Family Members' Views: What is Quality in Assisted Living Facilities Providing Care to People with Dementia?. 2.6 Analytic Methods


As noted, focus group data were collected in five forms: tape transcripts, structured notetaker forms completed during interviews, structured debriefing forms completed immediately after the focus group, "dot votes" on quality issues listed on flip charts during the focus groups, and a short survey completed by participants prior to the focus group interview. The use of such standardized data recording forms is critical for analysis of qualitative data.

All primary data from the focus group sessions were coded and entered into text-oriented analytic software. The short surveys completed by focus group participants were entered into a database that was analyzed using a software (i.e., Lotus) appropriate to producing simple descriptive statistics.

The initial lines of inquiry that guided our development of the moderator guidelines were based on a literature review also structured the general conceptual framework we brought to analyzing the resulting focus group data. The first step in this process was the creation of categories of codes. Following the completion of all the focus group meetings, RTI's full project team2 participated in a half-day meeting in which summaries of flip chart exercises and dot votes were presented and discussed. The team then used these lists to create the framework for the coding system used in qualitative analysis. The most commonly mentioned issues (and those that the focus groups gave the highest prior in their dot voting) were first divided into high level categories or domains, with sub-categories representing the full range of related issues raised by the groups. Exhibit 1 presents those categories and sub-categories.

We also took advantage of advances in qualitative research that have resulted in more systematic analysis of qualitative data. These advances include computer software to archive and analyze qualitative data and standardized analytical approaches. Furthermore, computer technology facilitates intercoder reliability checks and iterative coding techniques, both designed to reduce the subjectivity previously associated with qualitative data analysis.

After creating a coding system of major domains and, within these, sub-categories of topics or key issues raised during the focus groups, the transcribed tapes of verbatim comments were coded into the domains and sub-categories. Initially, all members of the project team discussed how they would code particular comments in order to generate discussion and consensus about how various issues and topics should be coded. In particular, we reviewed the lists from each focus group on which participants' "dot votes" were recorded and discussed how each of us would code particular responses. Next, transcribed data from one session and the "dot votes" from two focus groups were independently "double-coded" by two staff members. Then they compared their coding for the same data to determine whether there were any discrepancies. If they found discrepancies in their coding, they brought these to the project director for resolution. This process for enhancing reliability was important to ensure that we had reliability across the coders, particularly since we report the results of "dot voting" not only in terms of the content but also the frequency with which specific items or topics were cited by participants as the most important elements of quality. Then, throughout the coding process, the two staff performing the coding maintained frequent communication to discuss and reach agreement on interpretation or coding of any ambiguous data.

RTI staff then entered the coded data into a text-oriented data base, AskSAM, and sorted the data by codes, with cross-referencing of text having multiple codes. Following preliminary review of the sorted data by the 29 codes shown in Exhibit 1, we used the software to organize each coded comment into the five major domains. The resulting data were then presented by domain and sub-categories and analyzed for their content and meaning. This report presents these summary analyses. In addition, to maximize our use of these rich qualitative data, we include verbatim quotes that illustrate the overall tone and content of comments in a particular area. (It is important to note that the number of quotes presented in a topic area do not signify the prevalence with which the topic or issue was raised. Rather they are used to illuminate the topic or clarify different perspectives.)

  EXHIBIT 1. The Coding Scheme for Analyzing Comments on Quality  
  Major Categories or Domains   Sub-Categories of Topics
Staffing Features Training
Staffing levels/staff-resident ratios
Staff turnover
Communication with residents and family
Consistency of caregivers
Services Activities
Personal care
Alzheimer's specific services & approaches
Management of medications
Ancillary services
Food and meal service
Facility Environmental Features Safety
Alzheimer's specific features
Architectural lay-out
Aesthetic qualities of shared spaces
Room types
Aesthetic qualities of personal space
"Homelike" environment
Facility Policies Aging in place
Background checks on staff
Issues related to cost of care
Different levels of care
Separate units for residents with dementia  
Process of Shopping for a Facility Sources of information
Things to look for and to avoid

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