Browsing by Subject "ahdistuneisuus"

This review will address how individual symptomology may be used to model a person’s psychological disorder. The discussed disorders are depression, generalised anxiety disorder and social anxiety disorder, which will be discussed separately and as simultaneous compositions of symptoms. Traditionally mental health disorders have been elucidated by dividing them into separate categories. In 2010s network analysis has risen as an alternative method, where the relationship between symptoms is examined in time and visualised as a network. The network analysis viewpoint suggests that psychological symptoms cause each other and that activation spreads through the network via the interactions between those symptoms. Two disorders that occur simultaneously are thought to constitute separate clusters of symptoms, which are united by bridge symptoms that mediate activation from one cluster to another. This review will focus particularly on idiographic, personalised networks. These personalised models aspire to take into consideration all the variation in a person’s symptomology. These models are formulated from occurring symptoms in several points in time, so it is possible to speculate, although not prove, the direction of an interaction between symptoms. The symptoms that affect several other symptoms strongly spread activation all around them when activated, whereas those symptoms that receive several effects from other symptoms particularly often associate with other symptoms. The application of network models to clinical practice is based on this idea. To demonstrate idiographic modelling, two different cases will be considered. In both examples the person is afflicted with both depression and an anxiety disorder, and for each person an idiographic network model is formed. The observation can be made from these cases that the symptoms described as most central in categorical models are not equal to the symptoms in these networks that most maintain its activation. The idiographic networks of the example cases also do not indicate bridge symptoms, but rather the symptoms form a single cluster and maintain each other across disorder category boundaries. The conclusions made from personalised network analyses cannot be generalised to the population or even the same person in other points in time. In addition, conclusions cannot be made about the validity of DSM categories or the concept of comorbidity. Nevertheless, they open windows to the individual variation and complexity of symptomology, which categorical diagnostic classifications cannot consider. From these observations different study questions and designs can be formulated and novel clinical interventions developed.

This literature review focuses on the diagnostic criteria for selective mutism and its treatment. Selective mutism occurs in 0.3-1 % of the population. Its key features are anxiety and a consistent failure to speak in certain social situations despite speaking in others. The duration of the disturbance is at least one month. In the ICD-10 disease classification it is categorized as a disorder of social functioning with onset specific to childhood and adolescence. In the DSM-5 classification selective mutism is categorized as an anxiety disorder. Its comorbidity with other anxiety disorders, especially social phobia, is high. There are no international treatment recommendations for selective mutism, but individually designed cognitive-behavioral psychotherapy is preferred. If psychotherapy is insufficient, selective serotonin reuptake inhibitor fluoxetine may be considered. It is important to identify selective mutism as it has a major impact on one’s quality of life and ability to function. It also causes social disadvantages and weakens academic capacity and self-esteem. Sometimes selective mutism is interpreted as extreme shyness and the disorder remains undiagnosed. Increasing awareness of selective mutism among those working with the young and families is important in order to identify the disorder and start appropriate treatment as early as possible. Early treatment is important because it can improve the prognosis and reduce the human suffering caused by the disorder.

Tavoitteet: Ahdistuneisuushäiriöt ovat yleisiä mielenterveyden häiriöitä, joiden ydinoireena on liiallinen pelko tai ahdistus. On esitetty, että yksi ahdistusoireiden kehittymistä selittävä ja oireita ylläpitävä tekijä on toimimaton tunnesäätely. Ahdistuneisuushäiriöihin liittyy usein myös samanaikaisia uniongelmia, ja on mahdollista, että kyky säädellä tunnereaktioita tarkoituksenmukaisesti välittyy unen kautta. Aiemmissa tutkimuksissa erityisesti REM-uni on liitetty tunnetiedon käsittelyyn, mutta sen tarkemmista vaikutuksista tunnesäätelyyn tiedetään vähemmän. Tämän kandidaatintutkielman tavoitteena oli selvittää, liittyykö ahdistuneisuushäiriöihin REM-unen muutoksia, ja miten REM-uni tunnesäätelyyn vaikuttaa. Menetelmät: Kirjallisuuskatsauksen lähdemateriaali haettiin PubMed-, APA PsychINFO- ja Google Scholar -tietokannoista hakutermejä ”REM sleep”, ”paradoxical sleep” ja ”polysomnography”, ”anxiety disorder”, ”panic disorder” ja ”phobia” sekä ”emotion regulation”, ”emotion management”, ”emotion control”, ”reappraisal”, ”distraction”, ”suppression” ja ”emotional reactivity”. Tulokset ja johtopäätökset: Kirjallisuuskatsauksen perusteella ainakin yleistyneeseen ahdistuneisuushäiriöön ja paniikkihäiriöön saattaa liittyä REM-unen poikkeavuuksia. Lisäksi on jonkin verran näyttöä siitä, että REM-uni on yhteydessä tunnereaktiivisuuteen ja -säätelyyn, joskin tämän yhteyden yleistyminen ahdistuneisuushäiriöihin on toistaiseksi epäselvää. Tarkempaa tutkimusta unen muutoksista eri ahdistuneisuushäiriöissä sekä REM-unen tunnesäätelyvaikutuksista tarvitaan. Yksi mahdollinen hypoteesi REM-unen, ahdistuneisuuden ja tunnesäätelyn vuorovaikutuksesta on, että REM-unen häiriintyminen voimistaa tunnereaktiivisuutta ja hankaloittaa tunnesäätelyä, mikä edelleen lisää ahdistusta ja voi lopulta johtaa ahdistuneisuushäiriön kehittymiseen. Tieto ahdistuneisuushäiriöiden taustamekanismeista on tärkeää, jotta häiriöitä osattaisiin nykyistä paremmin ennaltaehkäistä ja hoitaa.