Carine Pianelli Laboratoire de Psychologie Sociale (Université de Provence)

Bar-Ilan Universit

y

Carine PianelliLaboratoire de Psychologie Sociale

(Université de Provence)

3rd International Lab Meeting – Summer session 2005

2-10 July 2005

Erik H. CohenBar-Ilan University (Israel)

Jean-Claude AbricLaboratoire de Psychologie Sociale

(Université de Provence)

The Social Representation of the Use of Seat Belts:

A Facet Theory Approach

The primary objectives of research on road safety are to determine principal factors leading to accidents and to identify types of drivers whose accident risk would be the highest.

According to researchers working in this field, behaviors of drivers which violate traffic rules are relatively stable over time.

Moget-Monseur and Biecheler-Fretel (1985) proposed the concept of “basic behavior of the driver” which is a system of rules of driving, both legal and conceptual, to which the driver strives to uphold.

According to these authors, this system refers to the social representation of traffic laws.

Previous research on driving 1/5


In research on driving, the principal methodology used is self-reported behavior.

The Driver Behavior Questionnaire (DBQ - Reason & al., 1990) consists of fifty driving behaviors, errors and violations. Subjects are requested to estimate the frequency of their engaging in these behaviors.

Reason emphasized that declared violations can be largely predicted by age, gender, driving skill and kilometers traveled.

Moreover, there is a clear link between self-reported violations and implication in accidents.


Many studies on driving have shown that young people (18-24 years) are particularly likely to violate traffic rules.

In addition, research has shown that while nighttime driving represents less than 10% of the traffic but it accounts for 47% of mortality on road.

The number of young people among victims of fatal accidents at night is high : they account for 57% of nighttime fatalities.


Use of safety seat belts has been respected much more during the last years by drivers in France.

In a study carried out by the SOFRES in 2000, drivers were asked to answer the following question: “For each of the following behaviors, would you say that you consider it: unacceptable, condemnable or acceptable?”

The results show that if “not putting on a seat belt in the front seat” is unacceptable for 64%, “not putting on a seat belt in the back seat” is considered to be unacceptable by only 31% : this violation is largely tolerated and normalized by drivers in the back seat.

Currently in France, seat belt is used in the front seat by 96% on the motorways and approximately 75% on residential roadways. In the back seat, percentages are 51% and 48%, respectively.


Moget-Monseur and Biecheler-Fretel (1985) showed that violations made in residential areas, which would seem relatively benign for experienced drivers, were considered unacceptable by recently-qualified drivers (those who have been driving for less than one year).

These authors also established the statute of rules of circulation. According to them, rules of driving would be considered useless because “the driver would trust only the feeling of immediate danger to satisfy his need for security”.

In the same way, Saad (1988) highlighted that risk-taking would depend on the importance of the perception and the assessment of the danger by the drivers.

Purpose and hypothesis of the current study

For recently-qualified drivers, rules of driving are rules of the highway code: they would be central and non contestable.

With the practice of driving, they will make violations by economy, to adjust and adapt them at the traffic or for the pleasure.

These violations go against rules considered as central and non contestable.

These violations would be thus in contradiction with the central system of the social representation of rules of driving.

In order to justify their violations, they will regard them as less dangerous (Moget-Monseur and Biecheler-Fretel, 1985).

However, the multiplication of these violations and rationalizations would lead to the transformation of the central core of the representation.

Thus, new informal rules would become central, and certain central rules would become peripheral.

Thus, certain rules would be more or less respected as regards to the context.

The most declared violations will be those considered as the least dangerous and rules associated will be the most disputed.

Purpose and hypothesis of the current study

The results shows there is a transformation of the social representation of traffic rules with the practice of driving.

Rules are not respected in the same way by experimented drivers as regards to the traveler's place in the vehicle, the time of the day and the type of road.

In this work presented today we chose to center on the social representation of the use of the seat belt.

In the previous study, evidence was provided by ANOVA that the use of the seat belt was more or less respected, not using it was considered dangerous and the rule mandating its use was disputed according to: gender, traveler's place in the vehicle, the time of the day and the type of road.

The current study will show that the Guttman approach is applicable to this type of material and that, more specifically, it allows the exposure of the structure of the data.

Population

Our population is taken from the study of the master's dissertation of Pianelli & Javoise (2002).

It comprises 160 drivers from 18 to 25 years, all students.

These drivers differ as regards to the gender (80 men, 80 women), driving experience (80 subjects have been licensed for less than one year, 80 for more than one year) and their frequency of driving (80 drive often, 80 seldom drive).

The building of the questionnaire was done individually in the universities of Law and Letters and Social Sciences of Aix-en-Provence and Paris.

However, the variable “place of residence” was not taken into account because no significant difference according to the place of residence was noted during the pretest.

Construction of the questionnaire

The questionnaire was built within the framework of the master's dissertation of Pianelli & Javoise (2002).

It was constructed from the items of the Driver Behavior Questionnaires of Reason (1990; 1995), those of Moget-Monseur (1985) and oral arguments from relevant lawsuits in France in the year 2000.

The questionnaire is composed of three parts. • The first part relates to the self-declared frequency of

various driving behaviors. • The second part deals with the contestable or non-

contestable nature of certain rules. • The third part addresses the perceived level of danger of

these behaviors by the subjects.

These three parts are organized around the same logic. Subjects must successively fill them out while thinking about driving in town, on trunk roads and on the motorway.

Facet Theory

We analyze these data using Facet Theory and its various procedures.

The facet analysis of the social representation of seat belt use will show the structural organization of the representation.

The current study will show that the Guttman approach is applicable to this type of material.

Mapping sentence for this research


The driver X states the degree of in the use/non use of

seat belt during time in the framework of road,

in relation to recipients who are sitting at the

of the car statement of Facet A.

essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

Structure of the questionnaire






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

Various periods of time






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

Various types of roads






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

Various types of travelers






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

Various places in the car

Items

Indicate if during the past year you produced this behavior: always,

often, sometimes, never.

Facets’ elements

A B C D E

TOWN

VF4 You don’t use the seat belt during the night. 1 2 1 1 1

VF12 You leave your passengers free not to use the seat belt.

1 3 1 2 3

VF20 You don’t use the seat belt during the day. 1 1 1 1 1

TRUNK ROAD

RF1 You don’t use the seat belt during the night. 1 2 2 1 1

RF10 You leave your passengers free not to use the seat belt.

1 3 2 2 3

RF16 You don’t use the seat belt during the day. 1 1 2 1 1

MOTORWAY

AF5 You don’t use the seat belt during the day. 1 1 3 1 1

AF12 You don’t use the seat belt during the night. 1 2 3 1 1

AF20 You leave your passengers free not to use the seat belt.

1 1 3 1 1

List of the 26 questions and their Facet profile

1/3

ItemsIndicate if during the past year you produced this

behavior: always, often, sometimes, never.Facets’

elements

A B C D E

TOWN






essdangerousn 3

litycontestabi 2

frequency 1

A

dunspecifie 3

night 2

day 1

B

motorway 3

trunk 2

town 1

C

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

dunspecifie 3

back 2

front 1

E

high

low

R

ItemsIndicate if during the past year you produced this

behavior: always, often, sometimes, never.Facets’

elements

A B C D E

TOWN


Items

Do you consider these rules as contestable or non-contestable?

Facets’ elements

A B C D E

TOWN

VC6 Use of the seat belt obligatory in the front of the car, during the night.

2 2 1 3 1

VC11 Use of the seat belt obligatory in the front of the car, during the day.

2 1 1 3 1

VC15 Use of the seat belt obligatory at the back of the car. 2 3 1 3 2

TRUNK ROAD

RC2 Use of the seat belt obligatory in the front of the car, during the day.

2 1 2 3 1

RC7 Use of the seat belt obligatory at the back of the car. 2 3 2 3 2

RC15

Use of the seat belt obligatory in the front of the car, during the night.

2 2 2 3 1

MOTORWAY

AC2 Use of the seat belt obligatory in the front of the car, during the day.

2 1 3 3 1

AC9 Use of the seat belt obligatory in the front of the car, during the night.

2 2 3 3 1

AC13 Use of the seat belt obligatory at the back of the car. 2 3 3 3 2


2/3

Items Do you consider this behavior as: little dangerous, dangerous, or very

dangerous?

Facets’ elements

A B C D E

TOWN

VD4 Not to use the seat belt. 3 3 1 3 3

VD9 Leave passengers free not to use the seat belt. 3 3 1 2 3

TRUNK ROAD

RD2 Not to use the seat belt in the front of the car, during the day.

3 1 2 3 1

RD14 Not to use the seat belt in the front of the car, during the night.

3 2 2 3 1

RD19 Leave passengers free not to use the seat belt. 3 3 2 2 3

MOTORWAY

AD3 Not to use the seat belt in the front of the car, during the day.

3 1 3 3 1

AD11 Not to use the seat belt in the front of the car, during the night.

3 2 3 3 1

AD19 Leave passengers free not to use the seat belt. 3 3 3 2 3


3/3

Results

Smallest Space Analysis (SSA)

The data were analyzed using a technique, also developed by Guttman, called a Smallest Space Analysis (SSA).

The first step in conducting the SSA is the calculation of a matrix of the correlation between the chosen variables.

The Monotonicity Coefficient, a regression-free coefficient of correlation (Guttman, 1986), was used.

The program calculates the correlations between each pair of items.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

+--------------------------------------------------------------------------------------------------------

VF4 1 | 100 69 99 100 64 99 98 98 39 66 87 51 82 54 66 66 69 58 36 47 62 66 61 71 35 46

|

VF12 2 | 69 100 64 61 95 94 85 85 90 22 22 42 67 53 58 58 66 71 24 63 63 41 72 50 26 77

|

VF20 3 | 99 64 100 98 76 98 99 98 35 64 77 66 68 60 64 64 67 54 48 43 59 42 45 47 55 57

|

RF1 4 | 100 61 98 100 72 97 98 98 17 71 71 63 75 57 85 39 62 51 56 26 34 39 54 75 29 40

|

RF10 5 | 64 95 76 72 100 86 75 83 96 41 41 45 77 68 70 70 76 70 36 55 64 41 75 77 58 86

|

RF16 6 | 99 94 98 97 86 100 99 100 54 56 56 58 60 58 56 74 76 70 64 72 71 74 73 60 67 59

|

AF5 7 | 98 85 99 98 75 99 100 98 44 77 77 65 80 64 77 77 78 64 55 52 84 77 67 64 71 63

|

AF12 8 | 98 85 98 98 83 100 98 100 60 22 22 52 28 51 59 59 48 64 55 66 55 59 77 64 51 63

|

AF20 9 | 39 90 35 17 96 54 44 60 100 30 30 48 71 69 76 65 64 79 39 66 60 50 85 71 54 79

|

VC6 10 | 66 22 64 71 41 56 77 22 30 100 99 93 99 95 96 96 100 87 73 71 96 96 81 95 95 79

|

VC11 11 | 87 22 77 71 41 56 77 22 30 99 100 93 99 95 93 96 99 87 73 71 92 93 81 95 91 79

|

VC15 12 | 51 42 66 63 45 58 65 52 48 93 93 100 100 98 84 84 100 91 71 80 77 73 68 81 79 67

|

RC2 13 | 82 67 68 75 77 60 80 28 71 99 99 100 100 100 97 99 100 96 78 76 97 97 86 98 96 90

|

RC7 14 | 54 53 60 57 68 58 64 51 69 95 95 98 100 100 81 89 100 95 53 77 75 81 79 87 78 72

|

RC15 15 | 66 58 64 85 70 56 77 59 76 96 93 84 97 81 100 93 99 79 82 88 92 93 88 95 91 92

|

AC2 16 | 66 58 64 39 70 74 77 59 65 96 96 84 99 89 93 100 100 93 82 80 96 96 88 97 97 92

|

AC9 17 | 69 66 67 62 76 76 78 48 64 100 99 100 100 100 99 100 100 100 94 94 100 100 94 99 100 95

|

AC13 18 | 58 71 54 51 70 70 64 64 79 87 87 91 96 95 79 93 100 100 63 80 75 79 82 91 79 72

|

VD4 19 | 36 24 48 56 36 64 55 55 39 73 73 71 78 53 82 82 94 63 100 85 91 89 86 97 92 82

|

VD9 20 | 47 63 43 26 55 72 52 66 66 71 71 80 76 77 88 80 94 80 85 100 94 93 92 96 86 93

|

RD2 21 | 62 63 59 34 64 71 84 55 60 96 92 77 97 75 92 96 100 75 91 94 100 100 94 98 98 96

|

RD14 22 | 66 41 42 39 41 74 77 59 50 96 93 73 97 81 93 96 100 79 89 93 100 100 93 99 99 92

|

RD19 23 | 61 72 45 54 75 73 67 77 85 81 81 68 86 79 88 88 94 82 86 92 94 93 100 100 92 97

|

AD3 24 | 71 50 47 75 77 60 64 64 71 95 95 81 98 87 95 97 99 91 97 96 98 99 100 100 98 100

|

AD11 25 | 35 26 55 29 58 67 71 51 54 95 91 79 96 78 91 97 100 79 92 86 98 99 92 98 100 91

|

AD19 26 | 46 77 57 40 86 59 63 63 79 79 79 67 90 72 92 92 95 72 82 93 96 92 97 100 91 100

The original coefficients were multiplied by 100 and rounded into integer numbers.

MONCO correlations between the 26 variables

Figure 1: Geometric representation of the MONCO correlations (alienation = .185)

Graphic representation of data by facets (1/7)

Figures 2 to 6 show the same graphic representation of the data, but with the profile for one facet shown in each figure.

The applicability of the facet is verified if contiguous regions for each element may be recognized in the SSA.

Results show that in general, the mapping sentence is empirically verified.

Facets A, D and E are excellent. They are perfectly confirmed by the data analysis.

One facet, the facet C, was not verified.

All three basic shapes of SSA are represented in our case: polar (Facets A and D), modular (Facets B and C) and axial (Facet E).


Figure 2: Data according to the Facet A ( = 1.00; = .369).

= 1.00;

0 = .369).

0


FACET A: Structure of the questionnaire

essdangerousn 3

litycontestabi 2

frequency 1

A

(polar structure)

Figure 5: Data according to the Facet D ( = 1.00; = .487).

= 1.00;

0 = .369).

0


FACET D: Various types of travelers

dunspecifie 3

elersother trav 2

fhim/herseldriver 1

D

(polar structure)

Figure 6: Data according to the Facet E ( = 1.00; = .378).

= 1.00;

0 = .369).

0


dunspecifie 3

back 2

front 1

E

FACET E: Various places in the car

(axial structure)

Figure 3: Data according to the Facet B ( = .956; = .495).

= 1.00;

0 = .369).

0


dunspecifie 3

night 2

day 1

B

FACET B: Various periods of time

(modular structure)

Figure 4: Data according to the Facet C

= 1.00;

0 = .369).


motorway 3

trunk 2

town 1

C

FACET C: Various types of roads

(modular structure)

Discussion concerning the facet C

Based on the results of this analysis, we suggest that facet C, related to the type of road, not be retained in the final mapping sentence and SSA map.

With the ANOVA, we had found that drivers use their seat belt on trunk roads and motorways more than in town and they consider not using seat belts on trunk roads and motorways to be more dangerous than not using them in town.

Based on these results, it was expected that attitudes towards seat belt use would be related to type of road traveled. However, this was not upheld by the empirical data.

Maybe for drivers, there is no difference between trunk roads and motorways : it would be better to propose them not three types of networks but two types (trunk roads and motorways together and town).

Figure 7: Integrative SSA with Facets A, B, D and E represented

Conclusions

Four of the five facets of the mapping sentence are confirmed in two-dimensional SSA.

One facet, type of road, was found to be problematic.

These results indicate that the Guttman approach is applicable to this type of material and it allows the exposure of the structure of the data, simultaneously representing the various facets.

Guttman approach could enrich and complete classic methods of studying social representations, notably by providing a visual representation of the structure of the social representation.

Bar-Ilan Universit

y

Thank you for your attention.

Carine Pianelli Laboratoire de Psychologie Sociale (Université de Provence)

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