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Lab Report Assignment - The Relationship between Age, Gender and Non-drinking Motives on Alcohol Reduction

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Abstract

The research examines the relationship between alcohol consumption and disgust message framing as an intervention for alcohol intentions, replication and other important individual factors such as demographics and non- drinking motives. Those who participated in the study were 400 respondents aged between 18 and 40 years from different parts of Australia. These respondents completed a questionnaire aimed at evaluating demographic details such as sex and years and other variables like identity, intention, condition and non-drinking motive.

This study explored different types of message framing and their effects on reducing the drinking intentions of alcohol users. Furthermore, the research explored the relationship between non-drinking motives, age and gender in predicting the intentions of drinking. The findings showed a significant relationship between age, gender and non-drinking motives in predicting drinking intentions.  Loss framing messages were found to be effective in reducing alcohol consumption.

Question - Introduction

The purpose of the intro is to:

1. Introduce the topic and build a rationale for the study

2. Introduce relevant content such as definitions and relationships as needed

3. Provide a rationale for the study (for both our hypotheses and for the replication-extension aspect)

4. Provide rationales for the predictions/hypotheses made

Solution- Introduction

Dietary Guidelines for Americans defines average consumption as taking about two drinks daily for men while for women is one drink daily. This defines average drinking per day and not for several days. Alcohol consumption is a significant problem in Australia with it problematic use connected to may negative results. The wide consumption is because of the availability of alcohol in social and cultural activities. Nonetheless, high consumption levels causes major issues related to health specifically increasing the risk of premature death, injury and chronic diseases. Reports indicate that majority of the population aged over 14 years are the victims of alcohol related incident.

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Multiple messaging has been used by the public health on different types of messaging frames such as gain or loss in a bid to assist drinkers to maintain low risk levels of consumption. Fear based messaging and particularly disgust-based messaging has proved to be mainly effective in minimizing drinking intention of alcohol (Collymore & McDermott, 2016).

The research based on Burry (2008) indicate that in England, over ten million people surpass standardized level of drinking use per day therefore making the countryincurr about 25.1 billion per year. This kind of trend causes serious effects such as illness, violent and aggressive behavior which are a matter of grave concern to the policy makers and government (The European Alcohol Policy Alliance, 2012). One way of assisting those who have high risk level of consumption has been through making them drink responsibly. Awareness initiatives such as Drinkaware has been doing so through informing of people standard alcohol limit use per day.

Thus the idea of risk drinking has been made easier and simple to identify. This way, health communication practitioners have tried to handle this risky drinking through the distribution of vital information using health communications that utilizes various kinds of message frames like gain or loss frames in a bid to promote healthier behavior, attitudes and intentions among the people (Gallagher and Updegraff, 2012). Based on the way messaging is relayed, benefit for embracing required level may be portrayed as a gain, while lack of adoption is presented as a loss frame.

Framing Message

The main idea about message framing is found in the literature given by Prospect Theory.This studies suggests, individuals portrayed as positive frames do not want to potentially risk those positive but rather prefer certainty (Kahneman, 2012). Nonetheless, when such people find themselves in possible loss, they have a tendencies of risking as a form of minimizing their probability of loss. Studies done by Salovey and Rothman (1997) depicts that the framing of message and healthy behavior indicate loss and gain frame messages play a different role in convincing people depending on certain health attributes. When health behavior have a more certain results, people are highly convinced by a gain framed whereas the health behavior that are uncertainpeople tend to be persuaded by loss framed. Even though these health messages use different frames of loss and gains, strategies of framing have been used in a broader concept of issues related to health.

Fear framing

Public health uses this form of framing in communication and therefore it is a subject of great scrutiny.  Loss or fear appeal put more emphasis on harmful impact that can be caused by not adopting message recommendation about health. Fear framing intents to cause fear among people so that they can embrace healthier behaviors. (Maloney et al, 2011) argues that when emphasizing on threat, individual either attempt to control danger or they attempt to lessen it through the perception that threat is less fatal. Controlling of danger leads to involvement with the recommendation of the message acts while controlling fear leads to discrediting the risk and non-involvement with recommended acts.

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Disgust framing

According to Bennet (1998) framing of fear strategically causes feeling of fear and also causes emotions that can regulate acts and views.Nonetheless, studies rarely concentrate on regulating impacts of other feelings for instance ant-smoking fear. Another studies have shown that framing that is able to adjust tends to prevent contamination of illness (Curtis, 2011). The review by Oaten et all 2009 shows that this type of framing have the ability to cause disease.

Question - Hypotheses

For between groups analyses:

What groups are being compared?

Compared on what?

What is the predicted outcome (based on literature and reasoning)?

For regression analyses:

What are the predicted relationships?

What about combined, individual, and relative effects?

Solution- Current study and hypothesis

Considering this review, this study aims to focus on the way people perceive framing messaging as methods that transform intentions of drinking alcohol and the impact of loss and gain affect. Considering the role of avoidance played by disgust framing, the research evaluates impact of framing information on drinking intention. This research will aim to answer the following research questions:

• Is alcohol consumption a problem in Australia?

• Is disgust message framing an effective strategy for reducing alcohol consumption?

• Why is replication important?

• What types of individual factors (no-drinking motives, age and gender) might also contribute to alcohol- related drinking intentions?

This research will answer the following hypothesis:

Hypothesis 1:  Different message framing effect on alcohol consumption and related gain and loss frames

Hypothesis 2:  the effect of individual factors such as age, gender non-drinking motives on the alcohol related drinking intention.

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Question- Methods

Write your own participants section (see specific requirements as set out in the ‘Method' and ‘Lab Report Instructions' documents) and the rest can be ‘cut-and-pasted' from the ‘Method' document (leave out the reference list information from your Method).

Solution

There were 400 participants in this study (138 male and 262 female) with ages ranging from 18- 40 years (M = 1.66, SD = 0.476, Min=1, Max=2). Total male were 34.5% while total female were 65.5%. Loss fear Health were 17%, Loss Disgust Social were 19.3%, Gain Health were 15%, Loss Fear Social were 16.3%, Loss Disgust Health were 16.5% and Gain social were 16. The overall sample of condition had a mean of 3.44 and SD of 3.916.

Materials

Age

Respondents entered their ages in years.

Sex

Respondents entered their gender as “Male”, “Female”, “Transgender” and “Other”. Only Males and Females responded to the current survey, therefore making this a dichotomous variable.

Message Frame Conditions – Experimental intervention

Following Collymore and McDermott (2016) participants were randomly allocated to a questionnaire in which one out of six photographs happened followed by a differentiated health convincing message. Messaging involved two gain-framed, two disgust-loss framed, two fear loss communications. These text and picture combinations can be seen on page 1911 of Collymore and McDermott (2016). Participants were instructed to check the photo and study the text related health, then to complete the remainder of the questionnaire.

Drinking Intentions

Intentions to minimize current levels of Alcohol Consumption was assessed by a question asking participants: The extent they intend to minimize current alcohol consumption level. This question was answered on a 5-point Likert scale, with higher scores indicating greater intentions to reduce alcohol consumption.

Non-drinking Motives

Following Bekman et al. (2011), five items from the intention for avoiding Alcohol use Questionnaire (MAAQ: Stritzke& Butt, 2001) were averaged to create an abbreviated measure giving summary of key reasons for not drinking. Every item was rated on a 5 point scale (not at all important to extremely important). This measure has demonstrated strong reliability previously (a = .82; Bekman et al., 2011), as well as in the current sample (a = .89).

Procedure

Participants were adults who were invited to participate via social media advertisements. The study was conducted via an online survey platform (Qualtrics). Respndentswho accepted to take part in the study were provided with the questionnaire link. Respondents were then assigned randomly to conditions of message and completed the questionnaire.

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Question - Results

•Descriptives then inferential statistics.

•Table the descriptives (all variables included in ONLY the regression analysis), describe one or two of these descriptives (see ‘example lab report')

•Your reported stats should correspond to the hypotheses you make

•Write up ANOVA in-text (see seminars 4/5 for APA examples)

•Write up regression in-text (see seminar 3 for APA example)

•Be concise in this section, do not interpret

Solution

Descriptive statistics

Means, minimum, maximum and standard deviation scores for every variable used in the regression analysis have been presented in Table1. Descriptive results of these participants indicate a moderate condition of framing across the six groups. With regard to drinking intention, majority of the participants has no intention of reducing their consumption. Majority of the respondents scored less than 3.

Table 1

 

N

Minimum

Maximum

Mean

Std. Deviation

The extent of alcohol reduction

400

1

5

2.54

.869

Condition

400

1

6

3.44

1.717

Gender

400

1

2

1.66

.476

Age

400

18

40

28.56

3.916

ID

400

1

400

200.50

115.614

MAAQ; Nondrinking motives

400

1.00

5.00

3.2850

.96785

Valid N (listwise)

400

 

 

 

 

The results from the independent t-test for sex indicated that there were no mean difference in the scores between males and females.

The results from the univariate regression analysis indicate that independent variables such as age, gender and non-drinking intentions significantly affect the dependent variable alcohol drinking intention. The multiple regression model summary indicated the R=0.724, multiple R= 0.524 and adjusted R-square= 0.518.  F-statistic= 0.00.

Anova Results indicate F-statistics=86.66 and P-val=0.00. Table 2 show the results for this analysis.

Table 2

Model Summary

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.724a

.524

.518

.604

ANOVAa

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

157.882

5

31.576

86.664

.000b

Residual

143.555

394

.364

 

 

Total

301.437

399

 

 

 

The Loss Fear Health and loss Disgust Health showed no significance mean difference.

The Loss Disgust Health and the Loss disgust Social have no significance difference

Loss Disgust Social and Gain Health have no significance difference in means

Loss fear health and Gain Health have no significance difference in means.

Table 3

Multiple Comparisons

Multiple Comparisons

Tukey HSD

(I) Condition

(J) Condition

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

Loss Fear Health

Loss Disgust Social

.00

.122

1.000

-.35

.35

Gain Health

.40*

.130

.031

.02

.77

Loss Fear Social

-.14

.128

.876

-.51

.22

Loss Disgust Health

-1.12*

.127

.000

-1.48

-.75

Gain Social

.15

.128

.864

-.22

.51

Loss Disgust Social

Loss Fear Health

.00

.122

1.000

-.35

.35

Gain Health

.40*

.127

.022

.04

.76

Loss Fear Social

-.14

.124

.875

-.49

.22

Loss Disgust Health

-1.11*

.123

.000

-1.47

-.76

Gain Social

.15

.124

.834

-.21

.51

Gain Health

Loss Fear Health

-.40*

.130

.031

-.77

-.02

Loss Disgust Social

-.40*

.127

.022

-.76

-.04

Loss Fear Social

-.54*

.132

.001

-.91

-.16

Loss Disgust Health

-1.51*

.131

.000

-1.89

-1.14

Gain Social

-.25

.132

.414

-.63

.13

Loss Fear Social

Loss Fear Health

.14

.128

.876

-.22

.51

Loss Disgust Social

.14

.124

.875

-.22

.49

Gain Health

.54*

.132

.001

.16

.91

Loss Disgust Health

-.98*

.129

.000

-1.34

-.61

Gain Social

.29

.130

.228

-.08

.66

Loss Disgust Health

Loss Fear Health

1.12*

.127

.000

.75

1.48

Loss Disgust Social

1.11*

.123

.000

.76

1.47

Gain Health

1.51*

.131

.000

1.14

1.89

Loss Fear Social

.98*

.129

.000

.61

1.34

Gain Social

1.26*

.129

.000

.90

1.63

Gain Social

Loss Fear Health

-.15

.128

.864

-.51

.22

Loss Disgust Social

-.15

.124

.834

-.51

.21

Gain Health

.25

.132

.414

-.13

.63

Loss Fear Social

-.29

.130

.228

-.66

.08

Loss Disgust Health

-1.26*

.129

.000

-1.63

-.90

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Question - Discussion

Frame the story: Restate aims & hypotheses

Address the predictions - Are hypotheses supported?

Implications

What does this mean for past research?

What does this mean (generally; or for theory)?

Are there practical implications? (Important)

Solution :

This study aimed at evaluating the different messaging frames relative to others with the intention to reduce alcohol consumption. The results shows that based on the hypothesis, there is a differential effect of the six conditions of messaging. The Loss Disgust Health was found to be the most effective in reducing alcohol consumption followed by Loss Fear social then Loss Fear Health and Gain Health.  The frames with the least effective at producing intention to minimize alcohol consumption were Gain social and Loss fear Health. Even though drinking is a habit that happens from a personal perspective, the framing messages that outline the risks associated with health and not those promoting social benefits of alcohol consumption seemed to be more effective for transforming the threat.

According to woolf (2007) outlines the three kinds of disgust, namely, interaction among people, immorality, and physical contact with undesirable others.Leshner et al (2011) argues that both disgust and fear have same effects on resources allocated to design messages. The study shows that there is a trend in using superior framing of messaging and from the results fear loss frames and loss disgust frames show have no statistical differences in reducing alcohol compared to less effective frames such as gain framed conditions. The results from this analysis indicate that when people are reminded of their health risks as a result of drinking they tend to be more concerned relating to their drinking habit and are more motivated to reduce their consumption of alcohol as opposed to social consequences.

The findings from this study indicate that using loss framed messages to reduce alcohol consumption habit and promoting health is more effective than using the health gain frames. This results is inconsistent with Rothmanet all (2006) argument of gained frames as more effective in preventing diseases and health related issues.

The findings from the multiple regression analysis indicated that the non-drinking motives, age and gender have statistical significance in predicting the intention to reduce the consumption of alcohol. Non-drinking motive was found to be contributing most in the reduction of alcohol consumption.

The study did not lack some limitations methodologically, one is the likelihood that processing of messaging frames could have been affected by the designers emotional states (Choi and Choi, 2010) and other personality factors may have also had a moderating effect. Additional studies might address these limitations and evaluate whether the kind of messaging frame can evoke too much disgust and as result become ineffective in a controlled setting.

In conclusion, the findings of this research suggest that a relationship exist between non-drinking motives, age and gender in predicting the intention of reducing alcohol consumption habits. The findings also conclude that the use of loss health frames are more effective in reducing drinking intentions. Additional research need to be done to replicate this findings considering the limitations identified in the study.

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