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Background This study aims to investigate the self‐perception of symptoms, medical help seeking, and self‐help strategies of women with interstitial cystitis (IC). Methods A mixed method of qualitative and quantitative approaches was employed. The qualitative approach used in‐depth interviews about the subjective experience of symptoms, medical help seeking, and self‐help strategies for their IC. The quantitative inquiry was conducted by a yes or no response to the question “Did self‐perceived severe symptoms of IC interfere with your daily life?” A loglinear model was applied to investigate the associations between possible factors. Results This study recruited 68 women aged 20 to 69 years, of whom 22 were interviewed for qualitative data. About 72.1% of the women responded that self‐perceived severe IC symptoms interfered with their daily life. A significant negative association between employment and self‐perceived severe IC symptoms (P < .05) was observed. Qualitative results revealed three important themes: (1) bothersome symptoms—all‐day bladder pain and lower urinary tract symptoms and deteriorated quality of life, (2) medical help seeking—exhaustion and frustration, (3) self‐help strategies—coexisting with IC or feeling helpless. Conclusions IC women feel exhausted and frustrated by seeking medical attention for this incurable disease for a long time. IC women have troubled and uneasy daily lives. Being employed or engaging in activities can divert attention to alleviate symptoms. IC patient support groups allow patients to share their self‐help experiences with interdisciplinary medical teams to provide physical and psychological treatment.

One in four women is estimated to be diagnosed with breast cancer during her lifetime, making breast cancer the commonest cancer among women worldwide (Bray et al., 2018). In Vietnam, breast cancer accounts for 8.9% of new cancer cases among women each year (International Agency for Research on Cancer, 2012). In addition, most Vietnamese patients receive diagnosis at an extremely late stage (Thuan, Anh, Tu, & Huong, 2017). According to a study conducted at the five largest cancer hospitals in Vietnam, 49.5% of newly diagnosed breast cancer patients received diagnosis at stages III and IV (Thuan et al., 2017). Moreover, nearly half of Vietnamese patients with breast cancer resided in rural areas (Hoang Lan, Laohasiriwong, Stewart, Tung, & Coyte, 2013), where women have low levels of education and income and limited access to health care. Furthermore, a high proportion of breast cancer patients in Vietnam are relatively young, and one-third of patients are diagnosed at a younger age (Hoang Lan et al., 2013) than are patients in Western countries (Youlden, Cramb, Yip, & Baade, 2014) (40-49 versus 55-65 years). Evidence shows that early screening and access to optimal treatment can improve survival rates in patients with breast cancer

Damage detection is one of the primary purposes of structural health monitoring to inform catastrophic risks of structures right after extreme loadings such as earthquakes and hurricanes. In structural design codes, story drifts are considered as an indicator to estimate the damage states of structures. For instance, when the story drift ratios achieve 0.2-0.4%, light damage may be present in a building. In addition, the remaining stiffness ratios can also reveal the damage levels of a structure. Previous studies have shown that structural stiffness changes can affect the frequency responses of structures, for example, changing the locations of poles in frequency response functions. In this research, two multi-target neural network models are developed to concurrently estimate story drifts and remaining stiffness ratios using floor accelerations under seismic excitation. One of the multi-target neural network models focuses on developing a physics-guided loss function with a parallel model combination. Meanwhile, the other neural network model sequentially integrates two deep learning approaches by transfer learning. For example, the long short-term memory units estimate story drift responses from floor accelerations. Then, the short-time Fourier transform layers of floor accelerations yield the remaining stiffness ratio estimation. The proposed models are numerically investigated and experimentally verified. As a result, both models can estimate story drift and remaining stiffness ratio using the proposed neural network models.

Accessible Summary What is known about the subject? Poor recovery will cause harm to the quality of life and well‐being of residents and that the scope of influence includes the self, family and society. No study to date has investigated empowerment and the other multiple factors associated with personal recovery among psychiatric nursing home residents. What does the paper add to existing knowledge? The factors associated with personal recovery are empowerment, social support and global functioning. This pioneer study contributes new evidence that personal recovery is mainly predicted by empowerment, social support and global function, with empowerment exhibiting the highest predictive value. What are the implications for practice? Strengthening empowerment in mental health nursing may contribute more to the personal recovery of psychiatric nursing home residents than improving global function or social support. Mental health professionals should shift to empowerment‐oriented care to improve individuals' personal recovery, such as offering more opportunities to achieve autonomy, encouraging individuals' involvement in decision‐making and promoting individuals' motivation for achieving their goals. Abstract IntroductionIndividuals diagnosed with mental illness have a need for recovery. No study to date has investigated empowerment and the other multiple factors associated with personal recovery among psychiatric nursing home residents. AimThe study aimed to identify the factors associated with personal recovery among psychiatric nursing home residents. MethodsThis was a cross‐sectional study with convenience sampling. Participants were recruited from a psychiatric nursing home in Northern Taiwan between April and June 2018. Data were collected through self‐reported, structured questionnaires with verified reliability and validity. Descriptive and hierarchical regression analyses were performed. The present study followed the STROBE guidelines. ResultsThe study included 158 participants. The factors associated with recovery according to bivariate associations were religious belief, psychotic symptoms, global function, social support and empowerment. In the hierarchical regression, empowerment, social support and global function were the main predictive factors of recovery, with the explained variation reaching 40.8%. Empowerment exhibited the highest predictive value for the recovery. Implications for clinical practiceStrengthening empowerment in mental health nursing may contribute more to the personal recovery of psychiatric nursing home residents than improving global function or social support.