ArticleJournal of psychiatric and mental health nursing2025
Data Measurement, Instruments and Sampling.
Article in Journal of psychiatric and mental health nursing, 2025. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Quantitative Data Quality Assurance, Analysis and Presentation.Journal of psychiatric and mental health nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data measurement, instrument selection, and sampling are fundamental elements in quantitative research and data collection. Data measurement is the systematic assignment of numeric values or categories to variables to permit measurement with precision and accuracy. Instrument selection involves selecting the right tool or method to collect data effectively and accurately and ensure the reliability and validity of the data. Sampling is the process of selecting a subset of individuals or items from a larger population to best represent that population, free of bias and generalizable. Understanding these key terms ensures that data collected is valid, reliable, and appropriate for future statistical analysis and interpretation.
Indexed as
Identifiers
What OpenQuestion holds
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.