Data Analysis
The data analysis strategy included interpretive analysis with subsequent content analysis.
This plan merged both qualitative and quantitative approaches necessary for inclusion of
participants’ subjective views and for objective confirmation of identification of happiness
themes. Data analysis for the first study phase used interpretive analysis, including three
components: descriptive (gender, age and context for happiness), topic (identifying all
themes of happiness; use of in vivo codes – those in the words of the study participants), and
analytic coding (reviewing data over time to refine themes) (Morse & Richards, 2002). One
researcher conducted this inductive and exploratory interview process and also coded and
revised themes in the interviews. Components of happiness materialized through use of this
reflective and iterative process.
Once these codes were identified, the same researcher created a Code Book with definitions
of each theme and explained its use to two professionals from other disciplines: psychology
and social work. These professionals used the Code Book to perform content analysis,
defined as: “systematic, objective, quantitative analysis of message characteristics,”
(Neuendorf, 2002, p. 1). This was the second phase of data analysis. Inter-rater reliability
was assessed through independent engagement in this activity. The coders were charged
with the task of matching codes from the Code Book with previously identified segments of
the transcripts. Once each coder completed identification of codes, percent agreement was
computed for a validity check. Methods used to heighten trustworthiness of data included:
prolonged engagement with the participants, triangulation of coders from different
disciplines, and member-checking within interviews.