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Although ageing itself does not lead to insomnia, changes in sleep architecture (the ‘typical’ physiological progression from wakefulness to deep sleep) and health status create a vulnerability to the development of insomnia, which can be precipitated by a trigger event. This review highlights some of the problems associated with insomnia in older people and offers insights into the possible approaches to stop insomnia from becoming a ‘rite of passage’. The main conclusion from this review however, is that sleep research focusing specifically on the ageing population is badly needed, alongside a unified diagnostic system and research structure (Leger, 2000). These findings are also discussed in relation to both healthcare policy and practice.

Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. The purpose of this paper is to explore the value of using the patient's own reasons for sleep disturbance.

Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self‐reported sleep problems were examined. Over two thirds (69.3 per cent) of respondents could identify a specific reason for their sleep problem with worry (37.9 per cent) and illness (20.1 per cent) representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons, as did the association with major correlates such as worry, depression, anxiety and poor health.

While prevalence surveys of “insomnia” or “poor sleep” often assume the identification of an underlying homogeneous construct, there may be grounds for recognising the existence of different sleep problem types, particularly in the context of the patient's perceived reason for the problem.

A typology based on reasons presents a different snapshot of the landscape of insomnia. Using patient's reasons to underpin a sleep nosology is an alternative way of sub‐dividing patients' symptoms which has some face validity given the “subjective” associations between reasons and symptoms.

The purpose of this paper is to assess and compare the knowledge and help-seeking behaviors toward depression among pharmacy students and non-pharmacy students.

The study was a cross-sectional descriptive survey and was carried out among undergraduate students of the oldest and largest university in Eastern Nigeria, the University of Nigeria, Nsukka. Open-ended questions were used to assess the participants’ recognition of depression and their preferred source of help for a vignette character. The open-ended responses were categorized based on the similarity of thematic content and presented as frequencies/percentages.

A total of 118 out of the 200 pharmacy students sampled responded (59 percent) and 270 students out of the 300 non-pharmacy students surveyed responded (90 percent). A significantly higher proportion of pharmacy students correctly labeled the vignette as depression (61.9 percent) compared to non-pharmacy students (39.6 percent) (χ²=16.57, p=<0.001). Psychologists were the most recommended source of help by both groups of students surveyed. A statistically significant greater proportion of pharmacy students recommended psychiatrists compared to non-pharmacy students (χ²=3.79, p=0.044). There was a significant association between academic level of study and ability to correctly label the vignette among pharmacy and non-pharmacy students [(χ²=18.08, p<0.001), (χ²=10.35, p=0.016)], respectively.

This is the first time the depression literacy of pharmacy students has been surveyed in an African country. The findings from this study are interesting in the context of current efforts to decrease the enormous treatment gap for depression by improving its recognition in community pharmacy settings.

The purpose of this study is to determine the mental health status and risk factors for the mental health of first-year university students on a health sciences campus.

This is a descriptive study. The research was conducted with first-year students in the health sciences, dentistry and medical faculties of a state university (n = 770). The data were collected with a sociodemographic questionnaire, the Risk Behavior of Young Adults Survey, the Bergen Insomnia Scale, General Health Questionnaire-28 and the Mental Health Improvement Scale. Body mass ındex was calculated.

Among the students, 53.7% experienced feelings of hopelessness in the last year and 1% had attempted suicide. The percentage of students found to be at risk in terms of mental health was 41.9%; 39.4% reported that they suffered from insomnia. It was found that those who had been subjected to bullying, felt hopelessness, had suicidal thoughts, planned to commit suicide and students who experienced sleeping problems were more at risk in terms of psychological issues (p < 0.01). Insomnia (β: 3.341) and smoking (β: 2.226) were identified as the strongest risk factors for mental health in first-year health sciences students (p < 0.005).

The results of the research offer an opportunity to get to know the characteristics of first-year university students who are at risk for mental health. It offers the opportunity to closely monitor and protect the mental health of students starting from the first grade.

In this study, it was determined that approximately half of the first-year university students were in the risk group in terms of mental health. Female gender, having a chronic illness, smoking a day or more in the past 30 days, not doing any physical activity, having a weak BMI, being bullied in the past 12 months, being cyberbullied in the past 12 months and having insomnia have been identified as risk factors that negatively affect mental health.

Depression and insomnia are very significant pathologies in cancer patients as they contribute to the patient's overall cure and quality of life. Moreover, untreated depression and ongoing insomnia are associated with decreased immune responses and lower survival rates. With all disease states and especially with cancer, close attention to drug-drug interactions and the potential impact on the efficacy of therapy is paramount. One area of particular interest due to the lack of well-done clinical trials is drug-drug interaction(s) between antidepressants and cancer treatment. Pharmacokinetics of a certain drug allows for prediction of certain drug interactions based on chemical properties of the agents involved. If the agents depend on their metabolites for activity, active drug level will be decreased through this enzyme inhibition. In this paper, we looked at the cytochrome-P450 drug interactions between antidepressants and sleep aids with Selective Estrogen Receptor Modulators (SERM). Newer SERM metabolisms are less influenced by interactions with medications used to treat depression. However, tamoxifen metabolism could be severely altered by several antidepressants. This has direct consequences as patients on tamoxifen and antidepressant can have double the risk of relapse to cancer in two years. We discussed those interactions and made recommendations for clinical use.

This chapter summarizes the knowledge on sleep and restitution. Sleep constitutes the recuperative process of the central nervous system. The use of the brain during wakefulness will lead to depletion of energy in the cortical areas locally responsible for activity. The level of depletion is monitored and sleep is initiated when critical levels are reached. The attempts to initiate sleep are perceived as sleepiness or fatigue. The ensuing sleep then actively restores brain physiology to normal levels. This also results in restored alertness, memory capacity, and mood. Also, peripheral anabolic processes (secretion of growth hormone and testosterone) are strongly enhanced and catabolic process (secretion of cortisol and catecholamines) are strongly suppressed. In the long run, reduced or impaired sleep leads to metabolic diseases, depression, burnout, and mortality. Stress and irregular hours are among the main causes of disturbed sleep.

This paper presents an approach for performing knowledge discovery in texts through qualitative and quantitative analyses of high‐level textual characteristics. Instead of applying mining techniques on attribute values, terms or keywords extracted from texts, the discovery process works over conceptss identified in texts. Concepts represent real world events and objects, and they help the user to understand ideas, trends, thoughts, opinions and intentions present in texts. The approach combines a quasi‐automatic categorisation task (for qualitative analysis) with a mining process (for quantitative analysis). The goal is to find new and useful knowledge inside a textual collection through the use of mining techniques applied over concepts (representing text content). In this paper, an application of the approach to medical records of a psychiatric hospital is presented. The approach helps physicians to extract knowledge about patients and diseases. This knowledge may be used for epidemiological studies, for training professionals and it may be also used to support physicians to diagnose and evaluate diseases.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

The purpose of this study is to identify the health information needs of senior online communities (SOCs) users, which could provide a basis for improving senior health information services.

A total of 14,933 health-related posts in the two most popular senior online communities (Yinling and Keai) in China are crawled as a corpus. Based on the results of word frequency analysis, text classification is performed based on two aspects: medical systems (Western medicine and traditional Chinese medicine) and topics. The health information needs of SOCs users are revealed from the composition, growth trends and popularity of health information. Finally, some key points of senior health information services are discussed.

The health information needs of senior users can be divided into four types: coping with aging, dietary nutrition, physical exercise and mental health. These needs are comprehensive and involve a variety of health issues. Users are mainly concerned with physical health issues. In terms of medical systems, the number of Western medicine posts is relatively larger, whereas traditional Chinese medicine appears more in posts on coping with aging and physical exercise. The health information needs of SOCs users are in a stable status. Both the medical systems and topics could have an impact on the popularity of health information, but the number of posts is inconsistent with the level of popularity.

This study combines multiple perspectives to identify the health information needs of seniors in China with a comprehensive overview.