Quantitative Research Analysis and Hypothesis Development in Mental Health and Physical Activity Studies RES4021

Task 1: Exploring study designs

I. State if the article refers to a quantitative study or a qualitative study.

The quantitative study is under discussion in the article of Klos et al. (2024). The method used in this study is quantitative and involves the assessment of PA utilizing self-reported tools and objective tools. More pointedly, it uses statistical techniques like clustering, and analyses of covariance to examine PA behaviors and the changes in the pattern of these behaviors during a lifestyle intervention for adults with prediabetes. The study relies on partitioning around medoids algorithms to determine the study participants into groups based on self-reported activities and compare overall device-derived metrics such as PA levels, sedentary time as well as light and moderate-to-vigorous PA across these clusters. The purpose is to get a full understanding of how and to what extent various activity profiles and shifts in activity levels are associated with the findings of the intervention. These results have been derived from quantitative measures recorded from 232 participants and thus statistical means have been used to identify clusters and change patterns of PA over time. Thus, it can be pointed out that the presented study is based on quantitative research approaches both in terms of methods used and findings obtained.

II. Justify your answer for 'Question l' above i.e., how do you know this study is qualitative OR quantitative? Please refer to key aspects of the study including the methodology to justify your selection

Klos et al. (2024) have conducted a quantitative study based on their research. This classification is based on several methodological elements:

1. Data Collection and Analysis: The study employs quantification through self-administered data of daily behaviors and employing ActiSleep+ accelerometers. (Hickman et al., 2024) With these numerical data, quantitative analysis methods involving the use of the partitioning around medoids algorithm to carry out clustering and the multiple analysis of variance by covariant, various patterns, as well as differences that exist between the formed clusters, are determined.

2. Statistical Techniques: The comparison and analysis, that has been conducted using statistical measures on physical activity, sedentary time, and changes over time for the different clusters can be characterized as quantitative. More notably, the study quantifies the clusters differences in physical activity levels (PAL), sedentary time (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) (Juraki? et al., 2024).

3. Objective Measurements: Using device-based assessments also offers quantitative data based on physical activity which supports a quantitative analysis (Pardamean et al., 2020). These objective data are helpful to support the self-reported data; the latter is analyzed quantitatively as well (Reichert et al., 2020).
All in all, the method of statistical analysis and numerical values to describe physical activity behaviors during the intervention supports the quantitive character of the study.

III. Describe in your own words the specific purpose/aim of the above study.

1. Evaluate Changes in Physical Activity: Thus, using data from both diaries and accelerometers the authors hope to establish how participants physical activity is affected by the lifestyle intervention, targeted at enhancing the well-being of pre-diabetic individuals (Klos et al., 2024).

2. Compare Data Collection Methods: This work is going to contribute to identifying how subjective evaluation measuring physical activity and using subjective self-reports together with objective data can help to better understand PA patterns. This comparison assists in identifying the efficacy and shortcomings of each of the methods in establishing the changes caused by the intervention (Klos et al., 2024).

3. Inform Intervention Strategies: The results of this study will therefore be useful in enhancing precision in the administration of lifestyle intercessions to reveal aspects of exercise modality that may be useful in enhancing compliance to provide specifics regarding how aspects of physical activity can be parameterized and evaluated (Klos et al., 2024).

IV. Ethics approval was required for this research as it involved human participants. Identify three principles of research ethics and explain how they would have been important to consider for this specific study.

Informed Consent: According to the guideline, participants should be able to understand and make decisions on whether to participate in the study and this involves explaining to them the general details about the study, its main objective, the procedures that will be used, the risks involved and the benefits (Berekeyeva et al., 2023).
Confidentiality: The study is required to protect the identification data of participants including physical activity frequency and status of health which is sensitive data (Pham et al., 2024).

Beneficence and Non-Maleficence: It is therefore the respondents right to benefit from the research and not be harmed in any way by the study. The intervention to be prescribed to the participants should focus on enhancing health status specifically for those with pre-diabetes (Onyango & Kiarie, 2024).

V. Discuss three strengths and three weaknesses of this study.

Strengths

1. Dual Data Collection Methods: One of the strengths of the study is the collection of data using diaries and accelerometers to measure physical activity. This combination makes it possible to have a parallel comparison between self-perceived data on changes in physical activity level and more objective assessments hence increasing the accuracy of the two measurements (Klos et al., 2024).

2. Focus on a Relevant Health Issue: The intervention is aimed at grown-ups with pre-dynamics which can potentially open a way to type 2 diabetes. (Klos et al., 2024).

3. Detailed Statistical Analysis: The accelerometers enable the quantification of physical activity, and the detailed statistical analysis used in the study aids in determining the effect of a lifestyle change. Said approach enhances the robustness of this work and adds meaningful data concerning physical activity interventions outcomes (Klos et al., 2024).

Weaknesses

1. Potential for Self-Report Bias: While diaries afford more contextual information to the accelerometer data collected they are nevertheless self-reported data with recognized limitations including but not limited to recall bias or over-reporting. This procedure could result in a decline in the quality of information gathered and producing work and more so an impact on the analysis of data (Klos et al., 2024).

2. Limited Generalizability: Clearly, the results of the study might not be transferable to other groups of adults, including those with pre-diabetes or most segments of society or other types of lifestyle interventions. The findings could not be extrapolated to other populations or other kinds of intervention (Klos et al., 2024).

3. Data Management Challenges: Integration of data from two different data sources, the diaries, and the accelerometers may pose some challenges in their management and analysis. Processing and analyzing these multi-type data is a delicate process because of the possibility of generating contradictions and generating errors (Klos et al., 2024).

Task 2

Question-1

Quantitative Hypothesis

Regular physical activity is associated with mental health and wellbeing for adult men aged 18 years and above. The increased level of physical activity is correlated with reduced symptoms of anxiety and depression which can be assessed using the standardised mental health assessment tools namely Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder (GAD-7).

Research Background

Physical activity not only improves physical health but also enhances the mental well-being of an individual. It is known that people involved in routine exercises have improved hypothalamus-pituitary adrenal axis which lowers their symptoms related to depression and anxiety (Mahindru et al., 2023). However, there is a need to develop a quantitative relationship between the physical activity and mental health using the standardised assessment tools namely PHQ-9 and GAD-7.

Methodology

A cross-sectional survey will be performed which will involve adult men above the age of 18 years from community centres and local gyms. The data will be collected using questionnaries and in-person interviews. PHQ-9 and GAD-7 will be used as the standard assessment tool for determining the scores related to anxiety and depression. Here, physical exercise will be considered as a dependent variable while PHQ-9 and GAD-7 will be considered as an independent variable (Schuch & Vancampfort, 2021).

Data Collection and Analysis

The data is collected using surveys and in-person interviews. Statistical analysis will be done to calculate the relationship between physical activity and reduced levels of anxiety and depression using pearson coefficient. In addition to this, multiple regression analysis will be performed to determine a correlation between the physical activity of an individual and scores of PHQ-9 and GAD-7. This will help in determining the different factors such as age, socioeconomic factors, etc. which are associated with reducing the symptoms of anxiety and depression using physical exercise (Andermo et al., 2020).

Expected Outcomes and Implications

Through this hypothesis, increased levels of physical activity will significantly reduce the PHQ-9 and GAD-7 scores. It will pave the way for public health policies and mental health care professionals to promote the importance of physical exercise in reducing the symptoms related to mental health disorders.

Question-2

Research Question

How cultural beliefs and values influence the perspectives of adult aged women above the age of 18 years and their role in reducing the symptoms of anxiety and depression in them (Melnyk et al., 2020)?

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