在瑞典预期的退休年龄之前自愿提前退出工作生活的先例和经验

Jeffrey Arnett's concept of emerging adulthood offers a framework to understand the unique developmental stage between adolescence and full-fledged adulthood, generally from ages 18 to 25. This period is marked by extensive exploration and shifts in identity, relationships, and career choices, a process known in psychology as role experimentation. Emerging adulthood reflects the evolving cultural expectations surrounding adulthood and the dynamic process of personal transformation during...

Erik Erikson's theory of psychosocial development outlines a series of stages through which individuals progress across the lifespan. Each stage involves a psychosocial conflict that significantly influences personal growth and well-being. Three key stages — intimacy versus isolation, generativity versus stagnation, and integrity versus despair — highlight the developmental challenges faced in adulthood.
Intimacy Versus Isolation in Early Adulthood
Individuals in early...

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...

Overview

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.