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LongitudinalCaring

tags: longitudinal, kindness, public health

Note: This is an AI-generated dataset so its content may be inaccurate or false

Dataset Description:

The 'LongitudinalCaring' dataset is designed to explore the relationship between kindness and public health outcomes over time. The dataset tracks individuals' exposure to kindness-related behaviors and activities and how these may correlate with various health metrics. The longitudinal nature of the data allows for the analysis of time-varying confounding effects, where past exposure to kindness could influence both the exposure and health outcomes being studied. The dataset includes various potential confounding variables such as socioeconomic status, age, gender, and prior health conditions to control for their effects in the analysis.

CSV Content Preview:

participant_id,time_period,kindness_exposure_score,health_outcome_score,socioeconomic_status,age,gender,prior_health_conditions,label
001,2015,7.5,85,Middle,35,Male,None,Positive_Care_Received
002,2015,6.0,78,Low,29,Female,Chronic_Illness,Mixed_Care
003,2016,8.2,90,High,40,Male,None,Positive_Care_Received
004,2016,5.4,82,Middle,32,Female,None,Neutral_Care
005,2017,9.1,92,High,41,Male,Diabetes,Positive_Care_Received

Source of the data:

The dataset was generated using the Infinite Dataset Hub and microsoft/Phi-3-mini-4k-instruct using the query 'time-varying, kindness, past exposure, longitudinal, confounding':

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