Mental health difficulties, attainment and attendance: a cross-sectional study

Lereya, Suzet Tanya; Patel, Meera; Santos, Joãο; Deighton, Jessica

doi:10.1007/s00787-018-01273-6

Cited by 26 publications

(23 citation statements)

References 13 publications

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“…In the overall student population, the association between poverty and exclusion is well established (e.g. Lereya & Deighton, 2019), but our data provide a more nuanced picture of socioeconomic correlates of school exclusion. We found a higher risk of school exclusion among single-parent, unemployed and well-educated parents.…”

Section: Discussionmentioning

confidence: 69%

Types and correlates of school non-attendance in students with autism spectrum disorders

Totsika

Hastings

Dutton

et al. 2020

Autism

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School non-attendance in autism spectrum disorders has received very little attention to date. The study aimed to provide a comprehensive description of school non-attendance in students with autism spectrum disorders. Through an online survey, parents of 486 children (mean age: 11 years) reported on school attendance over 1 month and reasons for instances of non-attendance. On average, students missed 5 days of school of a possible 23 days. Persistent non-attendance (absent on 10%+ of available sessions) occurred among 43% of students. School non-attendance was associated with child older age, not living in a two-parent household, parental unemployment and, especially, attending a mainstream school. School refusal accounted for 43% of non-attendance. School exclusion and school withdrawal each accounted for 9% of absences. Truancy was almost non-existent. Non-problematic absenteeism (mostly related to medical appointments and illness) accounted for 32% of absences. Non-problematic absenteeism was more likely among those with intellectual disability, school refusal was more likely among older students and school exclusion was more likely among students from single-parent, unemployed and well-educated households. Findings suggest that school non-attendance in autism spectrum disorders is a significant issue, and that it is important to capture detail about attendance patterns and reasons for school non-attendance. Lay abstract Our study aimed to describe school non-attendance in students with autism. We conducted an online survey. Parents of 486 students (mean age: 11 years) indicated which days their child had missed school (over a period of 1 month). If the child had missed a day, the parent was asked to select a reason from a list of 15 possible reasons (this is a measure of types of school non-attendance called SNACK (School Non-Attendance ChecKlist; Heyne et al., 2019)). On average, students missed 5 days of school of a possible 23 days. Missing over 10% of school is known as persistent absence, and in our study, 43% of students experienced persistent absence. Older students, who attended mainstream schools, who did not live in a two-parent household and whose caregiver was unemployed were more likely to miss school. Looking at the reasons for absence, school refusal was the most frequent reason, accounting for 43% of absences. Nine percent of absence was due to school exclusion. Nine percent of absence was due to school withdrawal. Truancy was almost non-existent. A final reason describes non-problematic absence that is mostly due to medical appointments and illness. This type of absence accounted for 32% of absences in our study, and it was more likely in student with intellectual disability. School refusal was more likely among older students. School exclusion was more likely among students from single-parent, unemployed and well-educated households. Findings from this study help us to understand better the difficulties students with autism experience attending school.

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Section: Discussionmentioning

confidence: 69%

Types and correlates of school non-attendance in students with autism spectrum disorders

Totsika

Hastings

Dutton

et al. 2020

Autism

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“…Our findings suggest that greater consideration should be given to the provision of counselling in primary schools. Early intervention at this young age, before mental health problems become entrenched in adolescence and young adulthood, may help to prevent the long-term impacts of childhood mental health problems, including adverse educational outcomes [12][13][14]. Children who received the counselling intervention were similar in terms of their mental health to individuals from a national population survey who had been in contact with specialist mental health and/or education services (see Table S6 in online supplementary information).…”

Section: Discussionmentioning

confidence: 99%

“…Children who are well educated have better health and wellbeing, while those with better health, including better mental health, perform better at school [11]. Children with mental health problems have poorer academic attainment, greater school absences, and an increased risk of school exclusion compared to their mentally healthy peers [12][13][14]. Recent research by the Institute for Public Policy Research showed that parents would like greater priority to be given to school-based mental health support, while more than 70% of teachers believed greater access to onsite mental health support would improve student attainment [15].…”

mentioning

confidence: 99%

Longer-term effects of school-based counselling in UK primary schools

Finning

White²,

Tóth³

et al. 2021

Eur Child Adolesc Psychiatry

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Children's mental health is deteriorating while access to child and adolescent mental health services is decreasing. Recent UK policy has focused on schools as a setting for the provision of mental health services, and counselling is the most common type of school-based mental health provision. This study examined the longer-term effectiveness of one-to-one school-based counselling delivered to children in UK primary schools. Data were drawn from a sample of children who received schoolbased counselling in the UK in the 2015/16 academic year, delivered by a national charitable organisation. Mental health was assessed at baseline, immediately post-intervention, and approximately 1 year post-intervention, using the Strengths and Difficulties Questionnaire (SDQ) completed by teachers and parents. Paired t tests compared post-intervention and follow-up SDQ total difficulties scores with baseline values. Propensity score matching was then used to identify a comparator group of children from a national population survey, and linear mixed effects models compared trajectories of SDQ scores in the two groups. In the intervention group, teacher and parent SDQ total difficulties scores were lower at post-intervention and longer-term follow-up compared to baseline (teacher:

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“…In the second stage of the psychiatrists' training program, only three months may be spent in child and adolescent psychiatry [14]. Thirdly, the mental healthcare system for children needs further development requiring collaboration at all levels of society, including schools, communities, hospitals, the regional Center for Disease Control and Prevention, and the local government [5,6]. However, difficulties still exist in implementing various policies and related activities due to the lack of cooperation and coordination among different institutions and organizations.…”

Section: Main Challenges For Improvement Of the Mental Healthcare Sysmentioning

confidence: 99%

Building the mental health management system for children post COVID-19 pandemic: an urgent focus in China

Deng

Wang

et al. 2021

Eur Child Adolesc Psychiatry

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Mental health difficulties, attainment and attendance: a cross-sectional study

Cited by 26 publications

References 13 publications

Types and correlates of school non-attendance in students with autism spectrum disorders

Types and correlates of school non-attendance in students with autism spectrum disorders

Longer-term effects of school-based counselling in UK primary schools

Building the mental health management system for children post COVID-19 pandemic: an urgent focus in China

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