Academic literature on the topic 'Depression, Mental Depressed persons. Blacks'

Depression is a common but serious mood disorder that negatively affects how people think, feel, and function in their everyday life, and it can lead to other emotional and physical problems. This chapter provides a foundation for understanding depressed mood within the framework of integrative mental health nursing. Integrative mental health nursing is founded on the principles of whole-person, relationship-based care provided within the personal, lived context using a range of therapies to support the individual’s health and healing. Nursing approaches are exemplified in the chapter through a case study of an adolescent experiencing depression. Integrative nursing care for persons with depression is based on interventions that move from least intensive/invasive approaches to more, depending on need and context. Integrative nurses incorporate evidence-informed traditional and nontraditional approaches and can effectively promote wellbeing in persons with depressed moods.

Epidemiological data regarding chronic pain and psychiatric disorders are reviewed. Particular attention is given to the interplay between pain and depressive and anxiety disorders. In the general population, 19 to 33% of responders report chronic pain, with higher rates in elderly people. Major depression is one of the most common medical problems, affecting nearly 6% of the population, with a lifetime prevalence of 11 to 14%. The presence of depression in persons with chronic pain is significantly higher (21%) than that in the general population, and this proportion is even higher (52–85%) in specific populations of patients attending specialist clinics. Conversely, convincing evidence published in numerous studies has documented that at least 50% of depressed patients report painful symptoms. Pain exerts a negative effect on treatment and a poorer outcome in multiple domains of quality of life. Moreover, pain increases the economic burden resulting from depression. A close relationship between pain and depression has been established in the functional somatic syndromes of fibromyalgia and irritable bowel syndrome. An association between anxiety disorders and pain has also been documented. Epidemiological studies have provided evidence suggesting the common co-occurrence of pain and selected psychiatric disorders. This is an indication for practitioners to examine patients with pain for symptoms of depression and anxiety disorders and conversely to interview patients with psychiatric disorders in regard to the presence or absence of pain. These studies also provide the inspiration for further investigations of the intriguing shared biological basis or pain and psychiatric disorders.

Hundreds of studies reveal than most cases of depression remain undetected and untreated. Yet there is growing concern that efforts to increase detection of depression entail unacceptable numbers of persons who are not depressed nonetheless being given a diagnosis and receiving medication. What factors underlie false-positive and false-negative errors? How might clinicians and services address these detection errors? Only about half of primary care practitioners (PCPs) feel confident in diagnosing depression or assessing suicide risk. Yet the issue of underdetection is by no means confined to PCPs or to depression. Convincing data show that clinicians in all medical specialties have difficulty recognizing mental disorders. This includes depression, anxiety, and delirium and dementia. Less discussed in the literature but increasingly recognized as important is the issue of overdetection. In this chapter I will review the predictors of diagnostic errors (false positives and false negatives) with reference to depression in primary care. I will focus on two essential barriers to correct identification: communication and illness complexity. To meaningfully discuss errors in recognition, it is important to first establish baseline rates of depression. Prevalence exerts a powerful influence upon detection accuracy, not least because clinicians usually have a higher index of suspicion for high-risk patients. The World Health Organization (WHO) study on Psychological Problems in General Health Care (PPGHC), conducted across 14 countries, found that 26% of individuals visiting their PCP had at least one psychiatric disorder as defined by ICD-10 criteria. Fourteen percent had major depression. Almost identical rates were reported from the European Study of the Epidemiology of Mental Disorders (ESEMeD). If one examines depression in older people, the point prevalence of major depression is lower in rural than urban primary care practices (8.3% versus 14.8%). Further, if one combines a 14% rate of major depression with 10% who have minor depression, then the combined rate approaches 25%. Approximately 100 studies concerning the unassisted recognition rate of depression in primary care have been published, but only a third have used a robust semi-structured interview as a gold standard.

This chapter discusses the possible impact of micro-targeting in social media for health. For example, a hypothetical social media platform called InstaTwitBook had an algorithm that could accurately judge that a user was suicidal from changes in the language she communicated online. Then that site’s administrators could send this at-risk person a gentle message suggesting that she is showing warning signs of depression, or maybe even nudge her toward help by sending advertisements about local mental health counseling. What if 3,500 persons could be reliably identified and sent such messages this year, and that one in 100 messages would lead to care-seeking, averting 35 suicides? Would this not be worthwhile? And it is not just InstaTwitBook that has the power of detection. Phone companies may be able to tell from someone’s voice if he or she is depressed and use that information to identify who may benefit from mental health help. However, there are challenges that arise from this approach—challenges like inevitable inaccuracy, false-positive results, and the sending of notifications to persons who are not suicidal. As such, more research on this approach is needed, which would require social media companies to be more open to third-party investigators using their data.