Impact Of Framing And Issue Involvement On Safety Messages About Mobile Phone Use While Driving

Materials and Methods

In order to motivate to change a certain behavior, persuasive messages are among the effective ways. These messages are tailored to make an awareness of a problem, either framed in terms of intrinsic goals contrary to extrinsic goals, could make them more effective by increasing the level of self-motivation, targeting young drivers (Pelletier, 2008).

Many drivers use cell phones in their vehicles, which distracts. Hence one of the major traffic safety issues. In 2010, the NHTSA of United States conducted a telephone survey of approximately 6,001 drivers aged 18 years and above in all 50 States. The aim of this national survey was to examine recent attitudes and reported behaviors about distraction during driving (Braitman, 2010). While most drivers pick a call while driving, others with an equivalent number will continue driving after answering. Statistically, about 18% send text messages and e-mails while driving. An estimated 49% of those aged 21 to 24 years old admit to send text messages while driving, with an assumption that by doing so, the driving performance is not affected. Otherwise, 90% of passengers confirmed that they would feel not secure if their driver was using a cell phone. In the survey, most males and younger participants underestimated the negative impact of the cell phone on driving.

Generally, most drivers agree that driving is more dangerous when they fail to concentrate for 2 seconds or more. About 35% of drivers aged 18 to 24 years old reported that they can text at an average of 3 or more securely (Tison, 2011).

Adolescent drivers cause accidents majorly due to dangerous distraction by cell phones while driving. The NYDS, (National Young Driver Survey), carried out a research of (N = 5665) adolescent drivers to determine how psychosocial correlates with cell phone use on driving. The outcome showed more advantages on abstaining from using phones while driving (Hafetz, 2010).

High gain messages are framed as an investment to intervene to change of road user behavior. This becoming most effective techniques (Fylan, 2014).

On road use safety, the impact of the gain-framed or loss-framed messages on changing drivers’ intention has not been fully researched on. For the effective use of such messages, I hypothesize that; Gain-framed, high issue involvement inducing safety messages, or both about mobile phone use while driving will be more effective in changing people’s intentions towards this behavior.

Participants

The research participants were recruited from Macquarie University by convenience sampling. At the beginning, 892 responded to participate. Later, the number reduced to 343 after removing participants who didn’t read the entire involvement statement. That is, (less than ten seconds spent on screen) and those aged above 26 years. From this final data, the participants were 74% female and 26% males with an age range of 18 to 26 years old.

Materials

One of the materials used for this research was the modified intention measure obtained from Hatfield, Kasparian, Murphy and Job, 2005. Which was used to measure the intention of drivers about driving while fatigued, in this context, driving while responding to calls and texts (Hatfield, 2005).

Results

In order to create a table showing the intention in driving while using a cell phone variable, results from different questions were averaged to create an intention score for analysis. In calculating the average, the pre-intention scores was negated from the post-intention score.

Procedures

After recruitment, the participants completed the study through the online survey platform Qualtrics provided. This was followed by filling of a demographic forms by every successful participant. The demographic questions consisted of the gender, age, ethnicity, education status or work.

Lastly, the participants filled the response forms related to the study for post measure and the pre measure of the intentions about using mobile phones while driving in the order of; high involvement/gain framed message, low involvement/loss framed message, high involvement/loss famed message and low involvement/gain famed message.

Descriptive statistics

Demographics

From the demographics, the mean age is 19.207 for N=343, the males 25.07%, females 74.34% and 0.58% others. The mean of years licensed for the participants was 3.018421.

Tabulation of mobile phone use.

How often do you use your phone while driving?	Freq.	percent	Cum.
Three or more times a week	47	13.70	13.70
Once or twice a week	93	27.11	40.82
Once or twice a month	35	10.20	51.02
Less than once a week	61	1778	68.80
Never	107	3120	100
Total	343	100

Tabulation of others mobile phone use    

How often do you think others use their phone while driving?	Freq.	percent	Cum.
Three or more times a week	194	56.56	56.56
Once or twice a week	118	34.40	90.96
Once or twice a month	21	6.12	97.08
Less than once a month	6	1.75	98.83
Never	4	1.17	100
Total	343	100

The data of a measure of drivers’ intentions to talk on phone as well as their intentions to text while driving were collected and tabulated as shown below.

Hypothesis testing

Talking

• Hypothesis 1: Gain-framed vs Loss-frame conditions

Two-sample t test with equal variances

Variable	Obs.	Mean	Std. err.	Std. dev.	95% conf.
Loss Gain	169 174	6.843195     5.675287	.9029805     1.000895	11.73875     13.20271	5.0605448.625846   3.69975  7.650825
Combined	343	6.250729	.6748446	12.4983	4.92336  7.578097
Difference		1.167908	1.35033		-1.488117 3.823933

Difference = mean(Loss) – mean(Gain)                 t =   0.8649

Ho: diff = 0                                                                          degrees of freedom = 341

Ha: diff < 0                 Ha: diff!= 0                 Ha: diff > 0

Pr(T < t) = 0.8062         Pr(|T| > |t|) = 0.3877          Pr(T > t) = 0.1938

Hypothesis 2: High-issue involvement vs Low Issue involvement conditions

Two-sample t test with equal variances

variable	Obs.	Mean	Std. err.	Std. dev.	95% conf. int
Low	182	4.431319	.845987	13.3611	2.762053    6.100584
High	161	8.307453	1.053002	13.3611	6.227878    10.38703
Combined	343	6.250729	.6748446	12.4983	7.578097
Difference		-3.876135	1.337841		-6.507594   -1.244676

Difference= mean (Low) – mean (High)                                 t = -2.8973

Ho: diff = 0                                                                            degrees of freedom = 341

Ha: diff < 0                 Ha: diff! = 0                 Ha: diff > 0

Pr(T < t) = 0.0020         Pr(|T| > |t|) = 0.0040          Pr(T > t) = 0.9980

Hypothesis 3: Gain-framed High-issue involvement vs. Loss-framed High-issue involvement

Two-sample t test with equal variances

variable	Obs.	Mean	Std. err.	Std. dev.	95% conf.
Loss Gain	81 80	8.37037        8.24375	1.399095   1.585037	12.59186 14.177	5.58608211.15466 5.08881311.39869
Combined	161	8.307453	1.053002	13.3611	10.38703
Difference		.1266204	2.112633		-4.045822    4.299063

Difference= mean (Loss) – mean (Gain)                                t =   0.0599

Ho: diff = 0                                                                            degrees of freedom = 159

Ha: diff < 0                 Ha: diff! = 0                 Ha: diff > 0

Pr(T < t) = 0.5239         Pr(|T| > |t|) = 0.9523          Pr(T > t) = 0.4761

The graph of mean change in intention to talk on the phone while driving between the four groups. 

Texting

• Hypothesis 1: Gain-framed vs Loss-frame conditions

Two-sample t test with equal variances

Variable	Obs.	Mean	Std. err.	Std. dev.	95% conf.
Loss Gain	169 174	4.955621      4.563218	1.002022     1.046107	13.02628     13.7991	2.9774456.933798 2.498443    6.627994
Combined	343	4.75656	.7238406	13.40572	3.33282      6.1803
Difference		.3924029	1.449801		-2.459276    3.244081

Difference = mean (Loss) – mean (Gain)                                t =   0.2707

Ho: diff = 0                                                                            degrees of freedom =      341

Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0

Pr(T < t) = 0.6066         Pr(|T| > |t|) = 0.7868          Pr(T > t) = 0.3934

Hypothesis 2: High-issue involvement vs Low Issue involvement conditions

Two-sample t test with equal variances

Variable	Obs.	Mean	Std. err.	Std. dev.	95% conf. interval
Low	182	4.568681	1.008786	2.578188	6.559174
High	161	4.968944	1.041172	2.912732	7.025156
Combined	343	4.75656	.7238406	13.40572	3.33282 6.1803
Difference	-.4002628	1.452366		-3.256986	2.456461

Difference = mean (Low) – mean (High)                                 t = -0.2756

Ho: diff = 0                                                                               degrees of freedom =      341

Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0

 Pr(T < t) = 0.3915         Pr(|T| > |t|) = 0.7830          Pr(T > t) = 0.6085

Hypothesis 3: Gain-framed High-issue involvement vs. Loss-framed High-issue involvement

Two-sample t test with equal variances

Variable	Obs.	Mean	Std. err.	Std. dev.	95% conf. interval
Loss	81	4.895062	1.259952	11.33956	7.402445
Gain	80	5.04375	1.670533	14.9417	8.368862
Combined	161	4.968944	1.041172	13.21099	7.025156
Difference		-.1486883	2.088889		3.976859

Difference = mean (Loss) – mean (Gain)                                t = -0.0712

Ho: diff = 0                                                                              degrees of freedom =      159

Ha: diff < 0                 Ha: diff!= 0                 Ha: diff > 0

Pr(T < t) = 0.4717         Pr(|T| > |t|) = 0.9433          Pr(T > t) = 0.528

Graph representing the mean change in intention to text while driving between the four groups.

The study was set to investigate the whether the message framing in terms of a gain or a loss impact to change drivers’ intentions and how the effectiveness of such messages can be increased by introducing high issue involvement to the individuals (Chaurand, 2015). From the research analysis, all the hypothesis are supported. Evidently, the high gain framed together with high involvement is effective way to change the intentions of the driver as it is a psychological factor. This can effectively reduce accidents among young drivers (Cazzulino, 2014).

In conclusion, the road safety campaign is dependent on its effectiveness to change the intention of drivers. The high gain frame messages with high involvement can be adopted as one of the current measures (Hoekstra, 2011). This practice for road safety has a psychological influence especially in change the intention of individual on the subject matter and this can help promote safe driving among young people (Millar, 2000).

References

Braitman, K. A. (2010). National reported patterns of driver cell phone use in the United States. . Traffic injury prevention, 11(6), 543-548.

Cazzulino, F. B. (2014). Cell phones and young drivers: a systematic review regarding the association between psychological factors and prevention . Traffic injury prevention, 15(3), 234-242.

Chaurand, N. B. (2015). A naturalistic study of the impact of message framing on highway speeding. Transportation research part F. traffic psychology and behaviour, 35, 37-44.

Fylan, F. &. (2014). Behavioural Change Techniques used in road safety interventions for young people. . Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 64(3), 123-129.

Hafetz, J. S.-E. (2010). Adolescent drivers’ perceptions of the advantages and disadvantages of abstention from in-vehicle cell phone use. Accident Analysis & Prevention, 42(6), 1570-157.

Hatfield, J. M. (2005). Risk perceptions, attitudes and behaviours regarding driver fatigue in NSW youth: The Development of an Evidence-Based Driver Fatigue Educational Intervention Strategy. Report to the Motor Accidents Authority of NSW.

Hoekstra, T. &. (2011). Improving the effectiveness of road safety campaigns: Current and new practices. . IATSS Research, 34, 80-86.

Millar, M. G. (2000). Promoting safe driving behaviors: The influence of message framing and issue involvement. Journal of applied social psychology, 30(4), 853-866.

Pelletier, L. G. (2008). Persuasive communication and proenvironmental behaviours: How message tailoring and message framing can improve the integration of behaviours through self-determined motivation. Canadian Psychology/Psychologie canadienne 49(3), 210.

Tison, J. C. (2011, 12). TRB: National phone survey on distracted driving attitudes and behaviors. Retrieved from TRID: https://rosap.ntl.bts.gov/view/dot/192