Technology gadgets in the daily life it has become

Technology gadgets can be literally labelled
as the ruling authority across the globe, as the life without technology has
become impossible. The modern technologies have factually changed the way
through which the individuals perceive and approach the world. However many individuals
are highly prone to be more dependent to the use of technology gadgets, but the
biggest challenge is the high necessity of the technology gadgets in the daily
life it has become very difficult to distinguish between the normal and
addictive use of technology gadgets and also have the high possibility to have
a huge impact on the human abilities that raises the necessities to study about
the technology gadgets influence on the cognitive functions. Researches show
that increases use of technology gadgets is associated with the issues in
everyday executive functioning of the individual and decreases the individual’s
ability to think analytically (Barr et al, 2015). Even
though the research on the negative impact of technology gadgets on cognition
of the individual is evolving, the results in most of the research tends to be
conflicting to each other and unconvincing which at times shows that not all
the technology gadgets and it service have an equal impact on the cognitive
abilities. Irrespective of the results media made an huge effect on the public
perception that all the research finding tends to be very convincing and the
technology gadgets are having an 
absolute negative influence on the cognitive functioning of the
individual (Richtel, 2010). Researches also clearly emphasizes that many of the negative cognitive
functioning are mostly caused through the indirect effect of the use of
technology gadgets such as its direct influence on the sleep and mood and the
quality of sleep and negative mood has an severe impact on the cognitive
abilities (Lim and Dinges, 2008). Fascinatingly, there is also some research
evidence signifying that individuals vulnerability to cognitive disruption from
technology use and the consequential influence on ability to perform cognitive
functions is more likely to depend on the individuals existing cognitive skills
set, particularly the individual’s ability to exert self regulatory control on
their behaviour (Tams et al, 2015).

One of the very
important cognitive ability is the cognitive flexibility. Cognitive flexibility
is defined as the ability to change behaviour such as thoughts or actions in
response to situational demands (Can˜as, Antoli, Fajardo, & Salmero´n,
2005; Lezak, 2004). It includes problem solving, planning, achievement and goal
development which is a element of executive functioning, the group of higher
order cognitive abilities (Anderson, 2002; Burgess & Alderman, 2004;
Dubois, Slachevsky, Litvan, & Pillon, 2000; Strauss, Sherman, & Spreen,
2006). These abilities are considered to be essential for focused individual
behaviour (Lezak, 2004) and necessitate spontaneous and reactive mechanism
(Eslinger & Grattan, 1993). The processes of foundation to cognitive
flexibility are dynamic, involving cycles of thought generation and suppression
that appear and dissolve as the individual interacts with varying environmental
factors like relative cues and task demands (Ionescu, 2012). This model
proposed by Ionescu (2012) has been described as a “unified framework of
cognitive flexibility”, linking a number of cognitive components or mechanisms
which includes various executive functions, attention, perception, goal
parameters and monitoring in conjunction with task demands, contextual cues and
sensory-motor input. Therefore cognitive flexibility encompasses more than
simple response switching. Research indicates that there are six core processes
such as acceptance, diffusion, self as context, contact with the present
moment, values and committed action which are involved in achieving cognitive
flexibility. These processes contribute to the development of
cognitive flexibility but the relative contribution of each process and how it differs
with each individual is highly vague. (Hayes, Luoma, Bond, Masuda, & Lillis, 2006) Research also suggests that whenever these
processes are not implemented it results in the cognitive inflexibility with
the rise of the experiential avoidance. Experiential avoidance, as opposed to
acceptance, occurs when a person actively attempts to change experiences, both
internal and external, that gives rise to difficult thoughts and emotions (Ruiz, 2010). Recent
research on technology addiction on adolescents have clearly outlined that
experiential avoidance explained the outcome of the pattern regarding the
addictive use of technology gadgets and the study concluded that experiential
avoidance should be considered while studying the technology dependence (Garcia
Oliva C, Piqueras JA, 2016). Another study also suggests that experiential
avoidance is positively related to the internet addiction (Wei-Po Chou et al,
2017)

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Researches show that individuals who are
addicted to internet tend to have impaired level of cognitive flexibility (Dong
G, Lin X, Zhou H & Lu Q, 2014). Research
also suggests that mobile technologies have high possibility to influence an
extensive array of cognitive domains, but empirical research on the cognitive impact
of mobile technology is narrow. This is reasonable because technology itself a
relatively very young and growing at a tremendous rate however every year
mobile technology is becoming a basic necessity in all the individual lives (eMarketer, 2014).

            However from the literature it is clearly evident that there is a huge
gap on the study of the technology dependence and there also arises a strong
need to study about the relationship between technology dependence, cognitive
flexibility and experiential avoidance. So this study is particularly opted to
bridge the gap on the study of the influence technology dependence on the
cognitive flexibility and experiential avoidance.

Methodology

Aim:

            The present study aimed to assess the
influence of technology dependence on cognitive flexibility and experiential
avoidance among the college students.

Objectives:

1.      To
examine the technology dependence, cognitive flexibility and experiential
avoidance among the college students

2.      To
examine the relationship between the technology dependence, cognitive
flexibility and experiential avoidance among the college students.

Hypothesis:

1.      There
exists no significant relationship between technology dependence and cognitive
flexibility and experiential avoidance among the college students.

2.       There exists no significant relationship
between cognitive flexibility and experiential avoidance among the college
students.

Sample:

            College students were selected
randomly from the colleges in and around the Coimbatore city, from these 100 college
students were filtered (50 males, 50 females) based on those who have exposure
to more than 2 technology gadgets, services and college students within the age
group of 17 to 22. Data was collected from the college students using
systematic random sampling method. Other inclusion and exclusion criteria are
as follows.

Inclusion
Criteria:

1.      Aged
from 17-22 year’s college students

2.      Exposed
to more than two technology gadgets and it services

3.      Those
who are willing to sign the informed consent form and Voluntary Participation

Exclusion
Criteria:

1.      Presence
of any health problems which might interfere in taking the administered tools

2.      College
students who exceeds or falls below the age category of 17-22

3.      Those
who are not exposed to more than two technology gadgets and it services

 

 

 

Tools:

1.      Socio
Demographic Details:

This
social demographic data is intended to gather information regarding the name of
the participant, age, gender, family type and domicile.

2.      Gadget’s
Use Scale:

This
scale was developed by Munduli in 2014. The Gadget Use Scale consists of the
questions regarding the use of the gadgets in a tabular form. The time spent
with different technology gadgets and its services with the options 1-2 hours,
2-4 hours, 4-6 hours and >6 hours. This scale is used to assess the time
spent on different technology gadgets and its services of the participants.

3.      Technology
Dependency Questionnaire:

This
questionnaire was developed by Munduli in 2014. The Technology Dependency
Questionnaire consists of 10 items. Participants have to indicate whether the
given statements were characteristic or uncharacteristic of them in 5 different
responses.  It assesses the level of dependency
to the technology gadgets of the participants, which shows that higher the
level of dependency the participant is more vulnerable to addiction of
technology gadgets.

4.     
Cognitive Flexibility
Scale

The Cognitive
Flexibility Scale consisting of 12 items was developed by Martin and Rubin in
1995. Participants
have to indicate whether the given statements were characteristic or
uncharacteristic of them in 6 different responses. This scale is used to
assess the participant’s level of cognitive flexibility. The
cronbach’s alpha is ?=0.84 which indicates the scale has good internal
consistency reliability.

5.     
Multidimensional
Experiential Avoidance Questionnaire

The Multidimensional
Experiential Avoidance Questionnaire consisting of 64 items was developed by Wakiza
Gamez in 2011. Participants have to indicate whether
the given statements were characteristic or uncharacteristic of them in 6
different responses. This scale is used to assess the participant’s level of experiential
avoidance. This questionnaire also assess the participants level of total
experiential avoidance in 6 dimensions behavioural avoidance, distress
aversion, procrastination, distraction/suppression, repression/denial and distress
endurance. The cronbach’s alpha is ?=0.92 which indicates the
scale has good internal consistency reliability.

Procedure:

            The informed
consent form was given to the participants. The subjects were asked to provide
information on certain socio demographic details followed by the administration
of the Gadget’s Use scale, Technology Dependency Questionnaire, Cognitive
Flexibility Scale and Multidimensional Experiential Avoidance Questionnaire. The instructions about
how to respond to the tests was explained in detail to the subjects in their
convenient language (English or in Tamil). The entire administration took up to
30 to 45 minutes. 

RESULTS AND DISCUSSION:

Data was coded for IBM
SPSS.20 analysis. The frequencies and percentages were calculated for the
socio-demographic variables. In order to test the hypothesis, correlation,
t-test was performed to find out the relationship between Technology use and
dependence, cognitive flexibility and experiential avoidance. The results are
as follows,

 

 

Table-1 shows the mean, standard
deviation and t-test of technology dependence, cognitive flexibility and
experiential avoidance among college students

 

Gender

N

Mean

Std. Deviation

Std. Error Mean

t-test

Technology dependence

Male

50

35.42

4.572

.647

-0.500(0.618)

Female

50

35.86

4.223

.597

Cognitive flexibility

Male

50

46.58

6.634

.938

-3.151(0.002)

Female

50

51.02

7.433

1.051

Behavioral Avoidance

Male

50

40.56

8.391

1.187

-1.590(0.115)

Female

50

43.02

7.017

.992

Distress Aversion

Male

50

46.28

9.249

1.308

-0.733(.465)

Female

50

47.66

9.576

1.354

Procrastination

Male

50

24.42

4.874

.689

-0.785(0.434)

Female

50

25.16

4.546

.643

Distraction/ Suppression

Male

50

26.20

5.555

.786

-1.692(.094)

Female

50

28.24

6.470

.915

Repression/ Denial

Male

50

45.36

7.899

1.117

2.449(.016)

Female

50

41.22

8.970

1.269

Distress endurance

Male

50

49.96

8.628

1.220

2.276(.025)

Female

50

46.32

7.308

1.033

Total Experiential Avoidance

Male

50

212.64

29.464

4.167

-0.569(.571)

Female

50

215.84

26.700

3.776

 

Table 1 Show the mean, standard deviation and t-
test of technology dependence, cognitive flexibility among college students in
terms of gender. It shows that there is significant
difference between the cognitive flexibility in terms of gender (t = -3.151; p
= 0.002). However, there exists no significant difference between males and
females in terms of technology dependence, behavioural avoidance, distress
aversion, procrastination, distraction/suppression, repression/ denial,
distress endurance and total experiential avoidance. Surprisingly the research findings
are very much contradicted to the previous research on experiential avoidance
suggested the significant gender difference (Wakiza Gamez, 2011).

 

Table-2 shows relationship between technology
dependence, gadgets use, cognitive flexibility and experiential avoidance among
college students

 

CF

BA

DA

P

D /S

R / D

D E

T E A

T D

-0.053

0.245

0.344

0.163

0.223

0.214

0.069

0.340

Mobile

-0.008

0.061*

0.119

0.149

0.017*

0.064

-0.019

0.108*

Computer

-0.023*

-0.008

-0.087

-0.033*

-0.044

0.057

-0.101*

-0.027

Tab

-0.001

-0.142*

-0.036

0.071

-0.062*

0.046

-0.144

-0.017*

Smart mob

0.180**

0.075**

-0.036

0.126**

0.007**

0.086

0.131**

0.002**

I pad

-0.085

-0.046**

0.012

0.018

-0.027**

0.038

-0.063

-0.020**

Headset

-0.014*

0.077*

0.092

0.170*

0.092*

0.156

0.082*

0.103*

Call

0.038*

-0.009**

0.046

0.087*

-0.003**

0.062

-0.025*

0.040**

Message

0.028**

-0.023**

-0.028

0.254**

0.017**

-0.001

-0.072**

0.105**

Net

0.012**

0.077**

-0.053

0.204**

0.016**

0.070

0.001**

0.073**

Social net

-0.058**

0.056

0.042

0.149**

-0.042

0.081

-0.042**

0.050

Study

-0.091

-0.097

-0.076

-0.261

-0.033

-0.063

-0.026

-0.122

Communication

0.003

0.044

0.056

0.128

-0.018

-0.019

-0.077

0.039

Entertainment

-0.149

0.214

0.211

0.245

0.114

0.198

-0.039

0.249

** Correlation
is significant at the 0.01 level

  * Correlation is significant at the 0.05
level

TD = Technology Dependence, CF = Cognitive
Flexibility, BA = Behavioural Avoidance, DA = Distress Aversion, D/S = Distraction/Suppression,
R/D = Repression/Denial, DE = Distress Endurance & TEA = Total Experiential
Avoidance

Table 2 shows the
relationship between the technology gadgets use, cognitive flexibility and
experiential avoidance among college students. It shows that the cognitive
flexibility of the participants is positively correlated with the use of smart
mobiles (0.180**), messaging services (0.028**), internet (0.012**) which is
significant at 0.01 level and call services (0.038*) which is significant at
0.05 level. It also shows that cognitive flexibility is negatively correlated
with the use of social network (-0.058**) which is significant at 0.01 level
and headset (-0.014*) which is significant at 0.05 level.

            It also shows that experiential avoidance is positively
correlated with the use of smart mobiles (0.002**), call services (0.040**),
message services (0.105**), Internet services (0.073**) which is significant at
0.01 level and mobile (0.108*), headset (0.103*) which is significant at 0.05 level.
It also shows that experiential avoidance is negatively correlated with the use
of I-Pad (-0.020*) which is significant at 0.01 level and tablet (-0.017*)
which is significant at 0.05 level.

            It also shows behavioural avoidance is positive
correlated with the use of smart mobiles (0.075**), internet services (0.077**)
which is significant at 0.01 level and mobile (0.061*), headset (0.077*) which
is significant at 0.01 level. It also shows that behavioural avoidance is
negatively correlated with the use of I Pad (-0.046**), Call services
(-0.009**), message services (-0.023**) which is significant at 0.01 level and
tablet (-0.142*) which is significant at 0.05 level.

            It also shows that procrastination is positively
correlated with the use of smart mobiles (0.126**), message services (0.254**),
internet services (0.204**), social network (0.149**) which is significant at
0.01 level and headset (0.170*), call services (0.087*) which is significant at
0.05 level. It also shows that procrastination is negatively correlated with
the use of personal computers (-0.033*) which is significant at 0.05 level.

            It also shows that Distraction/Suppression is positively
correlated with the use of smart mobiles (0.007**), message services (0.017**),
internet services (0.016**) which is significant at 0.01 level and mobile
(0.017*), headset (0.092*) which is significant at 0.05 level. It also shows
that Distraction/Suppression is negatively correlated with the use of I pad
(-0.027**), call services (-0.003**) which is significant at 0.05 level and
tablet (-0.062*) which is significant at 0.05 level.

            It also shows that Distress Endurance is positively
correlated with the use of smart mobiles (0.131**), internet services (0.001**)
which is significant at 0.01 level and headset (0.082*) which is significant at
0.05 level. It also shows that Distress Endurance is negatively correlated with
the use of message services (-0.072**), social network (-0.042**) which is
significant at 0.01 level and personal computer (-0.101*), call services
(-0.072*) which is significant at 0.05 level

            The table also clearly shows that technology dependence
has no correlation with the cognitive flexibility and experiential avoidance
and it dimensions. However the analyses clearly indicate that the use of the
different technology gadgets has a strong relationship with both the cognitive
flexibility and experiential avoidance. Interestingly 2 dimensions (Distress
Aversion & Repression/Denial) have no relationship with any of the
technology gadgets. The
literature also supports the relationship between the experiential avoidance,
cognitive flexibility and the technology use (Dong G, Lin X, Zhou H & Lu Q,
2014; Garcia Oliva C, Piqueras JA, 2016)

 

Table-3 shows relationship between
cognitive flexibility and experiential avoidance among college students

 

BA

DA

P

D

R & D

D E

T E A

CF

-0.024

0.046

0.041

0.221

-0.344

0.143

-0.101

 

** Correlation
is significant at the 0.01 level

  * Correlation is significant at the 0.05
level

CF = Cognitive Flexibility, BA = Behavioural
Avoidance, DA = Distress Aversion, D/S = Distraction/Suppression, R/D =
Repression/Denial, DE = Distress Endurance & TEA = Total Experiential
Avoidance

            Table 3 shows the relationship between the cognitive
flexibility and experiential avoidance. It shows that there is no significant
relationship between the cognitive flexibility and experiential avoidance.
However the previous research on the cognitive flexibility and experiential
avoidance suggested that lack of experiential avoidance leads to cognitive
inflexibility (Ruiz, 2010).  The current research is also
contradict to the results of the previous study.

 

 

 

 

 

 

 

 

 

 

 

 

Conclusion:

The present study derived at several conclusions. There exists
significant difference in the cognitive flexibility between males and females.
Cognitive flexibility is positively correlated with the use of smart mobiles,
calling, messaging, and internet and negatively correlated with the use of
personal computer, headset and social network. Experiential avoidance is
positively correlated with the use of personal computer, smart mobiles,
headset, calling, messaging and internet and negatively correlated with the use
of tablets and I pad/ I phone. The study also concluded that there exists a
significant relation between the technological gadget use and the cognitive
flexibility and experiential avoidance. So the technology usage is a great
challenge in recent times.

Unfortunately
in this current era the world is facing a lot of issues on the technology
because of the inability to categorize the technology use pattern and lack of
the convincing studies on this area so there is a need to have a deep study.

Further
research needs to be done in terms of longitudinal studies, to fully understand
the impact of technology gadgets on college students because they are the more vulnerable
group to have enormous exposure to technology. Further researches should also
focus on the intervention to diminish the cognitive function being influenced
and disrupted by the technology use and the research should extensively cover
much geographical area and should consider accounting of various other
variables in order to obtain even better understanding about the technology
dependence on cognitive flexibility and experiential avoidance.

The
study has limitations in such as, the present study was taken within the age
group of 17 to 22 college students and sample size was small (N=100), also the
study was conducted only with the students residing in Coimbatore. 

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