Reviewer’s report
Title: 
Cumulative Risk Exposure and Emotional Symptoms among Early
Adolescent Girls
Version: 
0 
Date: 
22 Jan 2021
Reviewer: 
Erling Rognli
Reviewer's report:
This manuscript reports on a secondary analysis of data from the HeadStart
evaluation. The authors investigate various theoretically derived risk factors for
elevated emotional symptoms among early adolescent females, using a
cumulative risk exposure model. They identify four risk factors associated with
elevated symptoms, and discuss findings in relation to current concerns about
increasing prevalence of emotional symptoms among female adolescents.
The paper is generally well written and easy to follow. The authors situate their
study in the current state of knowledge, and their results should be of interest to
the readers of this journal. The design is appropriate for their aims and the
methods and analytic approaches are adequately described. I believe the paper
would be suitable for publication after some revisions to adress a number of
concerns I had:
Major concerns:
The authors note and cite evidence of an increase in emotional symptoms and
disorders among adolescent girls in recent years, and this motivates their study
of factors associated with such symptoms. However, the authors do not discuss
whether the factors they identify in their dataset are reasonable explanations for
such an increase. Are the authors aware of evidence of increases in low academic
acheivement, special education needs (or perhaps lack of fulfillment of such
needs), low family income or youth caregiving responsibilities in their societal
context, coinciding with the increase in emotional symptoms and disorders? If
so, this needs to be cited and adressed in the discussion. If not, the discussion
needs to include a reflection on how the factors identified are unlikely to be
involved in the cited increase in prevalence, and discuss the implications of that
for future research.
The authors use a latent dependent variable of emotional symptoms with SDQ
subscale scores as indicators, which is a commendable approach, and preferable
to using summed raw scores. However, it is still quite difficult to grasp the
practical significance of the association they have found. Figure 1 shows a mean
increase of a little over 1 point on the SDQ Emotional symptoms scale when
moving from the bottom to the top level of risk, but does not show the predicted
variance of those scores or their practical significance. An approach to
increasing the interpretability is to simulate data from their fitted model at the
three levels of cumulative risk, and then to compare those distributions of
simulated data using summaries and/or plots. The SDQ is a well established
instrument with interpretable norms for different populations, and these could
also be used to evaluate the simulated distributions, for instance the proportion
of scores at or above caseness level at each degree of risk. I refer the authors to
«Gelman and Hill (2007) Data Analysis Using Regression and
Multilevel/Hierarchical Models» for one approach to the use of simulation in the
interpretation of regression models.
Minor concerns/suggestions:
Page 1, line 46: Sentence lacks precision. I would suggest something like «the
structure of psychopathology is continuous rather than categorical.» A citation
illustrating those perspectives would also be appropriate.
Page 7, line 50-60: A clearer statement of inclusion (and any exclusion) criteria
would be nice. I assumed that all pupils in classes included in the program were
approached for the evaluation, but it was not entirely clear to me whether this
was a universal or indicated prevention program.
Page 10, line 49-54: Did the relationship of neighborhood socioeconomic
deprivation remain in the opposite direction of the expected in a bivariate
regression model? I think it's perfectly reasonable to reject it, but it would
strengthen the manuscript if the authors noted the bivarate regression coefficient,
and if different from what found in the multivariate model, discussed possible
interdependencies with other variables (low family income seems likely)
explaining this unexpected coefficient sign.
Table 1: I was left a bit puzzled by the special education needs definition, as it
says «with or without a statement SEN» etc. How was SEN ascertained when
there was no statement or plan?
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Is the study design appropriate to answer the research question (including the use
of appropriate controls), and are the conclusions supported by the evidence
presented?
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Are the methods sufficiently described to allow the study to be repeated?
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Yes
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from apparent manipulation?
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