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Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

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...
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Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

The Sense of Self: Reflected Self-Appraisal and Social Comparison

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...
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

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.
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Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
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Suicide and media reporting: a longitudinal and spatial analysis.

Albert C Yang1, Shih-Jen Tsai, Cheng-Hung Yang

  • 1Department of Psychiatry, Taipei Veterans General Hospital, No. 201, Sec. 2, Shipai Road, Beitou District, Taipei, 11217, Taiwan, Republic of China. accyang@gmail.com

Social Psychiatry and Psychiatric Epidemiology
|August 11, 2012
PubMed
Summary

Media reports on suicide can influence copycat suicides, with effects varying by event type and location. Competitive reporting of minor suicide events should be avoided to mitigate potential delayed impacts.

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Area of Science:

  • Public Health
  • Media Studies
  • Epidemiology

Background:

  • Media reporting of suicide, particularly celebrity suicides, is known to influence suicide rates.
  • Limited understanding exists regarding the long-term spatial and temporal dynamics between suicide deaths and media coverage.

Purpose of the Study:

  • To investigate the longitudinal and spatial associations between suicide deaths and suicide news reporting.
  • To analyze the impact of media reporting on suicide over an extended period.

Main Methods:

  • Utilized data on 31,364 suicides in Taiwan from 2003-2010.
  • Retrieved suicide news from Google News and all available Taiwanese media.
  • Employed empirical mode decomposition and time-dependent intrinsic correlation to analyze temporal relationships.

Main Results:

  • Suicide news synchronized with increased suicide deaths during major events (e.g., celebrity deaths).
  • A one-month lag in association was observed during non-celebrity periods.
  • Charcoal burning suicide reports showed a specific copycat effect, while jumping reports had broader associations.
  • Media reports correlated more strongly with suicides in urban than rural areas.

Conclusions:

  • A delayed copycat suicide effect may be associated with media reports of minor suicide events.
  • Media professionals should avoid competitive reporting of minor suicide incidents.
  • Findings highlight the need for responsible media practices in suicide reporting.