Exploring Health Well-Being Scores Distribution among Caregivers

Apr 5, 2024, 12:59 PM

Distribution of Health Well-Being scores?

The distribution of Health Well-Being scores across 15 different metrics (HW1 to HW15) was visualized using histograms. Key observations include:
  • Variability: Each Health Well-Being score shows a different distribution, indicating variability in responses.
  • Common Patterns: Some scores tend to have higher frequencies in certain ranges, suggesting commonalities in certain aspects of well-being among caregivers.
  • Visualization: The use of histograms allows for an easy comparison across the different Health Well-Being scores, highlighting the diversity in well-being experiences among caregivers.

Explore correlations between Health Well-Being scores.

The correlation analysis of Health Well-Being scores revealed significant relationships between various metrics. Key findings include:
  • Positive Correlations: Certain scores, such as HW3 and HW5, show strong positive correlations, indicating that as one increases, so does the other.
  • Negative Correlations: There are also notable negative correlations, for example between HW1 and HW4, suggesting that improvements in one area may correspond to declines in another.
  • Complex Relationships: The correlations reveal complex relationships between different aspects of well-being, highlighting the multifaceted nature of health well-being among caregivers.

There is no significant difference in the Caregivers' Health - Wellbeing by sex and experience.

To investigate if there's a significant difference in Caregivers' Health-Wellbeing scores by sex and experience, we'll perform statistical tests. Specifically, we'll use:
  1. T-tests for comparing mean scores between two groups (e.g., male vs. female).
  2. ANOVA (Analysis of Variance) for comparing mean scores across more than two groups (e.g., different levels of experience).
We'll first clean the data to handle any non-numeric values, then proceed with the statistical tests.
The T-tests comparing Health Well-Being scores by sex show significant differences for several metrics. Specifically:
  • HW1, HW4, HW5, HW6, HW8, HW9, HW10, HW12, and HW13 have p-values below 0.05, indicating significant differences between male and female caregivers in these aspects of well-being.
  • Other metrics do not show significant differences based on sex.
Next, we'll analyze the impact of experience on Health Well-Being scores using ANOVA.
The analysis of Caregivers' Health-Wellbeing scores by sex and experience revealed:
By Sex:
  • Significant differences in several Health Well-Being scores between male and female caregivers, specifically for HW1, HW4, HW5, HW6, HW8, HW9, HW10, HW12, and HW13.
By Experience:
  • Experience levels significantly influence Health Well-Being scores in HW1, HW3, HW6, HW8, HW9, HW10, HW11, HW12, and HW13, as indicated by ANOVA tests.
These findings suggest that both sex and experience are important factors in the health well-being of caregivers.
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