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1.
J Obstet Gynaecol Res ; 43(1): 100-105, 2017 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-27933738

RESUMO

AIM: The aim of the study was to examine the possibility of converting subjective textual data written in the free column space of the Mother and Child Handbook (MCH) into objective information using text mining and to compare any monthly changes in the words written by the mothers. METHODS: Pregnant women without complications (n = 60) were divided into two groups according to State-Trait Anxiety Inventory grade: low trait anxiety (group I, n = 39) and high trait anxiety (group II, n = 21). Exploratory analysis of the textual data from the MCH was conducted by text mining using the Word Miner software program. Using 1203 structural elements extracted after processing, a comparison of monthly changes in the words used in the mothers' comments was made between the two groups. The data was mainly analyzed by a correspondence analysis. RESULTS: The structural elements in groups I and II were divided into seven and six clusters, respectively, by cluster analysis. Correspondence analysis revealed clear monthly changes in the words used in the mothers' comments as the pregnancy progressed in group I, whereas the association was not clear in group II. CONCLUSION: The text mining method was useful for exploratory analysis of the textual data obtained from pregnant women, and the monthly change in the words used in the mothers' comments as pregnancy progressed differed according to their degree of unease.


Assuntos
Mineração de Dados/métodos , Registros de Saúde Pessoal , Mães/psicologia , Adulto , Ansiedade , Feminino , Humanos , Gravidez , Estudos Prospectivos , Adulto Jovem
2.
J Obstet Gynaecol Res ; 42(6): 655-60, 2016 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-26935788

RESUMO

AIM: The aim of the present study was to examine the possibility of screening apprehensive pregnant women and mothers at risk for post-partum depression from an analysis of the textual data in the Mother and Child Handbook by using the text-mining method. METHODS: Uncomplicated pregnant women (n = 58) were divided into two groups according to State-Trait Anxiety Inventory grade (high trait [group I, n = 21] and low trait [group II, n = 37]) or Edinburgh Postnatal Depression Scale score (high score [group III, n = 15] and low score [group IV, n = 43]). An exploratory analysis of the textual data from the Maternal and Child Handbook was conducted using the text-mining method with the Word Miner software program. A comparison of the 'structure elements' was made between the two groups. RESULTS: The number of structure elements extracted by separated words from text data was 20 004 and the number of structure elements with a threshold of 2 or more as an initial value was 1168. Fifteen key words related to maternal anxiety, and six key words related to post-partum depression were extracted. CONCLUSION: The text-mining method is useful for the exploratory analysis of textual data obtained from pregnant woman, and this screening method has been suggested to be useful for apprehensive pregnant women and mothers at risk for post-partum depression.


Assuntos
Mineração de Dados , Depressão Pós-Parto/diagnóstico , Comportamento Materno , Prontuários Médicos , Mães/psicologia , Adulto , Ansiedade/diagnóstico , Depressão/diagnóstico , Feminino , Humanos , Gravidez , Estudos Prospectivos , Escalas de Graduação Psiquiátrica , Adulto Jovem
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