'Is Mental Health at Stake for High-Achieving Children in Poverty?' (AsPredicted #110,022)
Author(s) This pre-registration is currently anonymous to enable blind peer-review. It has 3 authors.
Pre-registered on 2022/10/19 13:07 (PT)
1) Have any data been collected for this study already? It's complicated. We have already collected some data but explain in Question 8 why readers may consider this a valid pre-registration nevertheless.
2) What's the main question being asked or hypothesis being tested in this study? Are children in poverty who are academically resilient at greater risk for internalizing symptoms? Prior evidence suggests that more LFPN-DMN connectivity is linked to higher cognitive and academic performance for children in poverty. However, research with children above poverty suggests this pattern of connectivity is also a risk-factor for mental health problems. Thus, we will also examine associations of resting state networks, particularly those involving LFPN, DMN, and CON, and their association with internalizing symptoms for children above and below poverty.
a. We will examine the relation between grades and internalizing symptoms for children above and below poverty. One possibility (H1a) is that higher grades will be associated with fewer internalizing symptoms for children above and below poverty. However, an alternate possibility (H2a) is that the association between grades and internalizing symptoms will differ for children in poverty. Specifically, they may show a weaker, or even opposite association, such that higher grades are associated with more internalizing symptoms.
b. We will examine whether LFPN-DMN connectivity is associated with internalizing symptoms for children above and below poverty. One possibility (H1b) is that higher LFPN-DMN connectivity will be associated with higher internalizing symptoms for children both above and below poverty. However, an alternate possibility (H2b) is that the association between LFPN-DMN connectivity and internalizing symptoms will differ for children in poverty. Specifically, children in poverty may show a less strong, or even opposite association, such that higher LFPN-DMN connectivity is associated with fewer internalizing symptoms, mirroring previous findings with cognitive and academic performance.
c. We will examine whether CON-DMN connectivity is associated with internalizing symptoms for children above and below poverty. One possibility (H1c) is that higher CON-DMN connectivity will be associated with higher internalizing symptoms for children both above and below poverty. However, an alternate possibility (H2c) is that the association between CON-DMN connectivity and internalizing symptoms will differ for children in poverty.
d. We will examine the relation between CON-LFPN connectivity and internalizing symptoms for children above and below poverty. One possibility (H1d) is that higher CON-LFPN connectivity will be associated with higher internalizing for children above and below poverty. However, an alternate possibility (H2d) is that the association between CON-LFPN connectivity and internalizing symptoms will differ for children in poverty. Specifically, children in poverty may show a stronger relation between CON-LFPN connectivity and internalizing symptoms, mirroring previous findings with cognitive and academic performance.
3) Describe the key dependent variable(s) specifying how they will be measured. We will use data from ABCD's baseline assessment (T0, ages 9-10).
- LFPN-DMN, CON-DMN, CON-LFPN connectivity: Resting state connectivity (average strength of correlation across nodes within/between specific brain networks/nodes) between LFPN and DMN, CON and DMN, and CON and LFPN as identified using the ABCD in-house processing at T0.
- Academic performance: CBCL mean of reported grades at T0 (Failing = 1…Above average = 4).
- Poverty level: Binary above- or below-poverty measure, considering annual household income and number of people in home. Children will be considered to be in poverty if they are living in a household of 4 or less with a total income of less than $25,000, or a household of 5 or more with a total income of less than $35,000.
- Internalizing symptoms: CBCL summary measure of the reported anxious/depressed, withdrawn/depressed, and somatic complaints subscales at T0, as scored by the in-house ABCD scoring.
4) How many and which conditions will participants be assigned to? None.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We will perform linear mixed effects models to investigate whether LFPN-DMN connectivity, CON-DMN connectivity, CON-LFPN connectivity, and grades, respectively, at age 9-10 are linked to more internalizing symptoms concurrently, and whether this effect differs for children above and below poverty. Specifically, we will run four separate models predicting internalizing symptoms from LFPN-DMN connectivity/CON-DMN connectivity/CON-LFPN connectivity/grades with an interaction of poverty level. We will include fixed effects to control for head motion (mean framewise displacement) and age, and random intercepts for site and family.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Exclusions: children whose resting state data were unusable due to reasons specified in the ABCD pipeline, children who didn't complete survey measures of interest.
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. As many as usable at T0 (baseline).
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Data have already been collected; we have previously obtained access but have not yet re-obtained access.
Regarding Grades
We plan to look at grades but if there is not enough range/variability we will instead look at cognitive performance as measured by the NIH toolbox fluid ability composite, as provided by the ABCD data curators.
Exploratory
Pending data availability, we may also look at longitudinal associations.
Internalizing
We also plan to further break down the internalizing measure, to consider the anxious/depressed, withdrawn/depressed, and somatic complaints subscales separately.
