OBJECTIVITY, RELIABILITY, VALIDITY, GENERALIZABILITY

Achieving sample randomisation in a study is essential for ensuring that the sample accurately reflects the parent population and that the findings are generalisable. Without randomisation, it can be challenging for researchers to match participants based on critical traits that could impact the study's outcomes. Even with systematic and protocolised procedures in place, external factors can still influence the results of experiments with humans, especially in longitudinal research designs.

Challenges to validity, both internal and external, as well as the Hawthorne effect, pose limitations to experimental research. Participants may alter their behaviour simply because they are observed, prompting researchers to adopt a 'double-blind' technique. Additionally, reliable, and validated outcome measures are crucial for meaningful results. Quantitative research designs can contribute significantly to the evidence base, while descriptive and correlational designs are essential for generating questions and hypotheses. Despite rigorous procedures to control error and bias, ethical and methodological concerns remain for experimental research.

A sound research design aims to reduce bias and increase the dependability of the data gathered and analysed. The design that produces the least experimental error is typically considered the optimal approach in scientific inquiry. Likewise, a suitable and effective design results in the acquisition of comprehensive information and enables consideration of various facets of a given problem. The traits of a robust research design include:

• Accuracy is crucial regarding the methods used to collect data and evaluate responses. To ensure Objectivity, it is essential to implement unbiased measuring tools that deliver consistent results, regardless of who performs the evaluation.
• Reliability, in turn, refers to the degree of consistency in responses obtained from multiple measurements. Essentially, if a participant offers a specific response to a particular question, they are expected to provide the same response if the question is posed again. Any fluctuations in their answers may weaken the Reliability of the data gathered. As such, researchers must design their surveys to ensure Reliability and consistency in the responses obtained.
• Quantitative Research Design faces a significant obstacle in accurately measuring intended variables. The validity of a measuring device or instrument must be deemed valid by measuring only what it intends to, and this quality can be demonstrated. For example, an IQ test should only measure intelligence and use appropriately framed questions. To estimate the validity of measures, including facial, convergent, discriminant, and predictive validity, agreement with available literature and quantitative analyses of consistency and available predictions are necessary despite the constantly evolving nature of measures.
• Generalizability refers to applying data collected from a sample to a larger population. It is crucial to design the research study carefully to ensure that a researcher's findings can be generalized. This involves accurately defining the population, selecting an appropriate sample, conducting proper statistical analysis, and ensuring that the study's conclusions can be applied to the population.

Sufficient information is essential to analyse the research problem from a broader perspective, create an effective research design, and identify important factors such as research objectives, methods for obtaining information, skilled human and financial resources availability, minimizing bias, and maximizing reliability and generalization. An ideal research design should be flexible, adaptable, efficient, and cost-effective.

The research design is the foundation for data collection and analysis. It outlines the methods and procedures for measuring and analysing data, allowing investigators to investigate research questions and establish the conditions for data collection and analysis so that the findings of a sample can be generalized to the larger population  (Kuçuksayraç, 2007).