Questions,Methods, Sampling,Collection,Analyses,Findings & Conclusions (Research Paper Sample)

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Research Design
Most studies generally agree that a good quantitative study is one that underscores objective measurements and the statistical, mathematical, or numerical breakdown of data gathered using surveys, questionnaires, and polls. The same can be achieved through the manipulation of secondary statistical data by employing computational procedures. Specifically, researchers collect data with the aim of determining the relationship between an independent variable and outcome variables within a given a population (Creswell, 2013). Thus, of importance to researchers is to employ a quantitative research design that not only answers the research questions but one that can also be replicated by other researchers and produce similar results under the same settings. This paper provides a brief critical review of Edvardsson, et al., (2014) study that examined point-prevalence of engaging in daily undertakings for persons with dementia. Specifically, the paper seeks to determine whether the research design, sample, and methodology applied by the researchers make the findings they established reliable.
The study by Edvardsson, et al., (2014) sought to determine the point- prevalence of involvement in daily routines for individuals with dementia in a nationwide model of Swedish housing aged care facilities. The specific objective was to determine whether the residents taking part in daily routines lived in more-people-centered settings and if they enjoyed better livelihoods in comparison to persons not taking part in daily activities. In achieving the objectives of their study, the researchers adopted a cross-sectional research design in collecting data touching on activity involvement, unit person-centeredness coupled with the quality of life (p. 3). The study’s sample size comprised 1266 individuals enrolled in residential aged care. Among other findings, the study established that only 18% of the respondents took part in in routine activities as preparing coffee, setting or dusting tables, another 62% were engaged in outdoor walks, another 27% was active in parlor games, while 14% and 13% partook in expeditions and went to church in that order (p. 3). The study nonetheless concluded that respondents that were active in daily activities dwelled in more people-centered homes, led relatively better quality of life coupled with greater cognitive indexes paralleled to those that were reluctant to join any everyday activity.
As earlier pointed out, the researchers adopted a cross-sectional research design. A cross-sectional research, just like a longitudinal study, employs observation such that the investigators take note information regarding the respondents without controlling the study environment (Von Elm, et al., 2014). Nevertheless, Creswell, (2013) notes that the defining piece of cross-sectional studies is they mostly seek to relate different population groups at a given point in time and the findings established from whatever fits into the frame. Edvardsson, et al., (2014) cross-sectional study involved observing the daily activities of dementia patients living in more person-centered units and determining whether their quality of lives differed from those dementia patients not taking part in everyday activities.
The study’s use of a cross-sectional design could be commended given that not only did the researchers manage to stick to what pertains a cross-sectional study, but the fact that the target population was extended to the entire population of people leaving with dementia in Sweden. Creswell, (2013) theorizes that what makes the findings of a cross-sectional study valid is, but not limited, to the sample size selected. Specifically, studies in support of this notion argue that researchers have to be careful and select a sample size that can comfortably act as a representative of the target population (Von Elm, et al., 2014). Though one might regard the sample size of 1655 as being small for a representative of the entire Swedish population of people diagnosed with dementia, Edvardsson, et al., (2014) put a spirited fight in support of their sampling strategy and size. The authors note that their sampling strategy saw them recruit units using a nationwide system of community-based dementia care practitioners that were requested to deliver information to metropolises across the country. More precisely, the nurses were required to convince concerned boroughs to contact the investigators for involvement in the study. Such explains why the researchers regard their sample of 1655 that received a response rate of 89% as a geographically representative sample (p. 3).
Edvardsson, et al., (2014) employed structured questionnaires in the collection of their data. The questionnaires were based on the quality of life in late-stage dementia scale (QUALID) as designed by Weiner et al., (2000). Weiner and his colleagues developed the tool to act as a late-stage dementia explicit form with a one-week window surveillance. The tool affords info pertaining to a respondent’s quality of life using valuations made by proxy informers. Nevertheless, a section of studies fault the tool’s efficacy given that little is known regarding its ability to respond to changes in therapeutic intervention. For instance, Benhabib, et al., (2013) sought to investigate the tools effectiveness in enhanced neuropsychiatric indicators among individuals with Alzheimer syndrome and concluded that the tool is still incapable of reflecting changes when a therapeutic intervention is applied.
However, despite its apparent limitations, several studies have praised the tool given its abilities to obtain reliable estimates of quality of life for individuals diagnosed with chronic dementia and dwelling in long-term care centers. The QUALID scale is made up of 11 items that comprise both positive and negative proportions that possibly indicate an individual’ quality of life in late-stage dementia (Benhabib, et al., 2013). The tool rates items by the incidence of happening on a five-step scale with tallies ranging from 11 (indicating an optimal quality of life) to 55 (poorest quality of life). Nonetheless, in an effort meant to fix the apparent limitations in the data collection instrument, Edvardsson, et al., (2014) adopted a Swedish version of the QUALID developed by Falk, Persson, & Wijk, (2007). Unlike the typical QUALID scale, the Swedish version employs the Multi-dimensional dementia assessment scale (MDDAS) in collecting data regarding the stated prevalence of individual involvement in daily routines. Interestingly, compared to the typical QUALID scale, the MDDAS is known to have decent intra-and inter-rate consistency, implying that it is a more reliable measure of point-prevalence of individual partaking in daily routines (Edvardsson, et al., 2014).
Edvardsson, et al., (2014) study took a descriptive approach in the analysis of data with more attention given to the point-prevalence of individual involvement in daily routines. The independent samples t-tests was employed in exploring the sample variances coupled with dissimilarities in unit resident-centeredness, quality of life and cognizance amongst individuals that took part in daily undertakings and those that did not. Taking a significance level of 5%, the study analyzed the data using the PASW Statistics 18 (SPSS), a widely used program among market, health, education and government researchers in the analysis of numerical data.
The findings revealed that respondents engaged in outside strolls, expeditions, parlor sports, went to church, and carried housing-related activities recorded considerably better qualities of life and cognitive capacity relative to those that did not partake in such doings. Specifically, though no statistically noteworthy differences were proven in the relationship between quality of life and activity participation across the genders, statistically significant differences for the same were established when all the subjects were considered (Edvardsson, et al., 2014). However, in a twist of events, the study reported that only a significantly low number of the residents were engaged in the everyday activities contrary to expectations (p. 4). Though, the researchers failed to provide the overall percentage of the extent to which the day-to-day activities improve the quality of life, the respective percentages in every activity was sufficient to support their claim. Nevertheless, one would question the reliance on the independent sample t-test given the fact that the test does not supply much information regarding the distinctive impact of the everyday deeds