Classification tree analysis of postal questionnaire data to identify risk of excessive gestational weight gain
Version 2 2024-06-04, 00:02
Version 1 2016-01-01, 00:00
journal contribution
posted on 2024-06-04, 00:02 authored by Matthew Fuller-TyszkiewiczMatthew Fuller-Tyszkiewicz, H Skouteris, B Hill, H Teede, S McPhieClassification tree analysis of postal questionnaire data to identify risk of excessive gestational weight gain
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Location
ScotlandLanguage
EnglishPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2016, ElsevierJournal
MidwiferyVolume
32Pagination
38-44ISSN
0266-6138eISSN
1532-3099Publisher
ELSEVIER SCI LTDUsage metrics
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Keywords
Science & TechnologyLife Sciences & BiomedicineNursingGestational weight gainPregnancyBMIClassification and regression tree analysisPsychosocial risk factorsSLEEP QUALITY INDEXBODY-MASS INDEXPOSTNATAL DEPRESSIONWOMENPREGNANCYHEALTHMODELSYMPTOMSOBESITYINTERVENTIONS170106 Health, Clinical and Counselling Psychology170110 Psychological Methodology, Design and Analysis111716 Preventive Medicine920408 Health Status (e.g. Indicators of Well-Being)School of Psychology4206 Public health5201 Applied and developmental psychology4204 Midwifery
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