Thursday, January 23, 2020

Article Review: Gender Differences in the Prevalence Rate of a Psychiatric Disorder

Mental disorder is a condition that many specialists struggle to handle. This paper reviews Eaton's et al. (2012) study on gender differences in the prevalence rates of a psychiatric disorder. The review will demonstrate the efforts that researchers have made to resolve the impasse and bring peace to millions of people experiencing a mental disorder. To validate the study, the researchers used a large sample size and analyzed them to determine the outcomes. The results showed that the dimensional multivariate liability model is important in addressing mental disorders in both men and women. Therefore, the study provides important information about interventions for mental diseases.

Article Review: Gender Differences in The Prevalence Rate of a Psychiatric Disorder
Mental disorders and gender differences have been an issue of significance for several decades. When it comes to gender, mental illness can be distinct. For example, women are vulnerable t depression and anxiety compared to their male counterparts who experience antisocial disorders or substance abuse. Many epidemiological studies on mental disorders found that gender differences are evident when it comes to the rate of mental disorder prevalence. Interestingly, these disorders are comorbid. based on the extreme gender differences in mental disorder prevalence, it is necessary to understand the impact of gender on comorbid and diverse mental illness. Studying the gender differences required the use of dimensional multivariate liability model. Based on the model, the disorder comorbidity pattern showed that anxiety and mood disorders have internal characteristics compared to the antisocial personality disorders that are characterized externally. To this effect, women demonstrated high levels of internalizing characteristics while men had externalizing liability dimensions.

Summary of the participants
In this study, 43,093 participants were involved. These participants formed part of “the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC),” thus forming the largest population sample to be used in an epidemiological study (Eaton et al., 2012, p. 282). The composition of this representative sample was the non-institutionalized and civilian population in America aged above eighteen years. However, the researcher oversampled young adults from the Hispanic and African-American population. Women formed the majority of the sample with 57%. The researcher used census-defined categories to select participants from ethnic groups. Based on the race/ethnicity, the participants included White, Hispanic, African American, Asian or islanders, and Alaska natives at 56%, 19.3%, 19.1%, 3.1%, and 1.6% respectively (Eaton et al., 2012). The participants consented to the study in writing, thus making the description of the study valid (Eaton et al., 2012).

The researchers relied on past 12-month DSM-IV diagnoses results (Eaton et al., 2012). Using structured interviews, the researcher manages to get information from the experienced participants. The interviews covered major antisocial personality disorders and depression, anxiety, and mood disorders. Some of the results were taken based on lifetime conditions. The AUDADIS-IV was better than the structured interviews because it helped to assess the clinically significant impairment and distress after characterizing the syndrome (Eaton et al., 2012).

Mplus version 6 where the WLSMV estimator and the Mplus default of delta parameterization were used to carry out the statistical analysis (Eaton et al., 2012). The estimator made it possible for the researchers to handle diagnostic parameters as categorical while the NESARC made it possible for them to weigh, cluster, and stratify variables. The comparative fit index helped the researchers to evaluate the fit of the model to the confirmatory factor analyses. The researchers also used the Tucker-Lewis index to evaluate the model. Based on the evaluation, the value of comparative fit index/ Tucker-Lewis index was less than 0.95 thus justifying that good model fit. The analyses showed that all odd ratios proved significant at ps<.001 except for the conditions that depended on the drug (p=0.005). It was found that women had higher rates for internalizing mental illness while men reported higher rates for externalizing syndromes.

On comorbidity structure, the researchers used the confirmatory factor analysis to parameterize the diagnosis using exploratory factors, including fear, distress and externalizing. The researchers loaded distress and fear on the highest-order internalizing exploratory factor thus making it possible to correlate them with the relevant factors. The results showed that there was a fit for the internalizing-externalizing model in the samples used. The model also fitted in each gender for both diagnoses for 12-months and lifetime.

Since the model fitted for both gender, it was important to understand the similarities based on the parameters. This implies that the factor standards or loadings were restricted to equality. For the unconstrained model, the standard was freed across men and women gender. The researchers had set the factor mean at zero and fixed the scaling factor at one (Eaton et al., 2012). In the constrained model, the researchers constrained the thresholds to equality, thus setting the factor mean for men at zero while freeing the mean factor for women while fixing the scaling factor at unitary (Eaton et al., 2012). The model used for this study was structured to support gender invariant psychopathology (Eaton et al., 2012). Women reported a higher standard deviation of .45 on internalizing liability compared to men for a lifetime. With the complete factorial invariance found, it demonstrated that differences in prevalence rates regarding disorders between genders could be determined by the differences in average latent externalizing and internalizing characteristics (Eaton et al., 2012).

The results supported the hypothesis because the underlying structures of the disorders were found to be gender invariant. In fact, the significance of this variance was evident in the mean liability levels. Based on the results, synthesizing the gender variance patterns and invariant latent structure of gender was possible in understanding the disorder comorbidity. This study provided important evidence to demonstrate that common mental diseases are associated with latent externalizing and internalizing liabilities. The results of this study raised varied implications. According to Regier et al. (2011), the DSM-IV has attracted the attention of scholars who are interested in organizing the DSM-5. The internalizing and externalizing model has defined the need to reflect on the structure of DSM-5. The finds of this article are in support of this classification implication because the researchers want to replicate the model structure in the future studies involving the epidemiologic research of psychopathology (Eaton et al., 2012). The researches in this study affirmed that the structure of the model is gender variant. The model can be applied in understanding various mental disorders in DSM-5 because it can accommodate both genders.

The results of this study supported the ongoing efforts to create interventions and preventive measures for latent disorder liabilities. This is in tandem with previous studies that showed that depressive symptoms required similar pharmacologic measures (Goldberg et al., 2011). Besides, cognitive behavioral therapy was essential to control or prevent depression and anxiety. For women, the preventive measures should focus on cognitive restructured skills to help in reducing the cognitive distortions and ruminations while in men; the prevention should be based on rewarding good behaviors (Eaton et al., 2012). Therefore, the findings in this study add value to the literature because it introduces new concepts regarding the impact of the model in addressing mental disorders across the genders.

Evaluation of the study
The study has proved necessary and beneficial to the stakeholders, especially medical practitioners and therapists who need new ways to handle mental disorder cases. The findings in the study emphasize the significance of developing psychotherapeutic interventions that encompass the shared internalizing liability. This implies that the internalizing-externalizing model should be replicated to help address multiple mental diseases. From the study, it can be concluded that the latent liability factors define the prevalence rates based on gender differences. Despite these strengths, the study presented various limitations. For instance, lifetime diagnoses could result in memory biases. Similarly, the researchers used lay interviewers to collect diagnostic data instead of using clinicians (Eaton et al., 2012, p. 282). The use of clinicians could have made it easy to interpret the data.

The Eaton’s et al. (2012) article has proved to be beneficial to the individuals struggling to understand the ways of addressing multiple mental disorders. Indisputably, women and men experience depression or mental disorders differently because women are ruminated. Therefore, preventing rumination would require gender-focused interventions. These findings have added value to my knowledge about the best ways to handle mental disorders.

Eaton, N.R., Keyes, K.M., Krueger, R.F…. Hasin, D.S. (2012). An invariant dimensional liability model of gender differences in mental disorder prevalence: Evidence from a national sample. Journal of Abnormal Psychology, 121(1), 282-288. Doi: 10.1037/a0024780.
Goldberg, D., Simms, L. J., Gater, R., & Krueger, R. F. (2011). Integration of dimensional spectra for depression and anxiety into categorical diagnoses for general medical practice. In D. A. Regier, W. E. Narrow, E. A. Kuhl, & D. J. Kupfer (Eds.), The conceptual evolution of DSM-5 (pp.19–35). Arlington, VA: American Psychiatric Publishing, Inc.
Regier, D. A., Narrow, W. E., Kuhl, E. A., & Kupfer, D. J. (Eds.). (2011). The conceptual evolution of DSM-5. Arlington, VA: American Psychiatric Publishing, Inc.