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Banding the Ethical Boundaries: How can observational research draw conclusions without random experimentation?
In the fields of epidemiology, social sciences, psychology and statistics, observational research can usually be inferred from the sample to the entire population. In such research, independent variables are not under the control of the researcher. This is mainly based on ethical considerations or practical limitations.A common example of observational research is to explore the potential impact of a certain treatment on the subject, but in such studies, the process of assignment of subjects to the treatment or control group is usually not controlled by the investigator.This is very different from the experimental method of randomized controlled trials such as randomized assignment of subjects to the treatment group or control group.Observational research with random allocation is not possible, and naturally faces the various challenges brought by inferential analysis.
The ethical and practical difficulties that researchers usually face have to turn to observational research to obtain precious health and social data.
Motivation
Why are independent variables uncontrollable?There are many reasons.For example, conducting random experiments may violate ethical standards.Assuming that we want to study the association between artificial abortion and breast cancer, this hypothesis believes that there is a causal relationship between the incidence of miscarriage and breast cancer in Sichuan.In hypothetical control experiments, researchers needed to randomly divide a large number of pregnant women into treatment groups that received miscarriage and control groups that did not undergo miscarriage, and then perform regular cancer screening on the two groups.However, such experiments are obviously contrary to general ethical principles, and there are deviations caused by various confusing factors.
In addition, the implementation of certain random experiments may also become impractical due to their high difficulty.For example, if you want to study the association between a drug and a group of very rare symptoms, random allocation will also seem unrealistic to consider rarity.Enough participants may not be found so that the symptom is manifested in the participants receiving treatment.In such cases, researchers usually start with participants who have preexisting symptoms and look back to those who have received the drug and subsequently develop the symptoms.
While observational studies cannot make absolutely factual statements, they can still provide information on the use of the "real world" and help form hypotheses.
Types of observational research
Observative studies can be classified into several different types, including case-control studies, cross-sectional studies, and longitudinal studies.Case-controlled studies originated from epidemiology, where comparisons were conducted between two existing populations to confirm certain hypothetical causal properties.Cross-sectional research is a method of collecting data at specific time points, while longitudinal research involves long-term repeated observations of the same variable.Each of these studies may provide different insights, but also raise different challenges and problems.
The effectiveness and reliability of observational research
Although observational research results cannot be used as clear criterion of facts, they can still provide important information and insights in real-world applications.According to the 2014 Cochrane review, the results of observational studies showed similar effects to randomized controlled trials. These differences may not be significant if factors such as subject population, comparison subjects, data heterogeneity and results are considered.
However, the challenge of performing observational studies is how to eliminate the obvious bias effects and evaluate the role of potentially hidden biases.
Prevention and remedy
Observational studies have potential risks of various biases compared to randomized trials.There may be bias in the investigator's ability to observe, which may lead to unintentional search for the desired information.For example, researchers may exaggerate the impact of one variable, or underestimate the impact of another variable.This bias can occur at any stage in the research process, thereby introducing systematic error measurements.
To minimize these difficulties, using methods such as matching, considering multiple comparison biases, and avoiding omitting variable biases has become problems that researchers today need to face and solve.As technology continues to evolve, researchers are also constantly looking for new methods of data analysis to improve the effectiveness of observational research.
In summary, observational research allows us to discover and confirm various health and social phenomena without our control, but as such research expands, how can we balance the boundary between results and ethics? ?
