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Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children.

Code ↔ Paper

3 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 3 matches
  1. [1] § Methods › Statistical analyses ↔ code/01_lmm.R, lines 140–200 · score 0.71 · linear mixed, lme4, family income, LMMs, race, BMI
  2. [2] § Methods › Statistical analyses ↔ code/03_clpm.R, lines 1–41 · score 0.62 · model fit, cross lagged, lavaan, temporal, CLPMs, covariates
  3. [3] § Methods › Statistical analyses ↔ code/03_clpm.R, lines 43–117 · score 0.52 · cross lagged, predicting, lavaan, CLPMs, BMI, education

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

R · 117 lines · 4.5 KB · no license · 2 matches

  1. # ======================================================================
  2. # Purpose:
  3. # This script performs cross-lagged panel modeling (CLPM) using lavaan
  4. # to follow up on significant activity–CBCL associations (Pfdr<0.05) identified via LMM.
  5. #
  6. # For each activity–CBCL pair found to be significant in LMM results,
  7. # this script loads corresponding input data and fits a CLPM model to
  8. # examine temporal directional effects between activity and CBCL scores
  9. # across two timepoints, adjusting for baseline covariates.
  10. #
  11. # Output includes:
  12. # - Standardized path estimates with Bonferroni/FDR-adjusted p-values
  13. # - Model fit indices
  14. # - Formatted HTML tables for reporting
  15. # ======================================================================
  16. # -----------------------------
  17. # Setup
  18. # -----------------------------
  19. library(lavaan)
  20. library(kableExtra)
  21. library(dplyr)
  22. # -----------------------------
  23. # Locate all input CLPM data
  24. # -----------------------------
  25. clpm_datapath_list <- list.files(
  26. path = "/Users/tianx/Documents/academic/Projects/ABCD_lifestyle/activity_cbcl_recheck/CLPM_physical28/results/clpm_results",
  27. pattern = "input_data.csv",
  28. recursive = TRUE,
  29. full.names = TRUE
  30. )
  31. # -----------------------------
  32. # Start loop
  33. # -----------------------------
  34. for (file_path in clpm_datapath_list) {
  35. cat("\n Processing:", file_path, "\n")
  36. tryCatch({
  37. # -----------------------------
  38. # Parse variable names from path
  39. # -----------------------------
  40. path_parts <- strsplit(file_path, "/")[[1]]
  41. x_var <- path_parts[length(path_parts) - 2]
  42. last_folder <- path_parts[length(path_parts) - 1]
  43. last_parts <- strsplit(last_folder, "-")[[1]]
  44. y_var <- last_parts[1]
  45. timepoint1 <- last_parts[2]
  46. timepoint2 <- last_parts[3]
  47. # -----------------------------
  48. # Read data and construct model
  49. # -----------------------------
  50. df_clpm_input <- read.csv(file_path)
  51. cv_list <- c("sex", "age", "family_income", "education", "zBMI", "puberty", "race", "site")
  52. cv_list_time1 <- paste0(cv_list, "_", timepoint1)
  53. cv_list_time2 <- paste0(cv_list, "_", timepoint2)
  54. model_desc <- paste0("
  55. # Cross-lagged paths
  56. ", x_var, "_", timepoint2, " ~ ", x_var, "_", timepoint1, " + ", y_var, "_", timepoint1, "
  57. ", y_var, "_", timepoint2, " ~ ", y_var, "_", timepoint1, " + ", x_var, "_", timepoint1, "
  58. # Covariances
  59. ", x_var, "_", timepoint1, " ~~ ", y_var, "_", timepoint1, "
  60. ", x_var, "_", timepoint2, " ~~ ", y_var, "_", timepoint2, "
  61. # Covariates for t1 variables
  62. ", x_var, "_", timepoint1, " ~ ", paste(cv_list_time1, collapse = " + "), "
  63. ", y_var, "_", timepoint1, " ~ ", paste(cv_list_time1, collapse = " + "), "
  64. # Covariates for t2 variables
  65. ", x_var, "_", timepoint2, " ~ ", paste(cv_list_time2, collapse = " + "), "
  66. ", y_var, "_", timepoint2, " ~ ", paste(cv_list_time2, collapse = " + "), "
  67. ")
  68. # -----------------------------
  69. # Run lavaan model
  70. # -----------------------------
  71. fit <- sem(model_desc, data = df_clpm_input, missing = "ML")
  72. fit_summary <- summary(fit, fit.measures = TRUE, standardized = TRUE)
  73. # -----------------------------
  74. # Save parameter results
  75. # -----------------------------
  76. path_results <- standardizedSolution(fit)
  77. path_results$p_adjusted_bonferroni <- p.adjust(path_results$pvalue, method = "bonferroni")
  78. path_results$p_adjusted_fdr <- p.adjust(path_results$pvalue, method = "fdr")
  79. write.csv(path_results, file.path(dirname(file_path), "lavaan_clpm_results.csv"), row.names = FALSE)
  80. fit_stats <- as.data.frame(fitMeasures(fit), stringsAsFactors = FALSE)
  81. write.csv(fit_stats, file.path(dirname(file_path), "lavaan_clpm_fit_eva.csv"), row.names = TRUE)
  82. # -----------------------------
  83. # Save HTML table for paths
  84. # -----------------------------
  85. path_results_display <- path_results %>%
  86. filter(op == "~") %>%
  87. select(lhs, rhs, est.std, pvalue, p_adjusted_bonferroni, p_adjusted_fdr)
  88. html_table <- path_results_display %>%
  89. kable(format = "html",
  90. col.names = c("Dependent", "Predictor", "Standardized β", "p-value",
  91. "Bonferroni-adjusted", "FDR-adjusted")) %>%
  92. kable_styling(bootstrap_options = c("striped", "hover", "condensed"), full_width = FALSE)
  93. save_kable(html_table, file = file.path(dirname(file_path), "path_results_display.html"))
  94. }, error = function(e) {
  95. message("Error in file: ", file_path)
  96. message(" → ", e$message)
  97. })
  98. }

03_clpm.R at commit 4eb54cb, no license · at the source

Overview

Authors: Xiaohan Tian1, Ruoxin Yang1, Jing Lou1, Yuqing Sun1, Meng Wang1, Qi Wang2, Wenkun Lei1, Ang Li3, Zhanjun Zhang1, Bing Liu1,4,5
  1. State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University,Beijing, 100091 China
  2. Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences,Beijing, 100190 China
  3. State Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences,Beijing, 100101 China
  4. IDG/McGovern Institute for Brain Research, Beijing Normal University,Beijing, 100091 China
  5. Chinese Institute for Brain Research,Beijing, 102206 China
Journal: Translational psychiatry, volume 16, issue 1, article 285
Dates: received 5 August 2025; accepted 9 April 2026; published online 16 April 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41398-026-04045-y · PMID 41991511 · PMCID PMC13216275 · OpenAlex W7154618217
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: structural MRI / diffusion (modality), human (organism)
Methods: Connectivity, Statistics
Keywords: Human behaviour, Psychiatric disorders, Neuroscience
MeSH: Brain*, Child Behavior*, Child Development*, Screen Time*, Social Behavior*, Adolescent, Child, Digital Media, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Neurodevelopment (* major topic)
Topic: Impact of Technology on Adolescents (Sociology and Political Science, Social Sciences), according to OpenAlex
Funding: National Natural Science Foundation of China (National Science Foundation of China) (82425024, 82372049); Beijing Nova Program (20230484425); STI 2030—Major Projects (2021ZD0200500)
Citations: not cited yet (Europe PMC); 90 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

linktianx/DualAxisEngagement

License: none: the authors keep all their rights
State: the link answers, verified on 29 September 2026
Evidence: files inventoried
Commit: 4eb54cbb61f2478850e688564c99b901cb019372, 24 April 2025
Languages: R (3), Python (1)
Size: 5 files, 4 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (3 files), broom (1 file), lavaan (1 file), lme4 (1 file), pandas (1 file), Pingouin (1 file), statsmodels (1 file)
Availability: 1 check, the latest on 29 September 2026: the link answers
  • 29 September 2026: the link answers
5 files

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41398-026-04045-y.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 4 scripts, each with its path and the digest of its content;
  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • no repository, dataset or request procedure was recognized in it

Read it in the paper: doi.org/10.1038/s41398-026-04045-y.

Versions

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 10 authors, 3 keywords, 14 MeSH terms, 3 funders, 88 references.

Cite

This paper

Tian, X., Yang, R., Lou, J., Sun, Y., Wang, M., Wang, Q., Lei, W., Li, A., Zhang, Z., & Liu, B. (2026). Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children. Translational psychiatry, 16(1), 285. https://doi.org/10.1038/s41398-026-04045-y

BibTeX

@article{tian2026physical,
author = {Tian, Xiaohan and Yang, Ruoxin and Lou, Jing and Sun, Yuqing and Wang, Meng and Wang, Qi and Lei, Wenkun and Li, Ang and Zhang, Zhanjun and Liu, Bing},
title = {{Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children}},
journal = {Translational psychiatry},
year = {2026},
month = apr,
volume = {16},
number = {1},
pages = {285},
publisher = {Nature Publishing Group},
issn = {2158-3188},
doi = {10.1038/s41398-026-04045-y},
url = {https://doi.org/10.1038/s41398-026-04045-y},
pmid = {41991511},
pmcid = {PMC13216275}
}

RIS

TY - JOUR
AU - Tian, Xiaohan
AU - Yang, Ruoxin
AU - Lou, Jing
AU - Sun, Yuqing
AU - Wang, Meng
AU - Wang, Qi
AU - Lei, Wenkun
AU - Li, Ang
AU - Zhang, Zhanjun
AU - Liu, Bing
TI - Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children
T2 - Translational psychiatry
J2 - Transl Psychiatry
PY - 2026
DA - 2026/04/16
VL - 16
IS - 1
SP - 285
SN - 2158-3188
PB - Nature Publishing Group
DO - 10.1038/s41398-026-04045-y
UR - https://doi.org/10.1038/s41398-026-04045-y
LA - en
ER -

CSL-JSON

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"id": "10.1038/s41398-026-04045-y",
"type": "article-journal",
"title": "Physical-Digital and social-nonsocial extracurricular engagement: differential effects on brain development and psychological outcomes in children",
"container-title": "Translational psychiatry",
"author": [
{
"family": "Tian",
"given": "Xiaohan"
},
{
"family": "Yang",
"given": "Ruoxin"
},
{
"family": "Lou",
"given": "Jing"
},
{
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"given": "Yuqing"
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{
"family": "Wang",
"given": "Meng"
},
{
"family": "Wang",
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{
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],
"container-title-short": "Transl Psychiatry",
"volume": "16",
"issue": "1",
"page": "285",
"DOI": "10.1038/s41398-026-04045-y",
"PMID": "41991511",
"PMCID": "PMC13216275",
"ISSN": "2158-3188",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s41398-026-04045-y",
"language": "en",
"issued": {
"date-parts": [
[
2026,
4,
16
]
]
}
}

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