BACKGROUND: The diagnosis of peripheral arterial disease (PAD) is commonly applied for symptoms related to atherosclerotic obstructions in the lower extremity, though its clinical manifestations range from an abnormal ankle-brachial index to critical limb ischemia. Subsequently, management and prognosis of PAD vary widely with the disease stage. A critical aspect is how this variation is addressed in administrative database-based studies that rely on diagnosis codes for case identification. The objective of this scoping review is to inventory the identification strategies used in studies on PAD that rely on administrative databases, to map the pros and cons of the International Classification of Diseases (ICD) codes applied, and to propose a first outline for a consensus framework for case identification in administrative databases.
METHODS: Registry-based reports published between 2010 and 2021 were identified through a systematic PubMed search. Studies were subcategorized on the basis of the expressed study focus: claudication, critical limb ischemia, or general peripheral arterial disease, and the ICD code(s) applied for case identification mapped.
RESULTS: Ninety studies were identified, of which 36 (40%) did not specify the grade of PAD studied. Forty-nine (54%) articles specified PAD grade studied. Five (6%) articles specified different PAD subgroups in methods and baseline demographics, but not in further analyses. Mapping of the ICD codes applied for case identification for studies that specified the PAD grade studied indicated a remarkable heterogeneity, overlap, and inconsistency.
CONCLUSIONS: A large proportion of registry-based studies on PAD fail to define the study focus. In addition, inconsistent strategies are used for PAD case identification in studies that report a focus. These findings challenge study validity and interfere with inter-study comparison. This scoping review provides a first initiative for a consensus framework for standardized case selection in administrative studies on PAD. It is anticipated that more uniform coding will improve study validity and facilitate inter-study comparisons.

Adults\' perceptions of children\'s disclosures have important implications for the response to that disclosure. Children who experience adult transgressions, such as maltreatment, often choose to disclose this experience to a peer. Thus, peer disclosure recipients may transmit this disclosure to an adult or provide support for the child\'s own disclosure. Despite this, the influence of peer disclosure on a child witness\'s credibility, as well as on the perceptions of peer disclosure recipients, is unknown. The present study examined how child witnesses\' and peer disclosure recipients\' credibility is impacted when the peer either confirms or contradicts the witness\'s disclosure (or concealment) of an adult transgression. Participants listened to a child witness and peer being interviewed by an adult in one of four disclosure patterns (consistent disclose, consistent conceal, witness disclose/peer conceal, or witness conceal/peer disclose). Participants rated both the witness and the peer on dimensions of credibility (honesty and cognitive competence). Results revealed that both the witness and peer were more credible when their reports were consistent with one another. When inconsistent, the witness/peer who disclosed was considered more credible than the one who concealed. The findings indicate the potential importance of peers in the disclosure process as they may support the witness\'s report and even be a credible discloser when the witness is reluctant to disclose.

A lack of suitable dumping sites in a town or city can have an impact on the health of the residents as well as the quality of the urban environment. There are no identified dumping sites in this study area that meet scientific or urban standards. Residents are dumping solid waste into ditches, roads, public water sources, and small streams. The solid and liquid wastes generated by residential areas, state prisons, religious areas, public markets, and business centers have a negative impact on the town. The purpose of this study is to demonstrate the novelty of using Multi-Criteria Analysis (MCA)-based geospatial analysis to select suitable dumping sites in Shambu town. Key factors for dumping site selection, such as LULC, road networks, private well locations, slope, geomorphology, geology, soil texture, drainage density, and lineament density, were confirmed as geospatial analysis criteria. In the Analytical Hierarchy Process (AHP), the importance of the key factors was weighted and prioritized, and thematic maps were created using weighted overlay analysis. The suitable dumping sites were identified using qualitative classifications such as \"highly suitable\" (13.84%), \"moderately suitable\" (7.35%), \"less suitable\" (30.41%), and \"not suitable\" (48.40%). The consistency of AHP was determined to be CI = 0.012, indicating that the weights assigned to each factor were correct. As a result, the use of geospatial and MCA analysis for dumping site suitability analysis was successful, and the findings of this study will be useful in taking action to reduce the impacts of solid waste by developing dumping plants on the identified sites.

BACKGROUND: In August 2017, Myanmar\'s Armed Forces, the Tatmadaw, launched an orchestrated attack on hundreds of Rohingya-majority villages in northern Rakhine state. This study seeks to validate the consistency of previous reports of violence against the Rohingya people in the region carried out by the Tatmadaw, Border Guard Police, and Rakhine villagers in the late summer and early fall of 2017.
METHODS: Internal validation data is from a three-armed study. Data analyzed in the external triangulation was sourced through a literature review of known, publicly available surveys and interviews. Both sets of data documented instances of violence against the Rohingya people in northern Rakhine state during the late summer and early fall of 2017. Consistency was evaluated across five indicators of violence: arson, presence of mass graves, reports of sexual violence and human injuries, as well as human fatalities, across 611 locales in northern Rakhine state. Further analysis was conducted to measure consistency of reports by locale and across locales by indicator.
RESULTS: Overall, an internal validation of 94 hamlets found that 98% of these locales were consistent across at least four of the five indicators (80% + consistency). Arson and reports of human injuries were the most consistent indicators across locales (100% and 99% consistency, respectively) and sexual violence was the least consistent indicator, with 84% of participating locales exhibiting consistent reports of sexual violence between the qualitative and quantitative data. Similarly, an external validation of 57 locations found that 50 of the 57 locations (88%) were consistent across indicators. Arson was the most consistent across sources (96%), whereas source agreement across locations was the least consistent for reports of sexual violence (58%).
CONCLUSIONS: The government of Myanmar has denied involvement in the 2017 attacks on Rohingya communities in northern Rakhine state and purports that reports of the violence and destruction are overstated. However, consistent reporting from multiple sources on the same locales clearly underscores the veracity of the evidence documented, both by investigative groups and as recounted by Rohingya survivors of violence. It is our hope that this cataloging and comparison of available data, along with this study\'s assessment of its consistency, will aid ongoing accountability efforts.

The analysis of subgroups in clinical trials is essential to assess differences in treatment effects for distinct patient clusters, that is, to detect patients with greater treatment benefit or patients where the treatment seems to be ineffective.
The software application subscreen (R package) has been developed to analyze the population of clinical trials in minute detail. The aim was to efficiently calculate point estimates (eg, hazard ratios) for multiple subgroups to identify groups that potentially differ from the overall trial result. The approach intentionally avoids inferential statistics such as P values or confidence intervals but intends to encourage discussions enriched with external evidence (eg, from other studies) about the exploratory results, which can be accompanied by further statistical methods in subsequent analyses. The subscreen application was applied to 2 clinical study data sets and used in a simulation study to demonstrate its usefulness.
The visualization of numerous combined subgroups illustrates the homogeneity or heterogeneity of potentially all subgroup estimates with the overall result. With this, the application leads to more targeted planning of future trials.
This described approach supports the current trend and requirements for the investigation of subgroup effects as discussed in the EMA draft guidance for subgroup analyses in confirmatory clinical trials (EMA 2014). The lack of a convenient tool to answer spontaneous questions from different perspectives can hinder an efficient discussion, especially in joint interdisciplinary study teams. With the new application, an easily executed but powerful tool is provided to fill this gap.

Objectives: Cochlear implants are known to significantly improve the quality of life (QoL) of implanted children. However, variability exists between self-reported outcomes and parental-reported QoL questionnaires. We evaluated the QoL agreement between children and their parents following cochlear implantation and determined which factors lead to increased agreement. Methods: A cross-sectional study was performed including pediatric cochlear implant recipients and their parents. We evaluated postoperative QoL using The Pediatric Quality of Life Inventory (PedsQL). To assess agreement between pediatric and parental QoL perception, PedsQL intra-class correlations (ICCs) were calculated. Results: Thirty-five children and their parents completed QoL questionnaires. Children who were evaluated between 8-12 years of age reported highest absolute total and subscale PedsQL scores. Highest agreement was found amongst parents and children when: (1) children were between 8-12 years at QoL assessment (ICC: between 0.917[95%CI: 0.676-0.981] and 0.972[95%CI: 0.882-0.994]), and (2) when evaluating the physical health QoL domain (ICC: 0.964[95%CI: 0.849-0.992]). Conclusions: This study demonstrates high agreement (ICC > 0.8) between pediatric and parental QoL report in children aged between 8-12 years at QoL assessment. Therefore, results confirm that: (1) QoL agreement between pediatric self-report and parent proxy-report is high in chronically ill children and (2) children using cochlear implants can reliably report QoL between 8-12 years.

Consistency is one of the crucial single-case data aspects that are expected to be assessed visually, when evaluating the presence of an intervention effect. Complementarily to visual inspection, there have been recent proposals for quantifying the consistency of data patterns in similar phases and the consistency of effects for reversal, multiple-baseline, and changing criterion designs. The current text continues this line of research by focusing on alternation designs using block randomization. Specifically, three types of consistency are discussed: consistency of superiority of one condition over another, consistency of the average level across blocks, and consistency in the magnitude of the effect across blocks. The focus is put especially on the latter type of consistency, which is quantified on the basis of partitioning the variance, as attributed to the intervention, to the blocking factor or remaining as residual (including the interaction between the intervention and the blocks). Several illustrations with real and fictitious data are provided in order to make clear the meaning of the quantification proposed. Moreover, specific graphical representations are recommend for complementing the numerical assessment of consistency. A freely available user-friendly webpage is developed for implementing the proposal.

In the context of single-case experimental designs, replication is crucial. On the one hand, the replication of the basic effect within a study is necessary for demonstrating experimental control. On the other hand, replication across studies is required for establishing the generality of the intervention effect. Moreover, the \"replicability crisis\" presents a more general context further emphasizing the need for assessing consistency in replications. In the current text, we focus on replication of effects within a study, and we specifically discuss the consistency of effects. Our proposal for assessing the consistency of effects refers to one of the promising data analytical techniques, multilevel models, also known as hierarchical linear models or mixed effects models. One option is to check, for each case in a multiple-baseline design, whether the confidence interval for the individual treatment effect excludes zero. This is relevant for assessing whether the effect is replicated as being non-null. However, we consider that it is more relevant and informative to assess, for each case, whether the confidence interval for the random effects includes zero (i.e., whether the fixed effect estimate is a plausible value for each individual effect). This is relevant for assessing whether the effect is consistent in size, with the additional requirement that the fixed effect itself is different from zero. The proposal for assessing consistency is illustrated with real data and is implemented in free user-friendly software.

Quality standards for single-case experimental designs (SCEDs) recommend inspecting six data aspects: level, trend, variability, overlap, immediacy, and consistency of data patterns. The data aspect consistency has long been neglected by visual and statistical analysts of SCEDs despite its importance for inferring a causal relationship. However, recently a first quantification has been proposed in the context of A-B-A-B designs, called CONsistency of DAta Patterns (CONDAP). In the current paper, we extend the existing CONDAP measure for assessing consistency in designs with more than two successive A-B elements (e.g., A-B-A-B-A-B), multiple baseline designs, and changing criterion designs. We illustrate each quantification with published research.

The current article presents a systematic review of consistency in single-case ABAB phase designs. We applied the CONsistency of DAta Patterns (CONDAP) measure to a sample of 460 data sets retrieved from 119 applied studies published over the past 50 years. The main purpose was to (a) identify typical CONDAP values found in published ABAB designs and (b) develop interpretational guidelines for CONDAP to be used for future studies to assess the consistency of data patterns from similar phases. The overall distribution of CONDAP values is right-skewed with several extreme values to the right of the center of the distribution. The B-phase CONDAP values fall within a narrower range than the A-phase CONDAP values. Based on the cumulative distribution of CONDAP values, we offer the following interpretational guidelines in terms of consistency: very high, 0 ≤ CONDAP ≤ 0.5; high, 0.5 < CONDAP ≤ 1; medium, 1 < CONDAP < 1.5; low, 1.5 < CONDAP ≤ 2; very low, CONDAP > 2. We give examples of combining CONDAP benchmarks with visual analysis of single-case ABAB phase designs and conclude that the majority of data patterns (41.2%) in published ABAB phase designs is medium consistent.