Cargando…
Effect of internet-based counselling with a cognitive-behavioural approach on premenstrual syndrome
OBJECTIVES: To assess the effect of internet-based counselling with a cognitive-behavioural approach on symptom severity of women with premenstrual syndrome (PMS) and their quality of life during the perimenstrual and late follicular phases of the menstrual cycle. Moreover, the PMS-related disabilit...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558396/ https://www.ncbi.nlm.nih.gov/pubmed/36224664 http://dx.doi.org/10.1186/s13104-022-06222-w |
Sumario: | OBJECTIVES: To assess the effect of internet-based counselling with a cognitive-behavioural approach on symptom severity of women with premenstrual syndrome (PMS) and their quality of life during the perimenstrual and late follicular phases of the menstrual cycle. Moreover, the PMS-related disability and attitude toward menstruation were investigated as secondary outcomes. DATA DESCRIPTION: We provide data generated in a randomized controlled trial with two-parallel arms carried out on 92 female university students aged 18–35 years who had moderate to severe PMS, residing at halls of the Tabriz University of Medical Sciences. PMS severity was assessed during two menstrual cycles before intervention (baseline) and during two cycles just after ending the two-month intervention using Daily Record of Severity of Problems (DRSP) and the quality of life using the Quality of Life Enjoyment and Satisfaction Questionnaire—Short Form (Q-LES-Q-SF) on days 1–2 and 11–13 of the menstrual cycle at the baseline and post-intervention. Also, the PMS-related disability was assessed using Sheehan Disability Scale (SDS) and attitude toward menstruation using Menstrual Attitude Questionnaire (MAQ) at the baseline and post-intervention. Participant satisfaction and views on intervention effectiveness were also assessed using a single Likert question. |
---|