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Statistical Analyses


Data analyses focused on descriptive statistics (frequency counts, histograms, etc.) to look at the characteristics of the data and help identify any problems or errors in data entry, and paired t-tests and chi-square tests, as appropriate, to look at pre/post differences in the numerous measures as they relate to the study hypotheses.

For purposes of analysis, Hypothesis 1 was broken down into four sub-hypotheses: Workshop participants will demonstrate a) improved health-related self-efficacy; b) improved nutritional awareness and behaviors; c) increased use of stress management techniques; and d) improved physical fitness. For all sub-hypotheses it is expected there will be no change for the Control group.

There also are a number of measurable Outcomes that are logical extensions of the hypotheses explicitly stated for this study. It is expected that the Workshop group will: a) experience fewer secondary conditions than at the beginning of the study; b) demonstrate improved physiological health; c) demonstrate improved psychological health; d) perceive an improved quality of life; e) demonstrate a change in their health knowledge; f) demonstrate a change in their health beliefs; and g) demonstrate a change in health behaviors. For all of these Outcomes it is expected that there will be no change for the Control group. Each of these Outcomes was analyzed using data from the Home Survey instruments.


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