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The goal of a thorough risk assessment is to learn about the circumstances of an individual person with regard to suicide, including warning signs, risk factors, and protective factors. [1] Risk for suicide is re-evaluated throughout the course of care to assess the patient's response to personal situational changes and clinical interventions.
Conversely, a Risk factor will increase the chances of a negative health outcome occurring. Just as statistical correlations and regressions can examine how a range of independent variables impact a dependent variable, we can examine how many Protective and Risk factors contribute to the likelihood of an illness occurring.
The SPF consists of twenty-four statements for which individuals are asked to rate the degree to which each statement describes them. The SPF assesses a wider range of protective factors than other scales. The SPF is the only measure that has been shown to assess social and cognitive protective factors. [2]
Suicide prevention is a term used for the collective efforts to reduce the incidence of suicide through preventive measures. Protective factors for suicide include support, and access to therapy. [61] About 60% of people with suicidal thoughts do not seek help. [173]
Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population.. It is a cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare.
Suicide prevention strategies focus on reducing the risk factors and intervening strategically to reduce the level of risk. Risk and protective factors unique to the individual can be assessed by a qualified mental health professional. Suicide prevention measures suggested by the CDC [95] Some of the specific strategies used to address are:
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In this way, investigators can eventually use the data to answer many questions about the associations between "risk factors" and disease outcomes. For example, one could identify smokers and non-smokers at baseline and compare their subsequent incidence of developing heart disease.