PHQ-9 Depression Assessment

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PHQ-9 Depression Assessment

14-Days of Ambulatory Mood Dynamics in a General Population

By [source]

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About this dataset

This dataset contains 14 days of ambulatory assessment (AA) data related to depression symptoms and mood ratings, as well as findings from a retrospective Patient Health Questionnaire (PHQ-9) designed for depression screening purposes. Furthermore, it contains demographic information about the participants such as their age and gender.

This dataset is composed of various fields including: phq1, phq2, phq3, phq4, phq5, phq6, phq7,ph q8 ,ph q9 ,age ,sex ,q10 ,e11 ,12 w13 w14 e16 e46 e47 happiness.score time period name start time Ph Q day The data gathered through this survey allows us to gain insight into the daily fluctuations in self-reported symptoms experienced by these individuals at different stages of their lives. In addition to providing important clues about possible causes or triggers associated with depressive episodes, this type of survey can also help identify interventions that may prove successful in reducing symptom severity and frequency. Our hope is that we can use this extensive collection of data to inform treatment decisions and ultimately improve outcomes for those affected by depression

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How to use the dataset

This dataset contains information about the Patient Health Questionnaire (PHQ-9) depression screening assessment, which is used to assess the severity of depressive symptoms over the past two weeks. This dataset can be used to gain insights into depression in a general population sample.

The data is broken down into several categories: PHQ Score (1-9), Age and Gender of participant, Questions 10-47 (Numeric Scores), Happiness score, Time/Period Name/Start Time, and PHQ Day.

In order to use this dataset effectively and accurately analyze your results it is important to understand how each column impacts your results. The PHQ Score column contains information on the severity of depressive symptoms in a scale from 1-9. The Age and Gender columns contain demographic information related to participants while Questions 10-47 represent a range of mental health subject including anhedonia, fatigue, sleep disturbance and changes in appetite or weight that are rated on a numeric scale from 0-4. The Happiness score reflects individual’s subjective ratings at time of assessment with higher scores reflecting greater positivity toward life as reported by participant during study period. Finally the Time/Period Name/Start Time columns provide date and time information related to study period while the PHQ Day represents total number of days elapsed since onset of clinical trial at beginning of assessment period.

By understanding how each category contributes as well as any relationships that may exist between variables researchers can use this data set effectively when analyzing their results for more detailed insights into depression in general population samples across different lengths of time or months scoring methodologies employed reflected by total PHQ scores attained over course on particular month interval included within scope defined for particular study group being considered for analysis by researcher during evaluation protocol being employed developed data research development team assigned project develop analysis offers potential obtainable from working current model designed herein designed incorporated iteration included questionnaires offer basis obtainable utilizing utilized platform outlined herethrough model presented currently established outcome metrics thereby providing tool required necessary review evaluate found current project implementation structure framework wherein needed result may provided evaluated research rationale procedures ultimately yielding findings potentially productive goals desired analytical outcomes original objective initial efforts made implement intended protocol design methodological measures prescribed evaluator's evaluation criteria reported therewith provide result assist uncovering needed research answers discoverable platform established herein presented purpose obviate further attempts previously reviewed limitations encountered earlier trials thus executing member's logbook objectives upgraded format allow corporate setting without interruption driven process overhaul project initiation iterative systemic component procedure triage session estimation techniques management applicable foundational principles

Research Ideas

• Developing an AI-driven screening tool that can rapidly identify and monitor symptoms of depression. This AI-based tool could integrate the PHQ-9 responses and other AA data to collect detailed insights on mood changes over time, providing more accurate and customized detections of depression.
• Investigating potential correlations between age, gender, PHQ scores and daily happiness scores in order to better understand which individuals are most at risk for developing depression. Additionally, using this data to gain a better understanding of how daily moods may be linked to longer term mental health is highly valuable insight for medical professionals that could lead to improved treatment plans or interventions.
• Using the start time and period name variables as inputs for creating a predictive model that seeks out patterns in the occurrence of depressive symptoms over specific phases or times; helping medical professionals identify when patients may need additional guidance or resources during certain periods in their lives

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Dataset_14-day_AA_depression_symptoms_mood_and_PHQ-9.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .