Related Experiment Video
Updated: Jun 28, 2025
10:46
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
10.7K
Recognising inaccuracies in Australian suicide and 'hidden suicide' data
John Snowdon1,2
1Department of Psychogeriatrics, Concord Repatriation General Hospital, Concord, NSW, Australia; and.
Summary
Australian mortality statistics revisions reveal higher true suicide rates than initially reported. Annual updates to death data improve accuracy, uncovering previously misclassified suicides.
Area of Science:
- Mortality statistics analysis
- Public health surveillance
- Epidemiology
Background:
- Australian Bureau of Statistics releases preliminary and revised mortality data annually.
- Suicide and 'hidden suicide' rates are subject to revision over time.
Purpose of the Study:
- To assess the impact of annual revisions on Australian suicide and 'hidden suicide' statistics since 2007.
- To understand how data revisions affect the reported numbers and rates of suicide.
Main Methods:
- Tabulation of suicide and accidental/undetermined/unknown cause death numbers and rates.
- Analysis of data revisions occurring up to three years after initial release.
Main Results:
- Suicide and accidental drug poisoning death numbers are revised upwards, indicating higher true rates than initially reported.
- Rates for undetermined and unknown cause deaths are revised downwards, suggesting some suicides are initially misclassified.
Conclusions:
- Finalised Australian suicide data are more accurate due to annual revisions compared to countries without such processes.
- Further investigation, including psychological autopsies, could further increase reported suicide rates globally.
Keywords:
accidental drug poisoning deathsmisclassificationmortality statisticssuicideundetermined deathsMore Related Videos
Related Concept Videos
01:20Actuarial Approach
77
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
77
02:16Surveys
14.8K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
14.8K
01:15Assumptions of Survival Analysis
125
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.
125
01:09Censoring Survival Data
87
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
87
01:15Systematic Error: Methodological and Sampling Errors
1.5K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
1.5K
01:08The Availability Heuristic
6.0K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
6.0K