Note: This document extends the poster presnted at APS 2019; however data collection is ongoing for the final sample size and therefore the data below reflects a preliminary analysis.
Abstract
The rising prevalence of smartphones has prompted research about how they can impact cognitive abilities. We explored: (1) individual differences in how people feel towards and interact with their smartphones, (2) how smartphones affect different aspects of cognition, and (3) interactions between individual differences and these effects.
Supporting Summary
Smartphones are nearly ubiquitous and as a result, researchers have begun to study whether or not there are negative consequences that result from this ubiquity. The rising prevalence of smartphones has prompted research about how they can impact cognitive abilities. Interestingly, recent research has found that even the mere presence of a smartphone can impact cognitive functioning and diminish attention. Ward et al. (2017) found that smartphone location can impact cognition. They asked participants to complete cognitive tasks that required attention while leaving their smartphones either on the desk, in their pocket/bag, or outside of the testing room. Without receiving any notifications, participants showed lower performance on a cognitively demanding task.
In the present study, we explored: (1) individual differences in how people feel towards and interact with their smartphones, and (2) how smartphones affect different aspects of cognition. For the first study, participants completed four questionnaires, which measured individual differences: the Smartphone Dependency Questionnaire, which measures how dependent one feels towards their phone (Ward et al.); the Mobile Phone Involvement Questionnaire, which measures the level of connection to one’s phone (Walsh et al., 2010); the Nomophobia Questionnaire, which measures fear of being separated from or inability to use one’s phone (Yildirim & Correia, 2015); and a Smartphone Use Questionnaire, which was designed for the pilot study to measure typical smartphone use and frequency of use.
For the second study, we used the 12 Cambridge Brain Sciences (CBS) tasks to investigate a variety of cognitive mechanisms. These short, computer-based tasks assessed various aspects of cognition, such as: reasoning, memory, attention, and verbal ability (Hampshire, Highfield, Parkin, & Owen, 2012). As seen in Ward et al., participants placed their smartphones in different locations: either on their desk or outside of the testing room while completing the CBS tasks. Participants were randomly assigned to their smartphone condition and then completed the CBS tasks in a random order. Our predictions for this study were mainly exploratory: we are investigating which aspects of cognition are affected by smartphone use and, therefore, we did not have explicit predictions for each aspect of cognition. The present studies demonstrated people’s typical smartphone use, how people interact with their smartphones (i.e., individual differences), and the mechanisms behind smartphone’s effect on cognition. These findings will help guide future research investigating the specific mechanisms behind smartphones’ effect on cognition.
Analysis Prep
Load Libraries
The following libraries were used for this analysis:
# install.packages(ggplot2)
library(ggplot2)
# install.packages(kableExtra)
library(kableExtra)
# set options for kable tables for all future tables
options(knitr.table.format = "html")
# install.packages(RColorBrewer)
library(RColorBrewer)
#install.packages(ggpubr)
library(ggpubr)
# install.packages(dplyr)
library(dplyr)
# install.packages(tidyverse)
library(tidyverse)
#install.packages(tidyr)
library(tidyr)
#install.packages(plyr)
library(plyr)
Import Data Files
Four data files will be used in these analyses (pilot study- 1; main study- 3)
1. Pilot Study Data
#this will import the raw excel data file for the pilot study
#this file has been ananymized, so any identifiable information has been removed
pilot_prelim_raw = read.csv("Pilot_prelim_data(may15).csv", header = TRUE)
This is the primary data file for the pilot study. It contains responses to the 4 pilot quiestionnaires:
- A Smartphone Use Questionnaire (made for the present study)
- The Nomophobia Questionnaire (NMP-Q; Yildirim & Correia, 2015)
- The Mobile Phone Involvement Questionnaire (MPIQ; Walsh et al., 2010)
- The Smartphone Attachment and Dependency Questionnaire (SAD; Ward et al., 2017)
(1) Smartphone Use Questionnaire - General Notes:
Paradigm Decision Questions
- These questions asked participants to report their general smartphone use with respect to (1) Power, (2) Location, and (3) Comfort Level. These are the key questions in the pilot that were used to decide the design of the main study.
Power Questions
All power questions were answered on a 7-point likert scale as follows:
PD_P_1: “I tend to turn my phone off when I am not using it.”.
PD_P_2: “I tend to have my notifications turned on.”
PD_P_3: “I tend to have my phone on vibrate.”
PD_P_4: “When I study, I typically keep my phone on.”
PD_P_5: “When I write an exam, I tend to keep my phone on.”
PD_P_6: “When I am in a lecture, I tend to keep my phone on.”
PD_P_7: “When I sleep, I tend to keep my phone turned on.”
Location Questions
All power questions were coded as follows:
PD_L_1: “Typically, I keep my phone:”
PD_L_2: “When I study, I keep my phone:”
PD_L_3: “When I write an exam, I keep my phone:”
PD_L_4: “When I am in a lecture, I keep my phone:”
PD_L_5: “When I am in a social setting (i.e., with friends, family), I keep my phone:”
Comfort Level Questions
All comfort level questions were answered on a 7-point likert scale as follows:
PD_C_1: “I am comfortable with letting others use my phone.”
PD_C_2: “I leave my phone unattended.”
PD_C_3: “I leave my phone with other people.”
PD_C_4: “I make sure my phone is locked when it is not in my hands.”
PD_C_5: “I would feel comfortable leaving my phone in another room while completing a task.”"
Exploratory Questions
- The following provides some notes on the exploratory quesitons in the study
Screen Time Questions
Screentime (ST) is an Apple application which tracks your device usage over time. This includes, but is not limited to: total hours used, notifications received, most used application, etc. The following provides some notes on the ST-specific questions (7 items in total).
- ST_1 refers to whether a participant reported currently owning an iPhone. Note: it was assumed that all iPhone users had access to the ST application on their smartphone. This was coded as follows:
- ST_2 refers to participant’s mosted used application (according to ST). This was coded as follows:
- 1 = Games (e.g., candy crush, clash of clans)
- 2 = Social Networking (e.g., Instagram, Facebook, Snapchat)
- 3 = Entertainment (e.g., music, YouTube)
- 4 = Other
ST_3 refers to participant’s most used application was ‘other’ (according to ST). This was a open response item, where “NA” denotes “other” was not chosen.
- ST_4 refers to whether a participant’s most used application was their text / messenger application (according to ST). This was coded as follows:
- ST_5 refers to participant’s weekly total screen time in hours (according to ST). This was coded as follows:
- 1 = 0-10
- 2 = 11-20
- 3 = 21-30
- 4 = 31-40
- 5 = 40+
- ST_6 refers to participant’s total “Pick-ups” per day (according to ST). “Pick-ups” refers to the number of times someone picks up their smartphone, regarless of whether the smartphone was used. This was coded as follows:
- 1 = 0-50
- 2 = 51-100
- 3 = 101-150
- 4 = 151-200
- 5 = 200+
- ST_7 refers to participant’s average notifications per day (according to ST). This was coded as follows:
- 1 = 0-50
- 2 = 51-100
- 3 = 101-150
- 4 = 151-200
- 5 = 200+
Distraction Questions
These explored how participants report feeling or being distracted by their smartphones during various settings.
Distr_1 shows the response to the question: “I find my phone can distract me from my daily activities (e.g., work, school, social interactions).”. This was coded as follows:
- Distr_2 shows the response to the question: “I find my phone distracting during this study.”. This was coded as follows:
- Distr_3 shows the response to the question: “In general, I find the following the most distracting electronic device:”. This was coded as follows:
- 1 = Computer
- 2 = Phone
- 3 = iPad / Tablet
- 4 = Smartwatch
5 = Other
Distr_4 shows refers Distr_3 if ‘other’ was selected. This was a open response item, where “NA” denotes “other” was not chosen.
- Distr_5 shows the response to the question: “I find the following the most distracting when I am studying/working:”. This was coded as follows:
- 1 = Computer
- 2 = Phone
- 3 = iPad / Tablet
- 4 = Smartwatch
5 = Other
Distr_6 shows refers Distr_5 if ‘other’ was selected. This was a open response item, where “NA” denotes “other” was not chosen.
- Distr_7 shows the response to the question: “I find the following the most distracting when I am in a social context (e.g., with friends):”. This was coded as follows:
- 1 = Computer
- 2 = Phone
- 3 = iPad / Tablet
- 4 = Smartwatch
5 = Other
Distr_8 shows refers Distr_7 if ‘other’ was selected. This was a open response item, where “NA” denotes “other” was not chosen.
General Exploratory Questions
- Exp_1 shows the response to the question: “How much money would it take for you to give up your phone for a full day?”. This was coded as follows:
- 1 = $0-$20
- 2 = $21-$40
- 3 = $41-$60
- 4 = >$60
- Exp_2 shows the response to the question: “Have you ever thought you heard your phone ring or thought you felt it vibrate, only to find out you were wrong?”. This was coded as follows:
- Exp_3 shows the response to the question: “Who do you mostly communicate with on your phone?”. This was coded as follows:
- 1 = Family
- 2 = Friends
- 3 = Work
- 4 = Other
Exp_4 shows refers to Exp_3 if ‘other’ was selected. This was a open response item, where “NA” denotes “other” was not chosen.
- Exp_5: shows the response to the question: “What do you use your phone for the most?”. This was coded as follows:
- 1 = Calling / Texting
- 2 = Social Media (e.g., Facebook, Instagram, Twitter, Snapchat)
- 3 = Email
- 4 = Other
- 5 = Games (e.g., candy crush, clash of clans)
Exp_6 shows refers to Exp_5 if ‘other’ was selected. This was a open response item, where “NA” denotes “other” was not chosen.
(2) The Nomophobia Questionnaire (NMP-Q; Yildirim & Correia, 2015)
NMP_Q_1 - NMP_Q_20 shows the responses to the 20 items in the NMP-Q. Participants were asked to indicate how much they agree or disagree to the statements on a 7-point likert scale (where, “1” = Strongly Disagree, and 7 = “Strongly Agree”).
The score was the sum of all responses (range is from 20–140), with higher scores corresponding to greater nomophobia severity. This range was interpreted as follows: 20 = absence of nomophobia, 21–59 = mild level of nomophobia, 60–99 = moderate level of nomophobia, ≥ 100 = severe nomophobia. This was coded as follows:
- The items were as follows:
- NMP_Q_1: I would feel uncomfortable without constant access to information through my smartphone.
- NMP_Q_2: I would be annoyed if I could not look information up on my smartphone when I wanted to do so.
- NMP_Q_3: Being unable to get the news (e.g., happenings, weather, etc.) on my smartphone would make me nervous.
- NMP_Q_4: I would be annoyed if I could not use my smartphone and/or its capabilities when I wanted to do so.
- NMP_Q_5: Running out of battery in my smartphone would scare me.
- NMP_Q_6: If I were to run out of credits or hit my monthly data limit, I would panic.
- NMP_Q_7: If I did not have a data signal or could not connect to Wi-Fi, then I would constantly check to see if I had a signal or could find a Wi-Fi Network.
- NMP_Q_8: If I could not use my smartphone, I would be afraid of getting stranded somewhere.
- NMP_Q_9: If I could not check my smartphone for a while, I would feel a desire to check it.
If I did not have my smartphone with me,
- NMP_Q_10: I would feel anxious because I could not instantly communicate with my family and/or friends.
- NMP_Q_11: I would be worried because my family and/or friends could not reach me.
- NMP_Q_12: I would feel nervous because I would not be able to receive text messages and calls.
- NMP_Q_13: I would be anxious because I could not keep in touch with my family and/or friends.
- NMP_Q_14: I would be nervous because I could not know if someone had tried to get a hold of me.
- NMP_Q_15: I would feel anxious because my constant connection to my family and friends would be broken.
- NMP_Q_16: I would be nervous because I would be disconnected from my online identity.
- NMP_Q_17: I would be uncomfortable because I could not stay up-to-date with social media and online networks.
- NMP_Q_18: I would feel awkward because I could not check my notifications for updates from myconnections and online networks.
- NMP_Q_19: I would feel anxious because I could not check my email messages.
- NMP_Q_20: I would feel weird because I would not know what to do.
(3) The Mobile Phone Involvement Questionnaire (MPIQ; Walsh et al., 2010)
- The MPIQ consists of 14 items and has three subscales, which measure: (1) The MPIQ, (2) The Self-Identity, and (3) Validation from Others. For each subscale, participants were asked to indicate how much they agree or disagree to the statements on a 7-point likert scale (where, “1” = Strongly Disagree, and 7 = “Strongly Agree”). The score was the average for each subscale. Each subscale was coded as follows:
- MPIQ_1 - MPIQ_8 shows the responses to the 8 items in the MPIQ subscale. The items were as follows:
- MPIQ_1: I often think about my mobile phone when I am not using it. [cognitive salience]
- MPIQ_2: I often use my mobile phone for no particular reason. [behavioural salience]
- MPIQ_3: Arguments have arisen with others because of my mobile phone use. [interpersonal conflict]
- MPIQ_4: I interrupt whatever else I am doing when I am contacted on my mobile phone. [conflict with other activities]
- MPIQ_5: I feel connected to others when I use my mobile phone. [euphoria]
- MPIQ_6: I lose track of how much I am using my mobile phone. [loss of control]
- MPIQ_7: The thought of being without my mobile phone makes me feel distressed. [withdrawal]
- MPIQ_8: I have been unable to reduce my mobile phone use. [relapse & reinstatement]
- MPIQ_self_ID_1 - MPIQ_self_ID_3 shows the responses to the 3 items in the Self-Identity subscale. The items were as follows:
- MPIQ_self_ID_1: Using a mobile phone is very important to me.
- MPIQ_self_ID_2: I feel as though a part of me is missing when I am without my mobile phone.
- MPIQ_self_ID_3: I cannot imagine life without my mobile phone.
- MPIQ_Validation_1 - MPIQ_Validation_3 shows the responses to the 8 items in the Validation from Others subscale. The items were as follows:
- MPIQ_Validation_1: I feel valued when I receive lots of mobile calls or messages.
- MPIQ_Validation_2_rev: Receiving mobile phone calls or messages does not make me feel special.
- Note, here MPIQ_Validation_2_rev denotes that this item should be reverse coded for final analysis.
- MPIQ_Validation_3: Receiving a mobile phone call makes me feel loved.
(4) The Smartphone Attachment and Dependency Questionnaire (SAD; Ward et al., 2017)
SAD_1 - SAD_13 shows the responses to the 13 items in the SAD. Participants were asked to indicate how much they agree or disagree to the statements on a 7-point likert scale (where, “1” = Strongly Disagree, and 7 = “Strongly Agree”).
The score was the sum of all responses (range is from 13–91), with higher scores corresponding to greater smartphone attachment and dependency. This range was interpreted (for the pirposes of this study) as follows: 13 = absence of attachment & dependency, 14–39 = mild level of attachment & dependency, 40–65 = moderate level of attachment & dependency, ≥ 66 = severe attachment & dependency.
- The items were as follows:
- Q12: I would have trouble getting through a normal day without my smartphone.
- Q13: It would be painful for me to give up my smartphone for a day.
- Q14: I feel like I could not live without my smartphone.
- Q15: If I forgot to bring my smartphone with me, I would feel anxious.
- Q16: It drives me crazy when my smartphone runs out of battery.
- Q17: I am upset and annoyed when I find I do not have reception on my smartphone.
- Q18: I feel impatient when the Internet connection speed on my smartphone is slow.
- Q19: I feel lonely when my smartphone does not ring or vibrate for several hours.
- Q20: Using my smartphone relieves me of my stress.
- Q21: I feel excited when I have a new message or notification.
- Q22: Using my smartphone makes me feel happy.
- Q23: I find it tough to focus whenever my smartphone is nearby.
- Q24: I become less attentive to my surroundings when I’m using my smartphone.
2. Main Study Data
#this will import the raw excel data file for the main study
#this file has been ananymized, so any identifiable information has been removed
main_prelim_raw = read.csv("Main_prelim_data(may15).csv", header = TRUE)
CBS_prelim = read.csv("CBS_scores_prelim(may15).csv", header = TRUE)
#this file contains the condition information for each participant in the main study
condition_CBS = read.csv("Condition_info_CBS(may15).csv", header = TRUE)
This data file contains…
Testing Notes refers to the testing notes taken during testing for each participant. These notes included and possible relevant issues that occurred while testing (e.g., possible external distractors, irregularities during testing, issues while running the tasks, etc.). Note, “no issues” denotes that there were no obsrved issues during testing by the researcher.
- Include refers to whether or not a participant was included based off of their testing notes (see above). This was coded as follows:
- 1 = Included
- 0 = Excluded
Analysis
The following results analyze a subset of the final sample size. For time purposes, only two location conditions are analyzed: (1) on desk, and (2) outside of the testing room.
Demographics
Here are the general descriptives for all participants in both studies, including: gender, age, age of first phone, first language, english proficiency
Pilot Study: Descriptives
|
|
Male
|
Female
|
Other
|
|
Gender
|
51
|
49
|
0
|
|
|
Min.
|
Max.
|
Mean
|
|
Age
|
17
|
24
|
18.84
|
|
|
Min.
|
Max.
|
Mean
|
|
First Phone Age
|
9
|
17
|
13.06
|
|
|
English
|
Other
|
|
|
First Language
|
73
|
27
|
|
|
|
Low
|
Moderate
|
High
|
|
English Proficiency
|
0
|
16
|
84
|
Main Study: Descriptives
|
|
Male
|
Female
|
Other
|
|
Gender
|
39
|
70
|
0
|
|
|
Min.
|
Max.
|
Mean
|
|
Age
|
18
|
27
|
18.84
|
|
|
Min.
|
Max.
|
Mean
|
|
First Phone Age
|
9
|
16
|
13.19
|
|
|
English
|
Other
|
|
|
First Language
|
89
|
20
|
|
|
|
Low
|
Moderate
|
High
|
|
English Proficiency
|
0
|
10
|
99
|
Frequency of Smartphone Use
The following tables depit the proportion of responses to the following question:
- At what age did you first get a smartphone? ________
Pilot Study: Age of First Phone
|
Age
|
Percentage
|
|
9
|
1
|
|
10
|
11
|
|
11
|
5
|
|
12
|
17
|
|
13
|
23
|
|
14
|
21
|
|
15
|
13
|
|
16
|
5
|
|
17
|
2
|
|
NA
|
2
|
Main Study: Age of First Phone
|
Age
|
Percentage
|
|
9
|
1
|
|
10
|
2
|
|
11
|
10
|
|
12
|
22
|
|
13
|
30
|
|
14
|
24
|
|
15
|
8
|
|
16
|
11
|
|
NA
|
1
|
The following tables depit the proportion of responses to the following question:
- What is the most used app in the last 7 days (excluding text message/messenger apps)?
- Games (e.g., candy crush, clash of clans)
- Social Networking (e.g., Instagram, Facebook, Snapchat)
- Entertainment (e.g., music, YouTube)
- Other, please specify:____________
Pilot Study: Most Used App
|
App
|
Percentage
|
|
Games
|
2
|
|
Social Networking
|
82
|
|
Entertainment
|
16
|
Main Study: Most Used App
|
App
|
Frequency
|
|
Games
|
3
|
|
Social Networking
|
86
|
|
Entertainment
|
19
|
|
Other
|
1
|
The following tables depit the proportion of responses to the following question:
- What is your weekly total screen time in hours (e.g., 5)?
- 0-10
- 11-20
- 21-30
- 31-40
- 40+
Pilot Study: Total Screen Time Proportions
|
Total Screen Time (hours)
|
Percentage
|
|
0-10
|
7
|
|
11-20
|
20
|
|
21-30
|
19
|
|
31-40
|
16
|
|
40+
|
18
|
|
NA
|
20
|
Main Study: Total Screen Time Proportions
|
Total Screen Time (hours)
|
Percentage
|
|
0-10
|
9
|
|
11-20
|
9
|
|
21-30
|
18
|
|
31-40
|
17
|
|
40+
|
12
|
|
NA
|
35
|
The following tables depit the proportion of responses to the following question:
- What are your notifications per day (i.e., “around __ per day”)? *Found below your pickups
- 0-50
- 51-100
- 101-150
- 151-200
- 200+
Pilot Study: Notifications (per day) Proportions
|
Notifications (per day)
|
Percentage
|
|
0-50
|
16
|
|
51-100
|
14
|
|
101-150
|
10
|
|
151-200
|
12
|
|
200+
|
28
|
|
NA
|
20
|
Main Study: Notifications (per day) Proportions
|
Notifications (per day)
|
Percentage
|
|
0-50
|
5
|
|
51-100
|
11
|
|
101-150
|
9
|
|
151-200
|
9
|
|
200+
|
31
|
|
NA
|
35
|
Distraction Questions
Most Distracting Electronic Device
Participants reported their most distracting electronic device based on three situations: (1) in general, (2) while studying/working, and (3) in a social context.
- The following tables depit the proportion of responses to the following question:
- In general, I find the following the most distracting electronic device: (choose one)
- Computer
- Phone
- iPad / Tablet
- Smartwatch
- Other, please specify: ____________
Pilot Study: Response to ‘I find the following the most distracting electronic device’
|
Response
|
Percentage
|
|
Computer
|
9
|
|
Phone
|
87
|
|
iPad / Tablet
|
3
|
|
Other
|
1
|
Main Study: Response to ‘I find the following the most distracting electronic device’
|
Response
|
Percentage
|
|
Computer
|
6
|
|
Phone
|
101
|
|
iPad / Tablet
|
1
|
|
Smartwatch
|
1
|
- The following tables depit the proportion of responses to the following question:
- I find the following the most distracting when I am studying/working:
- Computer
- Phone
- iPad / Tablet
- Smartwatch
- Other, please specify: ____________
Pilot Study: Response to ‘I find the following the most distracting when I am studying/working’
|
Response
|
Percentage
|
|
Computer
|
10
|
|
Phone
|
87
|
|
iPad / Tablet
|
3
|
Main Study: Response to ‘I find the following the most distracting when I am studying/working’
|
Response
|
Percentage
|
|
Computer
|
11
|
|
Phone
|
97
|
|
Smartwatch
|
1
|
- The following tables depit the proportion of responses to the following question:
- I find the following the most distracting when I am in a social context (e.g., with friends):
- Computer
- Phone
- iPad / Tablet
- Smartwatch
- Other, please specify: ____________
Pilot Study: Response to ‘I find the following the most distracting when I am in a social context (e.g., with friends)’
|
Response
|
Percentage
|
|
Computer
|
3
|
|
Phone
|
97
|
Main Study: Response to ‘I find the following the most distracting when I am in a social context (e.g., with friends)’
|
Response
|
Percentage
|
|
Computer
|
2
|
|
Phone
|
104
|
|
iPad / Tablet
|
1
|
|
Smartwatch
|
1
|
|
Other
|
1
|
Distracted During Study
These questions asked participants to report whether their smartphone distracted them either (1) in general, or (2) during the study.
- The following tables depit the proportion of responses to the following question:
- I find my phone can distract me from my daily activities (e.g., work, school, social interactions).
Pilot Study: Response to ‘I find my phone distracting during this study’
|
Response
|
Percentage
|
|
Strongly Disagree
|
4
|
|
Disagree
|
1
|
|
Somewhat Disagree
|
4
|
|
Neutral
|
5
|
|
Somewhat Agree
|
22
|
|
Agree
|
35
|
|
Strongly Agree
|
29
|
Main Study: Response to ‘I find my phone distracting during this study’
|
Response
|
Percentage
|
|
Strongly Disagree
|
3
|
|
Disagree
|
5
|
|
Somewhat Disagree
|
6
|
|
Neutral
|
2
|
|
Somewhat Agree
|
23
|
|
Agree
|
35
|
|
Strongly Agree
|
35
|
- The following tables depit the proportion of responses to the following question:
- I find my phone distracting during this study
Pilot Study: Response to ‘I find my phone distracting during this study’
|
Response
|
Percentage
|
|
Strongly Disagree
|
15
|
|
Disagree
|
15
|
|
Somewhat Disagree
|
12
|
|
Neutral
|
11
|
|
Somewhat Agree
|
19
|
|
Agree
|
13
|
|
Strongly Agree
|
15
|
Main Study: Response to ‘I find my phone distracting during this study’
|
Response
|
Percentage
|
|
Strongly Disagree
|
47
|
|
Disagree
|
33
|
|
Somewhat Disagree
|
7
|
|
Neutral
|
6
|
|
Somewhat Agree
|
6
|
|
Agree
|
6
|
|
Strongly Agree
|
4
|
Paradigm Decision Questions
Here is a stacked bar plot of the location questions, showing freqeucnies / proportions for each scenario of location
Comfort Level Questions
Overall average level of comfort for all 5 questions
- Average level of comfort specifically for ‘I would feel comfortable leaving my phone in another room while completing a task’
## [1] "Average Comfort level (one stat for all questions): 3.536"
## [1] "Average Comfort level for question #5: 4.62"
Pilot Study: Average Comfort Level for each question
|
|
Average Score
|
|
Q1: I am comfortable with letting others use my phone
|
3.84
|
|
Q2: I leave my phone unattended.
|
3.43
|
|
Q3: I leave my phone with other people.
|
3.27
|
|
Q4: I make sure my phone is locked when it is not in my hands.
|
2.52
|
|
Q5: I would feel comfortable leaving my phone in another room while completing a task.
|
4.62
|
## [1] "Average Comfort level (one stat for all questions): 4.0605504587156"
## [1] "Average Comfort level for question #5: 5.28440366972477"
Main Study: Average Comfort Level for each question
|
|
Average Score
|
|
Q1: I am comfortable with letting others use my phone
|
4.449541
|
|
Q2: I leave my phone unattended.
|
4.165138
|
|
Q3: I leave my phone with other people.
|
3.788991
|
|
Q4: I make sure my phone is locked when it is not in my hands.
|
2.614679
|
|
Q5: I would feel comfortable leaving my phone in another room while completing a task.
|
5.284404
|
Individual Difference Measures - Demographics
Pilot Study
- Looking at questionnaire results: proportion of scores by level
Main Study
- Looking at questionnaire results: proportion of scores by level
Correlations
A Pearson-Product Moment correlation analysis was conducted to examine the relationship between the three individual difference measures: the MPIQ, SAD, and NMP-Q. These correlations were conducted for the purpose of determining if these measures were related to each other, if participants’ responses were consistent, and if there were sensitivity differences. Results in both studies revealed a significant strong positive correlation between all the questionnaires (see Table 1A). In contrast, The Double Trouble task score was not significantly correlated with any of the questionnaires (see Table 1B).
T-Test for Double Trouble (between ‘Desk’ and ‘Ouside’ conditions)
- Perform assumption tests
- Assumption 1: Are the two samples independents?
- This assumption was met during testing.
- Assumption 2: Are the data from each of the 2 groups follow a normal distribution?
- Assumption 3. Do the two populations have the same variances?
- The residuals appear to follow the shape of a normal distribution, though they seem to be slightly platykurtic.
##
## Shapiro-Wilk normality test
##
## data: prelim_hon_DT_Res1
## W = 0.95914, p-value = 0.002047
- Based on an alpha level of .05, the assumption of normality was not met; W = 0.96, p = .002. As a result, rather than perform a t-test, we will use the non-parametric Wilcoxon-Mann-Whitney Test.
Compute the Wilcoxon-Mann-Whitney Test
##
## Exact Wilcoxon-Mann-Whitney Test
##
## data: Score by Condition (1, 3)
## Z = -0.3275, p-value = 0.7454
## alternative hypothesis: true mu is not equal to 0
Therefore, there was no significnat difference in DT scores between smartphone locations (i.e. desk and outside), Z = -0.33, p = .745.
Visualize the DT analysis in a bar chart 
