ICCP 2017 SYMPOSIUM - AU Purepure.au.dk/portal/files/116548159/ICCP_2017_JohanneLomholt.pdficcp 2017...

AARHUS UNIVERSITY

DEPARTMENT OF PSYCHOLOGYAND BEHAVIOURAL SCIENCES

ICCP 2017SYMPOSIUM:

RISK FACTORS FOR AND TREATMENT OF SCHOOL ABSENTEEISM IN CHILDREN AND

ADOLESCENTS

29 JUNE 2017 ASSISTANT PROFESSOR

JOHANNE JEPPESEN LOMHOLT

AARHUS UNIVERSITY


DANISH SCHOOLCHILDREN WITH LOW ATTENDANCE

Investigating contextual and individual risk factors

Presenter: Johanne Jeppesen Lomholt

JOHANNE JEPPESEN LOMHOLTE-MAIL: [email protected]

ICCP 201729 JUNE 2017

AARHUS UNIVERSITY


THE ROLE OF SCHOOL• School plays a significant role infusing the values of the society and culture

• School is one of the main social agencies for contributing to the development of the “citizen”.

• School is:

• A setting for academic development

• Linguistic rewarding environment

• Platform for developing social relationships

Not attending school may affect these areas negative

BACKGROUND Aim Methods Results Conclusion


ICCP 201729 JUNE 2017

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THE DANISH SCHOOL SETTING• There is compulsory education in Denmark from grade 0-9 (age 6-

16)

• About 77 % of all schoolchildren are registered at the public schools

• If the child is registered at the school it is the school managements obligation to ensure that the child receive instructions.

• Mandatory for public schools in Denmark to register daily school attendance:

• Average school absence 2015/2016: 11.2 days/200 school days (5.6%)



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PREVALENCE OF SCHOOL ABSENTEEISM IN DENMARK

Absence is categorized as either:Legal

1. Due to medical illness or other accepted causes

2. Absence with permission from the head master

llegal

3. E.g. truancy

Illegal

Legal absence (illness)

Absence (permission)



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WHY FOCUSING ON SCHOOL ABSENTEEISM?

The majority of schoolchildren attend school regularly, why focusing on absenteeism?

Serious consequences:

• Predictor for school dropout

• Key factor for social, economic, and health issues in adulthood

• Peer-effect

Two monthly absence days is equivalent to one year of lost education after 9th grade.



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AARHUS UNIVERSITY


ABSENCE AND TESTSCORES

40

45

50

55

60

65

P30 P40 P50 P60 P70 P80 P90 P100

Ave

rage

tes

tpoi

nt (

1-10

0)

Deciles based on school absence aug.-dec. 2011

Association between test scores and school absence

Danish. 2. grade

Danish. 4. grade

Danish 6. grade

Danish 8. grade



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ABSENCE AND GPA

Average level of absence in 8th and 9th grade

GPA

in 9

thg

rad

e



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NUMBER OF STUDENTS IN UPPER SECONDARY EDUCATION

0

500

1000

1500

2000

2500

3000

3500

4000

P10 P20 P30 P40 P50 P60 P70 P80 P90 P100

Num

ber o

f stu

dent

s

Deciles based on school absence

Går på gymnasiel uddannelse

Går på erhvervsuddannelse

Går ikke på gymnasiel ellererhvervsuddannelse

Students attending upper secondary schools

Students attending vocational schools

Adolescents not attending any schools



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IMPROVED ABSENCE FROM 7TH TO 9TH GRADE STILL HAVE AN IMPACT ON THE FINAL EXAMINATION GRADES

Absence in 9th grade

0% ]0-5% ]5-10% ]10-20% >20%A

bse

nce

in 7

th g

rad

e 0% 8.43 7.99 7.09 6.39 3.23

]0-5% 7.75 7.50 6.82 5.94 3.88

]5-10% 6.70 7.01 6.59 5.04 4.74

]10-20% 6.53 6.08 5.70 5.05 3.88

>20% - 4.89 5.23 4.80 3.19



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HOW TO DEFINE ABSENCE?Different definition:

• Kearney: Problematic absence (includes complete and partial absence from school (25%) and/or school refusal behavior)

• Chronic absenteeism: missing >10% of school year

• Aarhus Municipality, Denmark: Attention demanding school absence (21% of students)

• Lack of consensus regarding when absence is problematic

Diverse literature of varying conceptualizations



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AARHUS UNIVERSITY


RISK FACTORS FOR SCHOOL ABSENTEEISM

School absence

Child factors

Parentfactors

Family factors

Peer factors

School factors

Communityfactors



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AARHUS UNIVERSITY



School absence

Child factors

Parentfactors

Family factors

Peer factors

School factors

Communityfactors

Parent and family factors• Family structure• Education level• Income• Chronic illness/disability

• Parents• Siblings

• Emotional disorders• Parental involvement in the

school

Child factors• Gender• Age• Anxiety• Depression• Oppositional behavior• Chronic illness• Pain• Sleep problems/fatigue• Extreme obesity

School factors• Teacher-student relationship• Teacher-parent relationship• Students feeling of being:

• Safe• Accepted• Respected

Peer factors• Bullying• Early peer rejection



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School absence

Child factors

Parentfactors

Family factors

Peer factors

School factors

Communityfactors

Child factors:•Anxiety

•Depression

•Oppositional behavior

•Chronic illness

Parent factors:• Unemployment

• Parental involvement in school activities

Family factors:• Language

spoken at home



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AIM AND HYPOTHESESAIM:

To investigate the individual and relative importance of several domains of risk factors (individual, parental, family, peer, and school) for school absenteeism in a sample of children in elementary and lower secondary schools in Denmark.

Hypotheses:

1. Most risk factors will be associated with excessive school absenteeism.

2. When analyzed together, main predictors will be parental employment status, chronic illness, and externalizing and internalizing behavior.

Background AIM Methods Results Conclusion


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DESIGNCross-sectional study

I. Survey with students, parents, and teachers as informants

II. Absence data from the municipality

III. Register data, Statistic Denmark

Data collected in winter/spring 2014

Background Aim METHODS Results Conclusion


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AARHUS UNIVERSITY


PROCEDURE- TEACHERS

The class teacher completes the questionnaires during their working hours

1. A questionnaire for each student in the class

a) Strength and difficulties questionnaire (SDQ)

b) Questions about the child’s academic level

2. A questionnaire about the class

a) Wellbeing in the class

b) How the teacher managed absence



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AARHUS UNIVERSITY


PROCEDURE- PARENTS

One parent invited to complete questionnaire

at home. Distributed: intranet

Questionnaire:

I. Strength and difficulties questionnaire (SDQ)I. Child health

II. Anxiety



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PROCEDURE- STUDENTSCompleted survey in class using IPads/ schools laptop

Research assistants administered the data collection

Data from children from 5th to 9th grade are included in thispresentation



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DATA COLLECTION-STUDENTS• Anxiety (SCAS- social anxiety, separation anxiety)

• Wellbeing in school (teachers, friends, bullying)

• Upbringing

• Academic Self-efficacy

• Spare time

• Health and pain

• Strength and difficulties questionnaire (SDQ)



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SCHOOL ABSENCE DATARegistered on a daily basis by the teachers for each student and are monthly reported to the municipality of Aarhus.

The school absence data are linked to the child’s civil registration number



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REGISTER BASED DATAFrom Statistic Denmark (Statistics Denmark is the central authority on Danish statistics. They collect, compile and publish statistics on the Danish society)

• Parental educational level, employment status and income

• Ethnicity

• Family status

• Age of parents

• Outpatients care visits and hospitalization



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Assessed for eligibility5th-9th grade

n=1208

Non-participants• Changed school• Disagreed to participate• No consent from parents• Lack of teacher report or

register data

TEACHERSn= 1044(86%)

PARENTSn= 491 (41%)

STUDENTSn= 999(83%)

Background Aim Methods RESULTS Conclusion


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AARHUS UNIVERSITY


PREVALENCE

0

2

4

6

8

10

12

Total Legal (illness) Legal (other) Illegal

Average number of days with absence from school(5% of school days)

(3%of school days )

(1% of school days)(1% of school days)



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AARHUS UNIVERSITY


HIGH ABSENCEDefinition:

More than 10% absence from school in the school year.

Only absence classified as either due to illness or illegal

absence are included.

High absence group:

n= 10.3%

Mean age= 13.68 years (mean age 13.26 in the remaining sample)

56.2 % males (49.9 % males in the remaining sample)



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1. HYPHOTHESISMost risk factors will be associated with excessive school absenteeism



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EXTERNALIZING AND INTERNALIZING BEHAVIORS, WELL-BEING AND SCHOOL ABSENCE

Normal absenceMean

High absenceMean Difference t-value

SDQ scores: Informant:Peers Child 1,86 2,22 -0.355* (-1.99)

Teacher 0,91 1,95 -1.043*** (-5.87)Parent 1,15 1,93 -0.782* (-2.45)

Emotional Child 2,37 2,85 -0.487* (-2.13)Teacher 0,98 2,48 -1.505*** (-7.90)Parent 1,50 3,10 -1.596*** (-4.62)

Social Child 7,91 7,52 0.395* (2.23)Teacher 8,46 7,35 1.108*** (5.01)Parent 8,80 8,77 0.0371 (0.14)

Hyper active Child 2,98 3,38 -0.406 (-1.66)Teacher 2,01 3,09 -1.087*** (-3.89)Parent 1,79 1,93 -0.139 (-0.37)

Conduct Child 1,61 1,99 -0.379* (-2.28)Teacher 0,55 1,26 -0.703*** (-5.09)Parent 0,57 0,97 -0.395* (-2.08)

Social_phobia Child 5,35 5,61 -0.262 (-0.77)Sep_anxiety Child 2,72 2,89 -0.173 (-0.67)

Observations 881 102


ICCP 201729 JUNE 2017

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DEPARTMENT OF PSYCHOLOGYAND BEHAVIOURAL SCIENCES Normal absence

MeanHigh absence

MeanDifference t-value

School work Scores for factor on homework 0.06 -0.16 0.219** (3.25)Scores for self-efficacy factor 0.04 -0.37 0.409*** (4.27)Scores for factor on school satisfaction -0.05 0.40 -0.444*** (-5.44)Teacher’s assessment of students academic level 0.48 0.24 0.247*** (4.79)

School safety Scores for unsafety factor -0.01 0.10 -0.115 (-1.38)Scores for factor on classroom environment 0.01 -0.06 0.0618 (0.61)

Teacher demographic Teacher age 40.74 43.56 -2.818** (-2.70)Teacher is female 0.56 0.49 0.0607 (1.13)

Demographic Pupil is female 0.51 0.52 -0.010 (-0.19)Single child 0.14 0.22 -0.0783* (-2.13)More than 3 children in family 0.14 0.18 -0.038 (-1.04)

Socio-economic factors Non-western background 0.27 0.39 -0.124** (-2.65)Divorced 0.16 0.25 -0.097* (-2.49)Single parent 0.28 0.44 -0.164*** (-3.46)Social case within last three years 0.01 0.02 -0.006 (-0.48)Long education mother 0.21 0.15 0.0607 (1.45)Long education father 0.19 0.11 0.079* (1.98)Primary school mother 0.25 0.43 -0.186*** (-4.07)Primary school father 0.22 0.36 -0.144** (-3.26)Younger than 6 years by school enrolment 0.36 0.30 0.059 (1.18)Young mother (less than 20 at school start) 0.03 0.05 -0.0195 (-1.07)Unemployed mother 0.09 0.18 -0.09** (-2.94)Unemployed father 0.10 0.15 -0.047 (-1.47)Mother sick-listed 0.07 0.06 0.0116 (0.43)Father sick-listed 0.04 0.05 -0.007 (-0.33)Family gross income<250.000 dkr. 0.14 0.32 -0.186*** (-4.95)Observations 881 102


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Normal absenceMean

High absenceMean

Difference t-value

Up-bringing Scores for factor on child up-bringing (child assessment) -0.03 0.14 -0.178* (-2.38)

Health registers Number of outpatient care visits 5,98 13,31 -7.333* (-2.09)

Number of visits at emergency care 0,16 0,21 -0.0492 (-1.01)

Number of days with inpatient care. 0,14 0,12 0.0231 (0.09)

Any kind of hospitalization 0,02 0,04 -0.0188 (-1.21)

More than 4 visits at the doctor 0,07 0,17 -0.0997*** (-3.59)

Health survey Hours slept 8,83 8,66 0.172 (1.62)

Scores for pain factor -0,02 0,14 -0.162** (-3.15)

Diagnosed with depression (child assessment) 0,00 0,03 -0.0249** (-2.84)

Observations 881 102



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2. HYPOTHESIS

When analyzed together, main predictors will be parental employment status, chronic illness, and externalizing and internalizing behavior.



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LOW RESPONSE RATE AMONG PARENTS• Less than half of the parents responded

• Difference in SES between non-responder parents and responder

• Therefore, the joint model was only based on data from teachers and schoolchildren (n=873)



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Odds ratio t-valueSchoolwork Scores for factor on homework 1,32 (1.24)

Scores for self-efficacy factor 0,84 (-0.91)Scores for factor on school satisfaction 1,40 (1.52)Teacher’s assessment of students academic level 0,49** (-2.06)

School safety Scores for unsafety factor 0,65** (-2.09)Scores for factor on classroom environment 1,34* (1.88)

Teacher demographic Teacher’s age 1,04** (2.37)Teacher is female 0,47** (-2.27)

Demographic Pupil is female 1,27 (0.75)Single child 1,58 (1.28)More than 3 children in family 0,49 (-1.46)

Socio-economic factors Non-western background 0,97 (-0.08)Divorced 1,07 (0.18)Single parent 0,78 (-0.62)Social case within last three years 0,32 (-1.17)Long education mother 1,31 (0.68)Long education father 0,83 (-0.41)Primary school mother 1,80* (1.75)Primary school father 1,19 (0.55)Younger than 6 years by school enrolement 1,11 (0.34)Young mother (less than 20 at school start) 2,40 (1.24)Unemployed mother 1,21 (0.40)Unemployed father 1,25 (0.55)Mother sick-listed 0,99 (-0.02)Father sick-listed 1,26 (0.38)Family gross income<250.000 dkr. 3,20*** (2.63)


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Odds ratio t-valueHealth registers Number of outpatient care visits 0,99 (-1.33)

Number of visits at emergency care 0,60 (-1.40)Number of days with inpatient care. 0,40 (-0.76)Any kind of hospitalization 12,67 (1.14)More than 4 visits at the doctor 2,72** (2.32)

Health survey Hours slept 0,94 (-0.37)Scores for pain index 2,28*** (2.74)Diagnosed with depression (self-reported) 27,39*** (2.92)

Up-bringing Scores for factor on child up-bringing (self-reported) 1,10 (0.47)SCAS self-reported Social phobia 1,05 (0.83)

Separation anxiety 0,89* (-1.72)SDQ teacher informant Peers 1,18* (1.88)

Emotional 1,31*** (3.46)Social 0,93 (-0.84)Hyper active 0,84** (-2.18)Conduct 1,26* (1.74)Constant 0,05 (-1.57)

Other covariates School and grade dummies.

N 873

r2_p 0.243

df_m 50

ll -205.8


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THE RELATIVE IMPORTANCE OF EACH OF THE RISK DOMAINS ON SCHOOL ABSENCE

0 0,05 0,1 0,15 0,2 0,25 0,3

SDQ

SCAS

Up-bringing

Health survey

Health register

Socio-economic

Teacher demographic

School safety

School-work



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AARHUS UNIVERSITY


SUMMARY OF THE RESULTS1. As hypothesized most factors were individually related to high absence

2. The second hypothesis were partly confirmed:

In the joint model we found that having:

• an uneducated mother and low family income

• more than five annual contacts with general practitioners or specialists

• the experience of pain

• self-reported depression

• teacher age and gender

• The factor strongest related to high absence was the children’s emotional and behavioral problems proxy-reported by the teachers.

Background Aim Methods Results CONCLUSION


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CONCLUSIONThis study includes:

• a rich dataset with survey data from a representative sample of Danish schoolchildren

• register data with information on both socio-economic and health status

• absence data registered daily

• The children’s emotional and behavioral problems were more strongly related to having problematic absence than socio-economic factors.

• This study highlights the importance of considering children’s wellbeing in problematic school absenteeism.



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RESEARCH GROUPJohanne Jeppesen Lomholt , Department of Psychology, Aarhus University, Aarhus, Denmark

Jacob Nielsen Arendt, KORA, Danish Institute for Local and Regional Government Research, Copenhagen, Denmark

Iben Bolvig, KORA, Danish Institute for Local and Regional Government Research, Copenhagen, Denmark

Principal Investigator: Mikael Thastum, Department of Psychology, Aarhus University, Aarhus, Denmark


AARHUS UNIVERSITY


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