Digital Biomarkers Secondary Analysis Article

I am preparing a scientific paper that explores how digital phenotyping and digital biomarkers contribute to treating affective disorders—specifically depression and anxiety—through a Secondary Data Analysis approach. ; from public datasets, I need you to extract, analyze, and interpret relevant digital indicators of mood and behavioral change.

Scope of work
• Locate and curate the most appropriate variables within the provided public health databases that capture digital phenotypes or biomarker signals related to depression and anxiety.
• Apply sound statistical techniques (R, Python, SPSS, or Stata—use whichever you are most comfortable with) to uncover meaningful associations or treatment-response patterns.
• Report effect sizes, confidence intervals, and any necessary correction for multiple testing so the findings withstand peer review.
• Draft a full manuscript in APA 7th-edition format (Microsoft Word .docx) complete with Abstract, Introduction, Methods, Results, Discussion, Conclusion, and properly formatted References.
• Create clear tables and figures that visualize key outcomes and can be embedded directly into the document.

Deliverables
1. Cleaned, analysis-ready dataset (or reproducible code/notebook if data cannot be shared).
2. Statistical output files or scripts.
3. Manuscript (4,000–6,000 words) in .docx ready for journal submission, fully compliant with APA style.

I value clarity, methodological rigor, and concise scientific writing. If you have experience mining large health databases for behavioral or biomarker insights and turning those findings into publishable manuscripts, I look forward to working together.