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Coming to University: The Experience of Students Leaving Home

Researcher: Joscelyn Lester

University of Nottingham, School of Psychology

Abstract

The transition to University requires students to cope with many changes in their

lifestyle. The vast majority of students are able to deal with this transition well. However,

some struggle and may decide to leave University before graduating. This can have a

negative impact on the students’ well-being. Many factors have been highlighted in affecting

this transition. However, they do not fully explain the diversity between the experiences. This

study combined qualitative and quantitative methods to research students’ experience of the

transition to University. Two stages of data collection were used. The first stage produced

qualitative data using a narrative task, designed to collect units of events, thoughts, actions

and feelings. The second stage required participants to order the units chronologically

according to when they believed they would occur in the transition. There were three

conditions; own experience, fictional significantly bad experience, fictional extremely good

experience. Bad transitions were found to be more varied in both the events experienced and

the sequences in which they occurred. Negative events were clustered together in the

sequence of a good transition, compared to a bad transition where they were dispersed

amongst positive events. The results are discussed in relation to how they may enable

Universities to improve the overall student experience. This research is particularly important

in light of the impending increase in University fees.

Introduction

Coming to University

The experience of leaving home and coming to University is likely to be the first

experience many people have of being fully independent from their parents. This transition to

independence is different for everyone who embarks upon it. Some adapt well to the new

situation whereas others find it harder to settle in. Many factors have been highlighted as

contributors and possible variables in this experience. However, there does not seem to be a

particular determining factor. Perhaps it is the sequence in which the factors occur that is

important in determining the outcome of the transition. Identifying and supporting vulnerable

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students in these transitions is highly important for their well being and achievement (Leach,

2009). On average 7.4% of students who begin a University course leave before graduating.

This is a problem financially for Universities as it results in a waste of resources. Not all

students are suited to University life, and so make a rational decision to leave. However,

some students leave due to dissatisfaction with the institution or the course. It is in the

financial interest of Universities to understand problem areas within these transitions and to

help students overcome difficulties. Current students at a University provide the most

influential information for prospective students (Archer, 2010). Improving the current

students’ experience may impact on prospective students decisions to attend the University.

This is of particular importance in light of the new increase in University fees, commencing

in September 2012. Also, with the increase in fees, it is important to meet students’

expectations so they feel that the financial strain is worthwhile. Fully understanding the

factors involved may help to lower the number of students who leave University, thereby

supporting and improving students’ well being and helping Universities financially. It is

important now more than ever to be as efficient as possible with funds and to ensure that

students are making the transition to University life as smoothly as possible.

Most students come to University at what is believed to be a particularly vulnerable

age (Apter, 2002). People between the ages of eighteen to twenty five are not classified as

adolescents but they are also not necessarily viewed as adults. From the surface this point in

life seems wonderful as it appears to be full of all the independence of adulthood without the

responsibilities that the adult world inevitably involves. However, the transition from

adolescent to adult is complex, containing personal expectations of what lies ahead and also

what they believe is expected of them. These expectations can lead to stress when trying to

achieve them or disappointment when they are not achieved (Pitts, 2009; Agliata & Renck,

2008). Some people deal with the transition well, smoothly changing from adolescent to

adult. However, this is not the case for everyone. It has been noted that the prevalence of

panic attacks, phobias, suicide attempts and eating disorders are increasing in the student

population (Apter, 2002). Students’ levels of well-being were found to be reduced during the

first term of University, compared to levels taken prior to the transition (Bewick et al, 2010).

This evidence indicates that people at this stage in their life are vulnerable and so this

transition is important to study. It has also been noted that the experience of the transition to

University life impacts upon the later mental health and academic performance of a student

(Dyson & Renck, 2006). This indicates that the transition to University has a lasting effect on

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later life. It is important for the personal development of students to fully understand the

factors and sequences involved in the transition in order to support and help them in difficult

situations.

When a stressful event occurs in a person’s life it causes physiological arousal.

Adaptation to the new situation is needed to avoid the exhaustion caused by the biological

response to the stress (Seyle, 1936). This was supported by Cohen, Tyrell and Smith (1993)

who found that high levels of stress lead to an elevated risk of becoming ill. Students adapt to

numerous changes during the transition to University life (Clark, 2005). There are dramatic

changes in life style, course demands, social groups and amount of independence. Students

who are struggling to adapt are likely to be exposed to an elongated period of stress and so an

increase in chance of becoming ill.

The experience of the transition to University life is diverse; many factors have been

highlighted as affecting it. Creating a balance between academic and social life has been

found to be important for a good transition to University, if there is more involvement in

either aspect then the other is likely to negatively affected (Tinto, 1975). Wintre and Yaffe

(2000) found that positive parental support is a significant predictor of a good transition to

University. They specifically highlighted the importance of being able to discuss issues

surrounding University life. However, as yet there has not been one specific factor isolated as

determining the experience of the transition to University. Christie et al (2004) highlighted a

strong social network, course and University choice as important factors in determining

student satisfaction.

Support from family members has a positive effect on the transition to University

(Apter, 2002). This is further supported by (Ford, 2004) who stated that the support of family

is needed for longer than in previous decades as average years in education increases.

Traditional students are classed as those whose parents have attended University, as opposed

to first generation students who are the first in their family to attend. Evidence has been

found to indicate that first generation students misunderstand the expectations of their tutors

at University more often than traditional students (Collier & Morgan, 2008). Not

understanding the expectations of tutors may result in a bad transition to University as it may

lead to stress and confusion.

A strong social network is an important aspect of University life (Beck, Taylor &

Robbins, 2003). Furthermore, Friedlander et al (2007) found that social life is more important

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for a good transition to University than family support. Students seek support when they

come to University to help them deal with new situations as they are encountered (Morosanu,

2010). These new networks create a large learning curve for students, helping them to

understand themselves, others and relationships formed (Apter, 2002). This support provides

students with a sense of confidence within the new situation, aiding transition. Tieu et al

(2010), found a positive correlation between a higher amount of structure involved in the

preferred social interaction of a student and a positive adaption to University life, indicating

that social activities involving structure may help adaption.

The academic stress imposed on students is increased at University as the level of

education is higher. This stress has been reported as having a positive effect on academic

performance; it is believed to indicate an understanding of the task before them (Wintre &

Bowles, 2007). Higher average grades in the first semester were also highlighted as a

predictor of persistence to graduation. Enrolling on a course suited to the students’ ability

may help to increase levels of student retention. Choosing the appropriate course is

important. It should be of a level to suit the student and be of interest.

Self reported financial hardship is a strong predictor of students deciding to leave

University (Bennet, 2003). Financial stresses have been linked to an increase in students’

levels of anxiety and depression and also a lower academic performance (Andrews &

Wilding, 2004). The financial stress of not having money can impact on other factors such as

social life. The transition to University is also likely to be the first time that students have had

to deal with personal financial stresses and so adapting to them may be difficult. Support for

students under financial stress would appear to be of extreme importance. The negative

effects of financial stress are demonstrated in the extreme case of care home leavers. It has

been found that they are much more likely to leave University or suffer academically because

they have to take on too many hours of paid work (Blackburn, 2008). This has also been

supported in the general student population; Aurers, Rostoks and Smith (2007) found a

negative correlation between increase in paid employment hours and academic performance.

However, students will take on the financial stresses of attending University if they believe

that the University course is worthwhile and likely to improve their employability prospects

(Christie, 2009).

Women are more likely than men to stay in University until graduation (Wintre &

Bowles,2007). Women have also been identified as adapting more successfully to University

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life than men (Wintre & Yaffe,2000). This study also found a positive correlation for female

students between adjustment to University and prior discussion with parents about University

life; this was not found in men. This is an area of concern as there is a slightly elevated

percentage of men who leave University (9.9%) compared to women (7.9%) (Higher

Education Statistics Agency). However, not all data highlights gender differences (Mattanah

et al, 2010; Johansson and Rossamnn, 1973), and so the effect of gender on the transition to

university is under debate.

Links between these factors have been identified. Evidence has been found for the

feeling of stress affecting academic performance (Wintre & Bowles, 2007). Positive effects

of peer social support on academic achievement have also been identified (Hogan et al,

2010). A connection between confidence and a positive social life has been identified

(Barbalet, 1996). The importance of a balance between positive social life and academic

work has also been noted ( Tinto, 1975). These links may suggest a sequence in which factors

surround the transition to University occur. Perhaps differences in these patterns will help to

indicate vulnerability for a bad transition to University.

There are important practical implications for research involving the transition to

University. Being aware of vulnerability factors and supporting students with counselling and

practical support is important both for the wellbeing of the students and also for the

Universities from a business perspective. Leach (2009) found a positive correlation for

counselling and student achievement. However, people may not feel they need counselling or

are worried others will judge them. Online methods of counselling have been developed and

strongly supported to overcome these issues (Freeman & Barker, 2005; Evans, 2007). Student

adaption to University life has been found to be helped by previous social support, belief in

academic abilities and development of effective coping styles for new tasks (Shank land et al

2010). Perhaps Universities should enhance support in these areas for vulnerable students.

Extensive advertising can raise awareness of the counselling services available to vulnerable

students. However, identifying those who are subject to certain risk factors would allow

Universities to focus support on vulnerable students, thereby using funds more effectively.

Qualitative and quantitative data

Qualitative data receives a lot of criticism in scientific research, as it is difficult to

standardise and is open to experimenter bias. Therefore, a lot of scientific research uses

quantitative data which allows more control over variables. However, in some cases this data

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may overlook important aspects of the phenomena. Quantitative data can often lack

ecological validity as the methods used to collect the data do not correspond closely to the

natural phenomena.

The Anthropomorphic Model of Man (Harré & Seycord, 1972) is based on the Open

Souls Doctrine and details that personal reports of what happened in a situation are important

to understand fully the reasoning behind behaviour. People are language users and so have

the capacity to monitor their own and others’ actions. This makes personal reports crucial in

psychological research as they provide insight into the reasoning behind behaviour which is

not easily assessed using quantitative methods. It is argued that analysing these reports gives

insight to the rules behind social behaviour. Christie (2009) conducted an effective study

which used personal reports of students’ experiences of and reasons for coming to University.

However, the data were only discussed and not statistically analysed. It would be ideal to

combine both quantitative and qualitative data in a research design. This would allow the data

to be standardised by use of quantitative data and provide ecologically valid insight into the

behaviour using qualitative data.

Sequence analysis

The understanding of sequences in behaviour can give insight into the development of

situations (Gottman & Roy, 1990). Perhaps the indication of a bad transition to University is

not the factors present but instead the sequence in which they occur. In life, events naturally

follow on from one another and so they are unlikely to be independent. This makes it difficult

to research situations using the standard statistical methods which require the observations to

be independent. Sequence analysis can be used to investigate the pattern in which events are

likely to occur. This method is especially useful when the phenomena cannot be replicated in

the laboratory or when the data doesn’t satisfy the statistical criteria. Sequence analysis is a

quantitative method of analysis which can be applied to qualitative data. A wide variety of

situations have been researched effectively using sequence analysis. For example, the social

behaviour of chimpanzees (Van Hoof, 1973), therapist-patient interaction (Benjamin, 1979)

and sequences of sexual behaviour in stranger assault (Fossi et al, 2005). Prior to this study it

had not been used to research students’ experience of the transition to University.

Sequence analysis can be used to find differences in data which may not be

highlighted by the frequencies of events alone (Ivanouw, 2007). The experiences that a

student has during the transition to University are more suited to the sequence analysis

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approach than to a standard laboratory experiment due to the large scale, longitudinal nature

of the data required. The most indicative information of what will happen next in a sequence

of events is to know the immediately preceding event (Clarke, 1982). Therefore, using

sequence analysis to understand the connections between events will provide more insight

into the situation. Researching the sequences of events, thoughts, actions and feelings

involved in the transition to University may give insight into the causes of a bad transition

and also which students may be more vulnerable to the factors.

Sequence analysis is a standardised statistical method involving three stages;

unitisation, classification and tabulation. Unitisation involves splitting the data into chunks,

so that each event is separated from another. At this stage analyses can be completed looking

at the frequencies of units. Researchers must be careful at this stage not to unitise the data

according to what they expect will occur. This may cause the creation of false units which

may not actually exist; these are termed behaviour tessarae (Clarke, 1983). To control for

these false units an independent researcher is asked to complete unitisation on the same data

and the units identified by both researchers are compared. These units are then classified into

appropriate categories according their type. For example the classification of words in a

sentence, would involve nouns, verbs, adjectives and so on. These categories can then be

analysed to see if there is a sequence present. A matrix is created displaying the frequency of

occurrence for all the different pairs of events. This provides an understanding of the

sequence by highlighting the pairs of events which are more likely than chance to occur.

Viewing the links between events will help to understand the development of a situation, in

this case a bad transition to University.

Sequence analysis is based on Markov chains which were created to explain the

complex links between events. The simplest model makes connections between the present

event and the event immediately preceding; this is referred to as a first order Markov Model.

Higher order models can be used to account for increasingly more complex chains of events.

A second order Markov Model compares the present event and the occurrence of the two

immediately preceding events together as a pair. Third order compares three previous events,

and so on. These models increase in complexity, accounting for more of the variance within

data by providing longer chains of events. It is important to use the appropriate order for the

sequence so the most amount of variance can be accounted for. However, it is important not

to over fit the model, this refers to when the order of a sequence is calculated to be higher

than it actually is, and so assumptions made about the data are likely to be incorrect.

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Discovering the order of a sequence can be difficult, involving increasingly complicated

matrices. This can lead to mathematical problems where the functions increase very rapidly,

referred to as a combinatorial explosion. The Dawkins method of sequence analysis was

created to avoid this problem (Clarke & Crossland, 1985).

Data collection for sequence analysis research can be laborious and time consuming.

Techniques such as interviews and collating previously collected data, for example witness

statements or accident reports, have been used. This study had a limited amount of time

available for data collection, and so it needs to be efficient while managing to collect relevant

and useful data. For this reason two stages of data collection were used in this study. Stage 1

collected narratives of experiences of the transition to University, producing qualitative data.

These narratives will then be unitised, to construct a list of all possible events which were

mentioned. These units were then presented to participants in Stage 2 who were required to

order the items chronologically according to when they believed they would have occurred in

the experience. This stage provided quantitative data which was sequence analysed. There

were three conditions which were implemented in both stages of the study. One which asked

participants to provide a narrative of their Own Experience (OE) of the transition to

University and two fictional conditions; an Extremely Good Experience (EGE) of the

transition and a Significantly Bad Experience (SBE) of the transition. The data from Stage 2

were analysed to identify significant differences between the three conditions.

Method

Participants

In both stages participants were recruited using opportunity sampling within the

University of Nottingham. The surveys were handed out after lectures and in the library,

specifically to second year students (Mean age = 19.85, Standard deviation = 0.99). This was

to standardise for any memory effects which may affect the recall of the experience of

leaving University. No compensation was given to the participants for involvement in the

study. Table 1 displays the details of the participants from stage 1. Table 2 displays the

details of the participants in stage 2.

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Table 1. Participants for stage 1.

Condition Number of Males Number of Females Total

EGE 6 7 13

OE 7 7 14

SBE 7 10 17

Total 20 24 44

Table 2. Participants for stage 2.

Condition Number of Males Number of Females Total

EGE 13 13 26

OE 19 18 37

SBE 15 15 30

Total 47 46 93

Ethics

Prior to beginning the study, permission was obtained from the ethics committee.

Consent forms were completed and debriefing sheets were included in the task booklets.

Participants were asked if they had any questions concerning the study, all questions were

answered fully.

Pilot

A pilot study was conducted to ensure that the information sheet, task sheet and

debriefing sheets were able to explain the study effectively to the participants and to make

sure that the data produced would be useful to the research.

Stage 1

Stage 1 collected qualitative data. Participants were required to write a brief account

of the six months before coming to University and the first six months of University. They

were asked to include the thoughts, actions, events and feelings that they believed would be

involved in the year long experience in chronological order of when they occurred. The task

was described to participants on an information sheet which was the first page of the Stage 1

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task booklet (Appendix A). This information sheet was followed by a consent form, the task

sheet and a debriefing sheet. There were three conditions; Extremely Good Experience

(EGE), Significantly Bad Experience (SBE) and Own Experience (OE). These three

conditions were implemented to produce examples of a particularly good transition to

University (EGE), a significantly bad transition (SBE) and the overall average experience of

the transition (OE). There were three different task booklets differing slightly to explain the

task explicitly for each condition. The conditions were randomized by shuffling the task

booklets so they were not handed out in any particular order or to a particular participant. In

the EGE condition participants were asked to write their account according to what they

believe would be involved in a really good experience of coming to University. The SBE

condition also required a fictional account, but this condition asked for a significantly bad

experience of coming to University. In the OE condition participants were asked to write a

truthful account of their own experience of coming to University according to the tasks

requirements. The participants were given time to complete the survey and they were either

collected or handed back into the psychology office at the University of Nottingham.

The EGE and SBE conditions were conducted to produce examples of extreme

experiences of the transition to University, one good and one bad. This allowed the analysis

and the understanding of differences between the two. The OE condition provided data

concerning the average experience of a student’s transition to University, allowing

understanding of how closely it was related to either a good or bad transition. These

narratives were unitised to find the reoccurring thoughts, actions, events and feelings

involved in the event of coming to University to be presented to participants in Stage 2.

Stage 2

Participants were presented with the Stage 2 task booklet (Appendix B). The

information sheet explained that participants were required to cross out the items on the task

sheet they believed were not involved in the event of coming to University. The remaining

items were to be ordered chronologically according to when they believed they would occur

in the six months prior to coming to university and the first six months of University. The

same conditions as in Stage 1 were also implemented in stage 2; EGE, SBE and OE. The

information sheet was slightly altered for each condition to explain precisely what was

required of the participants. The task sheet consisted of a list of 94 units of thoughts, actions,

events and feelings collected from the Stage 1 material. The task booklets were shuffled prior

to handing them out to randomize allocation. Stage 2 allowed the collection of quantitative

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sequential data from a wide range of participants using a time effective method which has not

previously been implemented for this type of data.

Results and Discussion

1. Unitising

The narratives from Stage 1 were unitised to produce 94 units of thoughts, actions,

events and feelings to be used in Stage 2 (Appendix B). The unitisation was validated by an

independent researcher to control for behaviour tesserae.

The data collected in Stage 2 was collated using Microsoft Excel and Word. The units

were referred to using a coding system (Appendix C). The data were arranged in strings of

the sequences for all participants and conditions, presented in Appendix D.

2. Frequency analysis

The frequencies for all three conditions (EGE, OE, and SBE) are presented in

comparative graphs. Figures 1, 2 and 3 below visually display the frequency distribution of

the units for the three different conditions. Table to show frequency for all conditions and

units is presented in Appendix E.

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Fig1. Graph to show distribution of frequencies in the EGE condition

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Figure 4 displays a graph for the frequencies for all conditions, following the order of the Stage 2 task sheet, to display any differences

between the conditions for the frequencies of each unit.

Fig4 Graph to show the frequencies for all units separated according to condition.

Figure 4 indicates units which provide differing frequencies for the three conditions. To determine if these differences were

significant, z-scores were calculated using the z-Test for two proportions calculator (Dimension Research inc, 2005). Table 3 displays

units found to have significantly different frequencies.

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Table 3 shows z scores depicting main areas of difference between EGE and SBE conditions,

ordered according to decreasing confidence level with EGE value decreasing, followed by

increasing confidence level with SBE value increasing. Unit EGE average frequency SBE average

frequency z-score Confidence level (%)

happy with course 25 3 4.817 100 amazing freshers week 26 5 4.47 100

organised finances 23 4 4.269 100 Welcomed to university 21 3 4.251 100

Made Friends 26 6 4.236 100 Felt Confident 25 6 4.099 100

Romantically successful 16 1 4.045 100 Support of family and friends 21 4 3.981 100

Became independent 24 6 3.959 100 Nights out 27 8 3.949 100

Everyone was in the same position 19 3 3.933 100 Settled in 22 5 3.892 100

Parties 26 8 3.811 100 Getting first choice 23 6 3.796 100

Felt Excited 27 10 3.554 100 Exams went well 17 4 3.328 99.9

Achieved academically 21 7 3.277 99.9 Saved money 15 3 3.253 99.9

Holiday 17 5 3.077 99.8 Plan social meetings 17 5 3.077 99.8

Join societies 21 8 3.049 99.8 Upset to leave uni at Xmas 13 3 2.883 99.6

Preparation 19 8 2.701 99.3 Spending time with family 20 9 2.665 99.2 Organising academic work 20 9 2.665 99.2

Worked hard 19 10 2.282 97.8 A level exams 23 14 2.228 97.4

None of other friends worried 6 17 1.421 99.3 Became unwell 4 17 2.003 95.5

Felt Shy 2 13 2.048 95.9 Getting 2nd choice 1 11 2.139 96.8

Scared of meeting new people 3 16 2.152 96.9 Felt other home friends were having a better

time 3 16 2.152 96.9

Pressure from parents 2 14 2.189 97.1 Arrangements cancelled 0 9 2.263 97.6

Academics suffered 1 12 2.284 97.8 Not a great summer 1 12 2.284 97.8

Problems with student finance 3 17 2.305 97.9 Felt Homesick 3 17 2.305 97.9

Moved back home to commute 0 10 2.44 98.5 Arguing with parents 1 13 2.449 98.6

Prescribed anti-anxiety drugs 0 11 2.575 99 Hearing of a bad experience 1 14 2.579 99

Felt Anxious 2 17 2.624 99.1 Felt Stressed 2 17 2.624 99.1

Relationship difficulties 2 17 2.624 99.1 Voted president of society/ hall 9 1 2.7 99.3

Dropped out 0 12 2.703 97.9 Regrets 1 15 2.729 99.4 Felt Sad 3 21 2.821 99.5

Family problems 1 16 2.847 99.6 Not sure course is right 2 19 2.879 99.6

Felt worried 3 22 2.93 99.7 Fall out with school friends 0 14 2.971 99.7

Hospitalised 0 14 2.971 99.7 Dropped out 0 14 2.971 99.7

Didn’t make friends easily 1 17 2.986 99.7 Financial difficulties 1 17 2.986 99.7

Don’t get along with people in halls 2 20 2.989 99.7 Bad freshers week 1 18 3.096 99.8

Bullied 0 16 3.217 99.9 Felt panic 1 19 3.226 99.9

Felt Scared 2 23 3.321 99.9 Felt Lonely 1 20 3.328 99.9

Problems with course 0 18 3.447 99.9 Exams went badly 0 18 3.447 99.9 Felt disappointed 1 21 3.45 99.9

Pressure not to fail/dropout 0 16 3.217 100 Felt like a failure 3 30 3.669 100 Stressful course 1 23 3.641 100

People were not very nice 0 21 3.778 100

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Frequencies were examined for differences between male and female responses from Stage 2. These are displayed in Figure 5,

units ordered according to task sheet.

Fig.5 Graph to show the frequency of different units, separated for males and females.

Table 4 displays the units which were found to be significantly different, according to the z-score proportions test.

Table 4 Units which were found to be significantly different

Unit Female Male z-score Confidence Level

Hearing of bad experience 16 5 2.004 95.5

Arguing with parents 15 4 2.106 96.5

anti-anxiety drugs 11 1 2.5 98.8

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Frequency Discussion

Figures1, 2 and 3 show the differences between the frequency distribution of the three

conditions. The SBE graph (Fig. 2) shows a wider dispersion of frequencies for the units,

signifying that many factors may cause a bad experience. This gives insight into the

difficulties in identifying one specific factor which produces a bad transition to University.

The EGE graph (Fig.1) has higher frequencies for fewer more positively rated units,

suggesting a smaller variance in the units involved in the condition. The OE graph (Fig.3)

demonstrates a situation in between the two, involving high frequencies for a few units and a

general dispersion over the others. This indicates that both positive and negative events are

experienced in the average transition to University. However, OE and EGE display higher

frequencies for positive units compared to the SBE condition, suggesting that they don’t

involve as many negative units.

Figure 4 displays the differences between the conditions in the frequencies of the

units. There are clear variances between them. Table 3 presents the units that are significantly

different between the EGE and SBE condition. It shows that units associated with positive

academic experiences occurred significantly more often for the EGE condition compared to

the SBE condition. This supports the findings of Wintre and Bowles (2007), highlighting the

importance of being on the correct course and achieving academically. Positive social aspects

were also highlighted more often in the EGE condition, supporting Beck, Taylor and Robbins

(2003); Morosanu (2010); Blimling and Miltenberg (1981) and Apter (2002). The higher

frequency of students joining societies in EGE condition provides support for the positive

effect of structure in social life (Tieu et al, 2010). Stress caused by finances is indicated as

having a negative impact on the experience, supporting Bennet (2003). The units concerning

positive family experience are found to be more frequent in the positive transitions, providing

further support for Apter (2002) and Ford (2004). A significant difference was not found for

‘previous family member had been to University’ between the conditions, thereby not finding

evidence to support the effect of traditional versus first generation students. There is a higher

frequency of ‘became unwell’ in the SBE condition compared to the EGE condition. This

may indicate that the students who are experiencing a bad transition are struggling to adapt to

the new changes and are therefore becoming ill (Seyle, 1936; Cohen, Tyrell & Smith, 1993).

The importance of confidence for a good transition to University is also highlighted. This

may affect other aspects of University life such as social and academic. Differences in

perception of independence are also displayed. It would seem that a good transition to

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University more frequently involves the feeling of independence, compared to a bad

transition.

Gender differences were only highlighted in three out of the 94 units: ‘hearing of a

bad experience’, ‘arguing with parents’ and ‘taking anti-anxiety drugs’. For all three units

females reported them significantly more than males. However, these differences were not as

great as most found between the conditions. It is concluded that this study didn’t find gender

differences for the frequency of units reported during the experience of coming to University.

3. Relative position of Units

The frequencies found for the units in the EGE and SBE condition were very

different. Further analysis of the differences between these conditions was conducted using a

new and original method. The relative positions of units in the EGE and SBE conditions were

compared to see if there were differences, not only in frequencies of the units but also the

position in which they occurred. The average position of each unit for every participant was

calculated by finding the percentage from the total number of units used in the sequence. For

example, if in a sequence involving 34 units, ‘felt scared’ was ordered as number 13, then the

value for the proportional distance along the sequence was calculated by (13/34) x 100. The

units which were found to be significantly different, to a confidence level of above 95%, are

presented in Appendix F.

Relative Position Discussion

Negative events such as; ‘Arguing with parents’ and ‘Problems with people in halls’

were more frequent and occurred about half way through the SBE sequences. These events

occur much less often and also later in the EGE sequences. This shows the importance, not

only of the frequency of these events, but also their position within the sequences. The event

of moving to University is about half way through the sequences. This has been highlighted

as a more vulnerable time for students (Apter, 2002). The effect that these negative events

have on students during this period is likely to be magnified due to their vulnerability,

compared to later in the sequences.

Emotions of worry and panic were found to occur less often, but earlier in the

sequence, in the EGE condition compared to the SBE condition. This may indicate that these

students are aware of the large change that they are going to experience and so are prepared

for it. However, those in the SBE condition may not be as aware of the effect the change may

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have and so do not feel these emotions. This is similar to the effect found by Wintre and

Bowles (2007); students who experience stress around their exams are more likely to achieve

higher grades and continue to graduation, as they are aware of the work required.

4. Classification

The 94 units were categorized into 20 ‘super categories’ for sequence analysis. The

groups and units included in them are displayed in Appendix G. Table 5 shows the number of

units included in each ‘super category’.

Table 5. Displays number of units in each ‘Super Category’

‘Super category' (code) Number of units included Negative Emotions (NE) 20

Positive social (PS) 13

Negative social (NS) 10

Positive emotions (PE) 8

Negative academics NA 7

Positive academics PA 6

Positive Preparation (PP) 6

Negative Personal/ family experience (NPFE) 3

Gaining independence (GI) 3

Negative Preparation (NP) 2

Positive family experiences (PXE) 2

Results (d2) 1

A-levels (t1) 1

Negative Independence (NI) 1

Start Uni (j3) 1

Dropped out (DO) 1

Settled in (q4) 1

Start of sequence (a1) 1

End of sequence (x9) 1

previous family member gone to uni(PF) 1

Classification discussion

The original 94 units wouldn’t produce a meaningful sequence analysis as there

would be too many transitions, so categorization of the units was necessary. Ideally there

would be similar numbers of units in each category. The method used to produce the units

allows ecological validity as the units are provided spontaneously from participants’ reports.

However, it doesn’t allow control of the number of positive and negative units. As shown in

Table 7, there are more than twice as many negative emotions as positive. This provides

further support for the finding that the cause of a bad transition to university is diverse. This

imbalance should be taken into account when interpreting later results as it may affect the

sequences. However, the higher proportion of negative emotions may have simply allowed

more detail in the choice of negative emotion experienced compared to positive.

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5. Sequence Analysis

Matrices were created to present the frequencies of the occurrence of each pair of

‘super categories’. A matrix was created for each of the three conditions (EGE, OE and

SBE), presented in Appendix H. Matrices were not created for males and females separately

as the frequency analysis didn’t find enough significant difference. The Chi square and

standard residuals of the data were calculated using SPSS. A Significant chi square value

indicates a sequential pattern. The chi square value for the matrix presenting all the data were

x2(341) = 2470, p<0.001. The chi square values and standard deviations for the three

conditions are presented in Table 6. The SPSS output tables are displayed in Appendix I.

Table 6. Chi-square values for the three conditions.

All data produced a significant chi-square value, giving evidence of sequence in the

data. To determine if the pair is more likely than chance to occur, the standard residuals were

compared to a value calculated using the formula in Figure 6. This formula was created by

Colgan and Smith (1978) to compare large standard residuals.

Fig.6. Formula used to calculate a value to compare to the standard residuals.

The value calculated was 1.1. The Chi-square critical value for p=0.001 was found

using the Chi-square Calculator (2000). After comparing the standard residuals with the

value there were too many transitions to create meaningful sequence maps. To be able to see

the ‘core’ sequence the criterion level was increased. A median split was conducted using the

values from the matrix for the whole data set which was above the previously calculated

value. All values which were above the lowest value (2.9) of the upper half of the data were

used to create the sequence analysis maps. Figures 7, 8, 9 present these maps for the EGE,

OE and SBE conditions respectively.

Condition

Chi-square value Standard

Dev.

Degrees of

Freedom

Significance Level

EGE 707 5.57 289 <.001

OE 938 6.41 361 <.001

SBE 1300 8.06 342 <.001

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Fig.7 Sequence analysis map for EGE condition

Fig. 8. Sequence analysis map for OE

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Figure 9. Sequence analysis map for SBE condition.

The Dawkins method of sequence analysis was conducted to assess what order the

sequences may have. This involves highlighting the most frequent transition then finding the

event most likely to follow the pair and then the next most common event to follow and so on

until the sequence ends. The sequences found are;

OE–start-sequence!A-levels!Positive-academics!Positive-social

EGE–start-sequence !A-levels!Positive-academics!results

SBE–start-sequence!A-levels ! results.

Sequence Analysis Discussion.

All Chi-square values were significant to p<0.001, providing evidence for a

sequential pattern. The SBE sequence map involves more transitions than the EGE or OE

map, indicating the SBE condition to be more varied. This is further supported as the SBE

condition has the highest standard deviation. This also suggests that a bad transition to

University may be more complex than a good transition. The ‘negative academic’ category

wasn’t used included in any of the maps. This may be explained because all participants were

enrolled at The University of Nottingham, where entry requirements are high. Therefore,

participants are likely to have achieved academically.

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The EGE map depicts cyclic chains for ‘negative emotion’ and ‘negative social’.

‘Negative social’ also leads to ‘negative emotion’ which is connected to ‘negative academic’

reciprocally. This cluster of negative events is unexpected in a particularly good transition to

University. However, the connection from ‘negative social’ to ‘new experience’ may indicate

that negative events occur in a good transition, but are overcome by the student trying

something new and moving on from the negative situation. When compared to the SBE map

it appears that negative events follow other negative events such as ‘negative academic’

leading to ‘negative emotion’. This is to be expected in a bad transition to University.

However, in the SBE map it would seem that positive events don’t follow on from negative

events and instead lead to either the ‘end of sequence’ or ‘drop-out’. This may highlight the

importance of being encouraged to try something new, such as a change in course or social

group, when negative situations arise. ‘Positive family experience’ does not occur in the EGE

map, but ‘positive social’ does. This is in support of Friedlander et al (2007).

The SBE map shows that the ‘settled in’ unit occurs earlier in the sequence than in the

other conditions, as it directly follows ‘start University’. In the OE map ‘settled in’ follows

‘positive emotion’. This would seem more natural as it doesn’t give the impression of rushing

into the situation, allowing experiences to occur and appropriate identities to be formed. In

the SBE condition the negative events are not concentrated in one specific chain; they are

dispersed amongst other positive events. This may make it difficult for the student to deal

with and be prepared for negative events. The ‘positive social’ category is involved in three

cyclic chains in the SBE map. This gives evidence for the importance of a balance between

social and academic life (Tinto, 1975). It is also depicted that to end the sequence and leave

the chain a negative experience must be involved. Either ‘positive-social’!’negative-

independence’!’drop-out’ or ‘positive-social’!’positive-preparation’!’negative-

academic’!negative-emotion’!’end-sequence’. These chains highlight the importance of

keeping a balance between social and academic life. These chains illustrate that positive

experiences are involved in a bad transition to University, but inevitably they lead to negative

events. This is not found in the other maps. However, these chains are long and should be

treated with caution. Also ‘negative personal/family experience’ is likely to follow itself or

lead to ‘negative preparation’ in an SBE map. This pattern is not seen in either OE or EGE

maps. This highlights the importance of personal/family issues within the SBE condition. It is

important to be aware of students with such experiences and to build on successful support

interventions.

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It is expected that ‘positive preparation’ would lead to later positive experiences. This

is partly found in the OE map, as ‘positive-preparation’ is likely to lead to further ‘positive

preparation’. However, it also leads to ‘drop-out’. Interestingly ‘negative-preparation’ also

leads to ‘drop-out’. This is not easily understood with the analysis conducted so far. It may

indicate that preparation may lead to incorrect expectations. Further research into this

transition may help understanding.

It is important to read the maps with caution as the specific order of the sequences is

unknown. The Dawkins method of sequence analysis for this data suggests that the EGE and

OE condition are 3rd

order and the SBE condition is 2nd

order. Providing evidence for variety

in the pattern of events as well as the variety of causes of a bad transition to University as

there is a lower order. This implies that not only are more units used in the SBE condition but

also that they occur in a more varied order than the units in EGE and OE condition.

6. Correlation co-efficient; assessing the differences between the three conditions.

Table 7 displays the Pearson’s Correlation co-efficient between the three conditions,

calculated so that the similarities between the three conditions can be assessed.

Table7. Correlations for the three conditions.

Pair of

Condition

Pearson’s Correlation

Coefficient

Sig. level

EGE/SBE .099 .047

EGE/OE .848 <.001

OE/SBE .322 <.001

Correlation discussion

These values quantify the similarities between the three groups. They show that the

average students’ transition to University is likely to be successful. However, it is important

to understand the reasons for a bad transition, even if it is uncommon. Improvement in the

transition to University is in the interest of both students and Universities.

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General discussion

The occurrence of positive social factors, positive family experiences, feeling

confident and gaining independence have been shown to be more frequent in an good

transition to University compared to a bad transition. Financial stresses and becoming ill

were more associated with a bad transition. Examining the frequency of occurrence for these

factors showed differences between the conditions. However, most units occurred in all three

conditions, just with differing frequencies. The relative position of the units in the EGE and

SBE condition demonstrate further differences between a good and bad transition to

University. A negative event occurs in different positions in the two conditions. In the SBE

condition, negative events are more likely to occur closer to the event of starting University,

whereas in the EGE condition they are more likely to occur later on in the sequence. The

negative events occurring closer to the start of University may affect students more as they

are expected to be more vulnerable at this time (Apter, 2002), and so may struggle to deal

with them. This may lead to a negative overall experience of the transition.

The SBE condition appears to be more diverse than the EGE condition. It involves

more factors, presented in more widely varying sequences. This is supported by the

frequency distribution graphs, relative position analysis, sequence analysis maps, Dawkins

method and the standard deviations of the conditions. This finding explains why it is difficult

to predict and identify which students are going to have a bad experience of the transition, as

there are many factors and possible sequences which could occur.

Negative experiences were found in all three maps. However, the importance of being

able to move on from them was demonstrated in the EGE map. It was also found that the

negative events were clustered in the EGE map, and so the student would expect them to

occur. However, in the SBE condition the negative events were dispersed and led on from

positive events and so would be less predictable. This may lead to a bad transition to

University as being able to prepare or deal with negative experiences may prove more

difficult.

The novel method implemented in this study allowed integration of both qualitative

and quantitative data. This provided an increase in ecological validity and also data which

could be controlled and analysed effectively without experimenter bias. It should be taken

into account that the fictional conditions (EGE and SBE) are not based on personal

experiences and so may not be an accurate account of an average ‘Significantly Bad’ or

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‘Extremely Good’ experience. However, the findings from these data do provide some

insight into the differences between a good and bad transition while also adhering to ethical

considerations. This method was also successful in allowing fast, effective collection of

sequential data from an ecologically valid data base. This method may be useful when

researching other areas of social psychology as it creates a large data base which can be used

to carry out extensive statistical analysis. However, there were some limitations. For example

the number of units within each category was not even. This is not easily avoided as the units

were created spontaneously by participants, but it may have had an impact on the findings.

Due to the nature of the statistical analysis a lot of the descriptive data were removed.

Perhaps further analysis of the student narratives would provide further explanation of the

connections found in the sequences, especially the curious connection to ‘drop-out’ from both

‘positive preparation’ and ‘negative preparation’ in the OE map.

This study provides insight into students’ experience of the transition to University.

Using patterns to look at the transition as a whole, not just smaller sections, helps to

understand the transition more clearly. A negative event experienced close to the event of

moving to University has been found to be likely to cause a bad transition. This information

may help to identify those who are more vulnerable to a bad transition and could benefit from

support. Areas in which students need support are varied as it has been found that the cause

for a bad transition is diverse. Universities should be prepared to help students in all areas of

their lives; academic, social and financial. An on campus counselling service would offer

support for those students suffering negative personal or family experiences. The importance

of positive academic experiences were also highlighted, suggesting that Universities need to

support students, making sure they are on the correct course for their ability and that teaching

methods are effective. The importance of keeping a balance between social and academic life

should be emphasised to prospective students. Universities should be aware of the effect that

low levels of independence and confidence can have on a student’s transition to University.

Efforts should be made to encourage students to become independent with the availability of

support. The implications of the study are highly important. The further understanding of the

transition to University may help to improve students’ well being and academic performance.

This may in turn help to lower the numbers of students dropping out of University courses,

thereby also helping Universities from a financial perspective.

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Appendices

Appendix A; Example of Stage 1 Task Booklet. (Differences between the conditions are in brackets)

Coming to University: The Experience of Students Leaving Home.

Investigator: Joscelyn Lester

School of Psychology, University of Nottingham

Information Sheet

You are invited to write a brief account describing your experience of leaving home and

coming to university.

The aim of this study is to see the kind of events and experiences which people go through

during their experience of leaving home and coming to University. Please only complete this task if

you are in your second year having left home last year to begin your first year at University.

If you are willing to take part in the study, please write a brief (FICTIONAL) account of

(YOUR EXPERIENCE/A SIGNIFICANTLY BAD/ SIGNIFICANTLY GOOD EXPERIENCE) the

six months prior to coming to university and the first six months of University. Please write about the

actions, events, emotions, thoughts and beliefs which (YOU BELIEVE WOULD MAKE) made up

your ‘story’ at the time as a sequence of distinct units, described in the order they occurred in, and

which taken together in sequence capture the complete history of your move from home life to

University life.

Examples of events to discuss might include; making financial arrangements, planning trips

home, farewell meals and parties, meeting new friends at University, exploring campus, discovering

societies. Include problems you may have had and how you overcame them. Please aim for about a

page of writing for each account.

Participation in this study is totally voluntary, and you are under no obligation to take part in

this study. You are free to withdraw at any point prior to returning the account without need for

explanation (you may destroy your draft if you wish). If you do not feel comfortable with the subject

of the study or feel you may be distressed by completing it, please do not complete it. All data

collected will be kept confidential and used for research purposes only. The consent forms will be

kept separate from the completed tasks.

There is no right or wrong answer. Your name or any identifying characteristics will not be

available to anyone, other than my supervisor and me, at any point. During the task, do not refer to

people with their names, please use either their relationship to you or a pseudonym, this is to protect

their own confidentiality.

If you have any questions you may contact me on; lpycjjl@nottingham.ac.uk

Researcher: Joscelyn Lester

Supervisor: David Clarke

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!"%%"!"

'

Coming to University: The Experience of Students Leaving Home.

Investigator: Joscelyn Lester

School of Psychology, University of Nottingham

The participant should complete the whole of this sheet himself/herself. Please cross

out as necessary

Have you read and understood the participant information sheet YES/NO

Have you had the opportunity to ask questions and discuss the study YES/NO

Have all the questions been answered satisfactorily YES/NO

Have you received enough information about the study YES/NO

Do you understand that you are free to withdraw from the study:

at any time YES/NO

without having to give a reason YES/NO

Do you agree to take part in the study YES/NO

“This study has been explained to me to my satisfaction, and I agree to take part. I

understand that I am free to withdraw at any time.”

Signature of the Participant: Date:

Name (in block capitals)

I have explained the study to the above participant and he/she has agreed to take part.

Signature of researcher Date:

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"%&"!"

'

Coming to University: The Experience of Students Leaving Home.

Investigator: Joscelyn Lester

School of Psychology, University of Nottingham

Please write a description of (YOUR EXPERIENCE/ WHAT YOU WOULD

BELIEVE AN EXCEPTIONALLY GOOD EXPERIENCE/ WHAT YOU WOULD

BELIEVE AN SIGNIFICANTLY BAD EXPERIENCE) of leaving home and coming to

University. Include all important events, for example parties / confrontations and if possible

the feelings involved in the events. Concentrate on the (FICTIONAL) six months prior to

coming to University and the first six months of University. Discuss the events in

chronological order. Please complete this task with in a fair amount of detail, discussing

thoughts, feelings and actions. Also any problems that may have occurred which you were

able to overcome.

When discussing other people within your account do not use their names, please

instead refer to them as their relationship to you or by using a pseudonym. (Max 500 words).

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!"%'"!"

'

Coming to University: The Experience of Students Leaving Home.

Investigators: Joscelyn Lester and David Clarke

School of Psychology, University of Nottingham

Debriefing sheet

Thank-you for participating in this survey.

This survey was interested in finding out the important events, thoughts and feelings which

are involved in the event of leaving home for university and also the order in which they occur. This

research will help to further understand the experience of this event. It will also help to see if there are

any areas which need more support for students when coming to University. The data will also be

analysed to see if there are differences in the way in which men and women deal with the same

situation. Your data will be analysed to find the most common events, thoughts and feelings involved

and then these will be presented to the next group of participants in stage two who will place these in

order of when they occurred for themselves. These data will then be analysed to see if there are

sequences of events, thoughts and feelings which are more likely to occur than others. This will help

to more fully understand the experience of students at University and to discover if men and women

deal with the situation differently.

The data you have provided will not be seen by anyone but me and my research supervisor.

The data will be kept entirely confidential. Consent forms will not be kept with the task sheets and the

data will be referred to using numbers and not names. You have the right to withdraw and destroy

your data before returning it if you feel at all uncomfortable with the study.

The University of Nottingham provide a counselling service, if this study has brought

experiences to your attention which you would like to discuss with someone then they may be of help

to you. Their contact details are;

Telephone: +44 (0)1159513695

E-mail:counselling.service@nottingham.ac.uk

Address: Room A75, Trent Building,

The University of Nottingham, University Park

Nottingham, NG7 2RD

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!"%("!"

'

Appendix B; Stage 2 task booklet (differences between condition in brackets)

Coming to University: The Experience of Students Leaving Home.

Investigator: Joscelyn Lester

School of Psychology, University of Nottingham

Information Sheet for Participant Stage 2

You are invited to take part in a survey exploring the experiences involved in leaving home

and coming to University.

The aim of this study is to see the kind of events and experiences which people may

experience in the experience of leaving home and coming to University.

This study is concerned with the six months before coming to University and the first six months of

University, i.e. the year surrounding the event of coming to university.

If you are willing to take part in the study, please try to (REMEMBER/IMAGINE) the course

of events for (YOUR OWN/ONE PARTICULAR HYPOTHETICAL STUDENT) in which the

experience of coming to University (WENT VERY WELL/VERY BADLY). Then please describe

the course of events for this person in the following way.

Please cross out the items on the sheet which you believe would not be relevant for an

extremely good experience of coming to university. Then order the remaining items by putting a

number in the box next to it according to the chronological order in which they occurred for your

imaginary student, 1 for the first event to occur, 2 for the second, and so on. You cannot have any tied

(simultaneous) events. Two events, both numbered 4 to indicate they happened at the same time,

cannot be analysed in our system. You would have to put one before the other. The same event can

recur, so a given event may be numbered 2, 9, 20, meaning that same kind of event was second, ninth,

and twentieth in the sequence you are trying to describe.

Participation is totally voluntary, and you are under no obligation to take part in this study.

You are free to withdraw at any point prior to returning the task sheet (you may destroy your reply if

you wish). If you do not feel comfortable with the subject of the survey or feel you may be distressed

by completing it, please do not complete it. All data collected will be kept confidential and used for

research purposes only. The consent forms will be kept separate from the surveys.

There are no right or wrong versions. Your name or any identifying characteristics will not be

available to anyone, other than my supervisor and me, at any point.

If you have any questions you may contact me on; lpycjjl@nottingham.ac.uk

Researcher: Joscelyn Lester

Supervisor: David Clarke

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"%)"!"

'

Coming to University: The Experience of Students Leaving Home.

Investigator: Joscelyn Lester

School of Psychology, University of Nottingham

The participant should complete the whole of this sheet himself/herself. Please cross

out as necessary

Have you read and understood the participant information sheet YES/NO

Have you had the opportunity to ask questions and discuss the study YES/NO

Have all the questions been answered satisfactorily YES/NO

Have you received enough information about the study YES/NO

Do you understand that you are free to withdraw from the study:

at any time YES/NO

without having to give a reason YES/NO

Do you agree to take part in the study YES/NO

“This study has been explained to me to my satisfaction, and I agree to take part. I

understand that I am free to withdraw at any time.”

Signature of the Participant: Date:

Name (in block capitals)

I have explained the study to the above participant and he/she has agreed to take part.

Signature of researcher Date:

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"%*"!"

'

Task Sheet

Age: Gender: Course:

Actions, Thoughts and Feelings

[ ] Not sad to leave home

[ ] Felt Confused

[ ] Felt Overwhelmed

[ ] Felt Lonely

[ ] Extended time period away from home

[ ] Holiday

[ ] Felt Excited

[ ] Made Friends

[ ] Became independent

[ ] Achieved academically

[ ] Felt happy with course

[ ] Organised finances

[ ] Planning travel to and from university

[ ] Seeing friends – saying goodbye

[ ] Spending time with family

[ ] Join societies

[ ] Organising academic work

[ ] Plan social meetings

[ ] A level exams

[ ] Preparation (shopping for bedding/ packing)

[ ] Nights out

[ ] Felt worried

[ ] Boyfriend/girlfriend visits.

[ ] Arranging housing

[ ] Getting first choice

[ ] Getting 2nd choice

[ ] Felt Confident

[ ] Parties

[ ] Results

[ ] Felt Disappointed

[ ] Stressful course

[ ] Not a good freshers week

[ ] Amazing freshers week

[ ] Settled in better in 2nd semester

[ ] Hearing of a bad experience

[ ] Felt Nervous

[ ] Reading prior to university

[ ] Scared of meeting new people

[ ] Eager to move away

[ ] Problems with student finance

[ ] Didn’t make friends easily

[ ] Felt Panic

[ ] None of other friends worried

[ ] Dropped out

[ ] Felt Homesick

[ ] Romantically successful

[ ] Voted president of society/ hall

[ ] Saved money

[ ] Felt Scared

[ ] Worked hard

[ ] Felt Shy

[ ] Ended romantic relationship

[ ] Fall out with school friends

[ ] Arguing with parents

[ ] Problems with course (module enrolment)

[ ] Felt Anxious

[ ] People were not very nice.

[ ] Don’t get along with people in halls/flat

[ ] Felt Sad

[ ] Not sure that the course is right for you

[ ] Start University

[ ] Pressure from parents

[ ] Exams went well

[ ] Exams went badly

[ ] Support of family and friends

[ ] Regrets

[ ] Made to feel comfortable when arrived at

university

[ ] Gap year

[ ] Changed friendship group

[ ] Prescribed anti-anxiety drugs

[ ] Family problems (death/financial

difficulties/divorce/illness)

[ ] Pressure not to drop out or fail

[ ] Felt Stressed

[ ] Going to university in a different country

[ ] Upset to leave university at Christmas

[ ] Became unwell

[ ] Helped that everyone was in the same position

[ ] Parent(s) were upset

[ ] Happier because previous family members had

gone to university

[ ] Felt like a failure

[ ] Hadn’t drank/ been clubbing before

[ ] Too busy to be nervous

[ ] Bullied

[ ] Moved back home to commute

[ ] Academics suffered

[ ] Clearing

[ ] Hospitalised

[ ] Financial difficulties

[ ] Relationship difficulties

[ ] Dropped out

[ ] Not a great summer

[ ] Settled in

[ ] Arrangements cancelled

[ ] Felt other home friends were having a better

time.

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!"%+"!"

'

Coming to University: The Experience of Students Leaving Home.

Investigators: Joscelyn Lester and David Clarke

School of Psychology, University of Nottingham

Debriefing sheet Stage two

Thank-you for participating in this survey.

This study was interested in finding out the sequence of the important actions, thoughts and

feelings which are involved in the event of leaving home for university. This research will help to

further understand the experience of this event. It will also help to see if there are any areas which

need more support for students when coming to University. The data will be analysed to see if there

are sequences of events, thoughts and feelings which are more likely to occur than others. This will

help to more fully understand the experience of students at University and to discover if men and

women deal with the situation differently.

The data you have provided will not be seen by anyone but me and my research supervisor.

The data will be kept entirely confidential. Consent forms will not be kept with the surveys and the

data will be referred to using numbers and not names. You have the right to withdraw and destroy

your data before returning it if you feel at all uncomfortable with the study.

The University of Nottingham provide a counselling service, if this study has brought

experiences to your attention which you would like to discuss with someone then they may be of help

to you. Their contact details are;

Telephone: +44 (0)1159513695

E-mail:counselling.service@nottingham.ac.uk

Address: Room A75, Trent Building,

The University of Nottingham, University Park

Nottingham, NG7 2RD

'

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

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'

'

Appendix C-Coding system

Code Units Code2 Units2

a1 start of sequence w2 Saved money

b1 Not sad to leave home x2 Felt Scared

c1 Felt Confused y2 Worked hard

d1 Felt Overwhelmed z2 Felt Shy

e1 Felt Lonely a3 Ended romantic relationship

f1 time away from home b3 Fall out with school friends

g1 Holiday c3 Arguing with parents

h1 Felt Excited d3 Problems with course

i1 Made Friends e3 Felt Anxious

j1 Became independent f3 People were not very nice.

k1 Achieved academically g3 Probs with people in halls

l1 happy with course h3 Felt Sad

m1 Organised finances i3 Not sure course is right

n1 Planning travel j3 Start University

o1 Seeing friends k3 Pressure from parents

p1 Spending time with family l3 Exams went well

q1 Join societies m3 Exams went badly

r1 Organising academic work n3 Support of family & friends

s1 Plan social meetings o3 Regrets

t1 A level exams p3 Welcomed to University

u1 Preparation q3 Gap year

v1 Nights out r3 Changed friendship group

w1 Felt worried s3 anti-anxiety drugs

x1 Boyfriend/girlfriend visits. t3 Family problems

y1 Arranging housing u3 Pressure not drop out/fail

z1 Getting first choice v3 Felt Stressed

a2 Getting 2nd choice w3 Going to uni in diff. country

b2 Felt Confident x3 Upset to leave uni at Xmas

c2 Parties y3 Became unwell

d2 Results z3 everyone in same position

e2 Felt Disappointed a4 Parent(s) were upset

f2 Stressful course b4 family members gone to uni

g2 bad freshers week c4 Felt like a failure

h2 Amazing freshers week e4 Hadn’t drank/been clubbing

i2 Settled better in 2nd term g4 Too busy to be nervous

j2 Hearing of bad experience h4 Bullied

k2 Felt Nervous i4 Moved back home

l2 Reading prior to university j4 Academics suffered

m2 Scared of new people k4 Clearing

n2 Eager to move away l4 Hospitalised

o2 Problems with student m4 Financial difficulties

p2 Didn’t make friends easily n4 Relationship difficulties

q2 Felt Panic o4 Dropped out

r2 other friends not worried p4 Not a great summer

s2 Dropped out q4 Settled in

t2 Felt Homesick r4 Arrangements cancelled

u2 Romantically successful s4 friends having better time

v2 president of committee X9 End of sequence

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Appendix D – Sequence Strings For All Participants

Strings for EGEF

1. a1 t1 l3 d2 c2 b2 g1 p1 o1 x1 w1 z1 n2 o2 n3 a4 j3 h3 p3 z3 r3 m1 h1 i1 d1 j1 n1 r1 u1 y1 g2 k2 m2 p2 t2 w2 x2 z2 v1 f1 g3 i3

k1 s4 y3 l1 n4 a3 i2 q4 X9

2. a1 t1 l3 u1 k2 d2 k1 z1 g1 v1 u2 h1 m1 p1 o1 j3 p3 m2 n1 h2 c2 b2 n3 t2 b4 z3 x1 i1 q4 l1 j1 q1 r1 X9

3. a1 j3 p3 n3 h2 z3 q4 i1 b2 m1 l1 v1 q1 c2 h1 s1 r1 j1 y1 k1 d2 X9

4. a1 y1 m1 t1 d2 z1 l3 u1 h1 j3 p3 z3 i1 h2 q4 r1 b2 j1 l1 v1 c2 X9

5. a1 a4 h1 d2 z1 v3 c4 y3 o1 m1 y1 u1 r1 q1 j1 i1 o3 p4 e4 c2 v1 u2 b2 h2 l2 s1 l1 y2 v2 w2 x1 k3 k1 n1 g1 p1 X9

6. a1 t1 m1 h1 g1 d2 n2 l1 u1 x1 y1 a3 q2 m2 p1 w2 x2 o1 c1 d1 i1 q1 v1 b2 c2 h2 t2 z2 y2 j2 e1 f1 j1 n1 s1 w1 e2 f2 i2 g3 v3 n4

z3 t3 i3 h3 e3 l3 c4 g4 j4 s4 t4 j3m4 a4 r3 c3 n3 q4 X9

7. a1 t1 d1 w1 d2 n3 z1 h1 y1 u1 m1 p1 o1 j3 p3 z3 g4 c2 b2 h2 r3 q4 y3 y2 u2 f1 w2 x3 l3 X9

8. a1 t1 z1 a2 n2 j3 l3 p3 n3 g4 h2 q4 h1 i1 j1 k1 l1 m1 n1 q1 r1 v1 x1 y1 b2 c2 i2 u2 y2 s1 o1 p1 f1 X9

9. a1 y2 w2 k1 l1 m1 y1 b2 h1 r2 r1 t1 b2 p1 c2 d2 l3 k1 z1 h1 u1 p1 o1 n3 j3 i1 p3 q4 q1 i1 h2 s1 j1 i2 z3 X9

10. a1 y1 y2 k1 m1 t1 n1 h1 u1 v1 d2 z1 b2 l3 r2 w2 o1 n2 j3 b4 p3 i1 z3 n3 h2 q1 l1 s1 r1 c2 q4 u2 v2 j1 x3 p1 y2 l3 i2 X9

11. a1 y2 t1 g1 v1 o1 p1 w2 d2 z1 c2 h1 m1 u1 b2 j3 p3 h2 i1 l1 j1 q1 u2 q4 x3 X9

12. a1 t1 g1 k2 d2 c2 w2 z1 q3 j1 i1 p1 n1 m1 h1 u1 l2 r2 y1 b4 o1 j3 a4 z3 q4 v1 h2 b2 x1 l1 u2 q1 s1 v2 y2 k1 n3 X9

13. a1 p1 t1 u1 d2 z1 i1 n2 j1 b1 m1 l2 b2 f1 g1 h1 r1 n3 h2 u2 v1 j3 l1 v2 k1 c2 w2 n1 y2 x1 y1 o1 x3 z3 g4 p3 X9

Strings for EGEM

1. a1 l2 w2 y2 t1 m1 k1 p1 q3 o1 b1 f1 z1 y1 u1 i1 j1 h1 b2 q1 s1 v1 r2 h2 l1 r1 x1 g1 i2 n1 c2 q4 w3 b4 j3 r3 X9

2. a1 y2 t1 c2 d2 n2 g1 n3 b4 u1 l3 j3 h2 h1 i1 j1 q1 o2 k2 v1 b2 r1 l1 q4 s4 o1 v1 h1 X9

3. a1 t1 z1 g1 p1 o1 u1 e3 k2 h1 j3 i1 h2 p3 g4 z3 b4 r3 q1 h3 n3 y2 v1 m1 l1 j1 s1 r1 c2 b2 q4 x3 y1 d2 k1 l3 X9

4. a1 t1 z1 d2 h1 n3 j3 i1 p3 c2 b2 b1 j1 h2 e4 q4 b4 z3 q1 s1 v1 y2 k1 l1 m1 v2 u2 x3 y1 w2 i2 X9

5. a1 h1 g1 t1 k2 m1 p1 o1 u1 d2 j3 y2 l3 n3 z3 h2 g4 p3 b2 o2 s1 q1 i1 v1 z1 c2 l1 r1 q4 y3 x1 j1 k1 f1 X9

6. a1 t1 h1 z1 b2 m1 o1 y1 d2 k2 n2 j3 p3 n3 q4 i1 q1 j1 v1 u2 h2 c2 l1 x3 s1 r1 y2 p1 X9

7. a1 t1 g1 w2 d2 z1 u1 n1 p1 o1 k2 h1 j3 p3 n3 h2 b2 i1 u2 q4 g4 q1 j1 l1 s1 c2 r1 m1 x3 y2 y1 v1 k1 l3 X9

8. a1 t1 l3 d2 z1 y1 g1 p1 n1 u1 m1 o1 n3 w3 j3 p3 q4 b2 h1 h2 z3 i1 q1 r1 s1 j1 c2 f1 u2 l1 v1 k1 v2 x3 X9

9. a1 z1 t1 l3 d2 h1 g1 n1 c2 p1 o1 r2 l2 n2 z3 b2 u1 j3 p3 h2 q4 b1 i1 l1 m1 r1 s1 q1 v1 j1 w2 u2 n3 x1 y1 v2 x3 k3 k1 X9

10. a1 t1 d2 z1 c2 h1 b1 j3 h2 i1 p3 n3 z3 b2 l1 m1 q1 r1 v1 x1 j1 n1 p1 u2 r2 y1 f1 g4 x3 y2 g1 o1 l3 k1 X9

11. a1 t1 d2 g1 l2 k2 w2 z1 j3 d1 p3 h2 c1 a4 z3 q4 i1 q1 v1 c2 b2 u2 h1 k1 l1 j1 r1 y1 x3 X9

12. a1 g1 z1 k1 h1 n2 w2 j3 n3 p3 q4 z3 b2 i1 j1 c2 h2 u2 r1 s1 v1 v2 l1 l3 x3 b1 X9

13. a1 y2 t1 z1 u1 b1 j3 p3 b4 z3 n3 c2 h2 v2 v1 q1 l1 k1 i1 m1 s1 X9

Strings for OEF

1. a1 y2 c2 v1 v3 l3 t1 d2 y1 z1 k2 h1 o2 n2 e3 c3 n3 p1 q2 o1 j3 u1 s1 w1 x2 j2 h3 h2 e4 q4 p3 d1 i1 j1 l1 z2 h2 t2 u2 f1 e1 f2 z3

y3 s4 x3 i2 g1 k1 r1 X9

2. a1 z1 g2 b1 q1 u1 p2 m2 n2 e1 i1 j1 r1 x1 v1 i2 f2 b2 c2 g1 y1 p1 y2 w2 t2 s1 k1 X9

3. a1 t1 u1 y1 z1 w1 j3 h2 p3 n3 m4 q4 z3 g4 i1 h1 j1 k1 l1 x1 c2 b2 t2 e1 v1 d1 y3 x3 l3 q2 d2 i2 X9

4. a1 t1 y2 w1 i3 v3 d2 l3 a2 e2 m4 m1 o1 p1 u1 o2 e4 j3 a4 c1 e1 f1 g2 m2 k2 p2 z2 r2 q1 o3 s4 y3 h3 l1 i1 v1 c2 n1 i2 z3 f2 r1 y1

q4 g3 u3 k1 j1 b2 X9

5. a1 t1 d2 z1 c2 u1 h1 l3 j3 k3 z3 d1 b2 i1 j1 h2 q4 g4 h2 b4 i3 f2 i2 v1 X9

6. a1 y2 t1 c2 w1 d2 k1 h1 z1 g1 j1 u1 v1 o2 n1 n2 m1 o1 p1 n3 j3 f1 b1 h2 b2 r2 s1 i1 h2 z3 y3 r3 p3 q4 j2 g4 l1 r1 i3 x3 j4 m4 i2

u2 f2 X9

7. a1 t1 z1 k3 d2 m1 c2 d1 y1 w2 n2 h1 p1 n1 u1 v1 o1 j3 j1 h2 i1 q1 r1 o2 b2 c3 n3 h2 g4 q4 k1 l1 f2 e3 l3 p3 v3 z3 y2 i2 X9

8. a1 m1 z1 y1 t1 k1 d2 m2 u1 p1 o1 c2 n2 z2 i1 q1 s1 j1 h1 d1 l1 n1 t2 b2 i2 j2 r1 w2 x3 y3 b4 j3 l3 n3 f3 p3 g4 q4 v3 z3 X9

9. a1 u1 l3 d2 g1 w1 e2 a2 j3 d1 i2 c2 i1 h1 z3 q4 y1 a3 g2 r1 m1 n1 p3 n3 x3 j2 z1 X9

10. a1 u1 l3 d2 g1 w1 e2 a2 j3 d1 i2 c2 i1 h1 z3 q4 y1 a3 g2 r1 m1 n1 p3 n3 x3 j2 z1 X9

11. a1 h2 k3 u3 t1 l3 w1 d2 z1 k1 s1 g1 p1 o1 b1 b2 j3 p3 i1 z3 h2 g4 n3 r3 y3 q4 f1 h1 e1 j1 c2 l1 q1 v1 y1 X9

12. a1 n3 e3 z1 y1 m2 w1 l2 u1 t1 o1 o2 n1 s1 p1 k2 d2 k1 h1 r1 x2 m1 j3 a4 d1 p3 i1 r3 b1 x1 j1 b2 y2 f2 v3 y3 e1 z2 i1 l1 q4 n4 a3

l3 X9

13. a1 b4 g4 c2 t1 g1 p1 w2 o1 u2 d2 e2 a2 y1 u1 h1 n2 j3 n3 p3 h2 z3 q4 i1 m1 q1 v1 y3 a4 o2 s1 f1 t2 v2 x1 a3 c3 l1 j1 r1 y2 b2 x3

l3 k1 X9

14. a1 h1 u1 r1 t1 d2 k1 z1 g1 n3 j3 p3 z3 q4 h2 v1 i1 j1 i2 y1 X9

15. a1 h1 m1 b1 w2 b2 t1 g1 e3 d2 z1 u1 p1 o1 k2 n2 n1 a4 i1 z3 c2 v2 j1 d1 d3 u3 n3 i3 h3 v3 q1 e1 X9

16. a1 y2 u1 d2 h1 e2 l3 l1 a2 w2 v1 p1 q1 m2 k2 g1 j3 z3 q4 n3 c2 i1 j1 m1 r1 t1 w1 y3 p3 g4 t2 z1 x3 X9

17. a1 n2 v1 y1 l3 g1 c2 z1 m1 u1 n1 p1 o1 h1 t1 w1 k2 n3 j3 f1 i1 y3 c3 z3 l1 q1 x3 b3 k1 i2 X9

18. a1 t1 d2 n2 z1 l3 b4 c2 h1 v1 d3 u1 m1 o2 s1 d3 l1 y3 z3 n3 j3 p3 i1 h2 b1 j1 w2 b2 q4 r3 y1 n4 x3 k1 q1 r1 X9

Strings for OEM

1. a1 j3 k3 r3 c1 m4 h2 v1 p3 z1 h1 i1 d2 e2 c2 b2 f2 f1 g2 h2 g1 b1 d1 X9

2. a1 b1 i1 h1 b2 h2 i2 n2 u2 y2 v1 r1 y1 d3 m3 u3 a4 j3 z3 j4 h2 X9

3. a1 w3 b1 k1 l1 m1 n1 p1 o1 r1 z1 b2 p3 d2 n3 v3 j3 g4 n4 q4 r3 i1 j1 w2 X9

4. a1 d1 h1 l1 i1 j1 n1 h2 u1 q1 w2 r1 f2 b2 j3 i2 u2 y2 z3 X9

5. a1 t1 z1 n2 m2 u1 h1 j3 i1 q1 h2 v1 b2 g4 q4 i3 j4 m3 c2 r1 d2 l3 k1 y2 l1 i2 X9

6. a1 t1 l3 g1 o1 p1 u1 y1 z1 d2 j3 a4 z3 q4 c2 b2 h1 f1 i1 j1 q1 v1 y2 i3 v3 g4 x3 X9

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'

7. a1 m2 m1 y1 b1 s1 c1 d1 v1 h1 p1 t1 w1 b2 d2 z1 w2 u1 n1 k2 l2 g1 j3 k3 i1 x2 z2 e3 c3 a4 e4 r3 p3 j1 q1 o1 l1 q2 n2 r2 n3 v3

n4 o3 h3 e1 y2 k1 e2 r1 l3 X9

8. a1 t1 d2 h1 u1 n1 z1 o1 p1 c1 b1 w3 p3 j3 g2 i1 j1 r1 a3 v3 X9

9. a1 w3 j3 l1 h3 q1 r1 h1 b2 f2 p2 z3 n3 v3 q4 c1 d1 f1 e3 j1 g2 k2 j2 e2 i2 h2 e1 d2 l2 k1 t2 v2 x2 u2 m2 y2 a3 z2 c2 o2 q2 v1 s2

u1 u3 r2 X9

10. a1 t1 z1 c2 b2 h1 p3 j3 i3 h2 d2 j1 k1 i1 v1 a3 q4 r3 X9

11. a1 v1 g1 h1 c2 i1 d2 l1 e2 w1 b1 k1 a2 h3 e3 m3 c4 t4 u1 n1 o1 p1 k2 x2 n3 y1 a4 j3 t1 h2 q1 u2 t2 s1 b2 t3 n4 o3 y3 x3 i2 o2

X9

12. a1 x1 b2 t1 r2 z3 l3 z1 c2 h1 o1 a3 o2 n2 k2 j3 u1 y1 a4 p1 b4 k1 p3 n3 i1 v1 r3 q4 m4 w3 y3 q1 n1 l1 f1 s1 t3 v3 x3 c2 X9

13. a1 t1 d2 e2 v1 l3 v3 a2 n3 o2 n2 p1 o1 m1 u1 b2 m2 j3 e3 h1 y1 i1 c2 h2 f1 l1 y2 j1 p3 q4 g4 j4 m4 y3 x3 g1 i2 a4 k1 u2 X9

14. a1 v1 i1 c2 t1 d2 k1 l3 a2 b1 o1 v1 l1 u1 b4 h1 j3 p2 v1 o2 q1 z3 g3 p3 j1 f1 a3 x3 i2 q4 X9

15. a1 t1 l3 g1 p1 o1 v1 z1 w2 d2 b1 n2 m2 b2 j3 p3 r3 q4 h2 y3 z3 i1 h1 l1 m1 c2 j1 q1 k1 y1 x3 i2 X9

16. a1 t1 v1 c2 v1 g1 k1 l3 u1 a3 a4 o3 j3 m2 i1 h1 h2 x2 e3 z3 q4 d3 j4 h3 y3 o2 r4 s4 r3 q1 q2 d1 X9

17. a1 l1 n2 a2 v1 e2 s2 e1 u1 a4 i3 i4 b3 n3 e3 d3 j3 n4 r3 s3 o1 p1 x1 f2 b2 l2 q2 u2 x2 z2 r2 w2 g2 k2 g1 r1 c1 n1 w1 y1 z1 i2 f1

s4 h3 k3 h4 e4 m3 c4 y3 b4 k4 m4 q4 t4 r4 o4 l4 g4 X9

18. a1 t1 d2 q3 z1 m1 u1 h1 b2 k2 n2 n3 j3 h2 u2 v1 p3 q4 b4 y3 z3 l1 j1 i1 f2 g1 c2 p1 y1 r3 r1 m3 t4 i3 v3 c4 c2 v1 r1 v3 m3 t4 c4

e2 q1 X9

19. a1 y1 t1 g1 m1 d2 l3 h1 z1 o1 p1 n2 b2 n3 j3 j1 v3 q1 g2 p2 v1 y2 x1 r1 l1 u3 h3 y3 c4 o3 d2 e1 w1 i3 i1 m3 f2 d2 k1 s1 i2 n4

c2 w2 n3 l3 X9

Strings for SBEF

1. a1 p3 k4 a2 v3 p4 a4 c4 l2 o2 r2 t2 z2 z3 j3 c3 h3 e2 f2 g2 e1 c2 v1 p2 e3 f3 j3 t3 u3 s3 t4 s4 n4 i4 g4 n3 r4 b4 b3 d3 g3 l3 r3 d2

d1 c1 f1 q1 w2 y2 j2 k2 i2 y1 w1 w3 h4 m4 q3 o1 q2 x2 x3 l4 o4 X9

2. a1 t1 a2 b1 o2 m3 q2 w3 d1 r1 g3 d3 u3 s2 g4 x2 e1 e2 a3 i3 m4 f3 c3 s3 t4 o4 X9

3. a1 t3 s3 k3 o2 t1 a3 k4 l4 j4 p4 r4 m4 n4 j2 d2 e2 f2 d1 e1 f1 o1 n1 u1 y1 w1 z2 g2 x2 k2 m2 y3 b3 c3 a4 d3 o3 t4 s4 u3 e3 f3 h3

i3 g3 m3 c4 v3 o4 h4 X9

4. a1 e3 k3 o1 p2 x2 o2 j3 g2 f3 g3 h3 y3 e1 r2 c3 b3 i3 v3 u3 h4 j4 t3 s3 n4 a3 r4 o4 m3 l4 m4 t4 X9

5. a1 p4 m3 c4 e2 b3 h3 r3 n4 j2 k2 q2 a3 w1 o1 m2 j3 e3 f3 g3 i3 u3 v3 f2 g2 p2 t2 z2 c1 e1 f1 d1 x2 o2 c3 d3 k3 y3 l4 s3 j4 h4 t3

s4 m4 i4 s2 a4 o3 X9

6. a1 l4 g3 h4 f3 o4 t3 y3 m4 n4 d3 j4 f2 s4 X9

7. a1 t1 d2 a2 k1 m1 n1 o2 o1 p1 u1 j3 h3 b3 e1 j1 r1 y2 r3 q4 l3 X9

8. a1 j2 o1 g2 a2 f2 m2 p2 x2 z2 a3 b3 c3 d3 e3 g3 h3 f3 i3 k3 m3 o3 s3 t3 v3 y3 a4 c4 h4 l4 m4 p4 t4 e1 w1 e2 k2 q2 s2 X9

9. a1 d2 a2 p4 k4 q3 u3 w3 w1 x2 d1 r2 m2 p1 k2 j2 o1 j3 g3 f3 z2 p2 c3 q2 t2 g2 e1 e4 j1 h3 s4 a4 i3 d3 e3 k3 m3 o3 v3 j4 h4 y3

y2 o2 f2 e2 f1 c1 r1 s1 v1 s3 t3 m4 l4 i4 n4 x1 a3 r3 b3 y1 r4 s2 o4 c4 t4 X9

10. a1 t1 g1 d2 a2 e2 j2 j3 g2 f3 g3 h3 e1 r2 s4 i3 f2 q2 f1 n1 x1 n4 b3 a3 t2 y3 c3 a4 s3 j4 t4 w1 y1 x2 o3 o4 X9

11. a1 d2 k1 o2 g2 i3 g3 s4 d3 y3 h3 c1 d1 e1 f1 f2 p2 r2 y2 d2 e2 w1 x2 q2 t2 n4 m4 u3 e3 m3 v3 t4 X9

12. a1 t1 d2 z1 h1 y1 l2 u1 k2 j2 t3 p1 o1 r2 j3 g2 z2 y2 q1 r1 f1 e1 f2 p2 q2 f3 g3 e3 c4 a4 s4 d1 t2 n1 w1 m2 h3 v3 u3 y3 n4 o3 s3

t4 x2 i4 l4 o4 e2 n3 X9

13. a1 r2 a2 m2 o2 g2 f2 x2 z2 w1 o1 p2 h4 i3 h3 g3 d3 b3 f3 p4 m4 a4 y3 v3 m3 u3 y1 i2 j2 k2 e2 X9

14. a1 p4 b3 d2 a2 c3 j3 d3 e3 c1 d1 g3 f3 e1 f1 h3 j3 n1 w1 t2 m2 j2 g2 q1 p2 o2 k2 i3 k3 m3 f2 e2 x2 a3 o3 c4 a4 u3 v3 s3 t3 w3

j4 m4 n4 y3 l4 s4 t4 h4 o4 q2 i4 r2 X9

15. a1 o1 d1 t1 e2 k4 v3 a4 j3 w3 e3 f3 g3 r2 m2 o2 p2 g2 f2 e1 f1 a3 t2 x2 z2 j2 b3 c3 d3 i3 r3 t3 s3 y1 u3 w1 r4 s4 n4 m4 j4 h4 i4

t4 y3 k3 h3 c4 k2 l4 m3 d2 o3 o4 X9

Strings for SBEM

1. a1 t2 w1 c1 h1 x2 k2 e1 q2 m2 p2 e2 q1 o1 z2 f2 d2 f1 i1 s1 j3 X9

2. a1 c1 y1 e1 d1 y2 o1 q1 f2 d2 d3 h1 e2 i2 f3 m3 j2 w1 h3 t1 i1 v1 q2 p2 k2 r1 b2 s1 f1 r2 x2 w2 t2 z2 i3 n3 X9

3. a1 o1 u1 z2 k2 s4 u3 t3 q3 r3 r4 t4 k4 l4 m4 n4 o4 p4 o3 m3 k3 h3 e3 c3 b3 d3 a4 x3 c4 h4 g4 j4 e4 v3 f3 w3 i4 s2 f2 d2 g2 m2

r2 x2 a3 w1 y1 r1 p1 f1 m1 t2 z1 X9

4. a1 k1 h1 b1 g2 f2 e2 x2 m3 r3 q4 g4 h2 j3 z3 p3 v1 w1 q2 l2 k2 X9

5. a1 h4 e1 e2 f3 g3 h3 t3 s3 d2 a3 p2 o2 m2 f2 i3 s4 t4 v3 r4 m3 k3 a4 y3 g2 q2 s2 t2 w1 f1 x2 X9

6. a1 i1 q4 h2 p3 z1 j1 k1 l1 d2 v1 y1 n2 h1 f2 x3 X9

7. a1 y2 t1 c2 d2 k1 h1 z1 d1 g1 v1 o2 k2 c1 b2 m1 l1 o1 p1 y1 r2 n1 c4 i3 z3 d3 o3 q4 u3 e4 h2 i1 j1 q1 s1 t2 u2 X9

8. a1 t1 n2 z1 j1 b1 h1 j3 l3 X9

9. a1 t1 d2 c2 a2 s1 u1 o1 n1 o2 a4 u3 g4 t3 s3 y3 c3 b3 g2 s4 p4 l4 k4 j4 i4 h4 e4 c4 g3 h3 i3 j3 k3 o3 v3 t4 r3 r4 n4 m4 f3 e3 d3

e1 f1 d1 c1 e2 f2 j2 k2 p2 q2 r2 t2 x2 z2 a3 w1 r1 m2 m3 o4 X9

10. a1 t1 d2 h1 z1 m1 y1 n2 p1 o1 u1 n1 b1 h2 q1 i1 v1 j1 x1 b2 c2 l1 y2 k1 X9

11. a1 d2 k1 h1 g1 f1 v1 u1 w2 n2 m2 o1 g1 x2 w1 g4 p1 e3 n3 b1 j3 q4 q1 c2 f2 b2 q2 y1 n4 a3 r1 e2 X9

12. a1 t1 u1 x2 m2 l2 j2 d2 a2 e2 c4 a4 c3 e3 k2 o2 t3 b3 p4 j3 p2 q2 r2 e1 d1 o1 t2 g2 e4 s3 y3 s4 g3 f3 h3 f1 x1 a3 c1 h4 l4 i4 n1 t4

j4 m4 n4 r3 v3 k3 i3 u3 d3 f2 w1 o3 o4 X9

13. a1 t3 s3 o4 q2 n4 m2 w3 u3 l4 h4 g3 i4 d3 n2 e2 h3 r2 m3 j4 v3 d1 c2 d2 e1 o2 v2 x2 y2 y3 e3 f3 k3 o3 t4 r4 m4 a4 s4 i3 k4 f1

h2 k2 p1 o1 c1 i2 w1 p4 c4 e4 p2 X9

14. a1 t1 t4 m3 y3 e3 f3 g3 j3 o2 o3 q2 n2 f2 e2 d2 g2 a2 w1 x1 y1 g1 z2 r2 t2 d1 l3 k3 i3 h3 t3 h4 s2 X9

15. a1 k2 j2 c1 p4 i3 t1 d2 d1 y1 x2 w1 n1 p1 o1 h1 j3 e1 q2 p2 o2 t2 m2 i1 x1 d3 e3 g3 f3 k3 o3 s3 n4 y2 a3 f2 f1 r1 r2 s4 v3 w3 m3

m4 h3 j3 i2 X9

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&%"!"

'

Appendix E– Frequency table for all Units

Units EGE

TOTAL

Units2 OE

TOTAL

Units3 SBE

TOTAL Felt Excited 27 Start University 38 start of sequence 30 Nights out 27 start of sequence 37 End of sequence 30

start of sequence 26 End of sequence 37 Results 25 Made Friends 26 Made Friends 36 Stressful course 23

Parties 26 Felt Excited 33 Felt Scared 23 Amazing freshers week 26 Nights out 33 Felt worried 22

End of sequence 26 Results 32 Felt Disappointed 21 happy with course 25 Parties 31 People were not very

nice. 21

Felt Confident 25 Preparation 30 Felt Sad 21 Start University 25 A level exams 28 Felt Lonely 20

Became independent 24 Getting first choice 28 Seeing friends 20 Organised finances 23 Felt Confident 28 Probs with people in

halls 20

A level exams 23 Became independent 27 Start University 20 Getting first choice 23 Amazing freshers

week 27 Felt Panic 19

Settled in 22 Settled in 27 Not sure course is

right 19

Achieved academically 21 Achieved

academically 25 time away from home 18

Join societies 21 happy with course 25 bad freshers week 18 Results 21 Support of family &

friends 25 Felt Nervous 18

Support of family & friends 21 everyone in same

position 25 Problems with course 18

Welcomed to University 21 Organising academic

work 24 Exams went badly 18

Seeing friends 20 Arranging housing 24 Problems with

student 17

Spending time with family 20 Exams went well 24 Didn’t make friends

easily 17

Organising academic work 20 Spending time with

family 23 other friends not

worried 17

Preparation 19 Welcomed to

University 23 Felt Homesick 17

Worked hard 19 Join societies 22 Felt Anxious 17 everyone in same position 19 Settled better in 2nd

term 22 Felt Stressed 17

Arranging housing 18 Holiday 21 Became unwell 17 Holiday 17 Seeing friends 21 Financial difficulties 17

Plan social meetings 17 Became unwell 19 Relationship

difficulties 17

Exams went well 17 Organised finances 18 Felt like a failure 17 Romantically successful 16 Eager to move away 18 Felt Overwhelmed 16

Saved money 15 Planning travel 16 Scared of new people 16 Planning travel 13 Worked hard 16 Family problems 16

Upset to leave uni at Xmas 13 Upset to leave uni at

Xmas 16 Pressure not drop

out/fail 16

Boyfriend/girlfriend visits. 11 Felt Stressed 15 Parent(s) were upset 16 time away from home 9 Not sad to leave

home 14 Bullied 16

Felt Nervous 9 Felt Overwhelmed 14 friends having better

time 16

Eager to move away 9 Felt worried 14 Arranging housing 15 president of committee 9 time away from home 13 Regrets 15 Too busy to be nervous 8 Stressful course 13 A level exams 14

Settled better in 2nd term 7 Problems with

student 13 Hearing of bad

experience 14

family members gone to uni 7 Saved money 13 Fall out with school

friends 14

Not sad to leave home 6 Changed friendship

group 13 Pressure from parents 14

Reading prior to university 6 Too busy to be

nervous 13 Hospitalised 14

other friends not worried 6 Plan social meetings 12 Dropped out 14 Changed friendship group 5 Felt Disappointed 12 Felt Shy 13

Parent(s) were upset 5 Felt Nervous 12 Arguing with parents 13 Felt Overwhelmed 4 Parent(s) were upset 12 Felt like a failure 13

Became unwell 4 Felt Lonely 11 Felt Confused 12 Felt worried 3 Scared of new people 11 Dropped out 12

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&&"!"

'

Scared of new people 3 Romantically

successful 10 Academics suffered 12

Problems with student 3 Ended romantic

relationship 10 Not a great summer 12

Felt Homesick 3 Felt Anxious 10 Getting 2nd choice 11 Felt Sad 3 Not sure course is

right 10 anti-anxiety drugs 11

friends having better time 3 Getting 2nd choice 9 Felt Excited 10 Felt Confused 2 bad freshers week 9 Planning travel 10

Felt Scared 2 Felt Sad 9 Worked hard 10 Felt Shy 2 Felt Homesick 8 Moved back home 10

Ended romantic relationship 2 family members gone

to uni 8 Spending time with

family 9

Felt Anxious 2 Boyfriend/girlfriend

visits. 7 Organising academic

work 9

Probs with people in halls 2 Felt Scared 7 Changed friendship

group 9

Not sure course is right 2 Felt Shy 7 Arrangements

cancelled 9

Pressure from parents 2 Exams went badly 7 Join societies 8 Felt Stressed 2 Financial difficulties 7 Preparation 8

Going to uni in diff. country 2 Relationship

difficulties 7 Nights out 8

Felt like a failure 2 Felt Confused 6 Parties 8 Hadn’t drank/been clubbing 2 Hearing of bad

experience 6 Going to uni in diff.

country 8

Relationship difficulties 2 Felt Panic 6 Achieved

academically 7

Felt Lonely 1 other friends not

worried 6 Ended romantic

relationship 7

Getting 2nd choice 1 Problems with course 6 Clearing 7 Felt Disappointed 1 Pressure from parents 6 Not sad to leave

home 6

Stressful course 1 Pressure not drop

out/fail 6 Made Friends 6

bad freshers week 1 Didn’t make friends

easily 5 Became independent 6

Hearing of bad experience 1 Arguing with parents 5 Boyfriend/girlfriend

visits. 6

Didn’t make friends easily 1 Regrets 5 Getting first choice 6 Felt Panic 1 Felt like a failure 5 Felt Confident 6

Arguing with parents 1 Academics suffered 5 Eager to move away 6 Regrets 1 Reading prior to

university 4 Hadn’t drank/been

clubbing 6

Gap year 1 Going to uni in diff.

country 4 Too busy to be

nervous 6

Family problems 1 Hadn’t drank/been

clubbing 4 Holiday 5

Academics suffered 1 friends having better

time 4 Plan social meetings 5

Financial difficulties 1 Felt like a failure 4 Amazing freshers

week 5

Not a great summer 1 president of

committee 3 Settled better in 2nd

term 5

Felt like a failure 1 Dropped out 2 Settled in 5 Dropped out 0 Fall out with school

friends 2 Organised finances 4

Fall out with school friends 0 Probs with people in

halls 2 Reading prior to

university 4

Problems with course 0 Family problems 2 Exams went well 4 People were not very nice. 0 Arrangements

cancelled 2 Support of family &

friends 4

Exams went badly 0 People were not very

nice. 1 happy with course 3

anti-anxiety drugs 0 Gap year 1 Saved money 3 Pressure not drop out/fail 0 anti-anxiety drugs 1 Welcomed to

University 3

Came to university 0 Bullied 1 Gap year 3 Amazing freshers week 0 Moved back home 1 Upset to leave uni at

Xmas 3

Bullied 0 Clearing 1 everyone in same

position 3

Moved back home 0 Hospitalised 1 family members gone

to uni 2

Clearing 0 Dropped out 1 Romantically

successful 1

Hospitalised 0 Came to university 0 president of

committee 1

Dropped out 0 Amazing freshers

week 0 Came to university 0

Arrangements cancelled 0 Not a great summer 0 Amazing freshers

week 0

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&'"!"

'

Appendix F- Relative positions with confidence above 95%

Code UNIT EGE %

EGE

freq

SBE

%

SBE

freq Zvalue Confidence

c3 Arguing with parents 95 1 43 13 4.368 100

k1 Achieved academically 66 21 27 7 3.055 99.8

k3 Pressure from parents 89 2 52 14 3.105 99.8

g3 Problems with people in halls 74 2 37 20 2.879 99.6

b4

Happier because family members gone to

uni 53 2 19 13 2.769 99.4

s4 felt friends were having a better time 89 3 58 16 2.632 99.2

v2 president of committee 80 9 49 1 3.092 99.8

t3 Family problems 72 1 44 16 2.141 96.8

j4 Academics suffered 84 1 58 12 2.133 96.7

i3 Not sure course is right 79 2 54 19 1.97 95.1

m4 Financial difficulties 90 1 68 17 1.974 95.2

q3 Gap year 13 1 37 3 2.045 95.9

w1 Felt worried 29 3 58 22 2.21 97.3

q2 Felt Panic 21 1 59 19 3007 99.7

l3 Exams went well 49 17 88 4 3.287 99.9

As expected

Hyper conscientious?

Bads reported A levels?

Inappropriate for this analysis

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&("!"

'

Appendix G- Units in each of the ‘Super Categories’.

) ) ) 678%9&:)

;7-+,+<#)#97,+7&-)=;.>) ;7-+,+<#)?''?@#9+'-);2) '

AB) Felt Excited M>' Achieved academically CD) Felt Confident C>' Felt happy with course EF) Upset to leave university at Christmas C@' Exams went well CB) Not sad to leave home ,>' Organising academic work &D) Eager to move away .?' Worked hard +D) Settled in better in 2nd semester K>' Getting first choice GF) Helped that everyone was in the same

position

H#I?,+<#)?''?@#9+'-)H2) '

IJ) Too busy to be nervous :?' Getting 2nd choice H#I?,+<#).97,+7&-)=H.>) 8@' Problems with course 'B) Felt Confused 5?' Stressful course KD) Felt Nervous bA' Academics suffered ED) Felt Scared MA' Clearing <F) Felt Stressed #@' Exams went badly @B) Felt Overwhelmed 3?' Didn’t make friends easily 9D) Scared of meeting new people ;7-+,+<#);"#L?"?,+7&)=;;>) '

#B) Felt Lonely C?' Reading prior to university MD) Hearing of a bad experience #>' Organised finances GD) Felt Shy %>' Planning travel to and from university

'J) Felt like a failure 7>' Preparation (shopping for

bedding/ packing) #D) Felt Disappointed L?' Saved money #F) Felt Anxious .>' Arranging housing AF) Felt Sad H#I?,+<#);"#L?"?,+7&)=H;>) '

7F) Regrets "?' Problems with student finance

$D) Felt Panic ,A' Dropped out "D) None of other friends worried N#-%8,-)=@D>) '

-J) Felt other home friends were having better time 8?' Results ,D) Felt Homesick 2O8#<#8-)=,B>) '

PB) Felt worried (>' A level exams ,J) Felt like a failure H#I?,+<#)-7'+?8)=H4>) '

H#I?,+<#);#"-7&?8Q)R?9+8()#EL#"+#&'#)=H;!.>) :@' Ended romantic relationship ?J) Parent(s) were upset Z@' Fall out with school friends 'F) Arguing with parents 5@' People were not very nice. KF) Pressure from parents &?' bad freshers week 8J) Hospitalised &@' Don’t get along with people in

halls/flat

9J) Financial difficulties 1A' Bullied -F) Prescribed anti-anxiety drugs $@' Not sure that the course is right for

you

,F) Family problems (death/financial

difficulties/divorce/illness)

%A' Relationship difficulties

%F) Pressure not to drop out or fail 3A' Not a great summer (F) Became unwell /?+&+&I)+&@#L#&@?&'#)=/S>) '

;7-+,+<#)-7'+?8)=;4>) 5>' Extended time period away from home

AD) Amazing freshers week b>' Became independent +B) Made Friends F@' Gap year LF) Made to feel comfortable when arrived

at university

4,?",)*&+)=MF>) '

$B) Join societies b@' Start University -B) Plan social meetings T"7LL#@)7%,)=T1>) '

%D) Romantically successful -?' Dropped out <B) Nights out 4#,,#8#@)+&)=$J>) '

<D) Voted president of society/ hall FA' Settled in EB) Boyfriend/girlfriend visits. 4,?",)7R)-#$%#&'#)=?B>) '

'D) Parties -(:,('"5'-+F7+%4+' '

IB) Holiday .&@)7R)-#$%#&'#)=EU>) '

7B) Seeing friends – saying goodbye D%8'"5'-+F7+%4+'' '

"F) Changed friendship group L"#<+7%-)R?9+8()9#9C#")I7&#)),7)%&+=;!>)

;7-+,+<#)R?9+8()#EL#"+#&'#-)=;V.>) ZA' previous family members gone to uni

&F) Support of family and friends H#I?,+<#)S&@#L#&@#&'#)=HS>) '

LB) Spending time with family $A' Moved back home to commute ) ) ) ' ) ' ' ) )

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&)"!"

'

Appendix H- Matrices

Matirix For All Data Together 678%9&B' ?B' @D' T1' /S' MF' H2' H.' HS' H;' H;!.' H4' ;2' ;.' ;!' ;V.' ;;' ;4' $J' ,B' V.' VU'

?B) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

@D) @' =' =' =' =' c' >A' =' =' ?' >' >?' ?' =' =' =' >@' =' >d' =' ='

T1) =' =' =' =' =' >' e' ?' @' A' A' =' =' =' =' f' >' =' =' =' ='

/S) =' @' =' @' A' A' >e' =' =' ?' =' >c' f' =' @' =' @f' >' =' >' ='

MF) ?' ?' =' =' =' @' >>' =' >' c' A' @' >f' ?' e' >' >@' =' =' @' ='

H2) =' d' ?' >' @' >A' @f' >' d' >A' ?c' f' >@' >' =' A' >c' >' g' A' ='

H.) e' >?' d' >A' f' cd' >A=' ?' >>' A?' cc' ?c' @=' =' >?' ?f' cc' c' e' d' ='

HS) =' =' =' =' =' >' ?' =' =' @' A' =' =' =' =' =' =' =' =' >' ='

H;) f' =' @' >' >>' ?c' cc' >' d' Ac' ?f' e' >c' >' A' >?' >f' A' =' ?' ='

H;!.) A' =' @' >' >=' ??' Ac' >' c' A@' ?d' c' >=' >' ?' d' >>' A' =' ?' ='

H4) @' @' ?' d' g' >@' cA' @' @' ?e' @@' e' g' ?' ?' e' >=' @' >' >' ='

;2) >?' ?e' =' >g' d' @' ?g' =' =' e' ?c' Ad' @>' >' c' @>' cf' A' >d' =' ='

;.) c' >=' >' >?' d' >A' @g' >' ?' >d' e' @=' A>' c' g' @A' gf' >>' =' >' ='

;!) @' ?' =' =' @' >' >=' =' =' e' ?' e' >e' =' ?' >c' @f' =' =' >' ='

;V.) ?' =' =' =' ?' >' f' =' >' d' ?' g' >g' =' >' >@' @g' >' =' =' ='

;;) g' @' >' >@' @' @' @?' =' ?' @' >' A>' ?d' >' >?' A=' A>' ?' d' =' ='

;4) f' g' =' @A' ?@' e' cc' =' d' >?' >@' dA' g?' A' @c' AA' >?g' >d' >A' A' ='

$J) =' =' =' =' >' ?' ?' =' =' A' ?' @' >g' =' >' >' ?>' =' =' ?' ='

,B) @c' =' =' =' =' =' ?' =' >' =' >' >>' @' =' @' c' @' =' =' =' ='

V.) ?' =' =' =' >' ?' ?' =' >' c' d' =' >' =' >' =' ?' >' =' =' ='

VU) =' >' e' ?' >' ?' >c' =' >' =' >' >f' ??' =' c' @' >>' @' =' =' ='

Matrix for EGE 678%9&B' ?B' @D' T1' /S' MF' H2' H.' HS' H;' H;!.' H4' ;2' ;.' ;!' ;V.' ;;' ;4' $J' ,B' V.' VU'

?B) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

@D) =' =' =' =' =' =' @' =' =' =' =' c' >' =' =' d' A' =' @' =' ='

T1) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

/S) =' =' =' ?' =' =' ?' =' =' =' =' g' c' =' ?' >' >d' =' =' =' ='

MF) >' >' =' =' =' =' >' =' =' >' =' ?' f' >' @' ?' A' =' =' >' ='

H2) =' =' =' =' =' =' ?' =' =' =' =' >' >' =' =' =' =' =' =' =' ='

H.) =' >' =' =' ?' ?' >?' =' >' =' A' c' >' =' >' d' >A' >' ?' =' ='

HS) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

H;) >' =' =' =' >' =' @' =' =' >' =' =' A' =' ?' =' @' ?' =' =' ='

H;!.) >' =' =' =' >' =' @' =' =' >' =' =' ?' =' ?' =' ?' ?' =' =' ='

H4) =' =' =' >' =' =' ?' =' =' >' ?' >' >' =' >' ?' =' =' =' =' ='

;2) c' >>' =' d' @' =' A' =' =' A' >' ??' >=' =' g' >A' @=' ?' e' =' ='

;.) >' A' ' c' =' ?' A' =' =' @' ?' >=' >c' @' d' >c' @e' g' =' =' ='

;!) >' >' =' =' ?' =' @' =' =' >' =' c' g' =' ?' g' >e' =' =' >' ='

;V.) >' =' =' =' >' =' ?' =' >' >' =' c' d' =' >' =' >g' =' =' =' ='

;;) @' =' ' d' =' =' e' =' =' =' =' >f' >A' >' ?' >d' >e' =' A' =' ='

;4) >' @' =' >@' >d' =' e' =' >' @' =' @?' @@' @' ?=' ??' cA' d' A' >' ='

$J) =' =' =' =' =' =' =' =' =' =' =' ?' c' =' ?' =' >?' =' =' =' ='

,B) >@' =' =' =' =' =' =' =' =' =' =' d' =' =' >' ?' >' =' =' =' ='

V.) =' =' =' =' =' =' =' =' =' =' >' =' =' =' >' =' >' >' =' =' ='

VU) =' >' =' ?' =' =' =' =' =' =' =' d' e' =' @' =' A' ?' =' =' ='

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&*"!"

'

Matrix OE '' ?B' @D' T1' /S' MF' H2' H.' HS' H;' H;!.' H4' ;2' ;.' ;!' ;V.' ;;' ;4' $J' ,B' V.' VU'

?B) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

@D) =' =' =' =' =' >' e' =' =' >' =' c' >' =' >' =' c' =' e' =' ='

T1) =' =' =' =' =' =' >' =' >' =' =' =' =' =' =' @' >' =' =' =' ='

/S) =' ?' =' =' A' >' A' =' =' =' =' c' A' =' =' =' >f' >' =' =' ='

MF) >' >' =' =' =' @' c' =' =' ?' =' =' d' >' e' =' d' =' =' ?' ='

H2) =' =' =' =' >' c' >=' =' =' =' @' e' >e' >' =' >' d' >' =' >' ='

H.) ?' c' >' d' A' >>' @>' =' ?' >=' >>' >c' ?=' =' >f' d' ?d' =' A' =' ='

HS) =' =' =' =' =' =' =' =' =' =' >' =' =' =' =' =' =' =' =' =' ='

H;) =' =' >' =' d' c' >A' =' >' g' A' A' e' >' f' g' >>' >' =' >' ='

H;!.) =' =' >' =' d' c' >@' =' =' d' @' @' d' >' g' c' g' >' =' >' ='

H4) =' =' =' A' @' =' A' >' =' @' @' c' A' >' c' c' A' @' =' =' ='

;2) c' >@' =' e' ?' >' >@' =' =' A' A' ?>' >e' >' c' >A' ?d' >' e' =' ='

;.) A' c' =' d' A' g' ?A' =' A' >>' A' >c' ?@' ?' >A' >A' @f' @' =' >' ='

;!) ?' >' =' =' >' >' @' =' =' d' >' ?' e' =' g' g' >f' =' =' =' ='

;V.) >' =' =' =' >' >' @' =' =' A' >' >' e' =' c' d' >e' >' =' =' ='

;;) A' @' >' c' ?' @' >?' =' ?' >' =' ?=' f' =' g' >e' >A' ?' >' =' ='

;4) A' ?' =' >>' g' d' @?' =' @' e' @' ?d' @@' >' ??' >f' c@' e' g' ?' ='

$J) =' =' =' =' =' =' >' =' =' @' ?' >' >?' =' @' >' d' =' =' >' ='

,B) >@' =' =' =' =' =' =' =' =' =' =' A' @' =' ?' @' ?' =' =' =' ='

V.) ?' =' =' =' =' =' =' =' >' ?' >' =' >' =' ?' @' >' =' =' =' ='

VU) =' =' =' =' =' >' c' =' >' =' =' f' >>' =' =' =' d' >' =' =' ='

Matrix SBE 678%9&B' ?B' @D' T1' /S' MF' H2' H.' HS' H;' H;!.' H4' ;2' ;.' ;!' ;V.' ;;' ;4' $J' ,B' V.' VU'

?B) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

@D) @' =' =' =' =' A' @' =' =' >' >' =' =' =' =' =' =' =' c' =' ='

T1) =' =' =' =' =' >' g' ?' ?' A' A' @' =' =' >' =' A' =' =' =' ='

/S) =' >' =' =' =' @' >?' =' =' ?' =' =' =' =' =' =' @' =' =' ?' ='

MF) =' =' =' =' =' =' c' =' >' ?' A' =' A' =' =' >' f' =' =' =' ='

H2) =' d' ?' >' ?' f' ?g' >' A' >A' ??' c' A' =' ?' >g' >c' =' >' @' ='

H.) d' d' c' e' @' A@' fg' ?' e' @?' A=' =' f' =' =' =' =' =' ?' e' ='

HS) =' =' =' =' =' >' ?' =' =' @' @' A' =' =' >' =' c' =' =' >' ='

H;) @' =' ?' >' A' ?=' ?f' >' c' @g' ?c' ?' @' =' =' c' ?' >' =' ?' ='

H;!.) @' =' ?' >' @' >g' @e' >' =' @d' ?@' ?' ?' =' =' >' d' >' =' >' ='

H4) @' @' ?' ?' @' >@' Ae' ?' @' ?A' ?e' @' ?' >' =' >' @' =' >' >' ='

;2) ?' A' =' @' >' >' >=' =' =' >' @' c' @' =' >' @' ?' >' =' =' ='

;.) =' >' >' >' ?' c' f' >' =' ?' ?' =' @' =' =' c' =' >' =' >' ='

;!) =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' =' ='

;V.) =' =' =' =' =' =' =' =' =' =' =' ?' =' =' ?' =' f' =' =' =' ='

;;) =' =' =' ?' >' =' >?' =' =' ?' >' d' @' =' A' d' >d' =' >' =' ='

;4) A' ?' =' >=' =' ?' >c' =' ?' >' c' =' d' =' =' @' @' ?' @' c' ='

$J) =' =' =' =' >' =' >' =' =' =' =' >' =' =' =' =' =' =' =' =' ='

,B) f' =' =' =' =' =' ?' =' >' =' >' =' =' =' =' =' =' =' =' =' ='

V.) =' =' =' =' >' ?' A' =' =' @' A' A' =' =' ?' =' >' =' =' =' ='

VU) =' =' =' e' >' >' >=' =' =' =' >' =' ?' =' =' =' ' =' =' =' ='

) ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' '

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"&+"!"

'

Appendix I – SPSS output

SPSS All Data

ante * seq Crosstabulation

seq

DO GI NA NE NI NP NPF

E

NS PA PE PF PFE PP PS X9 XE d2 j3 q4 t1 Total

Count 0 0 2 6 0 3 3 2 0 1 0 0 1 0 8 0 0 0 0 0 26

Expecte

d Count

.2 .7 1.2 3.9 .1 2.0 1.7 1.6 2.3 2.3 .8 .7 1.7 3.9 .7 .2 .5 .6 .4 .4 26.0

DO

Std.

Residual

-.5 -.8 .7 1.0 -.3 .7 1.0 .4 -1.5 -.9 -.9 -.9 -.5 -2.0 9.1 -.4 -.7 -.8 -.6 -.7

Count 0 3 1 14 0 1 1 6 17 12 0 0 13 34 2 0 0 0 0 0 104

Expecte

d Count

1.0 2.9 5.0 15.7 .4 8.2 6.8 6.2 9.1 9.3 3.3 2.9 6.7 15.5 2.6 .8 1.9 2.3 1.7 1.8 104.0

GI

Std.

Residual

-

1.0

.1 -1.8 -.4 -.6 -2.5 -2.2 .0 2.6 .9 -1.8 -1.7 2.5 4.7 -.4 -.9 -

1.4

-

1.5

-

1.3

-

1.3

Count 1 4 14 56 1 25 22 13 3 14 1 1 3 8 2 2 5 3 2 0 180

Expecte

d Count

1.7 5.0 8.6 27.2 .7 14.2 11.7 10.8 15.7 16.1 5.8 5.0 11.5 26.8 4.5 1.4 3.4 3.9 2.9 3.1 180.0

NA

Std.

Residual

-.6 -.4 1.8 5.5 .4 2.9 3.0 .7 -3.2 -.5 -2.0 -1.8 -2.5 -3.6 -

1.2

.5 .9 -.5 -.5 -

1.8

Count 8 18 39 140 2 55 45 54 27 37 10 9 32 55 15 2 14 11 2 2 577

Expecte

d Count

5.5 16.0 27.5 87.2 2.2 45.4 37.5 34.6 50.3 51.7 18.5 16.2 36.9 86.0 14.

5

4.5 10.

8

12.

6

9.2 9.8 577.0

NE

Std.

Residual

1.0 .5 2.2 5.6 -.1 1.4 1.2 3.3 -3.3 -2.0 -2.0 -1.8 -.8 -3.3 .1 -

1.2

1.0 -.5 -

2.4

-

2.5

Count 2 0 1 2 0 1 1 3 0 1 0 0 0 0 0 0 0 0 0 0 11

Expecte

d Count

.1 .3 .5 1.7 .0 .9 .7 .7 1.0 1.0 .4 .3 .7 1.6 .3 .1 .2 .2 .2 .2 11.0

NI

Std.

Residual

5.8 -.6 .7 .3 -.2 .1 .3 2.9 -1.0 .0 -.6 -.6 -.8 -1.3 -.5 -.3 -.5 -.5 -.4 -.4

Count 3 0 6 11 0 6 5 3 0 2 0 1 2 6 1 1 0 1 0 1 49

Expecte

d Count

.5 1.4 2.3 7.4 .2 3.9 3.2 2.9 4.3 4.4 1.6 1.4 3.1 7.3 1.2 .4 .9 1.1 .8 .8 49.0

NP

Std.

Residual

3.7 -1.2 2.4 1.3 -.4 1.1 1.0 .0 -2.1 -1.1 -1.3 -.3 -.6 -.5 -.2 1.0 -

1.0

.0 -.9 .2

Count 4 2 14 42 3 45 43 28 8 16 8 6 3 12 0 5 2 5 4 0 250

Expecte

d Count

2.4 6.9 11.9 37.8 .9 19.7 16.3 15.0 21.8 22.4 8.0 7.0 16.0 37.3 6.3 1.9 4.7 5.5 4.0 4.3 250.0

NPFE

Std.

Residual

1.0 -1.9 .6 .7 2.1 5.7 6.6 3.4 -3.0 -1.4 .0 -.4 -3.2 -4.1 -

2.5

2.2 -

1.2

-.2 .0 -

2.1

Count 4 0 25 55 4 29 26 33 25 8 2 2 1 13 1 6 1 4 2 1 242

Expecte

d Count

2.3 6.7 11.6 36.6 .9 19.0 15.7 14.5 21.1 21.7 7.7 6.8 15.5 36.1 6.1 1.9 4.5 5.3 3.9 4.1 242.0

NS

Std.

Residual

1.1 -2.6 4.0 3.0 3.3 2.3 2.6 4.8 .8 -2.9 -2.1 -1.8 -3.7 -3.8 -

2.1

3.0 -

1.7

-.6 -

1.0

-

1.5

Count 0 15 9 25 0 8 5 8 46 30 8 7 41 64 19 0 12 3 3 11 314

Expecte

d Count

3.0 8.7 15.0 47.5 1.2 24.7 20.4 18.8 27.4 28.1 10.0 8.8 20.1 46.8 7.9 2.4 5.9 6.9 5.0 5.4 314.0

PA

Std.

Residual

-

1.7

2.1 -1.5 -3.3 -

1.1

-3.4 -3.4 -2.5 3.6 .4 -.6 -.6 4.7 2.5 4.0 -

1.6

2.5 -

1.5

-.9 2.4

ante

PE Count 0 9 13 30 0 15 10 7 31 41 18 17 26 72 22 1 2 19 17 3 353

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"',"!"

'

Expecte

d Count

3.4 9.8 16.8 53.4 1.3 27.8 23.0 21.2 30.8 31.6 11.3 9.9 22.6 52.6 8.8 2.7 6.6 7.7 5.6 6.0 353.0

Std.

Residual

-

1.8

-.3 -.9 -3.2 -

1.1

-2.4 -2.7 -3.1 .0 1.7 2.0 2.3 .7 2.7 4.4 -

1.0

-

1.8

4.1 4.8 -

1.2

Count 0 0 1 0 0 1 1 2 1 5 0 0 1 4 0 0 0 2 0 0 18

Expecte

d Count

.2 .5 .9 2.7 .1 1.4 1.2 1.1 1.6 1.6 .6 .5 1.2 2.7 .5 .1 .3 .4 .3 .3 18.0

PF

Std.

Residual

-.4 -.7 .2 -1.6 -.3 -.3 -.2 .9 -.5 2.7 -.8 -.7 -.1 .8 -.7 -.4 -.6 2.6 -.5 -.6

Count 4 5 14 54 3 49 45 30 13 23 10 7 15 47 5 6 2 13 5 3 353

Expecte

d Count

3.4 9.8 16.8 53.4 1.3 27.8 23.0 21.2 30.8 31.6 11.3 9.9 22.6 52.6 8.8 2.7 6.6 7.7 5.6 6.0 353.0

PFE

Std.

Residual

.3 -1.5 -.7 .1 1.5 4.0 4.6 1.9 -3.2 -1.5 -.4 -.9 -1.6 -.8 -

1.3

2.0 -

1.8

1.9 -.3 -

1.2

Count 9 0 4 29 0 12 6 8 31 34 15 13 40 44 3 0 0 1 1 5 255

Expecte

d Count

2.4 7.1 12.2 38.6 1.0 20.1 16.6 15.3 22.2 22.8 8.2 7.1 16.3 38.0 6.4 2.0 4.8 5.6 4.1 4.4 255.0

PP

Std.

Residual

4.2 -2.7 -2.3 -1.5 -

1.0

-1.8 -2.6 -1.9 1.9 2.3 2.4 2.2 5.9 1.0 -

1.3

-

1.4

-

2.2

-

1.9

-

1.5

.3

Count 1 39 15 55 0 19 11 10 59 79 39 37 41 127 11 2 13 13 21 3 595

Expecte

d Count

5.7 16.5 28.4 90.0 2.2 46.8 38.7 35.7 51.9 53.3 19.0 16.7 38.1 88.7 14.

9

4.6 11.

1

13.

0

9.5 10.

2

595.0

PS

Std.

Residual

-

2.0

5.5 -2.5 -3.7 -

1.5

-4.1 -4.5 -4.3 1.0 3.5 4.6 5.0 .5 4.1 -

1.0

-

1.2

.6 .0 3.7 -

2.2

Count 0 1 4 6 1 2 2 1 0 1 1 0 0 4 0 0 0 3 2 0 28

Expecte

d Count

.3 .8 1.3 4.2 .1 2.2 1.8 1.7 2.4 2.5 .9 .8 1.8 4.2 .7 .2 .5 .6 .4 .5 28.0

XE

Std.

Residual

-.5 .3 2.3 .9 2.8 -.1 .1 -.5 -1.6 -1.0 .1 -.9 -1.3 .0 -.8 -.5 -.7 3.1 2.3 -.7

Count 0 0 0 8 0 9 4 3 12 5 3 2 7 9 0 2 3 2 0 35 104

Expecte

d Count

1.0 2.9 5.0 15.7 .4 8.2 6.8 6.2 9.1 9.3 3.3 2.9 6.7 15.5 2.6 .8 1.9 2.3 1.7 1.8 104.0

a1

Std.

Residual

-

1.0

-1.7 -2.2 -1.9 -.6 .3 -1.1 -1.3 1.0 -1.4 -.2 -.5 .1 -1.7 -

1.6

1.3 .8 -.2 -

1.3

24.

9

Count 0 3 6 12 0 0 0 3 28 10 2 0 3 7 1 0 0 2 0 0 77

Expecte

d Count

.7 2.1 3.7 11.6 .3 6.1 5.0 4.6 6.7 6.9 2.5 2.2 4.9 11.5 1.9 .6 1.4 1.7 1.2 1.3 77.0

d2

Std.

Residual

-.9 .6 1.2 .1 -.5 -2.5 -2.2 -.8 8.2 1.2 -.3 -1.5 -.9 -1.3 -.7 -.8 -

1.2

.2 -

1.1

-

1.1

Count 0 4 3 9 0 11 10 7 6 6 3 2 3 23 1 1 0 0 1 0 90

Expecte

d Count

.9 2.5 4.3 13.6 .3 7.1 5.9 5.4 7.8 8.1 2.9 2.5 5.8 13.4 2.3 .7 1.7 2.0 1.4 1.5 90.0

j3

Std.

Residual

-.9 1.0 -.6 -1.2 -.6 1.5 1.7 .7 -.7 -.7 .1 -.3 -1.2 2.6 -.8 .4 -

1.3

-

1.4

-.4 -

1.2

Count 0 1 1 5 0 4 4 3 4 11 0 1 2 16 3 1 0 0 0 0 56

Expecte

d Count

.5 1.6 2.7 8.5 .2 4.4 3.6 3.4 4.9 5.0 1.8 1.6 3.6 8.3 1.4 .4 1.0 1.2 .9 1.0 56.0

q4

Std.

Residual

-.7 -.4 -1.0 -1.2 -.5 -.2 .2 -.2 -.4 2.7 -1.3 -.5 -.8 2.6 1.3 .9 -

1.0

-

1.1

-.9 -

1.0

Count 0 0 7 8 0 0 0 1 16 0 0 0 6 14 0 0 16 0 0 0 68

Expecte

d Count

.7 1.9 3.2 10.3 .3 5.3 4.4 4.1 5.9 6.1 2.2 1.9 4.4 10.1 1.7 .5 1.3 1.5 1.1 1.2 68.0

t1

Std.

Residual

-.8 -1.4 2.1 -.7 -.5 -2.3 -2.1 -1.5 4.1 -2.5 -1.5 -1.4 .8 1.2 -

1.3

-.7 13.

1

-

1.2

-

1.0

-

1.1

Count 36 104 179 567 14 295 244 225 327 336 120 105 240 559 94 29 70 82 60 64 3750

Total

Expecte

d Count

36.

0

104.

0

179.

0

567.

0

14.

0

295.

0

244.

0

225.

0

327.

0

336.

0

120.

0

105.

0

240.

0

559.

0

94.

0

29.

0

70.

0

82.

0

60.

0

64.

0

3750.

0

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'#"!"

'

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 7.074E2 289 .000

Likelihood Ratio 517.322 289 .000

N of Valid Cases 891

a. 277 cells (85.5%) have expected count less than 5. The

minimum expected count is .01.

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'$"!"

'

SPSS for EGE

ante * seq Crosstabulation

Seq

GI NA NE NP NPFE NS PA PE PF PFE PP PS X9 XE d2 j3 q4 t1 Total

Count 2 0 0 0 0 1 6 5 0 0 6 13 2 0 0 0 0 0 35

Expected

Count

1.4 .2 2.0 .7 .5 .4 5.0 4.5 1.9 1.4 3.6 8.6 1.0 .2 .9 1.0 .8 .9 35.0

GI

Std.

Residual

.5 -.4 -1.4 -.8 -.7 .9 .5 .2 -1.4 -1.2 1.3 1.5 1.0 -.4 -.9 -1.0 -.9 -1.0

Count 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 4

Expected

Count

.2 .0 .2 .1 .1 .0 .6 .5 .2 .2 .4 1.0 .1 .0 .1 .1 .1 .1 4.0

NA

Std.

Residual

-.4 -.1 3.7 -.3 -.3 -.2 -.8 2.1 -.5 -.4 -.6 -1.0 -.3 -.1 -.3 -.3 -.3 -.3

Count 2 2 12 3 3 2 4 4 3 2 8 8 0 0 3 1 0 0 57

Expected

Count

2.2 .3 3.3 1.1 .9 .7 8.1 7.4 3.1 2.2 5.8 14.1 1.7 .3 1.4 1.7 1.3 1.5 57.0

NE

Std.

Residual

-.2 3.4 4.8 1.8 2.2 1.5 -1.4 -1.2 .0 -.2 .9 -1.6 -1.3 -.5 1.3 -.5 -1.2 -1.2

Count 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 3

Expected

Count

.1 .0 .2 .1 .0 .0 .4 .4 .2 .1 .3 .7 .1 .0 .1 .1 .1 .1 3.0

NP

Std.

Residual

-.3 -.1 2.0 -.2 -.2 -.2 -.7 -.6 -.4 2.6 -.6 .3 -.3 -.1 -.3 -.3 -.3 -.3

Count 0 0 0 1 1 1 4 3 1 1 0 3 0 0 0 1 0 0 16

Expected

Count

.6 .1 .9 .3 .3 .2 2.3 2.1 .9 .6 1.6 4.0 .5 .1 .4 .5 .4 .4 16.0

NPFE

Std.

Residual

-.8 -.3 -1.0 1.3 1.5 1.8 1.1 .7 .1 .5 -1.3 -.5 -.7 -.3 -.6 .8 -.6 -.6

Count 0 0 4 0 0 2 1 2 0 0 0 0 0 1 0 0 0 0 10

Expected

Count

.4 .0 .6 .2 .2 .1 1.4 1.3 .5 .4 1.0 2.5 .3 .0 .2 .3 .2 .3 10.0

NS

Std.

Residual

-.6 -.2 4.5 -.4 -.4 5.3 -.4 .6 -.7 -.6 -1.0 -1.6 -.5 4.5 -.5 -.5 -.5 -.5

Count 7 1 5 0 0 1 22 10 5 5 19 32 6 0 5 2 2 6 128

Expected

Count

5.0 .6 7.5 2.4 2.0 1.6 18.2 16.5 6.9 5.0 13.1 31.6 3.7 .6 3.2 3.7 3.0 3.3 128.0

PA

Std.

Residual

.9 .6 -.9 -1.6 -1.4 -.5 .9 -1.6 -.7 .0 1.6 .1 1.2 -.8 1.0 -.9 -.6 1.5

Count 5 1 1 4 2 1 10 15 7 6 14 33 8 0 1 9 5 0 122

Expected

Count

4.8 .5 7.1 2.3 1.9 1.5 17.4 15.7 6.6 4.8 12.5 30.1 3.6 .5 3.0 3.6 2.9 3.1 122.0

PE

Std.

Residual

.1 .6 -2.3 1.1 .1 -.4 -1.8 -.2 .2 .6 .4 .5 2.4 -.7 -1.2 2.9 1.3 -1.8

Count 0 0 0 0 0 0 0 3 0 0 1 3 0 0 0 1 0 0 8

Expected

Count

.3 .0 .5 .2 .1 .1 1.1 1.0 .4 .3 .8 2.0 .2 .0 .2 .2 .2 .2 8.0

PF

Std.

Residual

-.6 -.2 -.7 -.4 -.4 -.3 -1.1 1.9 -.7 -.6 .2 .7 -.5 -.2 -.4 1.6 -.4 -.5

Count 1 0 6 0 0 2 14 15 7 0 16 22 0 0 6 2 0 2 93

Expected

Count

3.7 .4 5.4 1.8 1.5 1.1 13.3 12.0 5.0 3.7 9.5 23.0 2.7 .4 2.3 2.7 2.2 2.4 93.0

ante

PP

Std.

Residual

-1.4 -.6 .2 -1.3 -1.2 .8 .2 .9 .9 -1.9 2.1 -.2 -1.6 -.6 2.4 -.4 -1.5 -.3

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'%"!"

'

Count 16 0 14 3 2 0 30 38 18 17 18 54 4 1 4 4 12 1 236

Expected

Count

9.3 1.1 13.8 4.5 3.7 2.9 33.6 30.5 12.7 9.3 24.1 58.3 6.9 1.1 5.8 6.9 5.6 6.1 236.0

PS

Std.

Residual

2.2 -

1.0

.1 -.7 -.9 -1.7 -.6 1.4 1.5 2.5 -1.2 -.6 -1.1 .0 -.8 -1.1 2.7 -2.1

Count 2 0 1 2 2 1 7 6 2 1 2 20 3 1 0 3 2 1 56

Expected

Count

2.2 .3 3.3 1.1 .9 .7 8.0 7.2 3.0 2.2 5.7 13.8 1.6 .3 1.4 1.6 1.3 1.4 56.0

PXE

Std.

Residual

-.1 -.5 -1.3 .9 1.2 .4 -.3 -.5 -.6 -.8 -1.6 1.7 1.1 1.5 -1.2 1.1 .6 -.4

Count 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 3

Expected

Count

.1 .0 .2 .1 .0 .0 .4 .4 .2 .1 .3 .7 .1 .0 .1 .1 .1 .1 3.0

XE

Std.

Residual

-.3 -.1 -.4 -.2 -.2 -.2 -.7 -.6 2.1 -.3 -.6 .3 -.3 -.1 -.3 3.1 -.3 -.3

Count 0 0 0 1 1 0 5 1 1 1 3 1 0 0 0 1 0 13 28

Expected

Count

1.1 .1 1.6 .5 .4 .3 4.0 3.6 1.5 1.1 2.9 6.9 .8 .1 .7 .8 .7 .7 28.0

a1

Std.

Residual

-1.0 -.4 -1.3 .6 .8 -.6 .5 -1.4 -.4 .0 .1 -2.2 -.9 -.4 -.8 .2 -.8 14.4

Count 0 0 1 0 0 0 11 4 1 0 0 3 1 0 0 1 0 0 22

Expected

Count

.9 .1 1.3 .4 .3 .3 3.1 2.8 1.2 .9 2.2 5.4 .6 .1 .5 .6 .5 .6 22.0

d2

Std.

Residual

-.9 -.3 -.3 -.6 -.6 -.5 4.4 .7 -.2 -.9 -1.5 -1.0 .4 -.3 -.7 .4 -.7 -.8

Count 0 0 2 1 1 0 3 0 2 1 0 16 0 0 0 0 0 0 26

Expected

Count

1.0 .1 1.5 .5 .4 .3 3.7 3.4 1.4 1.0 2.7 6.4 .8 .1 .6 .8 .6 .7 26.0

j3

Std.

Residual

-1.0 -.3 .4 .7 .9 -.6 -.4 -1.8 .5 .0 -1.6 3.8 -.9 -.3 -.8 -.9 -.8 -.8

Count 0 0 1 2 2 0 2 7 0 0 0 6 2 1 0 0 0 0 23

Expected

Count

.9 .1 1.3 .4 .4 .3 3.3 3.0 1.2 .9 2.3 5.7 .7 .1 .6 .7 .5 .6 23.0

q4

Std.

Residual

-1.0 -.3 -.3 2.4 2.7 -.5 -.7 2.3 -1.1 -1.0 -1.5 .1 1.6 2.8 -.8 -.8 -.7 -.8

Count 0 0 2 0 0 0 8 0 0 0 4 4 0 0 3 0 0 0 21

Expected

Count

.8 .1 1.2 .4 .3 .3 3.0 2.7 1.1 .8 2.1 5.2 .6 .1 .5 .6 .5 .5 21.0

t1

Std.

Residual

-.9 -.3 .7 -.6 -.6 -.5 2.9 -1.6 -1.1 -.9 1.3 -.5 -.8 -.3 3.4 -.8 -.7 -.7

Count 35 4 52 17 14 11 127 115 48 35 91 220 26 4 22 26 21 23 891

Total

Expected

Count

35.0 4.0 52.0 17.0 14.0 11.0 127.0 115.0 48.0 35.0 91.0 220.0 26.0 4.0 22.0 26.0 21.0 23.0 891.0

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 7.074E2 289 .000

Likelihood Ratio 517.322 289 .000

N of Valid Cases 891

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'&"!"

'

SPSS for SBE

ante * seq Crosstabulation

seq

DO GI NA NE NI NP NPFE NS PA PE PFE PP PS X9 XE d2 j3 q4 t1 Total

Count 0 0 2 5 0 2 2 2 0 1 0 0 0 0 0 0 0 0 0 14

Expected

Count

.3 .3 1.6 3.1 .2 1.7 1.6 1.7 .5 .4 .2 .6 .7 .3 .2 .2 .3 .0 .2 14.0

DO

Std.

Residual

-.6 -.5 .3 1.1 -.5 .3 .3 .3 -.7 1.0 -.4 -.8 -.9 -.5 -.5 -.4 -.5 -.2 -.4

Count 0 0 1 8 0 1 1 2 3 1 0 2 10 8 0 0 0 0 0 37

Expected

Count

.9 .7 4.1 8.3 .6 4.4 4.2 4.4 1.2 1.0 .4 1.7 1.9 .7 .6 .5 .8 .1 .4 37.0

GI

Std.

Residual

-.9 -.8 -1.5 .0 -.8 -1.6 -1.6 -1.1 1.6 .0 -.6 .3 5.8 8.7 -.8 -.7 -.9 -.3 -.6

Count 1 3 9 43 1 20 17 13 1 5 0 0 2 1 2 4 0 0 0 122

Expected

Count

2.8 2.3 13.7 27.3 2.0 14.4 13.9 14.5 4.1 3.4 1.3 5.5 6.4 2.3 2.1 1.7 2.6 .3 1.3 122.0

NA

Std.

Residual

-1.1 .4 -1.3 3.0 -.7 1.5 .8 -.4 -1.5 .8 -1.1 -2.3 -1.7 -.9 .0 1.7 -1.6 -.6 -1.1

Count 7 12 27 97 2 29 38 48 10 9 0 12 15 10 4 3 5 1 2 331

Expected

Count

7.7 6.3 37.1 74.0 5.5 39.0 37.7 39.3 11.0 9.3 3.6 14.8 17.3 6.3 5.8 4.7 7.1 .8 3.6 331.0

NE

Std.

Residual

-.3 2.3 -1.7 2.7 -1.5 -1.6 .1 1.4 -.3 -.1 -1.9 -.7 -.6 1.5 -.7 -.8 -.8 .2 -.8

Count 2 0 1 2 0 1 1 2 0 1 0 0 0 0 0 0 0 0 0 10

Expected

Count

.2 .2 1.1 2.2 .2 1.2 1.1 1.2 .3 .3 .1 .4 .5 .2 .2 .1 .2 .0 .1 10.0

NI

Std.

Residual

3.7 -.4 -.1 -.2 -.4 -.2 -.1 .7 -.6 1.4 -.3 -.7 -.7 -.4 -.4 -.4 -.5 -.2 -.3

Count 2 0 4 8 0 5 0 3 0 0 0 0 2 0 0 0 1 0 1 26

Expected

Count

.6 .5 2.9 5.8 .4 3.1 3.0 3.1 .9 .7 .3 1.2 1.4 .5 .5 .4 .6 .1 .3 26.0

NP

Std.

Residual

1.8 -.7 .6 .9 -.7 1.1 -1.7 .0 -.9 -.9 -.5 -1.1 .5 -.7 -.7 -.6 .6 -.3 1.4

Count 4 2 14 32 3 37 36 24 1 2 0 2 1 0 3 1 2 0 0 164

Expected

Count

3.8 3.1 18.4 36.6 2.7 19.3 18.7 19.5 5.4 4.6 1.8 7.4 8.6 3.1 2.9 2.3 3.5 .4 1.8 164.0

NPFE

Std.

Residual

.1 -.6 -1.0 -.8 .2 4.0 4.0 1.0 -1.9 -1.2 -1.3 -2.0 -2.6 -1.8 .1 -.9 -.8 -.6 -1.3

Count 4 0 22 40 3 25 23 28 3 2 0 1 5 1 4 1 4 0 1 167

Expected

Count

3.9 3.2 18.7 37.3 2.8 19.7 19.0 19.8 5.5 4.7 1.8 7.5 8.7 3.2 2.9 2.4 3.6 .4 1.8 167.0

NS

Std.

Residual

.1 -1.8 .8 .4 .1 1.2 .9 1.8 -1.1 -1.3 -1.3 -2.4 -1.3 -1.2 .6 -.9 .2 -.6 -.6

Count 3 0 5 0 4 2 2 3 5 0 2 6 0 0 4 0 0 1 0 37

Expected

Count

.9 .7 4.1 8.3 .6 4.4 4.2 4.4 1.2 1.0 .4 1.7 1.9 .7 .6 .5 .8 .1 .4 37.0

PA

Std.

Residual

2.3 -.8 .4 -2.9 4.3 -1.1 -1.1 -.7 3.4 -1.0 2.5 3.4 -1.4 -.8 4.2 -.7 -.9 3.0 -.6

Count 0 0 4 9 0 3 2 2 3 3 0 3 6 2 0 0 4 0 0 41

Expected

Count

1.0 .8 4.6 9.2 .7 4.8 4.7 4.9 1.4 1.2 .4 1.8 2.1 .8 .7 .6 .9 .1 .4 41.0

ante

PE

Std.

Residual

-1.0 -.9 -.3 .0 -.8 -.8 -1.2 -1.3 1.4 1.7 -.7 .9 2.6 1.4 -.8 -.8 3.3 -.3 -.7

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"''"!"

'

Count 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1

Expected

Count

.0 .0 .1 .2 .0 .1 .1 .1 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 1.0

PF

Std.

Residual

-.2 -.1 -.3 -.5 -.1 -.3 -.3 2.6 -.2 -.2 -.1 -.2 -.2 -.1 -.1 -.1 -.1 .0 -.1

Count 0 0 17 0 0 5 1 1 3 5 0 6 3 0 0 0 1 0 0 42

Expected

Count

1.0 .8 4.7 9.4 .7 5.0 4.8 5.0 1.4 1.2 .5 1.9 2.2 .8 .7 .6 .9 .1 .5 42.0

PP

Std.

Residual

-1.0 -.9 5.7 -3.1 -.8 .0 -1.7 -1.8 1.4 3.5 -.7 3.0 .5 -.9 -.9 -.8 .1 -.3 -.7

Count 4 3 15 0 5 2 6 3 2 0 9 16 3 0 1 0 9 0 0 78

Expected

Count

1.8 1.5 8.7 17.4 1.3 9.2 8.9 9.3 2.6 2.2 .8 3.5 4.1 1.5 1.4 1.1 1.7 .2 .8 78.0

PS

Std.

Residual

1.6 1.2 2.1 -4.2 3.3 -2.4 -1.0 -2.1 -.4 -1.5 8.9 6.7 -.5 -1.2 -.3 -1.0 5.6 -.4 -.9

Count 1 0 2 0 1 0 0 0 1 0 2 4 0 0 2 0 0 0 0 13

Expected

Count

.3 .2 1.5 2.9 .2 1.5 1.5 1.5 .4 .4 .1 .6 .7 .2 .2 .2 .3 .0 .1 13.0

PXE

Std.

Residual

1.3 -.5 .4 -1.7 1.7 -1.2 -1.2 -1.2 .9 -.6 5.0 4.5 -.8 -.5 3.7 -.4 -.5 -.2 -.4

Count 0 2 3 8 1 2 1 1 0 1 0 0 5 0 0 0 0 0 0 24

Expected

Count

.6 .5 2.7 5.4 .4 2.8 2.7 2.9 .8 .7 .3 1.1 1.3 .5 .4 .3 .5 .1 .3 24.0

XE

Std.

Residual

-.7 2.3 .2 1.1 1.0 -.5 -1.0 -1.1 -.9 .4 -.5 -1.0 3.3 -.7 -.6 -.6 -.7 -.2 -.5

Count 0 0 0 6 0 3 3 3 2 0 0 0 4 0 0 3 0 0 9 33

Expected

Count

.8 .6 3.7 7.4 .5 3.9 3.8 3.9 1.1 .9 .4 1.5 1.7 .6 .6 .5 .7 .1 .4 33.0

a1

Std.

Residual

-.9 -.8 -1.9 -.5 -.7 -.5 -.4 -.5 .9 -1.0 -.6 -1.2 1.7 -.8 -.8 3.7 -.8 -.3 14.5

Count 0 1 6 6 0 0 0 3 4 1 0 0 2 0 0 0 0 0 0 23

Expected

Count

.5 .4 2.6 5.1 .4 2.7 2.6 2.7 .8 .6 .2 1.0 1.2 .4 .4 .3 .5 .1 .2 23.0

d2

Std.

Residual

-.7 .8 2.1 .4 -.6 -1.6 -1.6 .2 3.7 .4 -.5 -1.0 .7 -.7 -.6 -.6 -.7 -.2 -.5

Count 0 0 2 3 0 4 3 3 1 2 0 1 0 1 1 0 0 1 0 22

Expected

Count

.5 .4 2.5 4.9 .4 2.6 2.5 2.6 .7 .6 .2 1.0 1.2 .4 .4 .3 .5 .1 .2 22.0

j3

Std.

Residual

-.7 -.6 -.3 -.9 -.6 .9 .3 .2 .3 1.7 -.5 .0 -1.1 .9 1.0 -.6 -.7 4.0 -.5

Count 0 0 0 0 0 1 1 0 1 1 0 0 2 0 0 0 0 0 0 6

Expected

Count

.1 .1 .7 1.3 .1 .7 .7 .7 .2 .2 .1 .3 .3 .1 .1 .1 .1 .0 .1 6.0

q4

Std.

Residual

-.4 -.3 -.8 -1.2 -.3 .3 .4 -.8 1.8 2.0 -.3 -.5 3.0 -.3 -.3 -.3 -.4 -.1 -.3

Count 0 0 1 2 0 0 0 1 0 0 0 1 3 0 0 5 0 0 0 13

Expected

Count

.3 .2 1.5 2.9 .2 1.5 1.5 1.5 .4 .4 .1 .6 .7 .2 .2 .2 .3 .0 .1 13.0

t1

Std.

Residual

-.5 -.5 -.4 -.5 -.5 -1.2 -1.2 -.4 -.7 -.6 -.4 .5 2.8 -.5 -.5 11.2 -.5 -.2 -.4

Count 28 23 135 269 20 142 137 143 40 34 13 54 63 23 21 17 26 3 13 1204

Total

Expected

Count

28.0 23.0 135.0 269.0 20.0 142.0 137.0 143.0 40.0 34.0 13.0 54.0 63.0 23.0 21.0 17.0 26.0 3.0 13.0 1204.0

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'("!"

'

Chi-Square Tests

Value df Asymp. Sig. (2-

sided) Pearson Chi-Square 1.299E3 342 .000

Likelihood Ratio 854.220 342 .000

N of Valid Cases 1204

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"')"!"

'

SPSS for OE

ante * seq Crosstabulation

seq

DO GI NA NE NI NP NPFE NS PA PE PF PFE PP PS X9 XE d2 j3 q4 t1 Total

Count 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 4

Expected

Count

.0 .1 .2 .5 .0 .2 .2 .1 .4 .5 .2 .1 .3 .7 .1 .0 .1 .1 .1 .1 4.0

DO

Std.

Residual

-.1 -.3 -.4 .7 .0 1.6 1.9 -.4 -.6 -.7 -.4 -.4 1.3 -.8 -.3 -.2 -.3 -.3 -.3 -.3

Count 0 0 0 6 0 0 0 4 8 6 0 0 5 11 0 0 0 0 0 0 40

Expected

Count

.2 1.1 1.6 4.9 .0 2.3 1.8 1.3 4.1 5.1 1.6 1.4 2.9 7.0 1.0 .4 .8 1.0 .8 .8 40.0

GI

Std.

Residual

-.4 -1.1 -1.2 .5 -.2 -1.5 -1.4 2.4 2.0 .4 -1.3 -1.2 1.2 1.5 -1.0 -.6 -.9 -1.0 -.9 -.9

Count 0 1 5 11 0 5 5 0 1 7 1 1 3 6 1 0 1 3 0 0 51

Expected

Count

.2 1.4 2.0 6.2 .0 2.9 2.3 1.6 5.2 6.5 2.1 1.8 3.7 8.9 1.2 .5 1.1 1.3 1.1 1.0 51.0

NA

Std.

Residual

-.5 -.4 2.1 1.9 -.2 1.2 1.7 -1.3 -1.8 .2 -.8 -.6 -.4 -1.0 -.2 -.7 .0 1.6 -1.0 -1.0

Count 1 4 10 31 0 14 13 4 13 24 3 3 12 32 5 0 8 5 1 0 183

Expected

Count

.8 5.2 7.1 22.3 .1 10.3 8.4 5.8 18.6 23.2 7.5 6.5 13.4 31.9 4.4 1.7 3.9 4.5 3.9 3.5 183.0

NE

Std.

Residual

.3 -.5 1.1 1.8 -.4 1.1 1.6 -.8 -1.3 .2 -1.6 -1.4 -.4 .0 .3 -1.3 2.1 .2 -1.5 -1.9

Count 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1

Expected

Count

.0 .0 .0 .1 .0 .1 .0 .0 .1 .1 .0 .0 .1 .2 .0 .0 .0 .0 .0 .0 1.0

NI

Std.

Residual

.0 -.2 -.2 -.3 .0 -.2 -.2 5.4 -.3 -.4 -.2 -.2 -.3 -.4 -.2 .0 -.1 -.2 -.1 -.1

Count 1 0 0 2 0 1 0 0 0 4 0 0 2 3 1 1 0 0 0 0 15

Expected

Count

.1 .4 .6 1.8 .0 .8 .7 .5 1.5 1.9 .6 .5 1.1 2.6 .4 .1 .3 .4 .3 .3 15.0

NP

Std.

Residual

3.7 -.7 -.8 .1 -.1 .2 -.8 -.7 -1.2 1.5 -.8 -.7 .9 .2 1.1 2.3 -.6 -.6 -.6 -.5

Count 0 0 0 10 0 7 6 3 4 11 6 4 1 8 0 2 1 2 3 0 68

Expected

Count

.3 1.9 2.6 8.3 .0 3.8 3.1 2.2 6.9 8.6 2.8 2.4 5.0 11.9 1.6 .6 1.4 1.7 1.4 1.3 68.0

NPFE

Std.

Residual

-.5 -1.4 -1.6 .6 -.2 1.6 1.6 .6 -1.1 .8 1.9 1.0 -1.8 -1.1 -1.3 1.7 -.4 .2 1.3 -1.1

Count 0 0 3 11 1 4 3 3 4 4 1 1 0 3 0 1 0 0 2 0 41

Expected

Count

.2 1.2 1.6 5.0 .0 2.3 1.9 1.3 4.2 5.2 1.7 1.4 3.0 7.1 1.0 .4 .9 1.0 .9 .8 41.0

NS

Std.

Residual

-.4 -1.1 1.1 2.7 5.7 1.1 .8 1.5 .0 -.5 -.5 -.4 -1.7 -1.6 -1.0 1.0 -.9 -1.0 1.2 -.9

Count 0 5 8 15 0 4 3 5 21 15 2 1 20 26 9 0 5 0 1 4 144

Expected

Count

.6 4.1 5.6 17.6 .1 8.1 6.6 4.6 14.6 18.3 5.9 5.1 10.6 25.1 3.5 1.3 3.0 3.6 3.0 2.7 144.0

PA

Std.

Residual

-.8 .5 1.0 -.6 -.3 -1.4 -1.4 .2 1.7 -.8 -1.6 -1.8 2.9 .2 3.0 -1.1 1.1 -1.9 -1.2 .8

Count 0 4 18 20 0 8 6 4 18 23 8 8 9 33 11 1 1 6 12 3 193

Expected

Count

.8 5.4 7.5 23.6 .1 10.9 8.9 6.1 19.6 24.5 7.9 6.8 14.2 33.6 4.6 1.8 4.1 4.8 4.1 3.7 193.0

ante

PE

Std.

Residual

-.9 -.6 3.8 -.7 -.4 -.9 -1.0 -.9 -.4 -.3 .0 .5 -1.4 -.1 3.0 -.6 -1.5 .6 3.9 -.4

!"#$%&'("')%$*+,-$(./'01+'+23+,$+%4+'"5'6(78+%(-'9+:*$%&';"#+<'

!"'*"!"

'

Count 0 0 1 0 0 1 1 1 1 2 0 0 0 1 0 0 0 1 0 0 9

Expected

Count

.0 .3 .3 1.1 .0 .5 .4 .3 .9 1.1 .4 .3 .7 1.6 .2 .1 .2 .2 .2 .2 9.0

PF

Std.

Residual

-.2 -.5 1.1 -1.0 .0 .7 .9 1.3 .1 .8 -.6 -.6 -.8 -.5 -.5 -.3 -.4 1.6 -.4 -.4

Count 3 0 1 6 0 7 5 5 14 14 7 6 18 19 0 3 0 0 1 3 112

Expected

Count

.5 3.2 4.3 13.7 .1 6.3 5.1 3.6 11.4 14.2 4.6 4.0 8.2 19.5 2.7 1.0 2.4 2.8 2.4 2.1 112.0

PP

Std.

Residual

3.7 -1.8 -1.6 -2.1 -.3 .3 .0 .8 .8 .0 1.1 1.0 3.4 -.1 -1.6 1.9 -1.5 -1.7 -.9 .6

Count 1 19 6 26 0 11 7 4 26 39 19 18 14 53 6 1 5 6 6 2 269

Expected

Count

1.1 7.6 10.4 32.8 .2 15.2 12.3 8.5 27.3 34.2 11.0 9.5 19.7 46.9 6.5 2.5 5.7 6.6 5.7 5.1 269.0

PS

Std.

Residual

-.1 4.1 -1.4 -1.2 -.4 -1.1 -1.5 -1.6 -.3 .8 2.4 2.8 -1.3 .9 -.2 -.9 -.3 -.2 .1 -1.4

Count 0 0 0 19 0 9 7 5 5 14 7 5 7 22 0 2 1 8 3 2 116

Expected

Count

.5 3.3 4.5 14.2 .1 6.5 5.3 3.7 11.8 14.7 4.7 4.1 8.5 20.2 2.8 1.1 2.5 2.9 2.5 2.2 116.0

PXE

Std.

Residual

-.7 -1.8 -2.1 1.3 -.3 1.0 .7 .7 -2.0 -.2 1.0 .4 -.5 .4 -1.7 .9 -.9 3.0 .3 -.1

Count 0 0 1 0 0 1 1 0 0 1 0 0 0 2 0 0 0 2 1 0 9

Expected

Count

.0 .3 .3 1.1 .0 .5 .4 .3 .9 1.1 .4 .3 .7 1.6 .2 .1 .2 .2 .2 .2 9.0

XE

Std.

Residual

-.2 -.5 1.1 -1.0 .0 .7 .9 -.5 -1.0 -.1 -.6 -.6 -.8 .3 -.5 -.3 -.4 3.8 1.9 -.4

Count 0 0 0 2 0 0 0 0 5 4 2 1 4 4 0 2 0 1 0 13 38

Expected

Count

.2 1.1 1.5 4.6 .0 2.1 1.7 1.2 3.9 4.8 1.6 1.3 2.8 6.6 .9 .3 .8 .9 .8 .7 38.0

a1

Std.

Residual

-.4 -1.0 -1.2 -1.2 -.2 -1.5 -1.3 -1.1 .6 -.4 .4 -.3 .7 -1.0 -1.0 2.8 -.9 .1 -.9 14.4

Count 0 2 0 5 0 0 0 0 13 5 1 0 3 2 0 0 0 1 0 0 32

Expected

Count

.1 .9 1.2 3.9 .0 1.8 1.5 1.0 3.3 4.1 1.3 1.1 2.3 5.6 .8 .3 .7 .8 .7 .6 32.0

d2

Std.

Residual

-.4 1.2 -1.1 .6 -.2 -1.3 -1.2 -1.0 5.4 .5 -.3 -1.1 .4 -1.5 -.9 -.5 -.8 .2 -.8 -.8

Count 0 4 1 4 0 6 6 3 2 4 1 1 2 7 0 0 0 0 0 0 41

Expected

Count

.2 1.2 1.6 5.0 .0 2.3 1.9 1.3 4.2 5.2 1.7 1.4 3.0 7.1 1.0 .4 .9 1.0 .9 .8 41.0

j3

Std.

Residual

-.4 2.6 -.5 -.4 -.2 2.4 3.0 1.5 -1.1 -.5 -.5 -.4 -.6 .0 -1.0 -.6 -.9 -1.0 -.9 -.9

Count 0 1 1 0 0 1 1 3 1 3 0 1 2 8 1 0 0 0 0 0 23

Expected

Count

.1 .6 .9 2.8 .0 1.3 1.1 .7 2.3 2.9 .9 .8 1.7 4.0 .6 .2 .5 .6 .5 .4 23.0

q4

Std.

Residual

-.3 .4 .1 -1.7 -.1 -.3 .0 2.7 -.9 .0 -1.0 .2 .2 2.0 .6 -.5 -.7 -.8 -.7 -.7

Count 0 0 0 4 0 0 0 0 8 0 0 0 1 7 0 0 8 0 0 0 28

Expected

Count

.1 .8 1.1 3.4 .0 1.6 1.3 .9 2.8 3.6 1.1 1.0 2.1 4.9 .7 .3 .6 .7 .6 .5 28.0

t1

Std.

Residual

-.3 -.9 -1.0 .3 -.1 -1.3 -1.1 -.9 3.1 -1.9 -1.1 -1.0 -.7 1.0 -.8 -.5 9.6 -.8 -.8 -.7

Count 6 40 55 173 1 80 65 45 144 180 58 50 104 247 34 13 30 35 30 27 1417

Total

Expected

Count

6.0 40.0 55.0 173.0 1.0 80.0 65.0 45.0 144.0 180.0 58.0 50.0 104.0 247.0 34.0 13.0 30.0 35.0 30.0 27.0 1417.0

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Chi-Square Tests

Value df Asymp. Sig.

(2-sided) Pearson Chi-Square 9.383E2 361 .000

Likelihood Ratio 693.784 361 .000

N of Valid Cases 1417