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

ABSTRACT: 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.

SUBMITTER: Terry PC

PROVIDER: S-EPMC7853457 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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

Terry Peter C PC Parsons-Smith Renée L RL King Rachel R Terry Victoria R VR

PloS one 20210202 2

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 fun ...[more]

PMID: 33529196

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Project description:Executive functions (EFs) develop over the period of early childhood and adolescence up until young adulthood. Individual children differ substantially in the pace at which their EFs develop, and characteristics such as sex and the level of parental education (LPE) are thought to contribute to these differences. In the present study, we assessed age-related changes in EFs as perceived and evaluated by teachers and parents as well as the influence of sex and LPE on their evaluations. We used a newly developed observer-report questionnaire, the Amsterdam Executive Function Inventory (AEFI). The AEFI assesses three important components of the executive aspects of daily life behavior in 13 questions: Attention; Self-control and Self-monitoring; and Planning and Initiative taking. Teachers and parents evaluated these aspects of executive functioning in 186 schoolchildren in grades 3-6 (age: 9-12 years). Age effects within grades and differences in social economic status between the four participating schools were controlled. Results showed a significant increase in teacher-perceived EFs from third to fourth grades and from fifth to sixth grades. This development was influenced both by the sex of the child and by the LPE. As perceived by teachers, the component self-control and self-monitoring was higher for girls than for boys, and planning abilities were higher for children from families with a higher LPE. Additional analyses showed that there is a systematic and statistically significant difference between the evaluations of the teachers and that of parents. Parents reported higher scores for planning, whereas teachers reported higher scores for self-control and self-monitoring. Evaluations by parents and teachers were different for girls, but not for boys. These findings are important because they imply that the development of EFs as perceived by parents and teachers is influenced by child-related factors. Second, there are clear differences in evaluations between teachers and parents. The AEFI appears to be a tool that is easily used by parents and teachers and shows potential for monitoring the development of EFs as perceived by significant others during young adolescence.

Dataset Information

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

Publications

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

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