Participant Selection and Sample Size
The prevalence of chronic diseases has been attributed to the changing lifestyle which seems to adhere to the economic pressures that demand that people work overtime. As a result, there is physical inactivity and lack of adequate sleep. Studies have shown that physical inactivity and not maintaining proper sleep increases mortality rates caused by cardiovascular diseases (Shiroma & Lee, 2010; Hoevenaar-Blom et al., 2011) among other chronic illnesses (Shan et al., 2015; Aune et al., 2015). According to the World Health Organisation (2017), 32% of adults worldwide are physically inactive, 29% of adults sleep for less than six hours (Hoyos, Glozier, & Marshall, 2015), over 50% do not have regular patterns of sleep, and only 24% experience quality sleep (Duncan et al., 2016). There exists an abundant proof of the association between physical inactivity and low sleep quality (Rayward et al., 2017). Conversely, there exists no known global statistics on the percentage of people who simultaneously experience inadequate physical activity and low quality sleep. Therefore, there is need of an intervention that factors in both aspects to make significant help to public health. Furthermore, an intervention addressing both sleep quality and physical activity is necessary because of the mutual association that exists between the two variables (Kline, 2014). Thus, the objective of this paper is to critique the recommended m-health intervention method aimed at reducing the prevalence of chronic disease rates alongside the related burdens in the adult population by assessing physical activity and sleep quality simultaneously. The COREQ checklist developed by Tong, Sainsbury, and Craig (2007) has been used to critique the study by Murawski et al. (2018) on m-health intervention to improve sleep quality and physical activity in adults.
The authors cited the Social Cognitive Theory (SCT) as the basis on which the study was underpinned. The authors provide different justifications for the selection of a theory-based approach. The researchers argue that existing evidence has shown that theory-based interventions have overtime proved to be more effective in behavior change (Prestwich et al., 2014). Abraham, Conner, & Norman (2013) assert that SCT is significant in the theoretical comprehension of variations in behavior because it takes into consideration the interfaces between the fundamental factors that affect behavior change such as the environmental processes. Thus, this approach is the most appropriate because the study focuses on both sleep health and physical activity which are both affected by environmental factors.
Data Collection Methods
The study reports detailed procedures on participant selection. The potential participants were recruited using digital advertising such as Twitter and Facebook, and electronic print-based media such as newspapers and magazines that were distributed countrywide. The advertisements were directed towards target audiences that met the inclusion criteria. This implies that a purposive sampling method was used in recruiting the participants. This design guarantees the collection of detailed information that is relevant to the study objective. The authors also provide in-depth information on the inclusion and exclusion criteria with an explicit checklist of the reasons for non-participation of some of the people. This minimizes the possibility of giving non-evidenced accounts.
The sample size of both the intervention and the control group as reported by the researchers is 80 for each group. This is important since it will enable the potential users of the findings to examine the diversity of perspectives included in the outcomes. Based on the nature of the study which involved online survey, the authors could not access the non-participants and provide the reasons for them not participating in the study. This would have reduced the possibilities of making statements that are not supported. The researchers could only assume that their non-participation was due to their inability to meet the inclusion criteria that is explicitly provided by the researchers.
The study participants were not with the requirement to report to the research center for data collection, but instead, all the data was collected through online surveys that evaluated both the primary and secondary results, in addition to the demographic information and moderating features. All the instructions and access to the app were emailed to the intervention group and then reminder messages on the regular use of the app sent. The researcher did not, therefore, have control over the place of data collection since data was collected via online surveys. Additionally, the researchers pilot-tested the online surveys and secured them before the actual survey. This prevented any alterations from being made when the research was in process, thus limiting any intrusions that would compromise the credibility of the feedbacks. The provision of detailed information on the setting of the study is fundamental to the readers because it shows whether the responses of the participants were influenced or not. Thus, the inability of the researchers to determine the presence or absence of the non-participants while the respondents made their feedbacks via online affects the credibility of the responses upon which the findings are based, and conclusions derived. Furthermore, the demographic data collected enables the readers to consider the bearing of the outcomes and inferences to their situations. The readers will also be able to determine whether the data is all inclusive and if different views from different groups were factored in (James et al., 2016).
The Intervention
The researchers have provided a comprehensive step-wise process on the intervention and data collection. The app was primarily used to monitor and gather data using its components namely response, self-monitoring, educational resource, and goal-setting. Guidelines on how these components were utilized in data collection have also been provided. For the first three months of intervention baseline data was collected using a messaging system that offered customized feedback on the progress in goal achievement, provoking a review of the goals and practices of the actual behaviors. Emails were also used to collect data. The provision of the procedures on data collection is significant because they improve the understanding of the readers regarding the focus of the researchers and to allow them to ascertain whether the respondents were encouraged to provide their opinions freely. The report on the duration of the intervention is vital as it gives an indication of the amount of data obtained and whether the sample is a true representative of the entire population and whether it’s possible to generalize the findings. However, the researchers did not provide a basis for using emails and messaging system to gather data.
The study also reports the use of goal review strategies in which the participants are emailed customized weekly summary of their performance in the previous week and are allowed to re-assess and adjust their goals accordingly to meet the recent progress and promote self-efficacy. The detailed report on the data collection and method and any adjustments on the same improve the richness of the data. Additionally, the fact that the respondents checked their progress performance and assessed than about the goals they had initially set gives the accurate reflection of the opinions of the participants (James et al., 2016) thus minimizing any possible biasness due to the researchers’ interference. This also increases the validity of the interpretations of the researcher. However, the researchers only relied on the initial participants, and the credibility and reliability of their findings were to be based on the fact that the results were compared with a control group and the differences determined. However, the credibility and reliability of the findings could have been strengthened the more if there was a repeat of the same experiment with different participants due to their inability to control the settings of the participants while keying in their feedbacks.
There was data collection during and after the study. For instance, the participants could key in data at any time, and then they are sent the weekly summary of their progress in order to work towards achieving the objectives they had initially set or re-align them accordingly. The continual collection of data enables early detection of errors and correction accordingly thus increasing the authenticity of the findings.
Goal Review Strategies
There were more than one data coders. The random allocation of the participants to the two study groups was done by an independent researcher. Furthermore, an independent statistician supervised the analysis of the primary outcomes. According to Zohrabi (2013), the use of multiple data coders in research is significant as it points out to a comprehensive understanding of the study topic. The primary analyses were aimed at assessing the variations in the study variables between the control and intervention group. An explicit process of data coding and analysis has been provided for each identified theme in primary outcomes such as physical activity, and sleep quality, and secondary outcomes such as stress, depression and anxiety, resistance training among others. According to James et al. (2016), detailed descriptions of the coding and memoing process is an indication of the researcher’s perception, assessment, and understanding of the data. This further increases the credibility of the outcomes.
The researchers report having used the Generalised Linear Mixed Models (GLMM) in approximating the differences between sleep quality and physical activity between the groups. Furthermore, the effect of missing data on the findings was assessed using the Pattern Mixture Modelling. The collected data was keyed into Qualtrics in the form of a text file and later imported to statistics software for analyses. A summary of the outcomes will be sent to the participants as well. The use of software by researchers to store, assess, and code qualitative data in addition to obtaining comments on the outcomes by the participants strengthens the validity of the inferences made by the researcher. This is because it is an assurance that the actual perspectives of the participants were represented in the study and not manipulated by the researchers to meet their objectives (Pagel & Kwiatkowski, 2010).
The authors in their reporting have not included participant quotations to illustrate the various themes identified from the outcomes. According to Lopresti, Hood, & Drummond (2013), the use of direct quotations from participants in qualitative research is significant as it strengthens the transparency and trustworthiness of the outcomes and inferences. This might be due to the nature of the study because all the primary and secondary variables were measured using standardized instruments which captured quantitative information only. However, the inclusion of direct quotations on measurements that were based on the Linkert scale could have been included to at least strengthen the transparency and trustworthiness of the results and interpretations. But the study has not provided the data findings of the research but a rationale and techniques related to implementation and assessment of a theory m-health intervention.
Conclusion
The study doesn’t include the findings from the participants, but instead, it has provided the measurement and assessment instruments to be used to measure every sub-theme identified in the study. It can be said that there is the possibility of clarity among the primary themes and coherence between the expected data and the outcomes because under each sub-theme there is presented a standardized instrument to be used in the assessment and measurement of the participant feedback. Furthermore, references are made on the effectiveness of each measurement as used in other studies in addition to summary interpretations. For instance, under the theme of mediators and moderators, the authors have indicated that the sub-theme sleep hygiene will be measured using a 13-item Sleep Hygiene Index (SHI) designed by Mastin, Bryson, & Corwyn (2006). The authors further demonstrate the standard interpretation of the scores and that it has an internal consistency of alpha 0.66 and test-retest reliability of 0.71 in addition to the interpretations of its correlations.
The authors have presented the major themes to be considered in the findings. The major themes include primary outcomes, secondary outcomes, process outcomes, mediators and moderators, and power and sample size. Under these themes, several sub-themes have been discussed in detail with each one having a description of the standardized measurement instrument, validity and reliability and the global interpretation of the scores.
The study has established techniques to be used in the implementation and assessment of a theory m-health intervention integrated with individualized support aimed at promoting both physical activities and sleep health in Australian adults. Based on the demonstrated trustworthiness of the study, it is expected that the outcomes will provide a wealth of knowledge to the health professionals in the development and implementation of m-health interventions to help reduce the incidence of chronic diseases. There is a need for adequate information on attrition in m-health interventions so as future studies have large representative samples (Ho et al., 2015).
References
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