Influence of sex, age, and education on mood profile clusters

• Published in: PloS one Vol. 16; no. 2; p. e0245341
• Main Authors: Terry, Peter C, Parsons-Smith, Renée L, King, Rachel, Terry, Victoria R
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 02-02-2021; Public Library of Science (PLoS)
• Subjects: Adolescents; Age; Anxiety; Athletes; Biology and Life Sciences; Catalysts; Computer programs; Data analysis; Decision making; Demographic aspects; Drafting software; Eating disorders; Editing; Education; Emotions; Identification and classification; Injury prevention; Life Sciences; Medical research; Medicine and Health Sciences; Mental depression; Mental disorders; Mental health; Military personnel; Military psychology; Mood; Mood (Psychology); Moods; Nursing; Overtraining; People and Places; Population; Post traumatic stress disorder; Posttraumatic stress disorder; Psychological factors; Psychological stress; Quantitative psychology; Rehabilitation; Research ethics; Risk; Social Sciences; Software; Standard scores; Suicide; Australia; Queensland Australia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0245341

In the area of mood profiling, six distinct profiles are reported in the literature, termed the iceberg, inverse iceberg, inverse Everest, shark fin, surface, and submerged profiles. We investigated if the prevalence of the six mood profiles varied by sex, age, and education among a large heterogeneous sample. The Brunel Mood Scale (BRUMS) was completed via the In The Mood website by 15,692 participants. A seeded k-means cluster analysis was used to confirm the six profiles, and discriminant function analysis was used to validate cluster classifications. Significant variations in the prevalence of mood profiles by sex, age, and education status were confirmed. For example, females more frequently reported negative mood profiles than males, and older and more highly educated participants had a higher prevalence of the iceberg profile than their younger and lesser educated counterparts. Findings suggest that refinement of the existing tables of normative data for the BRUMS should be considered.