Direct searches

Given that a large number of repetition priming studies have used the LDT to assess RTs to word stimuli (e.g., Albrecht & Vorberg, 2010; Dannenbring & Briand, 1982;

Scarborough et al., 1977; see chapter 5), a word/ non-word LDT was used in Study 2 to assess message processing. The LDT involves participants responding as fast and as accurately as possible as to whether a presented letter string represents a word or a

pseudoword (i.e., a pronounceable non-word). Pseudowords were created by changing one letter from the current word stimuli (e.g., word to wrrd). The participants’ correct RTs to the words previously presented as part of the messages were analysed to assess differences in cognitive word processing and faster RTs to correct word responses were taken to reflect greater initial attention and processing of the initial message on the screen.

Message Word stimuli. Each word list consisted of 12 words from each of the physical messages, social messages, and motor vehicle message (i.e., a total of 36 word stimuli; see chapter 6). The 36 filler words that best matched the arousal and valence ratings of the road safety and vehicle message words (Studies 1a and 1b) were included in the LDT.

Non-word stimuli. A non-word generation program (WordGen; Duyck, Desmet, Verbeke, & Brysbaert, 2004) was used to create pseudowords by replacing one letter from the current message word stimuli and from the corresponding filler words. To ensure that the

122 non-words had a similar orthographic structure to the word stimuli, a vowel was used to

replace a vowel and a consonant was used to replace a consonant. With the exception of seven words,²⁹ the first and last letters in the message and filler word stimuli remained the same when creating the corresponding word stimuli. Tables 7.1 and 7.2 present the non-word stimuli and corresponding non-word stimuli included in the road safety messages and motor vehicle message, respectively.

Past research has also suggested that neighbourhood size and bigram frequency may influence participants’ RTs to non-word stimuli (see Duyck et al., 2004; Keuleers &

Brysbaert, 2010, for discussions on creating appropriate non-words). Neighbourhood size refers to the number of additional words that can be created by changing one letter in an existing word (Duyck et al., 2004). In terms of non-words, neighbourhood size is used to assess how closely a non-word is related to a word (i.e., non-words that have higher neighbourhood sizes are more closely related to words than non-words with lower

neighbourhood sizes). Bigrams are the number of letter pairs that are presented together in words (e.g., the word ‘list’ contains three bigrams, li, is, and st). Non-words with a higher bigram frequency are more closely related to words than non-words with a lower bigram frequency and thus, it is important to control for bigram frequency in lexical decision tasks.

Therefore, neighbourhood size and bigram frequency of the non-words were controlled between the message non-word lists. Of note, there were no significant differences between the neighbourhood size and bigram frequency of the non-words between the three message conditions (see Tables 7.3 and 7.4).

29 Seven words included in the LDT consisted of three letters. Since replacing a middle letter with a vowel in these words would still represent a word (e.g., put) or alternatively, would not be considered as an appropriate pseudoword (i.e., a pronounceable non-word), these seven words either had the first or last letter changed.

123 Table 7.1

Road Safety Message Word and Non-word Stimuli Physical messages Physical message

words

Physical message non-words

Physical filler words Physical filler non-words

each eath easy eacy

year yoar hand hund

australia ausyralia singapore sinyapore

people peoble father farher

obey orey rank rark

chance chasce change chalge

protect prodect forgive fortive

one ose any acy

posted possed lounge lounce

number nomber dinner dincer

physical plysical confused conrused

sustain sushain inspect inspact

Social messages Social message

words

Social message non-words

Social filler words Social filler non-words

choose choese decide dekide

friend friand family fasily

car cer dad dah

showing shoning weather weacher

really reanly little luttle

care cabe hope hofe

safety sakety spring spling

feel fiel must munt

comfortable comfoptable responsible ressonsible

put pul ask asy

being beang woman wogan

best beft real reil

124 Table 7.2

Motor Vehicle Message Word and Non-word Stimuli Motor vehicle message Vehicle message

words

Vehicle message non-words

Vehicle message filler words

Vehicle message filler non-words

achieve acheeve applied apphied

exceeds expeeds compile commile

vehicle vehacle journey joulney

powered powired immense imsense

engine engane market marlet

reaches reashes reflect redlect

top tok hot hof

street streit answer ansler

permitted perwitted entertain eentertain

test tect list lipt

today togay house hoose

all aly get gek

125 Table 7.3

Neighbourhood Size and Bigram Frequency Statistics for the Non-word Message Word Stimuli

Variable M (SD) t p 95% CI

Neighbourhood size

Social non-words 3.54 (2.96)

Physical non-words 3.31 (2.06) 0.23 .819 -1.83, 2.30 Social non-words

Vehicle non-words 3.31 (3.73) 0.18 .863 -2.50, 2.96 Physical non-words

Vehicle non-words < 0.01 1.00 -2.44, 2.44

Bigram frequency

Social non-words 10300.62 (6572.72)

Physical non-words 10241.38 (3760.68) 0.03 .978 -4275.46, 4393.912 Social non-words

Vehicle non-words 10277.69 (5325.53) 0.01 .992 -4819.44, 4865.29 Physical non-words

Vehicle non-words -0.02 .984 -3768.22, 3695.61

Note. CW = CI = Confidence Interval

126 Table 7.4

Neighbourhood Size and Bigram Frequency Statistics for the Non-word Filler Word Stimuli

Variable M (SD) t p 95% CI

Neighbourhood size

Social filler non-words 3.54 (2.44)

Physical filler non-words 3.08 (2.53) 0.47 .640 -1.55, 2.47 Social filler non-words

Vehicle filler non-words 3.08 (2.36) 0.49 .628 -1.48, 2.40 Physical filler non-words

Vehicle filler non-words < 0.01 1.00 -1.98, 1.98 Bigram frequency

Social filler non-words 9814.54 (7593.60)

Physical filler non-words 10857.38 (5721.83) -0.40 .696 -6485.44, 4399.74 Social filler non-words

Vehicle filler non-words 9762 (6855.16) 0.02 .985 -5803.43, 5908.51 Physical filler non-words

Vehicle filler non-words 0.44 .662 -4015.95, 6206.72

Note. CW = CI = Confidence Interval

127 7.3 Aims and Hypotheses

There were three overarching aims for Study 2: (i) to assess if individual differences in reward and punishment sensitivities influenced young drivers’ processing biases of content presented via gain-framed and loss-framed anti-speeding messages (as assessed via a

computerised LDT); (ii) to examine if these processing differences would influence subsequent message acceptance ratings (as assessed via self-report ratings of message effectiveness, attitudes, behavioural intentions, and actual behaviour);³⁰ (iii) to induce BIS activation to enable examination of its influence on processing and persuasive outcomes. This final aim was operationalised by exposing a subsample of young drivers to a loss-framed road safety message (emphasising the negative consequences of speeding behaviour; designed to activate the FFFS) and a high performance motor vehicle message (designed to activate the BAS). Four key hypotheses were generated from these research aims.

As discussed in chapter 2 (section 2.2.3), the BAS is activated by reward stimuli, and individuals with a stronger BAS are more sensitive to cues of reward (e.g., gain-framed messages) than those with a weaker BAS. By contrast, the FFFS is activated by punishment stimuli and individuals with a stronger FFFS are more sensitive to cues of punishment (e.g., loss-framed messages) than those with a weaker FFFS (Gray & McNaughton, 2000). From these basic tenets, three key predictions followed, namely that:

H.1. Individuals with a stronger BAS would demonstrate a greater cognitive bias towards the content presented via the gain-framed messages, compared to individuals with a weaker BAS. Further, these individuals would be more likely to accept these messages (as measured by subsequent ratings of message effectiveness, attitudes, behavioural intentions, and message compliance).

30 From this point forward the term ‘message compliance’ will be used when referring to participant’s self-reported actual behaviour.

128 H.2. Individuals with a stronger FFFS (compared to those with a weaker FFFS) would

demonstrate a greater cognitive bias towards the content presented via the loss-framed messages. It was further predicted that greater processing bias would predict greater acceptance and compliance for that message frame.

H.3. Stronger BAS would predict greater processing, acceptance and compliance of the physical gain-framed message compared to the physical loss-framed message. Similarly, it was anticipated that individuals with a stronger FFFS would show greater processing, acceptance and compliance of the physical loss-framed message than the physical gain-framed message. Further, it was hypothesised that this finding would be replicated for the social gain-framed and loss-framed messages.

The BIS is activated when conflict occurs between the BAS and the FFFS (see chapter 2, section 2.2.3). Such conflicts may arise when individuals are exposed

simultaneously to a reward cue that results in the activation of the BAS and to a punishment cue that results in the activation of the FFFS (Corr, 2008). To potentially create goal conflict, participants were exposed to a motor vehicle message that promoted a high performance vehicle (BAS) and a social loss-framed message that highlighted the negative consequences that speeding behaviour may have for the participant and for their family and friends (FFFS).

For those exposed to the mixed message cues (i.e., social loss-framed and motor vehicle message) it was predicted that (H.4.):

a) Individuals with a stronger BIS (compared to those individuals with a weaker BIS) would inhibit their responses, as demonstrated by slower RTs to the words from these

message stimuli (i.e., social-loss and motor vehicle message).

b) Individuals with a stronger BIS would respond slower to words from the framed message compared to their counterparts who were only exposed to the social loss-framed message.

129 c) Individuals with a stronger FFFS (compared to those with a weaker FFFS) would

report greater acceptance of the social loss-framed message. Similarly, it was expected that individuals with a stronger BAS in this condition would show greater acceptance of the vehicle message than those individuals with a weaker BAS.