Title: Sense of coherence and health in women: A 25-year follow-up study
Version: 3 Date: 25 Aug 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 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:
My previous comment was “The theory of SOC is well-developed and has a long history.
Moreover, the literature (e.g., prior research testing the assumption of the SOC theory) is huge
and I do not see the reason why this study has an exploratory nature.” The response was “The
outline of this study is based on existing theories and knowledge about SOC and associated
variables. However, few longitudinal studies investigated the association between mental and
somatic health and SOC, which is an important contribution to the field.” The response was not
relevant to the question.
My previous comment was “I would like to see an introduction that leads clearly and directly
to hypotheses.” We humbly disagree with the reviewer and find that the current introduction
leads to the aims and hypothesis investigated. We leave it to the editor to decide if the
introduction needs to be revised.” First, hypotheses were not reported in the first draft of the
manuscript (now are reported). So, without hypotheses, I wonder how it is possible to claim that
“the current introduction leads to the aims and hypothesis investigated.” 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 socio-demographic factors was not even
mentioned in the Introduction section.
Not all hypotheses are testable and specific. This is a major flaw of the present study. I ask
the authors to clearly define the aims of each study and to formulate the hypotheses. When
formulating a hypothesis, one cannot allow the relationship to be either positive or negative, and
to be of different “shapes” (linear, curvilinear etc.).” This is not a hypothesis, this is a fishing
approach.
The meaning of socio-demographic factors is not clear to me. In the literature, there are dozens
of factors that can be included in this vague and wide category. Please explain which socio-
demographic factor, why (theoretical justification), and what is its expected effect.
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?” The response was “As stated in the methods section, mothers who did
not have SOC-scores from all three measurements were excluded from the study/analyses.” The
response was only partially relevant to the question. The authors simply reported that they used
complete case analysis. Please also provide theory and evidence from methodological articles
supporting the use of complete case analysis in longitudinal studies.
My previous comment was “Please calculate and report the response rate for each wave and the
attrition rate. Was an analysis of the drop-out pattern carried out?” The response was “Dropout
rate/response rate has been added to figure 1, and corresponding text added to the manuscript.”
However, Figure 1 only displays the number of participants for each wave.
Inclusion and exclusion criteria were not reported in the manuscript.
None of the studies listed “Regarding the validation of the psychometric instruments
used in the current study” can be considered a validation study (e.g., https://
doi.org/10.3389%2Ffpubh.2018.00149). These studies report some psychometric properties of
the scales. Therefore, there are no validated instruments. This should be clearly stated in the
revised manuscript and these limitations should be addressed in the Discussion section.
Please report evidence from studies conducted in Sweden using the EPDS supporting the
following statements: “A lower cut-off of EPDS is recommended for screening whereas a cut-
off level of 12 is commonly used for detect women with clinical depression. The latter cut-off
has a lower sensitivity compared to a cut-off level of 12.” Moreover, the first of the studies in
the list was not conducted in Sweden.
This response was not relevant to my previous comment (e.g., I do not ask if the authors
are aware): “Thank you for this valuable comment. We are well aware of the problems
with respect to dichotomizing continuous variables. However, for the purpose of this study
dichotomized SOC scores were more suitable.” Given that the authors did not provide any
evidence supporting the use of dichotomized SOC scores, I reinstate my previous comment “The
SOC variable was dichotomized (into <=75th percentile and >75th percentile) without providing
any theoretical and methodological arguments supporting this decision. There is no need to
dichotomize variables unless there are strong theoretical reasons. I strongly advise against the
dichotomization of variables without providing any theoretical and methodological arguments
supporting this decision. See Dawson and Weiss’ article entitled “Dichotomizing continuous
variables in statistical analysis: A practice to avoid” (Journal: Medical Decision Making). The
reason is that categorization results in lost information, reduced power of statistical tests, and
increased probability of a Type II error (see Streiner’s article entitled “Breaking up is Hard to
Do: The Heartbreak of Dichotomizing Continuous Data”). There are other types of statistical
tests that can be used (e.g., OLS regression, ordinal regression).”
The theoretical and practical implications of the study findings are still not clear to me.
Confidence intervals (that quantify the degree of precision of the estimate) is not synonymous
with effect size. I reinstate my previous comment “I would like to see a discussion about the
magnitude of the effects, not P values.” For information about the concept of effect size, I
recommend the following book https://doi.org/10.1017/CBO9780511761676