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Student Guide

to the

CHERMUG Quantitative and Qualitative Games

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Contents The CHERMUG quantitative and qualitative games ................................................................................. 3

The CHERMUG videos…………………………………………………………………..……………………………………………………..3

What is research? ..................................................................................................................................... 4

The research methods cycle ..................................................................................................................... 4

Qualitative and quantitative approaches to research .............................................................................. 6

The qualitative and quantitative games ................................................................................................... 7

The CHERMUG qualitative game .............................................................................................................. 9

Introduction to the qualitative game .................................................................................................... 9

Level 1: being prepared for the qualitative test ....................................................................................... 9

Mini-game 1: Qualitative or quantitative data? ................................................................................... 9

Mini-game 2: Contrasting qualitative and quantitative approaches .................................................. 10

Mini-game 3: Qualitative and quantitative scenarios ......................................................................... 10

Level 2: Passing the qualitative test ........................................................................................................ 10

Mini-game 1: Study design ................................................................................................................. 11

Mini-game 2: Coding qualitative data ................................................................................................. 12

Level 3: Dealing with Qualitative Analysis .............................................................................................. 14

The CHERMUG quantitative game .......................................................................................................... 15

Introduction to the quantitative game ............................................................................................... 15

The sequence of activities in the quantitative game .............................................................................. 16

Study Design: correlational and experimental methods ........................................................................ 17

Operationalising and measuring your variables ..................................................................................... 18

Formulating the hypothesis .................................................................................................................... 20

Acknowledgements ..................................................................................................................................... 21

References…………………………………………………………………………………………………………………………………………….21

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The CHERMUG quantitative and qualitative games

The CHERMUG (Continuing/Higher Education in Research Methods Using Games) quantitative and

qualitative games are two online digital games which have been designed to provide activities to

support students as they learn about research methods and statistics. The quantitative game is a web-

based game which you can access at http://playgen.com/chermug. You will find the qualitative game

loaded onto the desktop of your computer in the folder qualitative. The two separate CHERMUG games

reflect the two main approaches (quantitative and qualitative) which have been developed to carrying

out research. The games have been designed to help you to acquire research skills in a fun way by

simulating some of the activities carried out by researchers as they tackle research methods problems.

The games guide you through different stages in research from formulating a hypothesis to analysing

and interpreting data, allowing you to practice some of the basic skills that students typically find

difficult. The games are designed to complement introductory modules on research methods and

statistics and can be played in any order. Each game can also be played on its own.

The CHERMUG videos

In addition to this student guide, four videos have been prepared which describe the CHERMUG games

and explain how they might be used for learning about research methods and statistics. The links are as

follows:

1. CHERMUG Games Introduction http://youtu.be/BDc1bUEjHbc

2. What are CHERMUG games? http://youtu.be/cB-JS4wntd0

3. Why CHERMUG games? http://youtu.be/NntlobanHLk

4. How to use CHERMUG games http://youtu.be/GVbO2zqnm0w

Game content The content for both the qualitative and the quantitative games focuses on obesity and

related issues. This topic has been chosen to be of relevance and interest to most people. During the

20th century obesity became a major global social and health problem and was recognized as a global

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epidemic in 1997 by the World Health Organization (WHO) (Caballero, 2007). By 2005 WHO estimated

that at least 400 million adults across the world were obese. There are many factors which impact on

obesity and the games provide an opportunity to examine how research methods and statistics can help

to provide more rigorous approaches to understanding these.

However it is important to realise that, although you are acquiring skills in the content area of obesity,

once you have acquired these qualitative and quantitative research skills you can apply them regardless

of the content area of the problem. These skills truly are transferable to other content areas.

Before we look at the games in more detail we will briefly consider what research is and describe the

research methods cycle which underpins both games. We will then also consider in more detail

differences between the qualitative and quantitative approaches to research.

What is research?

Research provides a method for tackling problems and developing knowledge which is more rigorous

and systematic than other less formal approaches such as asking friends or relying on the media.

Research is a systematic method of inquiry which uses a ‘scientific’ approach. The scientific method

provides a well-established approach to investigating phenomena, developing new knowledge or

advancing and modifying previous knowledge. It is based on the collection of empirical evidence to

advance or support an argument. Both qualitative and quantitative approaches to research collect

empirical evidence but they differ in the kinds of evidence that they collect.

The research methods cycle

The process of carrying out research can be depicted as a cyclical problem solving activity with different

activities and tasks which are carried out at different stages in the cycle. Authors differ in the number of

stages that they suggest but the basic stages are the research question, data collection, data analysis,

and discussion & conclusion (Couchman and Dawson, 1990).

The research question All research begins with an area that is being investigated and a more specific

idea, question or problem about that area. In new areas of research, ideas might emerge from

observations of phenomena, through discussions with colleagues or increasingly through the media.

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Very often there would be a perception that a pattern of behaviour or characteristics is emerging which

requires further investigation. In more established areas of research it is likely that some research has

already been carried out. A first step in developing your research idea would be to carry out a literature

review to track down previous high quality research in the literature which is relevant to your proposed

research idea or question.

In our case the research area under investigation is obesity. In order to make progress in investigating

obesity researchers would select a more specific issue that they are interested. For example they might

be interested in what determines the food preferences and choices of obese (and non-obese)

individuals, how effective different kinds of diet or exercise class are in supporting weight reduction, or

links between body image and obesity. In the game we will follow up some of these questions.

Developing the research question Having identified a research question the next stage is to refine this

question. There are many issues which need to be considered in developing your research question:

your aims and objectives in carrying out the study What do you want the study to achieve.

your research design In developing a research question one of the first questions to emerge

concerns the design of the study. The research design refers to the plan or structure that guides

the research process and determines what kind of data will be collected and how that data will

be collected and analysed. Research designs can take many forms and depend on the idea,

question or problem the researcher is studying. The most fundamental design decision is

whether you will adopt a qualitative or quantitative approach to research.

data collection method Whether you choose a qualitative or quantitative design, you will need

to consider an appropriate information-gathering methodology, where you will gather your data

and who from.

formulating your hypothesis If you are carrying out a quantitative study, you should develop a

hypothesis or hypotheses to test. A hypothesis is a statement predicting a relationship between

two or more variables.

links between these issues

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Data collection At the data collection phase you will collect the qualitative or quantitative data which

has been specified at the design stage.

Data analysis Once the data is collected, data analysis will take place. While data analysis can be

complex, it should be clear from the earlier stages of the study design how you will analyse your data.

Discussion Having analysed the data as specified, the results of the data analysis need to be interpreted.

You will need to examine whether the results provide evidence to support the hypothesis or research

question.

It is important to realise that the initial stages of developing a research question and designing your

study to address this research question are the most important since all the other stages follow from

that. If this stage is not carried out correctly the value of the research will be questionable.

Qualitative and quantitative approaches to research

The CHERMUG quantitative and the qualitative games recognise the fundamental distinction between

these two different approaches to carrying out research and in this section we will consider these

differences in more detail. The qualitative and the quantitative approaches to research provide the two

main ways in which scientists and social scientists investigate phenomena in a more systematic way.

Different research disciplines may emphasise one method over another. Both are used frequently in

health and social research.

Qualitative and quantitative approaches differ in terms of their epistemological and theoretical

underpinnings, research design, the kind of data collected and data analysis. Quantitative research

adopts the traditional experimental approach typically associated with science, sometimes called the

hypothetico-deductive approach. The researcher starts with something he or she knows a little about

and wants to explore further. Quantitative researchers make predictions about relationships between

variables in the form of hypotheses which they test by collecting relevant empirical data. In contrast

qualitative research adopts an inductive approach, gathering experimental evidence in an attempt to

generate broad conclusions. Qualitative research has a broader theoretical base than quantitative

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research and is based on a variety of underlying philosophies and traditions from a variety of different

disciplines.

It has been suggested that quantitative research is concerned with the identification and explanation of

facts while qualitative research is concerned with people's interpretation of those facts. Given these

distinctions, a qualitative approach is frequently often more suitable as an exploratory approach used at

the start of an investigation when not much is known about that phenomenon and where a researcher

is trying to identify issues and variables which might be important, while a quantitative approach would

be more useful once the researcher has an idea about variables which might be relevant to test. The

qualitative approach is used to capture expressive information which is not conveyed in quantitative

data about individuals’ subjective experiences, feelings, beliefs and perceptions of a phenomenon or

situation. For example a qualitative study might help us to understand the everyday experiences and

perceptions of an obese person. Qualitative research is more concerned with theory building while

quantitative research is concerned with theory testing (Morse & Field, 1985). With quantitative research

it is important that the researcher remains detached from the participants who are being studied, but in

qualitative research the researcher might get to know the participants well.

Both quantitative and qualitative approaches require the systematic collection of evidence but they

differ in terms of what kind of evidence they collect. Quantitative research adopts an objective approach

to collecting numerical data. Quantitative research collects numerical data, asking questions such as

how much? how many? how often? to what extent? The qualitative approach deals with participants’

verbal descriptions and accounts of phenomena and experiences asking questions such as why? how? in

what way? Qualitative researchers might also study pictures, images or films as data. Findings gained

from qualitative research are subjective. They only apply to the specific set of circumstances under

investigation and typically cannot be generalised in the same way as you might do with the results of

quantitative research studies.

The qualitative and quantitative games

Both the quantitative and qualitative games can be viewed from the perspective of the research

methods cycle which characterises the research process as a cyclical problem solving process with

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different activities and tasks which are carried out at different stages in the cycle. Each game highlights

specific aspects of the cycle. The qualitative game focuses on the differences between qualitative and

quantitative approaches, choosing an appropriate method and sample to address the research question

and carrying out qualitative coding. The quantitative game focuses on the many inter-connected issues

related to formulating and testing a hypothesis, including operationalizing variables, specifying the study

design, summarising and analysing data and interpreting results.

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The CHERMUG qualitative game

You will find the CHERMUG qualitative game loaded onto your computer under the folder CHERMUG

qualitative game. There are three levels of the qualitative game, Level 1, Level 2 and Level 3 which you

will see in that folder. The games should be played in order. To open each game click on the appropriate

level (e. g. Level 1). You will see 3 files: “jre”, “Qualitative-Level1v03” and “Run game”. Click on “Run

game”. There will be a short delay before the game opens up.

Introduction to the qualitative game

The CHERMUG qualitative game includes a narrative which explains that the aim of the game is for you

to become a successful member of a research team carrying out qualitative research on obesity and

that, to do this, you will have to acquire and demonstrate your expertise in qualitative research. You will

then see a few screenshots showing evidence from different sources about the global obesity epidemic,

including official statistics from the World Health Organisation (WHO) as well as stories about obesity in

popular newspapers.

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Level 1: being prepared for the qualitative test

Level 1 of the qualitative game will help you to develop and demonstrate your understanding of the

main differences between quantitative and qualitative approaches to research with respect to

philosophical underpinnings, methods and approaches, kinds of data and data analysis. There are three

mini-games at level 1.

Mini-game 1: Qualitative or quantitative data?

Mini-game 2: Contrasting qualitative and quantitative research

Mini-game 3: Qualitative or quantitative scenarios

Mini-game 1: Qualitative or quantitative data?

In the first mini-game you will be presented with examples of raw data in different formats (see Figure

1) and your task is simply to decide whether a specific data-set is qualitative or quantitative.

Figure 1: example of a qualitative data set

Mini-game 2: Contrasting qualitative and quantitative approaches

The next mini-game is a matching drag and drop game which allows you to demonstrate your

understanding of the differences between qualitative and quantitative approaches to research in four

different areas: general characteristics, theoretical underpinnings, kinds of data and data analysis. You

are presented with characteristics which are typical of either the qualitative or quantitative approach

and you have to match the characteristics to the correct research approach. When you are finished

matching the characteristics, you can check the accuracy of your responses. Characteristics which have

been categorised correctly will turn green, while those which are incorrect will turn red and flash. You

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cannot continue playing the game until all characteristics have been matched correctly (i. e. all have

turned green).

Mini-game 3: Qualitative and quantitative scenarios

In this mini-game you will be presented with a number of scenarios which provide short descriptions of

the background to a research study. Your task is to decide whether each scenario suggests that a

qualitative or quantitative approach would be more suitable in tackling the scenario described.

Level 2: Passing the qualitative test

At level 2 of the qualitative game you will experience some of the important steps that you need to

follow in designing a qualitative study and performing qualitative analysis. The game opens with a

specific research question and a short scenario describing the background to the research question. The

level 2 game is based on a paper by Holsten et al (2012) which is a qualitative study of factors which

influence children’s choices of food in the home environment. There are two mini-games at level 2:

Mini-game 1: Study design

Mini-game 2: Coding qualitative data

Mini-game 1: Study design

Selecting the method of data collection The first issue you need to think about in designing a game is the

method of data collection that you will use. Data collection methods most frequently encountered in

qualitative research are questionnaires, interviews, observation and focus groups, although electronic

methods such as online surveys and wikis are increasingly popular too. The method you chose will

depend on what your research question is as well as practical issues about feasibility. For example if the

research question concerns very sensitive material, personal interview would be best, while surveys are

good for collecting a lot of data quickly. All methods have advantages and disadvantages. Figure 2 shows

a screenshot showing the possible methods of data collection which a player can choose in the game.

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Figure 2: Options available in selecting an appropriate method to gather data

Selecting the participants – Where? The next issue you need to think about is where you will go to

collect your data. This will determine the people who you will invite to participate in the study. For

example in investigating food choices and obesity, would you only want to look at obese people’s

perceptions of why they chose the foods they eat or would you want to look at people of normal weight

too?

Selecting the participants – Who and how many? The next issue that you will be asked to think about is

how many participants you will need to take part in your study and who exactly they would be.

Feedback at level 2: In each of the three design activities described above, you select from among a set

of possible choices (as illustrated in figure 2). Following each selection, you will receive feedback about

how appropriate your choice of method and participants is. If you select the optimal solution, positive

feedback will be provided and the game will continue. If you select a sub-optimal but correct solution

the feedback will indicate why selecting this option might present problems but the game continues. If

you select an incorrect option you will be given feedback about the problems encountered. The game

does not continue and you will be asked to select another option.

Mini-game 2: Coding qualitative data

Coding of data is a key activity in qualitative analysis. Qualitative data typically comprise statements that

people make about their views, perceptions and experiences of the topic under consideration. In basic

qualitative studies, such as those adopting a descriptive or exploratory approach, participants’

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statements are used simply to illustrate specific opinions or experiences. More rigorous qualitative

approaches, such as thematic analysis, aim to extract common, broader themes from the data. The

statements that study participants make are read, their meaning is carefully considered and they are

coded with respect to broader themes or higher level categories that they address.

It is this kind of coding activity that you will carry out in this mini-game. You will be provided with data

taken from a journal article in the form of participants’ verbal statements about a specific topic (in this

case food preferences) and a number of pre-defined thematic categories. Your goal is to correctly

classify each statement according to the appropriate higher level thematic category. Figure 3 shows an

example item of data to be coded at the bottom of the screen, along with the higher level thematic

categories (child, parent, food and context of time) to which you have to assign each item of data at the

top of the screen. You are given eight data items to code and there are eight separate coding categories.

Each item can be coded under several higher level categories but when all eight items are considered

together each item has an optimal coding under a specific category. The items vary in difficulty and

some include an element of ambiguity. This reflects the difficulties which can arise in real life qualitative

coding. You can change your coding as you go through the exercise by cancelling your initial choice and

selecting a new choice. Once you have coded all eight data items, you can check the accuracy of your

coding. Correctly coded items turn green, while incorrectly coded items turn red. If you have coded an

item under, for example, three different higher level categories this will show up as incorrect since,

although the item might fit under the different categories, there is an optimal coding for each item. This

could of course lead to discussion out of the game about how to code ambiguous items. You are

required to code all data items correctly before you can advance in the game. On completion of the

coding exercise, players are given feedback about their scores for all level 2 activities.

Figure 3: Screenshot showing a data item and coding categories for the level 2 qualitative game

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Level 3: Dealing with Qualitative Analysis

Level 3 includes the same two design and coding mini-games as level 2 and follows a similar sequence of

activities. Again you are presented with a research question and a short background to a study and you

are required to choose an appropriate data collection method and suitable sample from the choices

provided as well as carrying out qualitative coding. However level 3 differs from level 2 in that there is

less support at the different stages and level 3 is more exploratory and game-like. For example, rather

than being presented with choices about the method, place and participants in a specific order, you

have to choose the order in which you want to tackle these yourself. If you choose to carry out data

analysis before you specify your study design, you will be informed that you have no data yet! You are

not provided with feedback until you have completed the study design and coding mini-games. In this

sense level 3 reproduces the process of sending a paper to a journal (or carrying out a student project)

where feedback is not provided at the different stages. The level 3 game is based on a paper by McCabe

et al (2007) which is a qualitative study of statements made by mothers about their children’s diet and

exercise habits and appearance which might influence children’s body image.

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The CHERMUG quantitative game

Introduction to the quantitative game

The quantitative game reflects the traditional experimental approach typically associated with science,

sometimes called the hypothetico-deductive approach. The researcher starts with something he or she

knows a little about and wants to explore further. Quantitative researchers aim to collect, organize and

summarise numerical data, use it to describe or examine relationships between variables and to

establish cause and effect relationships between variables.

There are many different issues which need to be considered in carrying out a quantitative study but,

since the central focus of quantitative research is on hypothesis testing, the CHERMUG quantitative

game centres around hypothesis testing. In the game you will be presented with a series of examples

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each focusing on a different research question related to obesity, such as food preferences, the

effectiveness of different diets and body image.

Figure 4: A scenario from one of the quantitative examples

The sequence of activities in the quantitative game

Each example starts with a short scenario which sets the scene for the proposed study providing a

rationale for the study and background information, such as information about the relevant variables

and how they were measured and information about the study participants (see figure 4).

The game then takes you through a sequence of activities which will help you to address the inter-

related issues that you need to consider in carrying out a quantitative study, such as operationalising the

variables, formulating the hypothesis, selecting and interpreting appropriate graphical representations

of data and relevant statistical tests. These activities reflect the sequence of operations required in

carrying out a research project. The activities are always presented in the same order with slight

variations in the question asked at each stage.

Read the scenario: First of all you should read the scenario describing the background to the

study. The scenario remains available to be accessed at any point while you are doing that

example, by clicking on “ready” so that players do not have to rely on memory.

Identification of variables: On the basis of the information presented in the study scenario, you

identify the key variables for the study from a number of possible options presented.

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Identification of independent and dependent variables: For the t-test examples, you will

identify firstly the independent and then the dependent variables, again from a number of

possible options presented.

Levels of variables: For the chi-square examples, you will state the levels of each variable from a

number of possible options presented.

Level of measurement (see section below on operationalising and measuring your variables):

You will decide which level of measurement is appropriate for each variable. For one variable

this decision is implemented through a hangman game. For the other variable this is

implemented via a multiple choice question.

Select design (see section below on design): You have to decide whether the design suggested

in the study is experimental or correlational, via a multiple choice question.

Formulate the null hypothesis (see section below on the null hypothesis): In this drag and drop

exercise you have to formulate the null hypothesis for the study by selecting three separate

clauses to make a sentence, such as (There is no difference) (between males and females) (in

foods selected).

Identify the correct raw data set: From a choice of two possible data-sets, you have to select

the data-set which is most appropriate to test the hypothesis. Each of the data-sets contains a

representative sample of 10 data-points.

Identify correct data summaries: You are required to select which tabular or graphical

representation is most appropriate for summarising and representing the data for that example.

Interpret graphs, tables and SPSS output: In the chi-square examples, you are presented with a

contingency table and nine true/false questions relating to the interpretation of that

contingency table. In the t-test examples, the nine Tic Tac Toe questions are more varied and

refer to histograms, box plots and SPSS output.

Identify/interpret correct statistical test: In the chi-square examples, players are given a

number of exercises to do interpreting the SPSS output.

Study Design: correlational and experimental methods

In selecting a quantitative design you will be dealing with numerical data. Different study designs are

used in quantitative research depending on the research question which is asked, but there is a

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fundamental distinction between correlational and experimental approaches. Correlational methods

examine what naturally happens in the real world without interfering with it, while with the

experimental design some aspect of the real world is manipulated and the effect of this manipulation of

another variable is examined.

Both correlational and experimental methods have a number of similarities: both aim to address the

research question in an objective way; empirical data is collected with both; both measure the variables

that are being studied and both seek to ensure that the results are replicable. However there is a

fundamental difference between the two approaches. With a correlational design the aim is to examine

pre-existing relationships (correlations) between two variables. In experimental research, rather than

simply examining the variables under study, the researcher manipulates variables in order to achieve an

explanation of cause and effect. The variable which is manipulated is called the independent variable (or

variables) and the outcome variable or dependent variable is the variable which is measured to assess

the effect of this manipulation.

Operationalising and measuring your variables

Formulating and testing hypotheses is at the heart of quantitative methodology, but there are a number

of issues which must be considered before you get to this stage. Operationalising and measuring your

variables is a very important aspect of study design. Operationalizing a variable means stating exactly

what the variable is and deciding how you will quantify and measure it, or finding a way to manipulate a

variable.

Variables have different characteristics and can be categorised according to how they should be

measured in terms of four different kinds of measurement scale: nominal, ordinal, interval or ratio.

Measurement scales are hierarchical in that data types higher in the tree assume all the properties of

types lower than them. Knowledge of levels of measurement is basic statistical knowledge which

underlies subsequent choices of appropriate graphical representations and statistical tests.

Nominal data With nominal data the variable which is being measured falls into distinct categories or

groups and for that reason nominal data is also called categorical data. Gender is a categorical variable

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since people are either male or female. This variable has two levels, male and female. Another example

of nominal data is your response to the question: “Did you eat chocolate last week?”.

The response to this would typically be either yes or no and this would be a nominal level of

measurement. The responses: “yes” or “no” are called the levels of the variable. Nominal data is also

called categorical because the variable which is being measured falls into distinct categories or groups.

An example of a nominal variable which has more than two levels is nationality.

Ordinal data Like nominal data, ordinal data can also be categorised but have the further property of

having an implicit order or rank. An example would be the position of 10 runners running a race as first,

second, third, fourth etc. where clearly it is better to be first than tenth. Ordinal measurements do not

imply differences in magnitude between two measurement points.

The Likert scale is a measure frequently used in research where attitudes are measured on a 1-5 scale

where 1 means that an individual strongly agrees and 5 means that they strongly disagree. This is an

example of interval data. Thinking again about how we might measure liking for chocolate, we might ask

participants to indicate their agreement to the statement: “I like eating chocolate.”. With children

attitudes can be measured using the graphical scale as below.

Interval data Interval data inherits the characteristics of the other two levels of measurement but also

has the property that the differences in values on the measurement scale have meaning and consist of a

series of equal intervals. An example would be inches on a ruler. An interval scale also has an arbitrary

zero point. An example is temperature.

Ratio data The last scale, the ratio scale, is similar to the interval scale but has no arbitrary zero point.

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Another way of measuring liking for chocolate would be to ask: “How much chocolate did you eat last

week?”. The answer might be provided in terms of the number of bars of chocolate you ate last week

(or the number of squares if you were less hungry!)

This would be a ratio level of measurement. Interval and ratio measures are frequently considered

together as scale measures.

It is important to realise that in terms of experimental design these different types of measurement will

lead you to very different kinds of descriptive and inferential statistics. Asking “Did you eat chocolate

last week?” leads to a yes or no answer and nominal data. The Likert scale question asking participants

to indicate their agreement with the statement “I like eating chocolate.” produces ordinal data.

Asking “How much chocolate did you eat last week?” will lead to a quantity of chocolate in terms of

number of bars and this is a ratio measure. If you are not familiar with the concepts of nominal, ordinal,

interval and ratio variables now is a good time to learn about it. Use this link to external resource (e.g.

http://www.socialresearchmethods.net/kb/measlevl.php)

Formulating the hypothesis

Formulating and testing a hypothesis is central to the progress of quantitative research. Operationalising

your variables and choosing an appropriate design are very closely linked to formulating your

hypothesis. A hypothesis is a statement of the relationship between two variables or differences in

outcome between two groups. We can think of a hypothesis as being composed of three separate

clauses of a sentence. The first part states either that “There is a no relationship” or “There is no

difference”. The hypothesis is always stated in terms of the NULL hypothesis which states that there is

no relationship or no difference. The next part of the sentence describes the different levels of the

independent variable and would state for example “between boys and girls”. The final part of the

sentence describes the dependent variable for example BMI. In this drag and drop exercise you need to

“construct” the null hypothesis from these separate clauses, e. g. “There is no difference between boys

and girls in BMI.”. If you want to find out more about testing the null-hypothesis follow this link:

http://www.alleydog.com/glossary/definition.php?term=Null%20Hypothesis

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Acknowledgements The development of the CHERMUG project is partially supported by the European Community under the

Lifelong Learning Programme project nr. 519023-LLP-1-2011-1-UK-KA3-KA3MP. This document does

not represent the opinion of the European Community, and the European Community is not responsible

for any use that might be made of its content.

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Couchman, W. & Dawson, J. 1990. Nursing and Health-Care Research: The Use and Applications of

Research For Nurses and Other Health Care Professionals. Scutari, London.

Holsten, J. E., Deatrick, J. A., Kumanyika, S., Pinto-Martin, J., & Compher, & C. W. (2012). Children’s food

choice process in the home environment. A qualitative descriptive study. Appetite, 58, 64–73.

Morse, J. M., Field, P. A. (1996.) Nursing Research: The application of qualitative approaches. Chapman

and Hall, London.

McCabe, M. P., Ricciardelli, L. A., Stanford, J., Holt, K., Keegan, S., and Louise Miller, L. (2007). Where Is

All the Pressure Coming From? Messages From Mothers and Teachers About Preschool Children’s

Appearance, Diet and Exercise. European Eating Disorders Review, 15, 221–230.