Baldwin et al (2016)
Baldwin et al (2016) is based on a cohort study. By definition, a cohort study is a research design which follows a group of people over a given period of time (Kazdin, 2021). Data from cohort studies is often used to determine social and environmental factors that influence human health. The researchers chose this method out of the need to understand whether childhood bullying impacts overweight during young adulthood.
The independent variables of this study included childhood bullying vicitimization, childhood chronicity of exposure to bullying, childhood weight, child maltreatment, mental health and cognition, pubertal development, food insecurity, socioeconomic status, and genetic risk for overweight (Baldwin et al., 2016). Dependent variables included young adulthood overweight, body mass index, and waist-hip ratio (Baldwin et al., 2016). One of the most important independent variables that should have been included in the study is the frequency of bullying. Children who are frequently bullied are more likely to become overweight than their non-victimized counterparts (Ashrafi et al., 2020). The dependent variables that should have been included in the study include anxiety, depression, criminality, suicidal thoughts, feelings of insecurity, thoughts of worthlessness, negative body image, and social avoidance. According to Armitage (2021) and Lidberg et al (2022), bullied children are more likely to experience such adulthood adversities than non-bullied ones.
The researchers engaged a cohort of British children. This group was followed and observed up to age 18. It was part of an Environmental Risk Longitudinal Twin Study. For childhood bullying victimization, data was collected from the mothers of the respondents. However, for bullying victimization during primary and early secondary levels of education, data was collected from the affected children themselves. Follow-ups were made when the participants were seven, ten, and eighteen years old. The follow-ups involved actual visitation of the homes of the research participants (Baldwin et al., 2016). The researchers resorted to this method in order to understand how environmental factors during childhood contributed to health problems as from early adulthood.
There is enough evidence for the validity and reliability of the measures that the researchers chose. In terms of validity, it was established that participants’ weight ratings at age 10 and age 12 correlated with their body mass that recorded at age12 (Baldwin et al., 2016). It was also found that the weight was predictive of the overweight measures taken when participants were 12 years old (Baldwin et al., 2016). The reliability of the measures lies within the fact that the findings of the study are compatible with various experimental researches conducted among nonhuman primates (Kaufman et al., 2007; Conti et al., 2012). Thus, childhood bullying is predictive of overweight during early adulthood.
The study design that the researchers opted to use had some limitations. Firstly, the researchers involved a cohort of twins in the study. For this reason, their findings cannot be used to generalize cases of singletons. Secondly, the researchers lacked anthropometric measures of the children who participated in the study. They only relied on the weight ratings of research workers that were taken when the children were 10 and 12 years old. Such ratings can lead to misclassification. Thirdly, the researchers did not monitor children’s weight throughout the period of observation. Due to this, it can be possible that some bullying victims were overweight at some points in the course of their childhood. Although the study design had such limitations, it needs to be pointed out that it was good for the study. It was be used to determine how environmental factors like childhood bullying contributed to poor health outcomes such as overweight.
References:
Armitage, R. (2021). Bullying In Children: Impact on Child Health. BMJ Paediatrics, 5 (1). http://dx.doi.org/10.1136/bmjpo-2020-000939
Ashrafi, A., Feng, C.X., Neudorf, C., & Alphonsus, K. B. (2020). Bullying Victimization among Preadolescents in a Community-Based Sample in Canada: A Latent Class Analysis. BMC Res Notes, 13 (138). https://doi.org/10.1186/s13104-020-04989-4
Baldwin, J. R., Arseneault, L. Odgers, C., Belsky, D. W., Matthews, T., Ambler, A., Caspi, A., Moffit, T. E., & Danese, A. (2016). Childhood Bullying Victimization and Overweight in Young Adulthood: A Cohort Study. Psychosomatic Medicine, 78: 1094-1103. DOI: 10.1097/PSY.0000000000000388
Conti, G., Hansman, C., Heckman, J. J., Novak, M. F., Ruggiero, A., & Suomi, S. J. (2012). Primate Evidence on the Late Health Effects of Early-Life Adversity. Proc Natl Acad Sci USA, 109: 8866–8871.
Kaufman, D., Banerji, M. A., Shorman, I., Smith, E. L., Coplan, J. D., Rosenblum, L. A., & Kral, J. G. (2007). Early-Life Stress and the Development of Obesity and Insulin Resistance in Juvenile Bonnet Macaques. Diabetes, 56:1382–1386.
Kazdin, A. E. (2021). Research Design in Clinical Psychology. Cambridge: Cambridge University Press.
Lidberg, J., Berne, S., & Frisen, A. (2022). Challenges in Emerging Adulthood Related to the Impact of Childhood Bullying Victimization. Emerging Adulthood. https://doi.org/10.1177/21676968211051475
Freeman et al (2005)
In their study, Freeman et al (2005) used a cross-sectional survey research design to study various paranoid thoughts, determine their level of distribution, identify coping strategies, and establish the associated social-cognitive strategies. A cross-sectional study allows the researcher to gather information from many different people at a given single point in time (Jhangiani et al., 2019). The researchers settled on this research design for the reason that it can lead to the study of multiple variables at the same time.
The major independent variables of the study were the level of paranoia, and suspicious thoughts (Freeman et al., 2005). The dependent variables included coping strategy, emotional expression attitude, social rank, and level of submission (Freeman et al., 2005). Other independent variables that should have been involved in the study include anxiety and depression. These factors help to determine the submission level, and strategy for coping. One of the dependent variables that researchers should have included in this study is health outcome. The identified independent variables probably lead to this particular dependent variable.
Data for the study was collected using survey questionnaires. Six questionnaires were administered to the research participants: paranoia scale, paranoia checklist, questionnaire of attitude to emotional expression, coping style questionnaire, submissive behavior scale, and social comparison scale (Freeman et al., 2005). The researchers probably decided to use this method to keep the anonymity of respondents, save time, and cut costs (Jhangiani et al., 2019). The participants of the study were invited using an e-mail address that directed them to a website with the survey questions. This helped to ensure that the targeted respondents were reached easily and that their identity was highly protected against third parties with bad intentions.
From the study, it is evident that the selected measures met reliability and validity requirements. For instance, the three Paranoia Checklist dimensions had a Cronbach’s alpha of either 0.9 and above (Freeman et al., 2005). This indicates that the checklist had a good internal validity. It is also important to note that the there existed convergent validity of the Paranoia Scale with the checklist (Freeman et al., 2005). The reliability of the chosen measures centers on the fact that the findings of this study derive from empirical evidence. This plays an important role in strengthening the arguments advanced by the researchers who conducted the survey in the study (Barker et al., 2015).
One of the major limitations of adopting the cross-sectional questionnaire design in this study was that it led to the selection and use of a sample that was less epidemiologically representative. The study sample was restricted to the students of the university, and was self-selected. Another limitation is that the research design limited the conclusions of the study. As a result, it made it difficult to establish the cause-and-effect relationship between different variables. For this reason, it would have been good for the researchers to adopt a longitudinal research design. Such a design helps to justify the relationship.
References:
Barker, C., Pistrang, N., & Elliott, R. (2015). Research Methods in Clinical Psychology: An Introduction for Students And Practitioners. Chichester, West Sussex: Wiley Blackwell.
Freeman, D., Garety, P. A., Bebbington, P. E., Smith, B., Rollinson, R., Fowler, D., Kuiperss, E., Ray, K., & Dunn, G. (2005). Psychological Investigation of the Structure of Paranoia in a Non-Clinical Population. British Journal of Psychiatry: 186: 427- 435.
Jhangiani, R., Chiang, I.-C. A., Cuttler, C., Leighton, D. C., & Price, P. (2019). Research Methods in Psychology. Place of publication not identified: publisher not identified.
Reichenberg et al (2006)
Reichenberg et al (2006) employed a historical population-based cohort study design. This is an epidemiology study whereby a given population is observed longitudinally and followed for the purpose of determining exposure versus outcome kind of relationship (Jhangiani, et al., 2019). The researchers opted to use this method to determine the association between advancing paternal ages and vulnerability to autism spectrum disorder (ASD).
In the current study, the main independent variables included advanced paternal age, genetic imprinting, and mutations related with advancement in age (Reichenberg et al., 2006). On the other hand, the major dependent variable was susceptibility to ASD (Reichenberg et al., 2006). Other independent variables that should have been dealt with in the study include family history for autism, low birth weight, and exposure to environmental toxins. Such factors are associated with ASD. On their part, other dependent variables that were supposed to be considered in this study include vulnerability to low intellectual capacity, and schizophrenia. Such problems are associated with advancement in paternal age.
The researchers collected data for this study using a cohort of Jews born in Israel for six consecutive years during the 1980s. This cohort was closely followed as well as observed before being assessed at age 17. Information on the health status of the research participants was obtained from the registry. The information was used to determine those with cases of ASD (Reichenberg et al., 2006). The researchers selected this method to purposely understand how social factors such as advanced paternal age influenced child health.
The chosen measures for the study have a high degree of reliability and validity. This is due to the fact that there is evidence for the association between neurodevelopmental disorders and advanced paternal age. Children of whose fathers are older at birth are at high risk for disorders such as Apert syndrome, hydrocephalus, and craniosynostosis (Savitz et al., 1991; Green et al., 2010). This relationship can be explained by vulnerability to de novo genetic mutations in germline among father with advanced age.
The research design that was adopted for this study had some notable weaknesses. One of the weaknesses is that there was a possibility for bias as a result of loss during follow-up. It is not all participants who were assessed at age seventeen. Another limitation is that the researchers lacked information on the autistic status of the cohort members’ parents. Due to this, parental constitutional factors like characteristics associated with autism phenotype could not be ruled out. It is also important to note that the researchers were not able to distinguish whether paternal age was associated with specific ASD psychopathologic features’ dimensions or specific diagnoses in ASD. The board registry did not provide this information. Despite this limitation, the use of a cohort research design was appropriate for this particular study. This is due to the fact that such a design is useful in studying both environmental and social factors influencing human health (Jhangiani, et al., 2019). This can be achieved through observation of participants and following them over time.
References:
Green, R. F., Devine, Q., Crider, K. S., Olney, R. S., Archer, N., Olshan A. F., & Shapira, S. K. (2010). Birth Defects Prevention Study, 1997 to 2004. Annals of Epidemiology, 20 (3): 241-249. https://doi.org/10.1016/j.annepidem.2009.10.009
Jhangiani, R., Chiang, I.-C. A., Cuttler, C., Leighton, D. C., & Price, P. (2019). Research Methods in Psychology. Place of publication not identified: publisher not identified.
Reichenberg, A., Gross, R., Weiser, M., Bresnahan, M., Silverman, J., Harlap, S., Rabinowitz, J., Shulman, C., Malaspina, D., Lubin, G., Knobler, H. Y., Davisson, M., & Susser, E. (2006). Advancing Paternal Age and Autism. Advancing Paternal Age and Autism. Arch Gen Psychiatry. 63: 1026-1032
Savitz, D. A., Schwingl, P. J., & Keels, M. A. (1991). Influence of Paternal Age, Smoking, and Alcohol Consumption on Congenital Anomalies. Teratology, 44: 429-440.
Yoshinaga, et al (2016)
Yoshinaga et al (2016) employed a prospective randomized open-blinded end-point (PROBE) trial. The PROBE research design uses strict randomized criteria to assign patients to various treatment regimens (Reis & Judd, 2018). The researchers used this particular design to study the efficacy of cognitive behavioral therapy in the treatment of symptomatic social anxiety disorder (SAD) patients who have received antidepressant treatment.
The study’s major independent variables included CBT, usual care, antidepressant treatment, and symptomatic status (Yoshinaga et al., 2016). On their part, the dependent variables included reduced social anxiety, depressive symptoms as well as functional disability (Yoshinaga et al., 2016). Some of the independent variables that should have been involved in this study include other mental health conditions such as schizophrenia and bipolar disorder, and other forms of therapy for SAD such as talking therapy. Such variables are also associated with positive treatment outcomes for social anxiety. The dependent variables which should have been part of this study include other improved health outcomes among SAD patients. Such outcomes depend on the medical or therapeutic interventions provided to patients.
During the study, the researchers randomly assigned participants to UC and CBT+UC groups. The participants were them assessed during weeks 0, 8, and 16. All changes in treatment were recorded in the course of this study (Yoshinaga et al., 2016). The researchers probably chose this method for similarity with standard clinical practice and low cost (Reis & Judd, 2018. Thus, the results of such studies are applicable in clinical settings. The studies also enable researchers to cut costs.
The measures that the researchers chose were both valid and reliable. There is enough evidence to prove that CBT can be useful for patients who have severe SAD symptoms and have not received effective antidepressant treatment (Rodrigues et al., 20111; Yoshinaga et al., 2013). Other researches such as Fava (2014) suggest that the use of antidepressants alone for the treatment of anxiety disorders should be avoided unless there is a comorbid major depression.
The major weakness of the current study design is that the researchers lacked follow-up data. This limits the possibility of generalizing the results of this research for other situations. Another weakness is that the study was based on a small sample. There is need for the findings of the study to be replicated in researches with large samples. The study design the researchers chose for this study was suitable for it. This is due to the fact that its results are similar to those ones that can be obtained from a real clinical setting (Reis & Judd, 2018). Therefore, there is no need for other study design in this case.
References:
Fava , G. A. (2014). Rational Use of Antidepressant Drugs. Psychother Psychosom, 83: 197-204.
Reis, H. T., & Judd, C. M. (2018). Handbook of Research Methods in Social and Personality Psychology. Cambridge: Cambridge University Press.
Rodrigues, H., Figueira, I., Gonçalves, R., Mendlowicz, M., Macedo, T., & Ventura, P. (2011). CBT for Pharmacotherapy Non-Remitters – A Systematic Review of a Next-Step Strategy. J Affect Disord, 129: 219–228.
Yoshinaga, N., Matsuki, S., Niitsu, T., Sato, Y., Tanaka, M., Ibuki, H., Takanashi, R., Ohshiro, K., Ohshima, F., Asano, K., Kobori, O., Yoshimura, K., Hirano, Y., Sawaguchi, K., Koshizaka, M., Hanaoka, H., Nakagawa, A., Nakazato, M., Iyo, M., & Shimizu, E. (2016). Cognitive Behavioral Therapy for Patients with Social Anxiety Disorder Who Remain Symptomatic following Antidepressant Treatment: A Randomized, Assessor-Blinded, Controlled Trial. Psychother Psychosom, 85: 208–217. DOI: 10.1159/000444221
Yoshinaga, N., Ohshima, F., Matsuki, S., Tanaka, M., Kobayashi, T., Ibuki, H., Asano, K., Kobori, O., Shiraishi, T., Ito, E., Nakazato, M., Nakagawa, A., Iyo, M., & Shimizu, E. (2013): A Preliminary Study of Individual Cognitive Behavior Therapy for Social Anxiety Disorder in Japanese Clinical Settings: A Single-Arm, Uncontrolled Trial. BMC Res Notes, 6: 74.
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