EPID1000 Foundations of Biostatistics and Epidemiology

eeks. The longitudinal effect would help immensely in identifying the singularities and reduces these random effects of the respondents. After collecting information from 400 respondents (large enough for effect size), the descriptive and inferential analyses would be performed to establish the relationship between the variables.

The four groups of the study (gender specific) would be (experimental group) smartphone dependent individuals with significant agreeableness, smartphone dependent individuals without significant agreeableness and (control group) smartphone independent individuals with significant agreeableness, and smartphone independent individuals without significant agreeableness.

ANS:

The present research could also be designed based on the case-control model of the survey. The sampling procedure would identify the difference in personality traits scores of respondents, and then assess the comparative analysis of smartphone dependency based on gender. The study would be conducted with the help of questionnaire survey method focusing on the Big 5 personality score. The observational study effect would help immensely in identifying the respondents based on their extraversion, conscientiousness, agreeableness, openness, and emotional instability.

The four groups of the study (gender specific) would be (experimental group) individuals of high agreeableness with smartphone dependence, individuals of high agreeableness without smartphone dependence and (control group) individuals with low agreeableness with smartphone dependence, and individuals with low agreeableness without smartphone dependence.

ANS:

The findings in the research were not considered as significant due to the high significance level. Considering that the p-values of the correlations were greater than the value of alpha () at 5% level of significance, the findings were not considered as significant.

Wakayama Smartphone-Dependence (WSD) sub scales were compared for the two genders. Difference of scores on subscale 1 for males (M = 5.2, SD = 3.1) and females (M = 4.9, SD = 2.9) was not found to be statistically significant as p = 0.52 at 5% level of significance. Similarly, difference of scores on subscale 2 for males (M = 9.7, SD = 3.8) and females (M = 11.0, SD = 4.0) was not found to be statistically significant as p = 0.07 at 5% level of significance. Difference of scores on subscale 3 for males (M = 13.2, SD = 8.6)and females (M = 13.8, SD = 3.7) was also not found to be statistically significant due to p = 0.36, and difference of scores on WSD scale for males (M = 28.2, SD = 8.6)and females (M = 29.7, SD = 8.4) was not found to be statistically significant as p = 0.32 at 5% level of significance.

ANS:

Spearman’s correlation was used to measure the association of WSD subscale variables and general health attributes.

Pearson's correlation is used to find a correlation between two continuous normal variables. The responses were collected from the respondents about their smartphone dependence on a Likert scale. Responses for GHQ-28 subscale were found to be not normal. Likert scale is ranked values instead of continuous data. Spearman's correlation was used for measuring the association of the ranked WSDS data with not normal GHQ-28 data, instead of Pearson’s correlation.

ANS:

Correlation between smartphone dependence and personality traits was evaluated by Pearson's correlation coefficient. The study was done separately for the two genders. Men who were greatly dependent on their smartphones were found to be adverse on agreeableness. Correlations of agreeableness with WSDS 1 (r = -0.26, p < 0.05) and WSDS 2 (r = -0.41, p < 0.01),  and WSDS 3 (r = -0.39, p < 0.01) were found to be statistically significant. A significant positive correlation was observed for WSDS 2 and emotional instability (r = 0.24, p < 0.05) at 5% level of significance. No other significant correlation values were observed for smartphone dependence and personality traits for men. Social involvement of men, responsiveness, and perception about society was not related significantly with smartphone dependence. Hence, it could be concluded that the personality traits of men, other than the ability to agree to different social conditions, were not related to smartphone usage. It could also be inferred that smartphone dependence was making men irritated enough to agree on various issues. For females, significant correlation was observed for WSDS 3 and extraversion (r = 0.37, p < 0.01) at 15 level of significance. No other significant correlations were present for females. Females were found to be totally independent of the effects of phone usage and dependence. In some instances, social involvement was positively affected by cell phone use (WSDS3). Probably, respondent females had very strong characters to get affected by the different smartphone usage problems.

ANS:

Pearson’s correlation value for the linear association between Extraversion and dependency on Smartphone (WSDS 3) for men was r = 0.18 in a positive direction.

For men, use of Smartphone while doing something else and neglecting etiquette was noted to have a low positive correlation (r = 0.18) with extraversion quality. The correlation between the variables was statistically not significant, which implied that the correlation value might have been due to the influence of some other external factor or might have happened purely by chance. Enough statistical evidence was not found for a considerable correlation between WSDS 3 and extraversion of men. From a realistic point of view, quality of enjoying the presence of people in a social gathering or getting importance from people (extraversion), do not go with the image of use of Smartphone while doing something else and neglecting etiquette. Hence, the correlation value of r = 0.18 was also not practically significant, and the direction (positive) of the correlation was also not acceptable.

ANS:

The value of Pearson’s correlation between conscientiousness and WSDS 2 of females was r = -0.14. The low and negative correlation between the variables was statistically not significant, which indicated that the value of the correlation coefficient might have been due to the influence of some other external factor. Enough statistical evidence was not found for a significant correlation between WSDS 2 and conscientiousness of females. From a realistic point of view, awareness about the surroundings or responsiveness of an individual is not compatible with the practice of using the smartphone for extended periods of time and neglecting social obligations. Hence, the correlation value of r = - 0.14 was also not practically significant, though the negative sign of the correlation was acceptable considering the characteristics of the two attributes.

ANS: Critical appraisal of the present article has been presented as follows.

The researcher, in the existing article investigated the relationship between dependence on Smartphone and personality qualities, and health conditions. The study was confined within the medical students of the university, which indicated that the responses were collected with a convenience sampling method. The selection of the particular sampling methodology produced biasness in the sample data. Adoption of the longitudinal survey could have eliminated the inherent errors of the sample. Effect of unusual conditions, such as the depressive mental status of the respondent, the distance of workplace from home, special medical conditions would have been eliminated from the sample. Though the study maintained the ethical protocol of the university, the exclusion criteria for the article (out of 184 responses, inferential analyses were performed for only 140 students) have not been specified by the scholar. Age distribution of males (N = 87, M = 21.2, SD = 2.1) and females (N = 53, M = 20.8, SD = 1.6) in the sample was noted as achieve of convenience sampling. The study was confined within the periphery of the university, and this reduced the generality of the study. This cross-sectional study yielded difference in use of Smartphone for the males (M = 170.4, SD = 113.5) and females (M = 130.5, SD = 99.1) as significant (t = 2.07, p < 0.05) factor. The effect size of the sample of 140 respondents was found from the daily Smartphone usage and was found to have a small effect size (Cohen’s d = 0.37) for the cross-sectional study.

Normality of the three scales WSDS (Wakayama Smartphone- Dependence Scale), GHQ – 28 (general health status), and TIPI (10-item Personality Inventory) was confirmed from the Kolmogorov-Smirnov test. For normally distributed TIPI scale, Pearson’s correlation was used; otherwise for GHQ – 28 nonparametric Spearman's correlation test was performed. Though the research hypotheses were not detailed, the inferential analyses were based on scrutinizing the correlation between the three scales and their subscales. The correlation tests were performed in accordance to the satisfaction of the assumptions.

No statistical significance was found in the gender wise cross-sectional analysis for the WSDS scale (Male: M = 28.2, SD = 8.6, Female:  M = 29.7, SD = 8.4, p = 0.32) for the present sample data. Convenience sampling could have been the reason for the result. Correlation of usage of Smartphone for extended periods of time (WSDS 2) was found to have a statistically significant correlation () with anxiety about the physical condition (SSD) for men. Similar paradigm was visible for females () at 5% level of significance. For females, correlation of WSDS 2 with depression (), and WSDS 3 with social dysfunctional () was also statistically significant. The results were in line with previous works of literature and were practically significant in nature. Men’s addiction to internet surfing (WSDS 1) (r = −0.26, p < 0.05), WSDS 2 (r = −0.41, p < 0.01), and WSDS 3 (r = −0.39, p < 0.01) was found to have statistically significant relation with agreeableness quality. For females, WSDS 2 had significant relation with somatic symptoms (r = 0.39, p < 0.01).

Effect of Smartphone dependence was established to have the expected effect on various personality traits. The gender difference in this cohort analysis was in parity with earlier research works. The sample data justified the conclusions made by the scholar about the association of the scales.