Sentiment analysis is the automated coding of emotions expressed in text. Sentiment analysis and other types of analyses focusing on the automatic coding of textual documents are increasingly popular in psychology and computer science. However, the potential of treating automatically coded text collected with regular sampling intervals as a signal is currently overlooked. We use the phrase \"text as signal\" to refer to the application of signal processing techniques to coded textual documents sampled with regularity. In order to illustrate the potential of treating text as signal, we introduce the reader to a variety of such techniques in a tutorial with two case studies in the realm of social media analysis. First, we apply finite response impulse filtering to emotion-coded tweets posted during the US Election Week of 2020 and discuss the visualization of the resulting variation in the filtered signal. We use changepoint detection to highlight the important changes in the emotional signals. Then we examine data interpolation, analysis of periodicity via the fast Fourier transform (FFT), and FFT filtering to personal value-coded tweets from November 2019 to October 2020 and link the variation in the filtered signal to some of the epoch-defining events occurring during this period. Finally, we use block bootstrapping to estimate the variability/uncertainty in the resulting filtered signals. After working through the tutorial, the readers will understand the basics of signal processing to analyze regularly sampled coded text.

This case study describes one client\'s progression through goal-focused positive psychotherapy (GFPP), a positive psychology inspired treatment. The study aims to contribute a more nuanced understanding of GFPP by illustrating the clinical use of approach goals, hope, positive emotion, and client strengths-interventions that constitute the heart of GFPP.
The case study methodology illuminates the 33-session treatment of a self-identified European-American heterosexual female in her mid-twenties, presenting with several interpersonal concerns, and symptoms of depression and anxiety. The client met the DSM 5 criteria for generalized anxiety disorder and borderline personality disorder.
Processes and outcomes are documented through clinician and client perceptions, and weekly assessments of symptomatology and subjective well-being.
The case study demonstrates a successful application of positive psychology consistent with GFPP\'s existential and humanistic psychology roots. The study should provide clinicians and theorists a greater understanding of GFPP processes and perspectives in an applied context.

Healthcare management is one practical tool for mediation and implementation of public health into clinical healthcare outcomes and is taken in our case study as an exemplar arena to demonstrate the vital importance of the person-centered approach. Healthcare personnel are frequently at risk for the \'burn-out\' syndrome. However, modern measures of burn-out recognize burn-out only at a late stage when it is fully developed. There are no available methods to assess the risk for vulnerability to burnout in healthcare systems. Our aim was therefore to design a complex person-centered model for detection of high risk for burn-out at an early stage, that has been termed \'flame-out\'. We accept the observation that decreased personal performance is one crucial expression of burn-out. Low personal performance and negative emotions are strongly related to low self-directedness as measured by the Temperament and Character Inventory (TCI). At the same time, burn-out is characterized by decreased interest and positive emotions from work. Decreased positive emotion is directly related to low self-transcendence as measured by the TCI. Burn-out is also frequently associated with feelings of social alienation or inadequacy of support, which is in turn related to low TCI Cooperativeness. However, high Persistence and Harm Avoidance are predisposing traits for burn-out in healthcare professionals who are often overly perfectionistic and compulsive, predisposing them to anxiety, depression, suicide and burn-out. Hence, people at risk for future burn-out are often highly conscientious over-achievers with intense mixtures of positive and negative emotions. The high demand for perfection comes from both intrinsic characteristics and from features of the social milieu in their psychological climate. Letting go of the unfulfillable desire to be perfect by increasing self-transcendence allows acceptance of the imperfection of the human condition, thereby preventing burn-out and other negative emotions while promoting positive emotions and work in the service of others. Hence, we can evaluate vulnerable populations via a person-centered diagnostic method using the TCI and also relate wellbeing to the psychological climate of the work place. The proposed diathesis-stress model can directly impact on the management of human resources and related decision-making. The introduction of such person-centered assessments can encourage and improve public health outcomes by promoting the personal wellbeing of healthcare employees.