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- Cross-cultural adaptation and psychometric evaluation of the Portuguese version of the family resilience questionnaire – short form (FaRE-SF-P) in women with breast cancerPublication . Almeida, Sílvia; Rodrigues da Silva, Daniel; Frasquilho, Diana; Costa, Beatriz; Sousa, Berta; Baptista, Telmo Mourinho; Grácio, Jaime; Lemos, Raquel; Oliveira-Maia, Albino J.Background: A diagnosis of cancer, and the resulting treatment process, can be perceived as a life-threatening event, affecting not only patients but also their social network and, more specifically, their relatives. While the ability to cope and adjust to difficult health situations may be challenging, family resilience may optimize a positive adaptation to adversity and contribute to enhance the patient’s quality of life. The Family Resilience Questionnaire (FaRE) is a self-report measure of family resilience that assesses this construct systematically. We aimed to validate the Portuguese version of a short form of the FaRE (FaRE-SF-P) in a sample of women with breast cancer. Methods: 147 women recently diagnosed with early breast cancer were recruited at the Champalimaud Clinical Centre in Lisbon. Participants completed psychometric assessment including the Portuguese version of the FaRE-SF-P, composed by two subscales of the original version – the FaRE Perceived Family Coping (FaRE-PFC) and the FaRE Communication and Cohesion (FaRE-CC). Confirmatory factor analysis (CFA) was performed to assess the factor structure of the FaRE-SF-P. Construct validity was assessed using the Hospital Anxiety and Depression Scale (HADS) for divergent validity, and the Modified Medical Outcomes Study Social Support Survey (mMOSSS) as well as the social functioning subscale from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) for convergent validity. Results: The CFA results confirmed a correlated two-factor structure model consistent with the Perceived Family Coping and the Communication and Cohesion subscales. Internal consistency reliability indicated good values both for Perceived Family Coping and Communication and Cohesion subscales. The results for construct validity showed acceptable convergent and divergent validity. Discussion: The FaRE-SF-P showed good psychometric properties demonstrating to be a valid and reliable family resilience measure to use in Portuguese women diagnosed with breast cancer. Since FaRE-SF-P is a short instrument it may be a useful screening tool in an oncological clinical practice routine
- Well‐being trajectories in breast cancer and their predictors: A machine‐learning approachPublication . Karademas, Evangelos; Mylona, Eugenia; Mazzocco, Ketti; Pat‐Horenczyk, Ruth; Sousa, Berta; Oliveira‐Maia, Albino J.; Oliveira, Jose; Roziner, Ilan; Stamatakos, Georgios; Cardoso, Fatima; Kondylakis, Haridimos; Kolokotroni, Eleni; Kourou, Konstantina; Lemos, Raquel; Manica, Isabel; Manikis, George; Marzorati, Chiara; Mattson, Johanna; Travado, Luzia; Tziraki‐Segal, Chariklia; Fotiadis, Dimitris; Poikonen‐Saksela, Paula; Simos, PanagiotisObjective:This study aimed to described istinct trajectories of anxiety/depression symptoms and overall health status/quality of life over a period of 18 months followinga breast cancer diagnosis,and identify the medical, socio-demographic,lifestyle, and psychologica lfactors that predict these trajectories.Methods:474 females (mean age=55.79 years) were enrolled in the first weeksafter surgery or biopsy. Data from seven assessmentpoints over 18 months, at 3-month intervals,were used. The two outcomeswere assessedat all points. Potential predictors were assessed at baseline and the first follow‐up. Machine‐ Learning techniques were used to detect latent patterns of change and identify the most important predictors. Results: Five trajectories were identified for each outcome: stably high, high with fluctuations, recovery, deteriorating/delayed response, and stably poor well‐being (chronic distress). Psychological factors (i.e., negative affect, coping, sense of control, social support), age, and a few medical variables (e.g., symptoms, immune‐ related inflammation) predicted patients' participation in the delayed response and the chronic distress trajectories versus all other trajectories. Conclusions: There is a strong possibility that resilience does not always reflect a stable response pattern, as there might be some interim fluctuations. The use of machine‐learning techniques provides a unique opportunity for the identification of illness trajectories and a shortlist of major bio/behavioral predictors. This will facilitate the development of early interventions to prevent a significant deterioration in patient well‐being