ArticlePsychological assessment2022
shinyDLRs: A dashboard to facilitate derivation of diagnostic likelihood ratios.
Article in Psychological assessment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Evolution of Colorectal Cancer Trends and Treatment Outcomes: A Comprehensive Retrospective Analysis (2019-2023) in West Kazakhstan.Asian Pacific journal of cancer prevention : APJCP · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Despite increased recognition of the importance of evidence-based assessment in clinical psychology, utilization of gold-standard practices remains low, including during diagnostic assessments. One avenue to streamline evidence-based diagnostic assessment is to increase the use of diagnostic likelihood ratios (DLRs), derived from receiver operating characteristic curve analyses. DLRs allow for the adjustment of the likelihood that an individual has a disorder based on self-report data (e.g., questionnaires, psychosocial, family history). Although DLRs provide strong and readily implementable psychometric data to guide diagnostic decision-making, analyses necessary to derive DLRs are not commonplace in psychological curriculum and available resources require familiarity with specialized statistical methodologies and software. We developed a free, researcher-oriented dashboard,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.