Assessing the needs of patients with breast cancer and their families across various treatment phases using a Latent Dirichlet Allocation model: a text-mining approach to online health communities.

PURPOSE: This study aimed to assess the different needs of patients with breast cancer and their families in online health communities at different treatment phases using a Latent Dirichlet Allocation (LDA) model. METHODS: Using Python, breast cancer-related posts were collected from two online health communities: patient-to-patient and patient-to-doctor. After data cleaning, eligible posts were categorized based on the treatment phase. Subsequently, an LDA model identifying the distinct need-related topics for each phase of treatment, including data preprocessing and LDA topic modeling, was established. Additionally, the demographic and interactive features of the posts were manually analyzed. RESULTS: We collected 84,043 posts, of which 9504 posts were included after data cleaning. Early diagnosis and rehabilitation treatment phases had the highest and lowest number of posts, respectively. LDA identified 11 topics: three in the initial diagnosis phase and two in each of the remaining treatment phases. The topics included disease outcomes, diagnosis analysis, treatment information, and emotional support in the initial diagnosis phase; surgical options and outcomes, postoperative care, and treatment planning in the perioperative treatment phase; treatment options and costs, side effects management, and disease prognosis assessment in the non-operative treatment phase; diagnosis and treatment options, disease prognosis, and emotional support in the relapse and metastasis treatment phase; and follow-up and recurrence concerns, physical symptoms, and lifestyle adjustments in the rehabilitation treatment phase. CONCLUSION: The needs of patients with breast cancer and their families differ across various phases of cancer therapy. Therefore, specific information or emotional assistance should be tailored to each phase of treatment based on the unique needs of patients and their families.

Competence in managing workplace violence among nursing interns: Application of latent class analysis.

AIM: To identify subtypes of competence in managing workplace violence (WPV) among nursing interns and to assess between-group differences. BACKGROUND: Nursing interns are reported to be a vulnerable population for experiencing workplace violence during their clinical placement. Although WPV could have a negative impact on nursing interns' health and attitudes towards the nursing profession, little is known about nursing interns' competence in workplace violence management or its influencing factors. DESIGN: A cross-sectional study. METHODS: Between March to April 2023, nursing interns at three tertiary general hospitals in Anhui Province, China, completed questionnaires including a general information questionnaire, the Management of Workplace Violence Competence Scale (MWVCS), the Utrecht Work Engagement Scale (UWES-9), the Emotional Labour Scale for Nurses (ELSN) and were classified into subtypes by latent class analysis. Subsequently, univariate analysis and multivariate logistic regression were performed to identify the influencing factors by subtypes. RESULTS: A total of 264 questionnaires were valid and the overall mean age of the participants was 21.06 ±1.41 years. Four classes were identified: low competency group (15.5%), low cognition-low coping competency group (18.2%), low cognition-medium to high competency group (21.6%) and high competency group (44.7%). The results of multinomial logistic regression analysis showed that placement hospitals with a WPV management department, emotional control effort in profession dimension and emotional pretense by norms dimension in the Emotional Labour Scale for Nurses, pursuing further education and vigour dimension in the Utrecht Work Engagement Scale were influencing factors of the potential categories of WPV management competence. CONCLUSIONS: Four classes were identified and there was competence variability among nursing interns. More attention should be given to nursing interns who did not receive WPV-related training in their school or placement hospital.