Improving Care for Depression in Obstetrics and Gynecology
Depression is a major illness that affects women disproportionately with a lifetime of 21%. The ratio of women to men who suffer depression is approximately 2:1 while major depressive episodes are noted to occur throughout their lifetime with highest rates occurring during reproductive and menopausal transition years (Melville et al., 2014). Research shows that many of the disadvantaged members of the society and minority women have the highest incidence of suffering from depression and are likely to seek routine care in the gynaecology rather than primary care settings. Women between the ages of 18-45 represent a third of women who regularly make visits to obstetrician while those under the age of 65 visits them for non-illness matters (Melville et al., 2014). It is estimated that 37% of the non-pregnant patients depends on them for routine care. Thus, the research focused on evaluating evidence-based collaborative depression care intervention adapted to obstetrics and gynaecology clinics compared with usual care.
Type of Validity Measurement Used in the Research
Validity refers to the extent to which a measurement tool measures what it is supposed to measure. Two types of validity exist; face and construct validity. While the former occurs when a tool subjectively appears to measure a construct, the latter measures the extent to which a tool measures a construct. Another difference is that face validity comes out as an expression of peoples’ opinion which may sometimes be wrong while the latter relates to observations of a construct which might be difficult to prove since many things may look alike. Nevertheless, the type of validity used in this case is construct validity since it involves the creation of constructs and noting various observations from the participants and deducing conclusions from those observed traits.
Describe the Frequency Distribution
Research associates screening patients in each clinic collected baseline data. Results were measured at 6, 12, and 18 months utilizing standardized questionnaires, which were collected by phone by a research assistant blinded to intervention status (Melville et al., 2014). Each follow-up was as up to 2 weeks before and 16 weeks following the assigned time point. The primary outcomes were a change from baseline 12 to SCL 20, while secondary outcomes were treatment response, complete remission of depressive symptoms, patient global improvement, and satisfaction with depression care. Demographic data included insurance, race, marital status, education, and age (Melville et al., 2014).
The Use of Percentage in the Article
Many randomised trials entail measurement of continuous outcomes such as blood pressure and body weight at baseline and after treatment, which requires a detailed comparison. In Melville et al.’s (2014) study, the use of percentages made it possible to compare the two interventions before and after the randomized trials. The percentages also helped present the results in terms understandable to clinicians and patients.
Cumulative Percentage Distribution
Approximately 94% of the total participants agreed and completed screening while only 16% screened positive for major depression based on the PHQ-9, while 64% nodded up for further eligibility screening (Melville et al., 2014). Furthermore, only 31% participants were randomized; in which case, 102 underwent intervention and 103 went through Usual Care (Melville et al, 2014). Later, follow-ups were completed at 6months at 89%, 12months at 88%, and 18months at 83%. From the results, one or more depression care manager visit was assigned to 96% of the women in the Intervention group (Melville et al., 2014). Out of those, antidepressant medication was given to 53.9% and 31.4% were treated using PST-PC alone (Melville et al., 2014).
Discuss the Type of Graph Used and its Purpose
In this research, the type of graph used is a linear graph. The graph highlights the progress of all participants through the trial. It shows how mean change in depressive symptoms changes for both the intervention and usual care groups (Melville et al., 2014). The graph is appropriate since it shows that despite the fact that the two use different modes of treatment and the average functional improvement was higher for the intervention group, the variation is not significant.
References
Melville, J., Reed, S., Russo, J., Croicu, C., Ludman, E., LaRocco-Cockburn, A., & Katon, W. (2014). Improving care for depression in obstetrics and gynecology. Obstetrics & Gynecology, 123(6), 1237-1246. http://dx.doi.org/10.1097/aog.0000000000000231
