Title: Sense of coherence and health in women: A 25-year follow-up study
Version: 4 Date: 14 Oct 2023
Reviewer's report:
PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses one or several
testable research questions? (Brief or other article types: is there a clear objective?)
No - there are major issues
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
No - there are major issues
EXECUTION - Are the experiments and analyses performed with sufficient technical rigor to
allow confidence in the results?
No - there are major issues
STATISTICS - Is the use of statistics in the manuscript appropriate?
No - there are issues with the statistics in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
No - there are major issues
OVERALL MANUSCRIPT POTENTIAL - Has the author addressed your concerns sufficiently
for you to now recommend the work as a technically sound contribution? If not, can further
revisions be made to make the work technically sound?
Maybe - with major revisions
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: The manuscript has improved over the previous version. However,
the authors did not respond adequately to each of the questions or concerns I raised in my
comments. Moreover, they also did not make changes to reflect their responses in the manuscript
itself.
REQUESTED REVISIONS:
Since there is a study from 1996 which concluded that a cut-off of 11.5 was suitable (Wickberg
B, Hwang CP. The Edinburgh Postnatal Depression Scale: Validation on a Swedish community
sample. Acta Psychiat Scand. 1996;94(3):181-4.), please use a cut-off of 11.5, not 12.
I reinstate my previous comment “I would like to see a discussion about the magnitude of the
effects, not P values. Mentioning the fact “that having a reaching a statistical significance does
not imply that the effect size is large” is not a discussion about the magnitude of the effects.
I strongly advise against the dichotomization of variables without providing any theoretical
and methodological arguments supporting this decision. Hochwälder, J. (2022) clearly states
that there are disadvantages in dichotomizing or trichotomizing SOC. These disadvantages in
dichotomizing or trichotomizing SOC are not even mentioned. Moreover, please demonstrate
that when using the ordinal or continuous score of the SOC the results are the same.
There are no validated instruments. This should be clearly stated in the revised manuscript and
these limitations should be addressed in the Discussion section. The following sentence is not
enough “Though the psychometric scales have been validated in other countries this validation
does not automatically transfer to a Swedish setting.”
My previous comment was “Second, some of the hypothesized variables come out of the blue
in the hypothesis. They were not even mentioned in the Introduction section. For instance, the
role of sociodemographic factors was not even mentioned in the Introduction section.” The
ANSWER: “We are very grateful for this comment, and apologize for not including a paragraph
in the introduction regarding sociodemographic factors and its associations with SOC and health.
We have now added a paragraph on this and hopefully this will be satisfactory, and further
improve the introduction.”
Sociodemographic factors were just an example. I shall repeat my previous comment: Some of
the hypothesized variables come out of the blue in the hypothesis/aims of the study. They were
not even mentioned in the Introduction section.”
Please remember that aims are different from hypotheses. Please correct (page 4).
My previous comment was “Did the author(s) carry out missing data analysis? What was
the amount of missingness? How did the author(s) handle item-level missingness as well as
longitudinal missingness?”
ANSWER: Once again, we sincerely apologize for not completely understanding the previous
comment. We understand the concern with the approach of complete-case-analyses. However,
under the assumption that the missing data is completely at random (MCAR), this approach
yields unbiased estimates. Another approach would be to perform some type of imputation
(multiple, hot deck), however considering that we wanted to study the stability/trajectory of SOC
(i.e. the outcome) we considered it extremely important to have complete-case on the outcome.
Also, since the proportion of missing data was large, there is a rather large possibility that this
would yield biased estimates and a complete-case-analysis is preferable.
Please provide evidence from methodological studies that when the proportion of missing data is
large a complete-case-analysis is preferable. To my knowledge, the opposite is true (see: https://
doi.org/10.1146/annurev.psych.58.110405.085530). In addition, please carry out missing data
analysis and report the amount of missingness.
In the drop-out analysis please report the magnitude of the effect or the odds ratios. Moreover,
the fact that the final study population only represents 24.5% of the baseline population and is
clearly biased (non-participants to a greater extent were immigrants, more often scored above
cut-off of 10 on EPDS, and had a greater exposure to total life stress at baseline) are important
limitations of this study and deserves a thorough discussion.