Correlation study on screen time and sleep

Aim

To find out if there is a correlation between estimated sleep duration and mobile phone screen time.

Hypothesis (directional)

There will be a negative correlation between the number of hours college students spend using their mobile phone and how many hours of sleep they get at night.

Variables

Co-variable 1 - estimated number of hours of sleep had the previous night

Why? - quick, easy and convenient method

Co-variable 2 - number of hours spent using a mobile phone (mobile phone data)

Why? - more objective than estimated duration

Null hypothesis

There will be no correlation between the number of hours college students using their mobile phone and how many hours of sleep they get at night.

Sampling

Opportunity sampling - quick and easy method of gathering participants from our target population e.g. we have access to a class of A-level psychology students.

What descriptive statistics were used?

Mean - We chose the mean because it takes into account all of the students sleep duration and mobile phone screen time data scores.

Range - We chose the range because it allows us to see the full dispersion of sleep duration and mobile phone screen time scores from highest to lowest values.

What graphical representations were used?

Scatter diagram - We used a scatter graph to display our data as we were looking for a correlation between two co-variables – number of hours spent using a mobile phone and number of hours of sleep

What statistical test was used?

Spearman’s rho - We used a Spearman’s rho statistical test because we are looking for a relationship between mobile phone screen time and sleep duration. We have collected ratio data as we are measuring both screen time and sleep in number of hours which has a true zero point. Finally, the data gathered is considered as related data as screen time and number of hours sleep were recorded from the same participant.

How did we assess reliability?

Test-retest reliability - the same group of A-level psychology students could complete the same questionnaire to provide data on their sleep duration and mobile phone screen time a week later and compare the similarity of the results to determine whether the study has good external reliability.

Issues of validity

Demand characteristics - participants were aware that the aim of the study was to find a correlation between sleep duration and screen time which may have caused them to alter their routine.

Social desirability bias - participants may have been embarrassed about their sleep duration or screen time. We improved this by providing anonymity.

How could we assess validity?

Content validity - we could ask an expert in the study of screen time and sleep duration to assess our procedures and measuring tools (estimated number of hours of sleep and mobile phone data) to determine if they are valid.

Face validity - we could test if our questionnaire measures sleep duration and screen time as it is supposed to by asking a naive respondent to identify what we are measuring by our measuring tools.

Ethical issues

Confidentiality - participants data on sleep duration and hours of screen time the previous night will be anonymised e.g. participants will be identified using numbers instead of names.

Risk of stress, anxiety, humiliation or pain - participants will be made aware of their right to withdraw themselves or their data on sleep and screen time at any point.

Valid consent - Participants will be provided with an introductory brief outlining the aims of the study. Participants were reminded within the brief that they have the right to withdraw before and after data collection, allowing them to make an informed decision about taking part.

Improvements

Issue - sample bias - due to opportunity sampling, only A-level psychology students took part. Therefore, the sample lacks population validity.

Improvement - Use stratified sampling to randomly select students from different courses at the college.