Dear Editor,
We have carefully reviewed an article that discusses antenatal depression. In this case, antenatal depression is significantly influenced by intimate partner violence (any lifetime-IPV, fear, emotional-IPV, physical-IPV and sexual-IPV). Meanwhile, of the eleven individual characteristic variables, six variables affect antenatal depression, namely civil status, family income, pregnancy planned, tobacco, alcohol and alcohol partners; while five variables (age, education level, occupation, mother tongue, and parity) did not affect it1.
There are three questions related to this condition: 1) ‘Is it true that age, education level, occupation, mother tongue and parity do not affect antenatal depression?’; 2) ‘Could the five variables influence antenatal depression indirectly?’; and 3) ‘What statistical analysis can be used to analyze this indirect effect?’.
In this study, the researchers used regression analysis, so that in the hypothesis it is assumed that all individual characteristic variables simultaneously affect antenatal depression directly. Referring to relevant references, these eleven variables should not all affect antenatal depression directly. There are several variables that influence antenatal depression indirectly through intermediary variables, for example: parity affects pregnancy planned, then pregnancy planned affects antenatal depression.
Referring to a similar case2, we present an alternative framework for the relationship between related variables (Figure 1), which should be reviewed and revised before use. In this case, logistic regression analysis cannot be used, and the most appropriate choice is path-analysis3,4. Because the researchers use categorical data, one of the statistical programs that can be used is Smart-PLS3.
Figure 1.
Pathways of influence of individual characteristic factors related to antenatal depression
Furthermore, we suggest that researchers perform further analysis using path-analysis, to obtain more complete information about the effect of these eleven variables on antenatal depression.
CONFLICTS OF INTEREST
The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none was reported.
FUNDING
There was no source of funding for this research.
ETHICAL APPROVAL AND INFORMED CONSENT
Ethical approval and informed consent were not required for this study.
DATA AVAILABILITY
Data sharing is not applicable to this article as no new data were created.
PROVENANCE AND PEER REVIEW
Not commissioned; internally peer reviewed.
DISCLAIMER
The views and opinions expressed in this article are those of the authors.
REFERENCES
- 1.Melby TC, Sørensen NB, Henriksen L, Lukasse M, Flaathen EME. Antenatal depression and the association of intimate partner violence among a culturally diverse population in southeastern Norway: A cross-sectional study. Eur J Midwifery. 2022;6(July):1–10. doi: 10.18332/ejm/150009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Nugroho HSW, Suparji S, Martiningsih W, Suiraoka IP, Acob JRU, Sillehu S. A Response to “Effect of Integrated Pictorial Handbook Education and Counseling on Improving Anemia Status, Knowledge, Food Intake, and Iron Tablet Compliance Among Anemic Pregnant Women in Indonesia: A Quasi-Experimental Study” [Letter] J Multidiscip Healthc. 2020;13:141–142. doi: 10.2147/JMDH.S247401. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Garson GD. Partial Least Squares: Regression & Structural Equation Models. Statistical Publishing Associates; 2016. Accessed April 7, 2022. https://www.smartpls.com/resources/ebook_on_pls-sem.pdf. [Google Scholar]
- 4.Nugroho HSW, Alamsyah T, Alvarado AE. APPLICATION OF PATH ANALYSIS TO MODELING FROM POPULATION-BASED DATA SOURCES. Aloha International Journal of Multidisciplinary Advancement. 2022;4(2) [Google Scholar]
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Data Availability Statement
Data sharing is not applicable to this article as no new data were created.