It's common for infants to be unsettled, especially in the first few months of life. While this is often normal, persistent symptoms can be stressful for families. Parents naturally seek explanations, and common suspected causes include colic, reflux, eczema, and cow's milk allergy (CMA). However, CMA is frequently over diagnosed, which can lead to unnecessary changes such as stopping breastfeeding or switching to expensive specialist formulas. To address this, we've developed an online questionnaire to help track and understand symptoms in unsettled infants. Our long-term goal is to use this tool to support more accurate diagnosis of CMA. Before that, we need to test and validate the questionnaire in a general population of infants, including those who are healthy and those with other temporary conditions like a recent immunisation or teething. This study involves an anonymous online survey for parents of babies under 12 months old. We aim to collect data from approximately 350 participants. The study will help us assess how well the questionnaire reflects the severity of symptoms and whether it can distinguish between healthy infants and those with underlying issues. Parents will be invited to take part using flyers with a QR code distributed in various healthcare settings, including GP clinics and children's clinics in hospital. The survey is anonymous and hosted on a secure platform. While we don't anticipate the questions to be distressing, we recognise some may touch on sensitive topics. Support resources and study team contact details will be provided. By validating this tool, we hope to improve how unsettled behaviour in infants is assessed-reducing unnecessary interventions and better supporting families and healthcare professionals.
Study Type
OBSERVATIONAL
Enrollment
350
Unsettled Infant Questionaire (UnIQue)
University Hospitals Southampton NHS Foundation Trust
Southampton, United Kingdom
Validation of the questionnaire by assessment of construct validity
1. Review scoring for each item and maximum and minimum overall score 2. Check internal consistency with the Cronbach alpha statistic assuming latent variables based on organ systems, reviewing the contribution of each item 3. For each item undertake factor analysis using principal component analysis and correlation matrices selecting factors based upon Eigen value \> 1. 4. Identify which items map to each factor using a component matrix 5. Explore construct validity of UnIQue in its correlation to the overall VAS ite
Time frame: Questionnaire reviews symptoms in last week
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