ArticleNewborn and infant nursing reviews : NAINR2010
Potential Pitfalls in Collecting and Analyzing Longitudinal Data from Chronically Ill Populations.
Article in Newborn and infant nursing reviews : NAINR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed, 3 citations in OpenAlex.
- Maternally administered interventions for preterm infants in the NICU: effects on maternal psychological distress and mother-infant relationship.Infant behavior & development · 2014Trial
- Supplement usage and doping attitudes in elite youth sports: The mediating role of dietary supplement acceptance.PloS one · 2024Article
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 at 1 institution in 1 country.
Funding
Abstract
Research on the prevention and management of chronic illnesses involves understanding changes in complex and interrelated aspects of each individual. To capture these changes or to control for them, nursing and health research needs to be longitudinal. However, there are a number of potential pitfalls in analyzing longitudinal data from a chronically ill population. This paper will examine four major pitfalls: selection of time points, measurement, choosing appropriate statistical procedures, and missing values. Although the frequency of data collection is often driven primarily by practical concerns, it will affect the results. In addition, outcome measures may capture different constructs at different points in times. Traditional analysis techniques often have assumptions about data characteristics that are violated in clinical populations. Missing values are common in research with chronically ill individuals because of problems of subject retention and because individuals have frequent medical complications. Solutions to these pitfalls are also discussed.
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.