For the evaluation of psychological processes in individuals, the scholars and specialists in the field of psychology usually use two types of research methods: qualitative and quantitative. While the qualitative methods allow the researchers to receive data related to the qualities of phenomena, the quantitative methods are meant to identify the extents of particular issues through the use of numerical data. These methods help the specialists to verify the theoretic and practical developments in the field of interest. The qualitative research assists in the understanding of the processes’ nature and helps to describe them, but the quantitative research methods provide a high level of the statistical indicators’ accuracy.
The purpose of this paper is the analysis of quantitative research methodology in the example of “Child maltreatment and children’s developmental trajectories in early to middle childhood” by Font and Berger. In their research, the authors evaluated the interrelations between childhood maltreatment and adverse outcomes in the cognitive and social-emotional development of individuals (Font & Berger, 2015, p. 536).
The analysis of the quantitative research design including study approach, sampling methods, and data collection tools will help to assess the efficiency of the given methodology in answering the formulated research question related to the identification of cause-effect relations between the variables of maltreatment and adverse developmental outcomes (Font & Berger, 2015, p. 536). The analysis of quantitative research will also help to comprehend the methodological characteristics that make the study conduction effective.
Quantitative Methodology Overview
The functional paradigm that is laid in the foundation of the quantitative methodology is based on the idea that reality is objective, and it provokes certain reactions in the individuals, who are also a part of this reality (Morgan & Smircich, 1980). The basis of the quantitative research is comprised of the calculations, the estimations of the particular phenomena, and the statistical analysis of the collected numerical indicators. It is considered that there is the objective truth about the particular processes, and this truth can be evaluated and scientifically explained by the application of quantitative methods that support the generalization and detection of the cause-effect relationships between the phenomena of the objective reality.
The quantitative research is deductive and is conducted according to the principle of scientific hypothesis formulation and its consequent empirical verification through the data collection. The possibility of result biasing influenced by the researchers’ characteristics and the suggested interpretation is reduced to a minimum. In quantitative research, a psychologist has an opportunity to assess the psychological processes as a specific and tangible phenomenon and analyze it from the side and without direct contact.
Font and Berger (2015) used the longitudinal cohort study approach. According to the recent estimations, nearly one million children are exposed to victimization through maltreatment, and it is observed that the maltreated individuals frequently experience the developmental problems while they are growing up (Font & Berger, 2015, p. 536). Since the psychological, cognitive, and emotional aspects of development are deeply interrelated, the negative experiences and their adverse effects on the psychological state of individuals may be reflected in the social-emotional and cognitive impairments.
Through the assessment of a large cohort sample consisted of 4.898 children under the age of 9 throughout their development, the researchers aimed to find evidence for four hypotheses that were formulated based on the previous research findings.
Font and Berger (2015) revealed that there may be a direct link between the variables of childhood maltreatment and the adverse developmental outcomes; the interrelations between them may be characterized by the likelihood; the variable of maltreatment may have an influence only in combination with other negative social-economic factors, and the link between the variables may be associated with the “ongoing feedback loop” (p. 536). The researchers developed an extensive theoretical framework for the study conduction, and through the analysis of a large sample, they aimed to detect and characterize the dynamics of the relationships between the evaluated variables.
The longitudinal cohort study approach in combination with the accurate and detailed formulation of the scientific problem and the compliance with the precisely established research and assessment procedures helps to receive the objective results and check the accuracy of hypotheses. Other strengths of the quantitative research methods are the accurate identification of variables, the opportunity of conduction the repeated estimations and assessments, and the minimization of results subjectivity. All these factors ensure the credibility of the study findings. But on the other hand, the quantitative research format itself can provoke limitations because of the high level of accuracy in the formulation of objectives interferes with the ability to evaluate the phenomenon from other perspectives.
Sampling
The purpose of sampling in quantitative research is the assessment of the representative population and generalization of the study results to the population as a whole. Font and Berger (2015) used the data from the Fragile Families and Child Wellbeing Study (FFCW) consisting of the sample from twenty cities (p. 540). The sample includes 4.898 children from disadvantaged families, born from 1998 to 2001. The cohort studies are characterized by large sample size. The retrospective study by Font and Berger (2015) includes both exposed and non-exposed participants who were at risk of exposure to childhood maltreatment. The authors implemented the probability sampling technique because it assists the generalization of data and supports adequate estimation of results.
The researchers applied cluster sampling. In contrast to a simple random sampling that requires the identification of the exact sample size, the elaboration of selection criteria, the creation of lists including the units from which the population should be drawn, etc., the cluster sampling implies the use of the sample from the groups of study units that are already available. Cluster sampling helps researchers to save time because sometimes the random sampling may be time-consuming and difficult to implement.
However, in comparison to random sampling, cluster sampling is associated with less sample representativeness and generalization of estimation. It may be considered the main weakness of clusters. Nevertheless, large sample size in the study by Font and Berger (2015) increases the likelihood of the sample’s representativeness. And it is possible to say that in the cohort research design, the cluster sampling technique may be considered efficient and effective.
Data Collection
The study variables included childhood maltreatment and cognitive and social-emotional well-being, and the data collection was aimed at the assessment of these indicators in individuals. The cognitive skills were assessed through the Peabody Picture Vocabulary Test (PPVT), and the social-emotional aptitude was measured with the Child Behavior Checklist (CBC) (Font & Berger, 2015, p. 541).
The data collection tools are comprised of scales and subscales that allowed the researchers to obtain numeral and systematized data. The data collected through surveys and tests may be easily managed and standardized according to age and other demographic characteristics. Therefore, it is possible to say that the selection of such data collection tools as PPVT and CBC was appropriate for the quantitative research design as it reduces the possibility of biasing and misinterpretation.
Childhood maltreatment was measured through the interviews with the parents, the children’s self-reports, and the indoor observations. Self-reports and interviews are associated with subjectivity, and there is always a potential that the information can be underreported or exaggerated. Thus, the assessment has a limitation. he potential bias should always be considered by the researchers in data analysis; otherwise, the outcomes may lack validity. Font and Berger (2015) regarded the underreporting as the factor that makes the research results conservative and characterized by “lower bound” (p. 541). In this way, they attempted to decrease data bias.
Internal and External Validity
The concept of internal validity relates to the cause-effect relationships between the constructs of the study. Since the Font and Berger’s work is meant to assess the effects of childhood maltreatment on cognitive and social-emotional development, internal validity is relevant to it. Adequate internal validity implies the ability to track the causal relations between the program of the study and its outcomes (Trochim, 2006). Thus, the establishment of causal relationships is necessary for the provision of internal validity. The research by Font and Berger (2015) is characterized by consistency, and the study outcomes are logically interrelated with the data analysis, data collection tools, sampling methods, and literature review. It is possible to say that their research is internally valid.
The external validity concept indicates the level of data generalization. Only the conclusions and study outcomes that can be generalized to the total population may be regarded as externally valid. To ensure external validity, the researchers need to take into consideration sampling techniques and develop appropriate sample selection criteria. The probability cluster sampling used by Font and Berger (2015) and the large sample size guarantee that the sample represents the total population.
Research Design Efficiency
The researchers concluded that exposure to childhood maltreatment negatively impacts individuals’ cognitive and emotional development (Font & Berger, 2015). The quantitative research methods and the descriptive statistics methods helped to obtain the numerical data that allowed the researchers to increase the objectivity of conclusions, high level of their validity and accuracy. The research design assisted in the formulation of the research questions, and the identification of research variables. The quantitative research design helped to follow the research objectives aimed at the detection of cause-effect relations between the variables. Although some data collection tools provoked the limitations for the provision of data validity, the researchers managed to reduce the potential biasing by considering these limitations in the analysis. Overall, quantitative research design supported a high level of outcomes’ objectivity that helped to verify the introduced hypothesis.
Conclusion
The quantitative methodology reduces the possibility of research results’ subjectivity. However, it is important to take into account multiple aspects of research design to ensure the work’s internal and external validity. Data collection tools and sampling techniques allow the attainment of accurate and objective data that may be generalized. There also must be consistency in the establishment of causal relationships between the research constructs because it demonstrates the adequacy of conclusions. The consideration of the mentioned methodological issues contributes to the increase of research value.
References
Font, S. A., & Berger, L. M. (2014). Child maltreatment and children’s developmental trajectories in early to middle childhood. Child Development, 86(2), 536-556. Web.
Morgan, G., & Smircich, L. (1980). The case for qualitative research. Academy of Management.the Academy of Management Review, 5(4), 491. Web.
Trochim, W. M. K. (2006). Internal validity. Research Methods Knowledge Base. Web.