The Sampling Procedure
This paper reviews a qualitative study by Daelemans, Vandevoorde, Vansintejan, Borgermans, and Devroey (2013) that examined the physicians’ utilization of family history data inpatient treatment. The study identifies its target population as the family physicians in a Belgian university called the Vrije Universiteit Brussel or VUB. The physicians also served as supervisors of students training in family medicine. The accessible population totaled 200 physicians, whose personal details, including “gender, workplace category, type of practice, and years of experience,” were available in the university’s database (Daelemans et al., 2013, p. 4). The study used non-probability sampling to select 16 participants who were included in the final sample. However, the authors do not name the specific sampling method they used to select the study sample.
The authors describe their sampling method as being two-phased. In the first phase, email notifications were sent to all physicians, but only ten agreed to participate. This sample could not yield sufficient data. Consequently, an additional six participants were recruited from the non-responders. The sampling approach was appropriate for the study because it ensured proportionate participation and saturation of data. The participants’ demographic characteristics, such as gender, work experience, training, and practice location, were analyzed and presented in the form of a table. The sample size (n = 16) for this study was not adequate, as it falls outside the 5% margin of error (Russell & Gregory, 2003). As such, the sample size is not representative of the accessible population of 200 family health physicians. Sampling biases arising from the selection and screening of the participants are not identified in this paper. In addition, the authors have not discussed the subjects’ dropout rate or non-response during the interviewing process.
Data Collection Procedures
The research article reports that data were collected through in-depth interviews by the authors. Daelemans and Devroey checked for the saturation of data through thematic analysis. Information regarding when the physicians seek information about the patient’s family history, kinship relationships as well as the dependability, importance, and limitations of such information was collected between “November 2011 and February 2012” (Daelemans et al. 2013, p. 5). In the study, data collection involved personal and telephone interviews.
In the study, the level of measurement was appropriate, as the values assigned to the variables tested were based on the number of responses received. A level of measurement describes the nature of values assigned to the different variables (Russell & Gregory, 2003). In the report, the authors describe in detail the instrument they used to collect data, i.e., the questionnaire. The description of the semi-structured questionnaires used to collect data is thorough, as it includes a sample of the fixed questions asked. This instrument was adapted from the interview questions employed in Mathers et al.’s (2010) research, which focused on family genealogy. The researchers conducted a pilot interview to test for the reliability of the questionnaire prior to the main study. Based on the data obtained from the pilot interview, 23 questions were found to be reliable and thus, included in the final questionnaire.
The validity of the questionnaire was achieved through cross-case comparisons. In this regard, the researchers ensured the contextual validity by comparing the interview responses of the participants to establish whether the results are true and valid (Creswell, 2009). They found the results to be consistent, which underscored the validity of the instrument. A pilot interview, involving one respondent, was done prior to the actual study. The authors used a similar questionnaire to conduct the pilot interview.
Data Collection Methods: General Criteria
The authors describe in detail the method used to collect data in this study. Data collection involved the interviewing method. The sixteen participants were interviewed using semi-structured questionnaires in sessions lasting between nine and thirty minutes. Either a personal or telephone interview was conducted depending on the respondent’s availability.
The researchers hypothesized that understanding a patient’s family history enhances the quality of primary care given. The interviewing method was appropriate to test this hypothesis, as it allowed the views of the family medicine practitioners (the respondents) to be explored. The study involved a psychological method to collect the views of the participants regarding their use of family history inpatient treatment. However, a physiological method might have gathered more valid and objective data. In this study, only the interviewing method was used to collect data. The study would have benefitted from other data collection methods like observation and focus groups.
In this study, 23 semi-structured questions were included in the questionnaire administered to the participants. The authors estimated that it took the respondents between nine and thirty-three minutes to complete the questionnaire. The authors administered the questionnaires to the respondents providing their answers in one session. Thus, the response rate was 100 percent. The sampling biases related to the participant screening and recruitment are not discussed in the article. The sampling biases may have affected the representativeness of the sample. The respondents were assured of confidentiality before signing an informed consent to participate in the survey.
Before the interview began, the participants were informed that the session would not take more than thirty minutes. This duration was based on the results of the pilot interview. The interview sessions spanned between nine and thirty-three minutes for both personal and telephone interviews. The article does not state whether the interviewers underwent training to prepare them for the interviews. The five authors conducted the interviews, transcribed, and analyzed the data. Confidentiality was assured through the digital recording of the participants’ responses. The participants interviewed by telephone gave verbal responses that were recorded using an audiotape. In the article, the actual identities and contacts of the participants are not revealed to the reader.
The only data collection method used is interviewing. The authors did not use additional methods, such as the semantic differential, to collect data. Questionnaires containing semi-structured questions were administered during the interviews. The authors included additional questions to probe each issue further. The authors do not describe any other data collection method besides the interviews. Moreover, no other scoring method or data collection instrument is described beside the questionnaire.
Descriptive Statistics
This study utilizes qualitative data analysis techniques, including descriptive statistics, to analyze the results. Descriptive statistics are methods used to summarize the key aspects of qualitative data (Trochim & Donnelly, 2006).). They describe the common themes present in data using descriptive measures. The authors used descriptive statistics to describe the demographic characteristics of the participants, including their average experience in years, distribution in health care centers (rural or urban), and family history training. The authors also used descriptive statistics to describe the percentage of patients who had their family background checked by the physicians.
Three types of descriptive statics were included in the study. These include distribution, central tendency (mean), and dispersion. With regard to distribution, the authors used descriptive statistics to describe the participants’ age and gender. The participants were aged between four and forty years and included nine female and seven male physicians. Their average experience in family medicine was 19.4 years (Daelemans et al., 2013). The participants were equally distributed between rural health centers and city clinics. With regard to the nature of their practice, the number of family practitioners who practiced alone, as a duo, and as a group was four, three, and nine physicians respectively.
The descriptive statistics used in the study were appropriate because the variables measured could only be expressed using averages, percentages, and other measures of distribution. Variables, such as the number of patients who had their family records examined, the instances where case history was needed, how it was inquired, and its reliability, were expressed using measures of descriptive statistics. The measures of central tendency and variability were both presented in this study. The authors presented the physician’s experience in family health practice using the mean. The average experience, in years, was 19.4 with a standard deviation of 11.7 (Daelemans et al., 2013). The range is a measure of variability that shows the spread in a dataset (Trochim & Donnelly, 2006). The authors indicated that the subjects were aged between four and forty, representing an age range of 36.
The demographic characteristics of the participants are clearly presented in the article. The authors use descriptive statistics to describe the subjects’ demographic characteristics such as age, gender, nature of the practice, and work experience. The demographic characteristics, besides being presented within the text, are summarized in the form of a table. The information contained in the table matches with the details given in the text of the article.
Inferential Statistics
Inferential statistics give conclusions and inferences about a population based on the sample data (Creswell, 2009). In this article, inferential statistics are presented using a thematic analysis. The authors made a cross-case comparison to identify common themes. The inferential statistics for comparing data, such as ANOVA and t-test, were not used in the thematic analysis because the study only collected qualitative data. The authors indicate that they used thematic analysis to analyze the results and draw conclusions. The information presented is not sufficient for the reader to determine whether the inferential tests used were appropriate or not. The conclusions given in the article are based solely on the thematic analysis results.
In the article, the reader is not provided with the specific value of the inferential statistic used. Additionally, the degrees of freedom, which describe the independent measures in a study, is not given. The level of significance the authors used to determine the statistically significant results is also not clear to the reader. Parametric tests, which are important in inferential statistics, allow researchers to draw more conclusions than non-parametric measures do (Creswell, 2009). However, the study did not use parametric and non-parametric tests. The qualitative data were only analyzed using a thematic analysis. In their study, the authors did not use any statistical test, which means that the number of groups and the sample size were not considered.
The study hypothesized that family history screening improves the quality of primary care (Daelemans et al., 2013). However, the authors do not present inferential statistics to test the validity of this hypothesis. The hypothesis is validated based on the results of the thematic analysis. However, the results of inferential statistics are not clear in the article. Moreover, the article does not use tables or graphs to present the results of inferential statistics. Instead, the authors use tables to present the results of the descriptive statistics.
References
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The Use of Family History in Primary Health Care: A Qualitative Study. Advances in Preventive Medicine, 2(1), 1-8. Mathers, J., Greenfield, S., Metcalfe, A., Cole, T., Flanagan, S. & Wilson, S. (2010).
Family history in primary care: understanding GPs’ resistance to clinical genetics—qualitative study. British Journal of General Practice, 60(574), 221–230.
Russell, C. & Gregory, D. (2003). Evaluation of qualitative research studies. Evidence Based Nursing, 6(1), 36-40.
Trochim, W. & Donnelly, J. (2006). The Research Methods Knowledge Base. Cincinnati, OH: Atomic Dog Publishing.