Investigation of attributional patterns for moods in the menstrual cycle

dc.contributor.authorDing, Johanna Mai
dc.date.accessioned2022-03-28T19:26:13Z
dc.date.available2022-03-28T19:26:13Z
dc.date.issued1993en
dc.description.abstractIn this replication study, 40 women who experienced regular menstrual cycles and did not use oral contraception read passages , that were manipulated across three independent variables, mood state (positive or negative), menstrual cycle phase (premenstrual or intermenstrual), and events of the environment (pleasant or unpleasant). causal ascriptions for mood state were assessed on the 4-Attributional Dimensions Scale. Self-reports of menstrual symptomatology were obtained using the Menstrual Distress Questionnaire. Attitudes toward menstruation were assessed on the Menstrual Attitude Questionnaire. The attributional data replicated past research. Negative moods (but not positive ones) occurring premenstrually were more often attributed to internal causes. Stronger internal attributions were made when mood was inappropriate to the situation, with stronger external attributions for moods appropriate to the situation. Attitude data suggest menstruation is multidimensional, with negative and positive aspects occurring concurrently. Comparisons between the MDQ and MAQ were conducted, as well as their relation to attributions. A conceptualisation of menstrual symptoms and attributional patterns from a social cognition perspective is presented.en
dc.identifier.urihttps://hdl.handle.net/10092/103502
dc.identifier.urihttp://dx.doi.org/10.26021/12603
dc.languageEnglish
dc.language.isoenen
dc.rightsAll Rights Reserveden
dc.rights.urihttps://canterbury.libguides.com/rights/thesesen
dc.subjectMenstrual cycle--Psychological aspectsen
dc.subjectMood (Psychology)en
dc.titleInvestigation of attributional patterns for moods in the menstrual cycleen
dc.typeTheses / Dissertationsen
thesis.degree.disciplinePsychologyen
thesis.degree.grantorUniversity of Canterburyen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Scienceen
uc.bibnumber429320en
uc.collegeFaculty of Scienceen
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