Density of Vertically Aligned Carbon Nanofibers Decorated with Gold Nanoparticles.

An ethanol gas sensor based on carbon nanofibers (CNFs) with various densities and nanoparticle functionalization was investigated. The CNFs were grown by means of a Plasma-Enhanced Chemical Vapor Deposition (PECVD), and the synthesis conditions were varied to obtain different number of fibers per unit area. The devices with a larger density of CNFs lead to higher responses, with a maximal responsivity of 10%. Furthermore, to simultaneously improve the sensitivity and selectivity, CNFs were decorated with gold nanoparticles by an impaction printing method. After metal decoration, the devices showed a response 300% higher than pristine devices toward 5 ppm of ethanol gas. The morphology and structure of the different samples deposited on a silicon substrate were characterized by TEM, EDX, SEM, and Raman spectroscopy, and the results confirmed the presence of CNF decorated with gold. The influence of operating temperature (OT) and humidity were studied on the sensing devices. In the case of decorated samples with a high density of nanofibers, a less-strong cross-sensitivity was observed toward a variation in humidity and temperature.

The role of infant attention and parental sensitivity in infant cognitive development in the Netherlands and China.

Infant attention and parental sensitivity are important predictors of later child executive function (EF). However, most studies have investigated infant and parent factors in relation to child EF separately and included only mothers from Western samples. The current study examined whether both infant attention at 4 months and parental sensitivity at 4 and 14 months were related to infant EF (i.e., inhibition, working memory, and cognitive flexibility) at 14 months among 124 Dutch and 63 Chinese first-time mothers and fathers and their infants. Findings revealed that parental sensitivity at 4 months was not correlated with infant EF abilities at 14 months. However, infant attention at 4 months was significantly related to 14-month working memory, but not to inhibition and cognitive flexibility. Maternal sensitivity at 14 months was significantly related to 14-month inhibition, but not to working memory and cognitive flexibility. No country differences were found in the relation among 4-month infant attention, parental sensitivity, and EF outcomes. Results show that both infant and parent factors are associated with early EF development and that these correlates of early EF skills may be similar in Western and non-Western samples.

Accurate detection of circulating tumor DNA using nanopore consensus sequencing.

Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant ctDNA molecules based on somatic variants, extremely sensitive sequencing methods are required. Here, we describe a new technique, CyclomicsSeq, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule. Consensus calling of the DNA copies increased the base-calling accuracy ~60×, enabling accurate detection of TP53 mutations at frequencies down to 0.02%. We demonstrate that a TP53-specific CyclomicsSeq assay can be successfully used to monitor tumor burden during treatment for head-and-neck cancer patients. CyclomicsSeq can be applied to any genomic locus and offers an accurate diagnostic liquid biopsy approach that can be implemented in clinical workflows.

Correction: Intergenerational transmission of child maltreatment using a multi-informant multi-generation family design.

[This corrects the article DOI: 10.1371/journal.pone.0225839.].

Dataset on maternal attitudes about child maltreatment in nine countries using a Q-sort methodology.

Analyses of the present data are reported in the article "Crossing Boundaries: A Pilot Study of Maternal Attitudes about Child Maltreatment in Nine Countries" [8]. Data were collected during home visits using the Maltreatment Q-Sort (MQS). A total of 466 mothers from nine different countries gave their opinion about child maltreatment by sorting 90 cards with parenting behaviors taken from the literature that reflect four types of child maltreatment, into 9 evenly distributed stacks (with 10 cards each) from least to most harmful for the child. This data article provides an overview of the content of the 90 items, which type of maltreatment they reflect, and the source of the items. The percentage of mothers labelling each of the MQS items as maltreatment is also presented. In addition, instructions are included about the administration of the MQS as well as data-entry and analyses of Q-sort data, accompanied by example datasets and syntaxes. This can serve as a manual for researchers interested in using Q-sort data.

Intergenerational transmission of child maltreatment using a multi-informant multi-generation family design.

In the current study a three-generational design was used to investigate intergenerational transmission of child maltreatment (ITCM) using multiple sources of information on child maltreatment: mothers, fathers and children. A total of 395 individuals from 63 families reported on maltreatment. Principal Component Analysis (PCA) was used to combine data from mother, father and child about maltreatment that the child had experienced. This established components reflecting the convergent as well as the unique reports of father, mother and child on the occurrence of maltreatment. Next, we tested ITCM using the multi-informant approach and compared the results to those of two more common approaches: ITCM based on one reporter and ITCM based on different reporters from each generation. Results of our multi-informant approach showed that a component reflecting convergence between mother, father, and child reports explained most of the variance in experienced maltreatment. For abuse, intergenerational transmission was consistently found across approaches. In contrast, intergenerational transmission of neglect was only found using the perspective of a single reporter, indicating that transmission of neglect might be driven by reporter effects. In conclusion, the present results suggest that including multiple informants may be necessary to obtain more valid estimates of ITCM.

Standardized Regression Coefficients and Newly Proposed Estimators for [Formula: see text] in Multiply Imputed Data.

Whenever statistical analyses are applied to multiply imputed datasets, specific formulas are needed to combine the results into one overall analysis, also called combination rules. In the context of regression analysis, combination rules for the unstandardized regression coefficients, the t-tests of the regression coefficients, and the F-tests for testing [Formula: see text] for significance have long been established. However, there is still no general agreement on how to combine the point estimators of [Formula: see text] in multiple regression applied to multiply imputed datasets. Additionally, no combination rules for standardized regression coefficients and their confidence intervals seem to have been developed at all. In the current article, two sets of combination rules for the standardized regression coefficients and their confidence intervals are proposed, and their statistical properties are discussed. Additionally, two improved point estimators of [Formula: see text] in multiply imputed data are proposed, which in their computation use the pooled standardized regression coefficients. Simulations show that the proposed pooled standardized coefficients produce only small bias and that their 95% confidence intervals produce coverage close to the theoretical 95%. Furthermore, the simulations show that the newly proposed pooled estimates for [Formula: see text] are less biased than two earlier proposed pooled estimates.

Rebutting Existing Misconceptions About Multiple Imputation as a Method for Handling Missing Data.

Missing data is a problem that occurs frequently in many scientific areas. The most sophisticated method for dealing with this problem is multiple imputation. Contrary to other methods, like listwise deletion, this method does not throw away information, and partly repairs the problem of systematic dropout. Although from a theoretical point of view multiple imputation is considered to be the optimal method, many applied researchers are reluctant to use it because of persistent misconceptions about this method. Instead of providing an(other) overview of missing data methods, or extensively explaining how multiple imputation works, this article aims specifically at rebutting these misconceptions, and provides applied researchers with practical arguments supporting them in the use of multiple imputation.

Crossing boundaries: A pilot study of maternal attitudes about child maltreatment in nine countries.

BACKGROUND: Definitions of child maltreatment vary widely between studies, and even more so between different cultural contexts. OBJECTIVE: In this pilot study, we examine between-country variations in maternal notions about what constitutes child maltreatment. PARTICIPANTS AND SETTING: The sample consisted of 466 mothers recruited in Chile, China, Greece, Iran, the Netherlands, Portugal, South Africa, Turkey, and Uruguay. METHODS: All mothers completed a new Q-sort measure, ranking 90 parenting behaviors linked to subtypes of maltreatment (emotional neglect, emotional abuse, physical neglect, and physical abuse) from least to most detrimental to child development. RESULTS: Between-country agreement regarding the harmfulness of the parenting behaviors was high (r = .45), but there were different patterns of reported harmfulness of subtypes of maltreatment (although driven mostly by deviating patterns in the South African sample). Further, there were significant country effects on the number and type of behaviors labeled as maltreatment (pƞ2 = .15), and the number of items labeled as requiring intervention (pƞ2 = .19). CONCLUSIONS: Variations in conceptions of maltreatment need to be studied in larger more representative samples and taken into account in the assessment and treatment of child maltreatment across cultures.

A randomized controlled trial of an Internet-based intervention for eating disorders and the added value of expert-patient support: study protocol.

BACKGROUND: E-mental health has become increasingly popular in interventions for individuals with eating disorders (EDs). It has the potential to offer low-threshold interventions and guide individuals to the needed care more promptly. Featback is such an Internet-based intervention and consists of psychoeducation and a fully automated monitoring and feedback system. Preliminary findings suggest Featback to be (cost-)effective in reducing ED symptomatology. Additionally, e-mail or chat support by a psychologist did not enhance the effectiveness of Featback. Support by an expert patient (someone with a lived experience of an ED) might be more effective, since that person can effectively model healthy behavior and enhance self-efficacy in individuals struggling with an ED. The present study aims to replicate and build on earlier findings by further investigating the (cost-)effectiveness of Featback and the added value of expert-patient support. METHODS: The study will be a randomized controlled trial with a two-by-two factorial design with repeated measures. The four conditions will be (1) Featback, in which participants receive automated feedback on a short monitoring questionnaire weekly, (2) Featback with weekly e-mail or chat support from an expert patient, (3) weekly support from an expert patient, and (4) a waiting list. Participants who are 16 years or older and have at least mild self-reported ED symptoms receive a baseline measure. Subsequently, they are randomized to one of the four conditions for 8 weeks. Participants will be assessed again post-intervention and at 3, 6, 9, and 12 months follow-up. The primary outcome measure will be ED psychopathology. Secondary outcome measures are experienced social support, self-efficacy, symptoms of anxiety and depression, user satisfaction, intervention usage, and help-seeking attitudes and behaviors. DISCUSSION: The current study is the first to investigate e-mental health in combination with expert-patient support for EDs and will add to the optimization of the delivery of Internet-based interventions and expert-patient support. TRIAL REGISTRATION: Netherlands Trial Register, NTR7065 . Registered on 7 June 2018.

Significance Tests and Estimates for R2 for Multiple Regression in Multiply Imputed Datasets: A Cautionary Note on Earlier Findings, and Alternative Solutions.

Whenever multiple regression is applied to a multiply imputed data set, several methods for combining significance tests for R2 and the change in R2 across imputed data sets may be used: the combination rules by Rubin, the Fisher z-test for R2 by Harel, and F-tests for the change in R2 by Chaurasia and Harel. For pooling R2 itself, Harel proposed a method based on a Fisher z transformation. In the current article, it is argued that the pooled R2 based on the Fisher z transformation, the Fisher z-test for R2 , and the F-test for the change in R2 have some theoretical flaws. An argument is made for using Rubin's method for pooling significance tests for R2 instead, and alternative procedures for pooling R2 are proposed: simple averaging and a pooled R2 constructed from the pooled significance test by Rubin. Simulations show that the Fisher z-test and Chaurasia and Harel's F-tests generally give inflated type-I error rates, whereas the type-I error rates of Rubin's method are correct. Of the methods for pooling the point estimates of R2 no method clearly performs best, but it is argued that the average of R2 's across imputed data set is preferred.

Cell-free nucleic acids in body fluids as biomarkers for the prediction and early detection of recurrent head and neck cancer: A systematic review of the literature.

Liquid biopsy is a minimally invasive detection method for molecular biomarkers in body fluids which may serve as a novel tool in management of head and neck cancer. The purpose of this systematic review is to outline the current status of liquid biopsy in head and neck squamous cell carcinoma (HNSCC) patients by systematically identifying and qualifying all published studies on the diagnostic or prognostic value of cell-free nucleic acids detection for posttreatment disease monitoring and/or disease outcome. A search was performed in PubMed, EMBASE, and Cochrane Library. Thirty articles met the inclusion criteria for further analysis. Study and patient characteristics, molecular analysis method and treatment or prognostic outcomes were extracted. Seventeen studies investigated circulating miRNAs in blood. Of these studies, 16 found statistically significant results for a total of 24 different candidate miRNAs for prognostication or treatment monitoring. The remaining studies investigated circulating tumor DNA by targeting somatic mutations, allelic imbalances, hypermethylation, or HPV-DNA. Of these studies, 2 found a statistically significant association between nucleic acid levels (tumor DNA targeted by allelic imbalances and HPV-DNA) in blood and/or saliva and prognostic outcome. One study found significantly different pre- and posttreatment levels of mitochondrial DNA in serum. Despite large differences among these studies in both design and results, individual results are promising and provide ground for more large-scale studies with standardized serial assessment of patient samples in the future.