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Abstract

Objective:

Despite growing literature on psychotic experiences, no nationally representative study has reported on the prevalence of both hallucinatory experiences and delusional experiences in Australian adolescents. Also, while many studies have examined the association between psychotic experiences and certain demographic and clinical correlates, there are more variables of interest to be investigated, including disordered eating behaviour and hours of sleep. The aims of this study were to examine (1) the prevalence of hallucinatory experiences and delusional experiences in Australian adolescents, and (2) the associations between different types of psychotic experiences with a broad range of demographic, clinical, and psychosocial variables.

Methods:

A random sample of Australian adolescents aged 14- to 17-year-olds were recruited in 2013–2014 as part of the Young Minds Matter Survey. Participants completed self-report questions regarding five different psychotic experience types (auditory and visual hallucinatory experiences, and thoughts read, special messages, spied upon) experienced in the past 12 months. Using logistic regression analyses, we investigated associations between psychotic experiences and demographic, clinical, and psychosocial factors.

Results:

The 12-month prevalence ranged from 3.3% (95% confidence interval = [2.6, 4.3]) for special messages to 14.0% (95% confidence interval = [12.3, 15.8]) for auditory hallucinatory experiences. At the bivariate level, each psychotic experience subtype was associated with increased likelihood of major depression, being bullied, psychological distress, low self-esteem, mental health service use and insufficient sleep (<8 hours per night). Multivariate analyses revealed both auditory and visual hallucinatory experiences were associated with an increased likelihood of four of these variables (depression, being bullied, service use, insufficient sleep), whereas associations with delusional experiences were inconsistent.

Conclusion:

Hallucinatory and delusional experiences are common in Australian adolescents. Hallucinatory experiences, rather than delusional experiences, may be more clinically relevant in this demographic. When psychotic experiences are endorsed by adolescents, further assessment is indicated so as to ascertain more detail on the phenomenology of the experiences to better understand their clinical relevance.

Keywords

Psychotic experiences hallucinations delusions adolescents Australia

Introduction

There has been increasing interest in population-based studies of psychotic experiences (PEs) in adolescents. These experiences, defined as occurring outside the context of sleep or substance use, may be appraised as clinically relevant symptoms (hallucinations or delusions) through to subclinical/subthreshold experiences, not prompting help-seeking behaviour (van Os et al., 2009; Yung and Lin, 2016). While PEs in adolescents are associated with an increased risk of psychosis (Connell et al., 2016; Poulton et al., 2000), they more commonly reflect other forms of mental illness such as depression, cannabis use and anxiety (Dolphin et al., 2015; Scott et al., 2009; Yung et al., 2009). PEs have also been strongly linked to physical health problems (Moreno et al., 2013) and negative environmental exposures, such as bullying and childhood trauma (Kelleher et al., 2013), and are robustly associated with an increased likelihood of suicidal behaviours (Hielscher et al., 2017; Honings et al., 2016). In adolescents, PEs are indicators for an increased risk of current and future poor mental health and psychosocial outcomes.

In a cross-national survey of 31,261 respondents, McGrath et al. (2015) found that 5.8% of the population reported PEs in their lifetime, with hallucinatory experiences (HEs; 5.2%) more common than delusional experiences (DEs; 1.3%). Among adolescents the prevalence was higher, particularly for DEs in younger (< 29 years) versus older respondents (60 + years) after multivariate adjustment, odds ratio (OR) = 2.4; 95% confidence interval (CI) = [1.1, 5.0]. A 19-study international meta-analysis reported a median PE prevalence of 7.5% among adolescents aged 13-18 years (Kelleher et al., 2012). This is consistent with the prevalence reported in Australia.

The prevalence of hallucinations in Australian adolescents has previously been reported as 8.4% (Scott et al., 2009) from the first national youth mental health survey (The Australian National Survey of Mental Health and Wellbeing; Sawyer et al., 2001), which was conducted in 1998. However, there are some existing gaps in the literature. Australian studies reporting the prevalence of other PE subtypes (e.g. persecutory ideation, grandiose thinking, Scott et al., 2008; Varghese et al., 2011; Yung et al., 2009) have been conducted in either young adult samples (18+ years) (Scott et al., 2008; Varghese et al., 2011), or non-representative samples of Australian adolescents (Yung et al., 2009). To date, no nationally representative Australian study of adolescents has reported the prevalence of both HEs and DEs independently.

The relationship between PEs and mental ill health has been reported as bidirectional (McGrath et al., 2016). Adolescents who hallucinated were more likely to have high symptom scores for anxiety, depression and inattention-hyperactivity (McGee et al., 2000). Hallucinations have also been shown to be associated with a Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) diagnosis of depression, and they were three times more likely to occur in those adolescents who had smoked cannabis in the previous month (Scott et al., 2009). However, these studies either examined associations of mental ill health with HEs (Scott et al., 2009), or they collapsed HEs and DEs into one broad PE variable (McGrath et al., 2015). Studies that have investigated the correlates of different PE subtypes have found each one is differentially associated with mental illness and impairment in functioning (Capra et al., 2015; Dhossche et al., 2002; Dolphin et al., 2015). For example, Dhossche et al. (2002) found adolescents who reported auditory but not visual HEs had higher rates of depressive disorders, whereas Dolphin et al. (2015) found those with HEs, but not paranoid thoughts, had higher rates of recent cannabis use. Therefore, it is important for studies to distinguish the different types of PEs as there is variation in their clinical relevance.

While many studies have examined the association between PEs and some demographic and clinical correlates, there remain variables of interest which have not been investigated (Dolphin et al., 2015). Only one study of adults (Koyanagi et al., 2016) has explored the association between PEs and disordered eating behaviour, which reported a strong association (OR = 3.44; 95% CI = [1.85, 6.39]). Given disordered eating often emerges in adolescence (Favaro et al., 2009), there is a need to examine this association in this demographic. Also, despite several studies on the association between PEs and sleep disturbances, as measured by the presence of nightmares or subjective sleep ratings (Lee et al., 2012; Oh et al., 2016), no study to date has investigated the association between PEs and hours of sleep. Adolescents sleeping less than 8 hours per night have an increased risk of a broad range of health and other problems, including poor academic performance, obesity, and increased risk of suicidality (Lui, 2004; Snell et al., 2007). It would be useful to investigate whether this 8-hour cut-off for insufficient sleep is also associated with PEs in adolescents.

To address the gaps in the literature, we had the opportunity to examine the prevalence of auditory and visual HEs, as well as DEs in a nationally representative sample of Australian adolescents. Furthermore, we examined the associations between different types of PEs with a broad range of demographic, clinical and psychosocial variables including disordered eating behaviour and hours of sleep. Finally, we aimed to determine the variability between the strengths of the associations with each type of PE and the demographic and clinical variables so as to ascertain which PEs are clinically important in adolescents.

Methods

Sample

The Young Minds Matter (YMM) survey is a national study of mental health and wellbeing of children and adolescents aged 4–17 years, where data were collected between 31 May 2013 and 10 April 2014. The design, sampling and survey interview methods are described extensively elsewhere (Hafekost et al., 2016; Lawrence et al., 2016). Briefly, the survey employed area-based random sampling with voluntary recruitment and consent of households in scope where there was at least one child aged 4–17 years (up to but not including the age of 18) who were residing in private dwellings in Australia. Children who usually spent more than 50% of their time in another household and less than 50% in the selected household were not in scope. Other exclusion criteria were: The 1% most remote SA1s in Australia (considered standard practice for surveys that aim to yield estimates at a national level); children who were homeless or in institutional care (a completely different approach would be required to represent this population adequately); and children in families where the interview could not be conducted in English. Also, it should be noted that the survey could not produce estimates of mental disorders and service use for Indigenous Australians nor other minority groups (e.g. refugees and asylum seekers) which experience higher levels of distress and trauma than the general population (Silove et al., 2007), and thus would likely report an elevated prevalence of PEs.

As previously described in Hafekost et al. (2016), the survey sample was recruited in two parts. In total, 46,248 households were approached to yield a main sample of 5508 participating families with children aged 4–17 years, supplemented by an additional sample of 802 participating families with 16- to 17-year-olds recruited by approaching 30,358 households. Of the 46,248 households approached for the main sample, 32,526 did not have children aged 4–17 years, 3778 did have children but did not participate, and for 4438, no contact was made. For the supplementary sample of 16- to 17-year-olds, of the 30,358 households approached, 27,800 did not have children aged 16–17 years; 452 did have children but did not participate; and for 1304 no contact was made or it was not possible to determine if they had children aged 4–17 years, yielding an overall response rate of 55%.

Of the final participating sample of 6310 families with children aged 4–17 years, 2251 of the children were aged 14–17 years. Of these, 2004 completed the youth self-report questionnaire (89%) which assessed for PEs. For all these young people, the primary carer completed a survey which included a question on whether the young person had ever been diagnosed with a psychotic disorder. The research protocol for the study was approved by the Australian Government Department of Health Human Research Ethics Committee, and The University of Western Australia Human Research Ethics Committee.

National representativeness of sample

Comparisons with 2011 Census data showed that the YMM sample was broadly representative of the overall Australian population in terms of the following demographic characteristics: socio-economic status indicators, geographic area, gender of child, family structure, household income, country of birth, labour force status and dwelling tenure (Lawrence et al., 2016). The YMM sample only differed from the 2011 Census data in terms of age of the child (higher proportion of 4- to 7-year-olds) and number of children in the household (survey sample under-represented children from families with only one eligible child).

Measures

A self-report questionnaire was completed in the home by survey participants aged 11–17 years. Consenting participants completed the questionnaire in private using a tablet computer. All responses were confidential and not shared with the consenting parent. The questions about PEs were only asked of those aged 14–17 years (n = 2004). This sample was the focus of the current study.

PEs

The 12-month PEs were assessed in the YMM survey using five items from the Diagnostic Interview Schedule for Children (DISC-IV; Shaffer et al., 2000) psychosis module: auditory HEs (‘In the last year have you heard things other people could not hear, such as a voice?’ Yes/No); visual HEs (‘In the last year have you seen something or someone that other people who were present could not see, that is had a vision when you were completely awake?’); thoughts read (‘In the last year, have you ever believed that someone was using special powers to read your mind?’); special messages (‘In the last year, have you ever believed that you were being sent special messages through the TV or radio or that a programme had been arranged for you alone and no one else?’); and spied upon (‘In the last year, have you ever believed that people were spying on you?’). If participants responded ‘Yes’ to any of these questions, a follow-up question was asked: ‘Did these experiences happen when you were taking drugs or drinking alcohol?’ Participants were classified as endorsing PEs if they responded ‘No’ to this question.

Three participants did not complete all the PE questions, and therefore were excluded from the sample. In the parent or carer interview, three respondents reported their child had been diagnosed with schizophrenia or other psychotic disorders. As the focus of the study was on PEs in those who did not reach the clinical threshold for a psychotic diagnosis we also excluded these participants, leaving a final sample for analysis of 1998 adolescents.

Correlates of interest

Potential correlates of interest were selected based on the results of existing reviews or other papers on PEs (de Armando et al., 2010; Dolphin et al., 2015; De Leede-Smith and Barkus, 2013; Scott et al., 2009, 2008). Specifically, we followed the approach taken by Dolphin et al. (2015), where the authors examined the association between PEs and factors from five domains in adolescents. In this study, we considered correlates across seven domains. Sociodemographics included age, sex and school attendance status; mental health disorders/problems included diagnosis of major depressive disorder (assessed using the youth self-report version of the DISC-IV) and symptoms of disordered eating behaviour (measured using questions from the Avon Longitudinal Study of Parents and Children (e.g. ‘During the past 12 months, how often did you make yourself throw up [vomit] to lose weight or avoid gaining any weight?’), together with participants’ self-reported body mass index (BMI); substance use included lifetime use of cannabis or other illegal drugs; environmental factors included being bullied or cyber bullied in the past 12 months, and social isolation (a composite score [0–5] which included the following: frequency of contact with family and friends, involvement per week in extracurricular activity and perceived ability to rely on friends); psychological factors included psychological distress (Kessler Psychological Distress Scale; K10) experienced in the past 4 weeks, self-esteem (Adolescent Self-Esteem Questionnaire [ASQ], Hafekost et al., 2017), and usual hours of sleep per night (‘How many hours of sleep do you usually get on [a school night/a night when you have work the next day]?), recoded into below (insufficient sleep) versus equal to or above 8 hours of sleep per night (sufficient sleep). An 8-hour cut-off was incorporated as it is part of national guidelines for defining insufficient sleep for adolescents and has been associated with a number of poor outcomes in this demographic (see Supplementary Material I); intervention factors included mental health service use in the past 12 months; and family history factors included parental mental illness as reported in the parent or carer interview. Self-harm and suicidality were also correlates of interest (Honings et al., 2016). Their association with PEs has been investigated in a separate paper. See Supplementary Material I for further details about relevant YMM items included in the current study.

Statistical analysis

All analyses were conducted using Stata/IC 14 (Stata Corp., College Station, Texas, USA, 2015). Survey data were weighted using the Stata svyset procedure to represent the full Australian population of 14- to 17-year-olds accounting for sex, age, family size, household income and deliberate oversampling of 16- to 17-year-olds (Hafekost et al., 2016). The statistical analysis was mainly descriptive in nature, where we report on the prevalence of each PE subtype (auditory and visual HEs, as well as thoughts read, special messages and feeling spied upon). Survey estimates and associated CIs were calculated using the method of Taylor Series Linearisation (Wolter, 2007).

The associations between correlates of interest and each PE subtype were investigated using univariate logistic regression, reported as unadjusted ORs. A second multivariate logistic regression analysis was also conducted, including all variables in the model, to ascertain the relationship between PEs and each factor while controlling for potential confounders. There was no evidence of multicollinearity based on standard thresholds for the variance inflation factor.

Results

Prevalence of PEs

Of the 1998 participants, the 12-month prevalence of auditory HEs was 14.0% (95% CI = [12.3, 15.8]) (see Table 1). In terms of the other PE subtypes, 13.8% reported being spied upon (95% CI = [12.1, 15.6]), 10.6% reported visual HEs (95% CI = [9.1, 12.3]), 5.6% reported their thoughts being read (95% CI = [4.6, 6.8]), and 3.3% reported receiving special messages through the television or radio (95% CI = [2.6, 4.3]).

Table 1.

Psychotic experiences among 14-17 years in the Young Minds Matter (YMM) survey, by sex.

	Complete dataset (n = 1998)				Males (n = 1027)				Females (n = 971)
	Pop. Est.	95% CI	%	95% CI	Pop. Est.	95% CI	%	95% CI	Pop. Est.	95% CI	%	95% CI
12 month auditory HEs	158,900	[136,800, 181,000]	14.0	[12.3, 15.8]	69,200	[55,100, 83,200]	11.8	[9.8, 14.2]	89,700	[73,700, 105,700]	16.2	[13.8, 19.0]
12 month visual HEs	120,500	[101,200, 139,800]	10.6	[9.1, 12.3]	55,300	[42,800, 67,900]	9.4	[7.6, 11.7]	65,200	[51,100, 79,300]	11.8	[9.6, 14.4]
12 month thoughts read	63,500	[50,400, 76,500]	5.6	[4.6, 6.8]	24,400	[16,300, 32,500]	4.2	[3.0, 5.8]	39,100	[28,500, 49,700]	7.1	[5.4, 9.1]
12 month spied upon	156,600	[135,300, 178,000]	13.8	[12.1, 15.6]	69,400	[56,200, 82,600]	11.8	[9.8, 14.2]	87,200	[71,400,103,100]	15.8	[13.3, 18.7]
12 month special messages	38,000	[27,900, 48,000]	3.3	[2.6, 4.3]	20,700	[13,100, 28,300]	3.5	[2.5, 5.0]	17,300	[11,000, 23,600]	3.1	[2.2, 4.4]

Pop. Est: population estimate; %: weighted percentage of respondents; 95% CI: 95% confidence interval; HEs: hallucinatory experiences.

Correlates of PE subtypes

Tables 2 –6 present the bivariate associations between each PE subtype and variables in each of the seven domains. In terms of sociodemographics, thoughts being read (Table 4) and feeling spied upon (Table 6) were the only PEs to be associated with both age and sex; where younger, female respondents were more likely to endorse these items compared to their older, male counterparts. In terms of clinical and psychosocial variables, each subtype was associated with major depression, being bullied, psychological distress, low self-esteem, mental health service use, insufficient sleep, and substance use (except for thoughts being read, which was not associated with substance use at the bivariate level). None of the PE subtypes were associated with parental mental illness. Only auditory HEs and feeling spied upon were associated with social isolation. Two of the three DEs (thoughts read, spied upon) were associated with disordered eating behaviour, whereas HEs (both auditory and visual) were not.

Table 2.

Sociodemographic, clinical, and psychosocial correlates of auditory hallucinatory experiences (N = 1998).

Variable	+ Auditory hallucinatory experiences, n = 269			– Auditory hallucinatory experiences, n = 1729			Bivariate statistics^a
Variable	n	%	95% CI	n	%	95% CI	OR	95% CI
Age (years)
M (SE)	15.39 (0.08)	–	–	15.53 (0.04)	–	–	–	–
Range	14–17	–	–	14–17	–	–	–	–
14–15^b	100	54.6	[47.67, 61.3]	548	48.5	[45.4, 51.5]	1.28	[0.96, 1.70]
16–17	169	45.4	[38.7, 52.4]	1181	51.5	[48.5, 54.6]	(ref)	(ref)
Sex
Female	155	56.5	[49.7, 63.0]	816	47.2	[44.8, 49.7]	1.45	[1.09, 1.92]
Male	114	43.5	[37.0, 50.3]	913	52.8	[50.3, 55.2]	(ref)	(ref)
School attendance status
Not attending school	25	7.4	[5.0, 10.7]	199	9.4	[8.0, 11.0]	0.77	[0.50, 1.18]
Attending school	244	92.6	[89.3, 95.0]	1530	90.6	[89.0, 92.0]	(ref)	(ref)
Lifetime substance use^c	69	23.3	[18.2, 29.4]	276	13.6	[12.0, 15.5]	1.93	[1.37, 2.72]
Major depressive disorder^d	78	27.3	[21.9, 33.4]	163	8.6	[7.3, 10.0]	3.99	[2.82, 5.64]
Disordered eating behaviour^e	11	4.3	[2.2, 8.1]	41	2.4	[1.7, 3.4]	1.81	[0.84, 3.92]
Bullied in past 12 months	130	49.4	[42.7, 56.0]	469	27.8	[25.4, 30.3]	2.53	[1.90, 3.38]
K10 clinical cut-off
Below 19	198	74.8	[68.9, 80.0]	1581	92.0	[90.6, 93.2]	(ref)	(ref)
19 or above	71	25.2	[20.0, 31.1]	148	8.0	[6.8, 9.4]	3.86	[2.75, 5.42]
Self-esteem^f
Low (≤17)	28	10.0	[6.8, 14.5]	51	2.9	[2.2, 3.8]	3.75	[2.22, 6.33]
Healthy (>17)	241	90.0	[85.5, 93.2]	1678	97.1	[96.2, 97.8]	(ref)	(ref)
Mental health service use^g	95	35.3	[29.3, 41.8]	254	14.1	[12.4, 15.9]	3.34	[2.46, 4.52]
Parental mental illness	109	41.3	[34.9, 48.0]	629	37.0	[34.5, 39.5]	1.20	[0.90, 1.61]
Hours of sleep
Insufficient (<8 hours)	150	53.0	[46.9, 59.0]	683	36.3	[33.9, 38.9]	1.98	[1.52, 2.57]
Sufficient (≥8 hours)	119	47.0	[41.0, 53.1]	1046	63.7	[61.1, 66.1]	(ref)	(ref)
Social isolation (0–5)^h
M (SE)	0.95 (0.07)	–	–	0.84 (0.02)	–	–	–	–
Range	0–5	–	–	0–5	–	–	–	–
Below score 3	241	91.3	[87.4, 94.1]	1630	94.5	[93.2, 95.6]	(ref)	(ref)
Score 3 or above	28	8.7	[5.9, 12.6]	99	5.5	[4.4, 6.8]	1.65	[1.04, 2.62]

n: unweighted number of respondents; %: weighted percentage; OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

All sociodemographic, clinical, psychological and environmental variables were statistically compared (with vs without psychotic experiences) using logistic regressions. For all logistic regressions, the reference group is no endorsement of psychotic experiences (n = 1729).

Similar result found when comparing the individual levels of age (14, 15, 16, 17), where the odds ratio was non-significant (OR = 0.89, 95% CI = [0.78, 1.01]).

Cannabis or other illicit substance use in their lifetime.

Youth-reported major depressive disorder, Diagnostic Interview Schedule for Children (DISC-IV).

Binge eating/purging or low weight/problem eating group (groups devised by YMM survey team).

Adolescent Self-Esteem Questionnaire (ASQ), recoded into above (healthy) vs equal to or below cut-off of 17 (low self-esteem).

Mental health service use in past 12 months.

Social isolation composite score (0–5) included: number of friends, face-to-face contact per week with friends outside of school, online contact per week with friends/family, level of involvement in clubs, groups or activities outside of school per week, and perceived ability to rely on friends. A higher score indicated greater social isolation. Continuous scores were recoded into a binary variable: scores less than 3 versus scores 3 or above.

Table 3.

Sociodemographic, clinical and psychosocial correlates of visual hallucinatory experiences (N = 1998).

Variable	+Visual hallucinatory experiences, n = 194			–Visual hallucinatory experiences, n = 1804			Bivariate statistics^a
Variable	n	%	95% CI	n	%	95% CI	OR	95% CI
Age (years)
M (SE)	15.19 (0.08)	–	–	15.55 (0.03)	–	–	–	–
Range	14–17	–	–	14–17	–	–	–	–
14–15^b	94	65.1	[57.9, 71.6]	554	47.5	[44.4, 50.5]	2.06	[1.52, 2.80]
16–17	100	34.9	[28.4, 42.1]	1250	52.5	[49.5, 55.6]	(ref)	(ref)
Sex
Female	105	54.1	[46.1, 61.9]	866	47.9	[45.4, 50.4]	1.28	[0.92, 1.79]
Male	89	45.9	[38.1, 53.9]	938	52.1	[49.6, 54.6]	(ref)	(ref)
School attendance status
Not attending school	26	9.9	[6.8, 14.2]	198	9.1	[7.7, 10.6]	1.11	[0.72, 1.70]
Attending school	168	90.1	[85.8, 93.2]	1606	90.9	[89.4, 92.3]	(ref)	(ref)
Lifetime substance use^c	48	22.2	[16.4, 29.4]	297	14.1	[12.5, 16.0]	1.74	[1.17, 2.57]
Major depressive disorder^d	58	28.5	[22.4, 35.5]	183	9.2	[7.9, 10.6]	3.96	[2.75, 5.70]
Disordered eating behaviour^e	8	4.5	[2.1, 9.6]	44	2.5	[1.8, 3.4]	1.89	[0.78, 4.54]
Bullied in past 12 months	94	49.8	[41.8, 57.7]	505	28.5	[26.2, 31.0]	2.48	[1.76, 3.48]
K10 clinical cut-off
Below 19	146	75.3	[68.1, 81.3]	1633	91.3	[89.9, 92.5]	(ref)	(ref)
19 or above	48	24.7	[18.7, 31.9]	171	8.7	[7.5, 10.1]	3.44	[2.33, 5.08]
Self-esteem^f
Low (≤17)	19	9.1	[5.7, 14.4]	60	3.3	[2.5, 4.2]	3.00	[1.66, 5.39]
Healthy (>17)	175	90.9	[85.6, 94.3]	1744	96.7	[95.8, 97.5]	(ref)	(ref)
Mental health service use^g	64	33.0	[26.5, 40.3]	285	15.1	[13.4, 17.1]	2.77	[1.96, 3.92]
Parental mental illness	86	44.5	[37.2, 52.0]	652	36.7	[34.3, 39.2]	1.38	[0.99, 1.91]
Hours of sleep
Insufficient (<8 hours)	109	55.2	[47.7, 62.5]	724	36.7	[34.3, 39.2]	2.12	[1.55, 2.91]
Sufficient (≥8 hours)	85	44.8	[37.5, 52.3]	1080	63.3	[60.8, 65.7]	(ref)	(ref)
Social isolation (0–5)^h
M (SE)	0.99 (0.07)	–	–	0.84 (0.02)	–	–	–	–
Range	0–5	–	–	0–5	–	–	–	–
Below score 3	179	93.2	[88.7, 96.0]	1692	94.2	[92.9, 95.3]	(ref)	(ref)
Score 3 or above	15	6.8	[4.0, 11.3]	112	5.8	[4.7, 7.1]	1.17	[0.65, 2.14]

n: unweighted number of respondents; %: weighted percentage; OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

Similar result found when comparing the individual levels of age (14, 15, 16, 17), where the odds ratio was significant between 14 and both 16 and 17 years (OR range = 2.03–2.17, p < .05), as well as between 15 and both 16 and 17 years (OR range = 1.96–2.10, p < .05).

Cannabis or other illicit substance use in their lifetime.

Youth-reported major depressive disorder, Diagnostic Interview Schedule for Children (DISC-IV).

Binge eating/purging or low weight/problem eating group (groups devised by YMM survey team).

Adolescent Self-Esteem Questionnaire (ASQ), recoded into above (healthy) vs equal to or below cut-off of 17 (low self-esteem).

Mental health service use in past 12 months.

Table 4.

Sociodemographic, clinical and psychosocial correlates of thoughts being read (N = 1998).

Variable	+Thoughts read, n = 104			–Thoughts read, n = 1894			Bivariate statistics^a
Variable	n	%	95% CI	n	%	95% CI	OR	95% CI
Age (years)
M (SE)	15.29 (0.12)	–	–	15.53 (0.03)	–	–	–	–
Range	14–17	–	–	14–17	–	–	–	–
14–15^b	44	59.5	[48.8, 69.4]	604	48.7	[45.7, 51.7]	1.55	[1.01, 2.37]
16–17	60	40.5	[30.6, 51.2]	1290	51.3	[48.3, 54.3]	(ref)	(ref)
Sex
Female	63	61.6	[50.5, 71.6]	908	47.8	[45.4, 50.2]	1.75	[1.11, 2.76]
Male	41	38.4	[28.4, 49.5]	986	52.2	[49.8, 54.6]	(ref)	(ref)
School attendance status
Not attending school	7	5.3	[2.5, 11.1]	217	9.4	[8.0, 10.9]	0.55	[0.25, 1.22]
Attending school	97	94.7	[88.9, 97.5]	1677	90.6	[89.1, 92.0]	(ref)	(ref)
Lifetime substance use^c	25	21.9	[14.6, 31.6]	320	14.6	[12.9, 16.4]	1.64	[0.99, 2.72]
Major depressive disorder^d	38	32.0	[23.2, 42.2]	203	10.0	[8.7, 11.4]	4.24	[2.67, 6.75]
Disordered eating behaviour^e	8	7.4	[3.4, 15.4]	44	2.4	[1.7, 3.3]	3.28	[1.37, 7.85]
Bullied in past 12 months	45	42.7	[32.9, 53.2]	554	30.1	[27.8, 32.5]	1.73	[1.13, 2.67]
K10 clinical cut-off
Below 19	69	70.0	[59.7, 78.5]	1710	90.8	[89.2, 92.1]	(ref)	(ref)
19 or above	35	30.0	[21.5, 40.3]	184	9.2	[7.9, 10.8]	4.21	[2.56, 6.92]
Self-esteem^f
Low (≤17)	17	16.1	[9.8, 25.5]	62	3.1	[2.4, 4.1]	5.91	[3.12, 11.19]
Healthy (>17)	87	83.9	[74.5, 90.2]	1832	96.9	[95.9, 97.6]	(ref)	(ref)
Mental health service use^g	36	30.9	[22.2, 41.1]	313	16.2	[14.5, 18.1]	2.31	[1.46, 3.66]
Parental mental illness	48	46.5	[35.9, 57.5]	690	37.0	[34.7, 39.4]	1.48	[0.95, 2.31]
Hours of sleep
Insufficient (<8 hours)	48	50.5	[39.9, 61.0]	777	38.0	[35.6, 40.5]	1.60	[1.03, 2.47]
Sufficient (≥8 hours)	56	49.5	[39.0, 60.1]	1117	62.0	[59.5, 64.4]	(ref)	(ref)
Social isolation (0–5)^h
M (SE)	1.08 (0.11)	–	–	0.84 (0.02)	–	–	–	–
Range	0–5	–	–	0–5	–	–	–	–
Below score 3	92	89.7	[82.0, 94.3]	1779	94.3	[93.1, 95.4]	(ref)	(ref)
Score 3 or above	12	10.3	[5.7, 18.0]	115	5.7	[4.6, 6.9]	1.91	[0.99, 3.70]

n: unweighted number of respondents; %: weighted percentage; OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

Similar result found when comparing the individual levels of age (14, 15, 16, 17), where the odds ratio was significant between 15 and 17 years (OR = 2.02, 95% CI = [1.07, 3.85]).

Cannabis or other illicit substance use in their lifetime.

Youth-reported major depressive disorder, Diagnostic Interview Schedule for Children (DISC-IV).

Binge eating/purging or low weight/problem eating group (groups devised by YMM survey team).

Adolescent Self-Esteem Questionnaire (ASQ), recoded into above (healthy) vs equal to or below cut-off of 17 (low self-esteem).

Mental health service use in past 12 months.

Table 5.

Sociodemographic, clinical and psychosocial correlates of receiving special messages (N = 1998).

Variable	+Special messages n = 69			–Special messages n = 1929			Bivariate statistics^a
Variable	n	%	95% CI	n	%	95% CI	OR	95% CI
Age (years)
M (SE)	15.57 (0.16)	–	–	15.51 (0.03)	–	–	–	–
Range	14–17	–	–	14–17	–	–	–	–
14–15^b	21	46.7	[33.3, 60.7]	627	49.4	[46.4, 52.4]	0.90	[0.52, 1.56]
16–17	48	53.3	[39.3, 66.7]	1302	50.6	[47.6, 53.6]	(ref)	(ref)
Sex
Female	31	45.5	[33.1, 58.6]	940	48.6	[46.2, 51.0]	0.88	[0.52, 1.49]
Male	38	54.5	[41.4, 66.9]	989	51.4	[49.0, 53.8]	(ref)	(ref)
School attendance status
Not attending school	13	15.6	[8.9, 26.0]	211	8.9	[7.7, 10.4]	1.89	[0.99, 3.58]
Attending school	56	84.4	[74.0, 91.1]	1718	91.1	[89.6, 92.3]	(ref)	(ref)
Lifetime substance use^c	21	27.5	[17.6, 40.3]	324	14.6	[12.9, 16.4]	2.23	[1.27, 3.91]
Major depressive disorder^d	20	27.9	[17.7, 41.0]	221	10.6	[9.3, 12.1]	3.25	[1.80, 5.85]
Disordered eating behaviour^e	4	4.7	[1.7, 12.2]	48	2.6	[1.9, 3.5]	1.85	[0.63, 5.39]
Bullied in past 12 months	31	46.6	[33.9, 59.8]	568	30.2	[27.9, 32.7]	2.01	[1.18, 3.43]
K10 clinical cut-off
Below 19	52	76.3	[63.6, 85.6]	1727	90.1	[88.6, 91.4]	(ref)	(ref)
19 or above	17	23.7	[14.4, 36.4]	202	9.9	[8.6, 11.4]	2.81	[1.51, 5.20]
Self-esteem^f
Low (≤17)	7	10.4	[4.7, 21.5]	72	3.6	[2.9, 4.6]	3.08	[1.29, 7.34]
Healthy (>17)	62	89.6	[78.5, 95.3]	1857	96.4	[95.4, 97.1]	(ref)	(ref)
Mental health service use^g	21	27.9	[17.8, 40.7]	328	16.6	[14.9, 18.5]	1.93	[1.08, 3.45]
Parental mental illness	22	31.4	[20.6, 44.7]	716	37.8	[35.5, 40.1]	0.76	[0.43, 1.33]
Hours of sleep
Insufficient (<8 hours)	40	56.8	[44.1, 68.7]	793	38.0	[35.6, 40.5]	2.14	[1.28, 3.57]
Sufficient (≥8 hours)	29	43.2	[31.3, 55.9]	1136	62.0	[59.5, 64.4]	(ref)	(ref)
Social isolation (0–5)^h
M (SE)	1.05 (0.13)	–	–	0.85 (0.02)	–	–	–	–
Range	0–5	–	–	0–5	–	–	–	–
Below score 3	63	91.5	[81.0, 96.5]	1808	94.2	[92.9, 95.2]	(ref)	(ref)
Score 3 or above	6	8.5	[3.5, 19.0]	121	5.8	[4.8, 7.1]	1.50	[0.60, 3.71]

n: unweighted number of respondents; %: weighted percentage; OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

Similar result found when comparing the individual levels of age (14, 15, 16, 17), where the odds ratio was non-significant (OR = 1.05, 95% CI = [0.82, 1.33]).

Cannabis or other illicit substance use in their lifetime.

Youth-reported major depressive disorder, Diagnostic Interview Schedule for Children (DISC-IV).

Binge eating/purging or low weight/problem eating group (groups devised by YMM survey team).

Adolescent Self-Esteem Questionnaire (ASQ), recoded into above (healthy) vs equal to or below cut-off of 17 (low self-esteem).

Mental health service use in past 12 months.

Table 6.

Sociodemographic, clinical and psychosocial correlates of feeling spied upon (N = 1998).

Variable	+Spied upon, n = 264			–Spied upon, n = 1734			Bivariate statistics^a
Variable	n	%	95% CI	n	%	95% CI	OR	95% CI
Age (years)
M (SE)	15.36 (0.08)	–	–	15.54 (0.04)	–	–	–	–
Range	14–17	–	–	14–17	–	–	–	–
14–15^b	103	56.3	[49.4, 63.0]	545	48.2	[45.1, 51.3]	1.38	[1.04, 1.84]
16–17	161	43.7	[37.0, 50.6]	1189	51.8	[48.7, 54.9]	(ref)	(ref)
Sex
Female	147	55.7	[49.0, 62.2]	824	47.4	[44.8, 50.0]	1.40	[1.04, 1.87]
Male	117	44.3	[37.8, 51.0]	910	52.6	[50.0, 55.2]	(ref)	(ref)
School attendance status
Not attending school	33	10.3	[7.2, 14.4]	191	9.0	[7.6, 10.5]	1.16	[0.76, 1.76]
Attending school	231	89.7	[85.6, 92.8]	1543	91.0	[89.5, 92.4]	(ref)	(ref)
Lifetime substance use^c	68	23.2	[18.2, 29.1]	277	13.7	[12.0, 15.6]	1.91	[1.37, 2.66]
Major depressive disorder^d	72	26.7	[21.2, 33.1]	169	8.7	[7.5, 10.1]	3.81	[2.70, 5.39]
Disordered eating behaviour^e	13	5.1	[2.8, 9.1]	39	2.3	[1.6, 3.2]	2.33	[1.14, 4.76]
Bullied in past 12 months	126	48.9	[42.3, 55.6]	473	27.9	[25.6, 30.3]	2.48	[1.86, 3.30]
K10 clinical cut-off
Below 19	187	71.0	[64.8, 76.5]	1592	92.6	[91.2, 93.7]	(ref)	(ref)
19 or above	77	29.0	[23.5, 35.2]	142	7.4	[6.3, 8.8]	5.08	[3.59, 7.19]
Self-esteem^f
Low (≤17)	32	11.0	[7.7, 15.4]	47	2.7	[2.0, 3.7]	4.39	[2.64, 7.29]
Healthy (>17)	232	89.0	[84.6, 92.3]	1687	97.3	[96.3, 98.0]	(ref)	(ref)
Mental health service use^g	87	31.1	[25.4, 37.3]	262	14.8	[13.0, 16.7]	2.60	[1.90, 3.56]
Parental mental illness	102	39.1	[32.7, 45.8]	636	37.3	[34.9, 39.8]	1.08	[0.80, 1.45]
Hours of sleep
Insufficient (<8 hours)	153	54.4	[47.8, 60.8]	680	36.2	[33.7, 38.7]	2.11	[1.60, 2.78]
Sufficient (≥8 hours)	111	45.6	[39.2, 52.2]	1054	63.8	[61.3, 66.3]	(ref)	(ref)
Social isolation (0–5)^h
M (SE)	1.08 (0.07)	–	–	0.82 (0.02)	–	–	–	–
Range	0–5	–	–	0–5	–	–	–	–
Below score 3	232	88.5	[83.6, 92.0]	1639	95.0	[93.7, 96.0]	(ref)	(ref)
Score 3 or above	32	11.5	[8.0, 16.4]	95	5.0	[4.0, 6.3]	2.47	[1.54, 3.95]

n: unweighted number of respondents; %: weighted percentage; OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

Results found when comparing the individual levels of age (14, 15, 16, 17) was slightly different, where the odds ratio was non-significant (OR = 0.87, 95% CI = [0.77, 0.98]).

Cannabis or other illicit substance use in their lifetime.

Youth-reported major depressive disorder, Diagnostic Interview Schedule for Children (DISC-IV).

Binge eating/purging or low weight/problem eating group (groups devised by YMM survey team).

Adolescent Self-Esteem Questionnaire (ASQ), recoded into above (healthy) vs equal to or below cut-off of 17 (low self-esteem).

Mental health service use in past 12 months.

Although a significant U-shaped association has been reported between sleep duration and several morbidities (obesity, diabetes, cardiovascular disease; Léger et al., 2014), there was no significant association with any of the PE subtypes and excessive sleep (equal to or above 11 hours per night; Snell et al., 2007).

Multivariate regressions

Table 7 presents the factors associated with each PE subtype at the multivariate level. Factors independently associated with both auditory and visual HEs were: younger ages (14–15 years), depression, being bullied, mental health service use and insufficient sleep. The associations with DEs were less consistent: feeling spied upon and thoughts being read were the only subtypes associated with younger ages, whereas only special messages and thoughts being read were associated with depression. Feeling spied upon was the only delusional subtype associated with being bullied, psychological distress and insufficient sleep, and none were associated with mental health service use at the multivariate level.

Table 7.

Multivariate regression analysis of correlates of 12-month psychotic experiences, using odds ratios adjusted for each variable (n = 1998).

Variable	Auditory hallucinatory experiences		Visual hallucinatory experiences		Spied upon		Thought read		Special messages
Variable	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Age (binary)^a	1.51	[1.10, 2.08]	3.03	[2.10, 4.39]	1.90	[1.37, 2.63]	1.81	[1.14, 2.87]	1.24	[0.67, 2.30]
Sex	1.08	[0.80, 1.47]	0.94	[0.65, 1.35]	1.07	[0.78, 1.45]	1.35	[0.83, 2.21]	0.64	[0.36, 1.14]
School attendance status	0.69	[0.43, 1.11]	1.61	[0.97, 2.67]	1.20	[0.74, 1.96]	0.51	[0.22, 1.20]	1.72	[0.90, 3.29]
Substance use	1.48	[0.98, 2.23]	1.33	[0.82, 2.16]	1.38	[0.92, 2.07]	1.29	[0.80, 2.08]	1.54	[0.83, 2.87]
Major depressive disorder	1.81	[1.14, 2.85]	2.27	[1.38, 3.73]	1.52	[0.91, 2.51]	2.27	[1.26, 4.08]	2.02	[1.01, 4.48]
Disordered eating behaviour^b	0.75	[0.26, 2.15]	0.90	[0.28, 2.89]	1.07	[0.41, 2.74]	1.42	[0.52, 3.86]	1.07	[0.34, 3.39]
Bullied	1.72	[1.24, 2.37]	1.62	[1.09, 2.40]	1.62	[1.16, 2.25]	0.99	[0.58, 1.68]	1.50	[0.78, 2.91]
Psychological distress (K10)	1.48	[0.94, 2.33]	1.39	[0.82, 2.38]	2.45	[1.52, 3.95]	1.77	[0.89, 3.52]	1.19	[0.44, 3.22]
Self-esteem	1.15	[0.58, 2.31]	0.93	[0.46, 1.88]	1.06	[0.55, 2.04]	2.00	[0.91, 4.41]	1.38	[0.47, 4.04]
Mental health service use	1.92	[1.33, 2.76]	1.55	[1.01, 2.36]	1.33	[0.89, 1.97]	1.06	[0.61, 1.83]	1.19	[0.61, 2.33]
Parental mental illness	1.00	[0.73, 1.36]	1.16	[0.82, 1.66]	0.90	[0.65, 1.24]	1.30	[0.81, 2.10]	0.62	[0.34, 1.15]
Insufficient sleep (hours)^c	1.47	[1.09, 2.00]	1.91	[1.31, 2.77]	1.61	[1.15, 2.25]	1.12	[0.67, 1.88]	1.78	[0.97, 3.25]
Social isolation (binary)^d	1.18	[0.71, 1.97]	0.88	[0.48, 1.61]	1.80	[1.06, 3.06]	1.37	[0.67, 2.79]	0.86	[0.33, 2.23]

OR: odds ratio; 95% CI: 95% confidence interval; K10: Kessler Psychological Distress Scale.

Bold indicates significant odds ratio (p < .05).

Participants aged 14–15 years were compared to those aged 16–17 years (reference group).

Koyanagi et al. (2016) showed the association between psychotic experiences and disordered eating behaviour differs by sex. To achieve consistency, we stratified the PE-disordered eating association by sex, while including all other variables in the analysis. All associations were still non-significant, with odds ratio ranging between 1.81–2.89 for males and 0.55–1.34 for females.

Usual hours of sleep per night variable was recoded into insufficient (< 8 hours per night) versus sufficient sleep (≥ 8 hours per night).

Participants with a social isolation score of less than 3 (reference group) were compared to those who scored 3 or above.

Supplementary analyses

To further our understanding of the above associations, we repeated the analyses in the subgroup of participants who reported DEs alone (i.e. without HEs). Many of the associations presented in Table 7 persisted indicating that the associations were with DEs and not with HEs, which are commonly present in those with DEs (see Supplementary Material II). Specifically, the factors associated with DEs alone at the multivariate level were as follows: younger age, being bullied, psychological distress, insufficient sleep and social isolation. In contrast, HEs alone (auditory or visual) were associated with younger age, major depression, being bullied, mental health service use, and insufficient sleep.

The focus of the paper has been the prevalence and correlates of each PE subtype (HEs, thoughts read, special messages, spied upon). To enable comparisons with previous studies, Supplementary Material (III) reports on the main results for the ‘any PE’ variable. The results were generally consistent with those already reported in this paper. At the multivariate level, any PE was associated with a range of symptoms of mental illness and adverse psychosocial factors including a twofold to fourfold increased likelihood of depression diagnosis, being bullied, psychological distress, low self-esteem, and mental health service use.

Discussion

This study reports on the prevalence and correlates of PEs in a nationally representative sample of Australian adolescents aged 14–17 years. PEs were highly prevalent, with 12 month prevalence ranging from 3.3% (95% CI = [2.6, 4.3]) for special messages to 14.0% (95% CI = [12.3, 15.8]) for auditory HEs. This is higher than reported in the first national mental health survey, where Scott et al. (2009) found 8.4% of adolescents (13–17 years) reported hallucinations which were assessed by clinicians reviewing the descriptions of the experiences provided by respondents.

Consistent with international studies (Dolphin et al., 2015; Kelleher et al., 2012), younger adolescents were more likely to endorse HEs and DEs, with the exception of special messages. The other demographic and family history variables (sex, school attendance and parental mental illness) were not associated with each PE subtype at the multivariate level. In terms of the other domains (mental disorders/problems, psychological, environmental, intervention factors), the results supported existing evidence that subtypes are differentially implicated in psychosocial functioning (Barragan et al., 2011; Dhossche et al., 2002). At the bivariate level, each subtype was associated with increased likelihood of depression, being bullied, high levels of psychological distress, low self-esteem, mental health service use, and insufficient sleep. All these associations (except for distress and low self-esteem) persisted in the multivariate model for auditory and visual HEs, but not for DEs. Feeling spied upon was the only delusional subtype associated with numerous (being bullied, high levels of psychological distress, insufficient sleep) at the multivariate level, highlighting that the presence of HEs may have more clinical relevance than DEs in adolescents.

To our knowledge, this is the first study outside of England (Koyanagi et al., 2016) to investigate the relationship between PEs and disordered eating. Unlike Koyanagi et al. (2016), we did not find a significant association between disordered eating behaviours and any type of PE; even when stratified by sex as in the previous study (Koyanagi et al., 2016) (see Table 7). This was also the first study, to our knowledge, to investigate the association between PEs and hours of sleep, as opposed to broader sleep disturbances (Lee et al., 2012; Oh et al., 2016). We showed that adolescents sleeping less than 8 hours were almost twice as likely to report HEs or DEs, compared to adolescents sleeping eight or more hours per night. This association persisted in the multivariate analysis (for HEs and feeling spied upon) and is consistent with the broader literature which has found adolescents sleeping less than 8 hours are at increased risk of a broad range of health problems (Lui, 2004; Snell et al., 2007).

Strengths and limitations

This study was nationally representative, and we were also able to report on several PE subtypes, which is valuable considering they have different underlying mechanisms and treatment implications (Bak et al., 2005; McCarthy-Jones et al., 2014). No previous Australian study has reported on the prevalence and correlates of both HEs and DEs independently in adolescents; existing Australian studies have already reported on both of these experiences when collapsed into one broad PE variable (Lin et al., 2011; Yung et al., 2009).

This study was limited by the cross-sectional self-report data, where there may be overreporting or underreporting of certain experiences compared to an interview-based survey. However, Kelleher et al. (2011) have shown some self-reported PEs, in particular auditory and visual hallucinatory DISC-C items (with similar wording but different potential responses to the current items, e.g., ‘Have you ever heard voices or sounds that no one else can hear’: yes definitely, maybe, no never), have high concurrent validity with clinician-rated symptoms in adolescents. However, a lower prevalence was reported in the first national mental health survey (8.4%; Scott et al., 2009), where the authors used a two-stage method whereby HEs were classified by clinicians to exclude those experiences of no clinical significance. This, in addition to the difference in item wording between the DISC-IV and the Youth Self-Report (e.g. ‘I hear sounds or voices that other people think aren’t there’; Achenbach, 1991), could explain the discrepancy in PE rates between the first and second national survey. International studies report higher and more comparable 12-month PE prevalence rates, ranging from 5% to 28% in adolescent community samples (Kelleher et al., 2012; van Os et al., 2009). Major depressive disorder was the only diagnosis assessed using information from the adolescents gathered by a diagnostic instrument and therefore other youth-reported diagnoses were unavailable. This included eating disorders, where symptoms of disordered eating behaviour were assessed using questions (e.g. ‘During the past 12 months, how often did you make yourself throw up (vomit) to lose weight or avoid gaining any weight?’) answered by the adolescent participants, together with their self-reported BMI (see Supplementary Material I for details). Finally, the YMM survey did not collect data on a history of childhood trauma, which has been shown to predict PE occurrence in adolescence (Kelleher et al., 2013; Norman et al., 2012).

Future research and clinical implications

Future epidemiological surveys should explore additional dimensions of psychosis that have been largely overlooked, including cognitive and negative symptoms (e.g. disorganised speech, affective flattening, avolition; Barragan et al., 2011; Bromet et al., 2017), although symptoms such as affective flattening are difficult to assess in epidemiological studies and typically require a multi-method approach (Kring et al., 1994). Barragan et al. (2011) attempted to capture a range of different negative symptom subtypes in adolescents using the Community Assessment of Psychic Experiences (CAPE), where social withdrawal and avolition were associated with depressive symptoms while affective flattening was not. In addition to a limited PE scope, many epidemiological surveys (including the current one) cannot distinguish between a single fleeting episode and recurrent PEs, and so future studies should continue to further investigate the frequency and predictors of persistence versus remission of PEs (DeVylder et al., 2015), as there is growing evidence that frequent PEs which persist over time are more specific predictors for psychotic disorders (Dominguez et al., 2011; Poulton et al., 2000), as well as other clinical or functional impairments later in life, including increased levels of depressed mood, self-harm, and general psychopathology (Connell et al., 2016; De Loore et al., 2011).

The current study demonstrated that PEs are common in Australian adolescents, and that HEs have the greatest clinical relevance in this demographic. However, it is important to recognise that epidemiological surveys generally capture dichotomous assessments of PEs without precise characterisation of the phenomenological quality of the experience. Stanghellini et al. (2012) reported on the qualitative attributes of experiences in a clinical (23 patients with schizophrenia) and non-clinical sample (n = 60 Spanish university students). In the clinical sample, hallucinations were intimately related to the person’s identity and disrupted self-world relationship, whereas experiences in the non-clinical group were related to a circumstantial event (e.g. mourning) or were reported as an isolated phenomenon. It is likely that in the YMM survey, and in other epidemiological surveys, the endorsement of HEs and DEs captures a broad construct inclusive of true hallucinations and delusions but also responses that misinterpret the phenomenological dimensions being sought. For example, an adolescent who has reasonable concerns about privacy in school or online might report feeling spied upon with the accompanying mislabelling of these individuals.

Even though these concerns about diagnostic mislabelling are warranted, this broader and heterogeneous PE construct is clinically relevant in this demographic. van der Steen et al. (2018) explored PEs endorsed on the Composite International Diagnostic Interview (CIDI) survey that could not be confirmed by clinical interview (i.e. false-positive PEs). The authors found that these experiences were not truly ‘false’ as they indexed risk for the development of clinically relevant psychotic symptoms, development of mood/anxiety disorders, and overall reduced functioning over time. Self-reported PEs, even unconfirmed, warrant monitoring and follow-up (van der Steen et al., 2018) but also further clinical assessment of the experience beyond determining their presence or absence (Kendler, 2008). As recommended by Kendler (2008), initial screening for hallucinatory or delusional symptoms should be followed-up by clinicians with a detailed phenomenological analysis of these young people’s experiences to fully understand their context, clinical significance and, if necessary, appropriate treatment options.

Conclusion

This study found that HEs and DEs are common in adolescents and those who endorse these experiences are more likely to report behavioural/emotional problems (major depression, insufficient sleep), stressful life experiences (being bullied), and recent mental health service use, compared to those without PEs. Furthermore, this study showed variation in clinical relevance with the different types of PEs, whereby HEs were associated with an increased likelihood of depression, being bullied, mental health service use, and insufficient sleep at the multivariate level, whereas these associations with DEs were inconsistent. Overall, this study highlights the importance of screening adolescents for HEs, which have been consistently shown to be associated with an increased risk of current and future mental health and psychosocial problems in adolescents.

Supplemental Material

Supplementary_Material_III_30June2018 – Supplemental material for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents

Supplemental material, Supplementary_Material_III_30June2018 for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents by Emily Hielscher, Melissa Connell, David Lawrence, Stephen R Zubrick, Jennifer Hafekost and James G Scott in Australian & New Zealand Journal of Psychiatry

Supplemental Material

Supplementary_Material_II_30June2018 – Supplemental material for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents

Supplemental material, Supplementary_Material_II_30June2018 for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents by Emily Hielscher, Melissa Connell, David Lawrence, Stephen R Zubrick, Jennifer Hafekost and James G Scott in Australian & New Zealand Journal of Psychiatry

Supplemental Material

Supplementary_Material_I_30June2018 – Supplemental material for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents

Supplemental material, Supplementary_Material_I_30June2018 for Prevalence and correlates of psychotic experiences in a nationally representative sample of Australian adolescents by Emily Hielscher, Melissa Connell, David Lawrence, Stephen R Zubrick, Jennifer Hafekost and James G Scott in Australian & New Zealand Journal of Psychiatry

Footnotes

Acknowledgements

The authors wish to express their gratitude to the 6310 families who participated in the survey.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The second Australian Child and Adolescent Survey of Mental Health and Wellbeing was funded by the Australian Government Department of Health. Emily Hielscher is supported by the Dr F and Mrs ME Zaccari Scholarship, Australia. Associate Professor James Scott is supported by a National Health and Medical Research Council Practitioner Fellowship Grant (grant number 1105807). Professor Stephen Zubrick is supported by a Centre of Excellence grant from the Australian Research Council (CE140100027).

ORCID iD

Emily Hielscher

References

Achenbach

(1991) Manual for the Youth Self-Report and 1991 Profile. Burlington, VT: Department of Psychiatry, University of Vermont.

Armando

Nelson

Yung

et al . (2010) Psychotic-like experiences and correlation with distress and depressive symptoms in a community sample of adolescents and young adults. Schizophrenia Research 119: 258–265.

Bak

Myin-Germeys

Delespaul

et al . (2005) Do different psychotic experiences differentially predict need for care in the general population? Comprehensive Psychiatry 46: 192–199.

Barragan

Laurens

Navarro

et al . (2011) Psychotic-like experiences and depressive symptoms in a community sample of adolescents. European Psychiatry 26: 396–401.

Bromet

Nock

Saha

et al . (2017) Association between psychotic experiences and subsequent suicidal thoughts and behaviors: A cross-national analysis from the world health organization world mental health surveys. JAMA Psychiatry 74: 1136–1144.

Capra

Kavanagh

Hides

et al . (2015) Subtypes of psychotic-like experiences are differentially associated with suicidal ideation, plans and attempts in young adults. Psychiatry Research 228: 894–898.

Connell

Betts

Alati

et al . (2016) Hallucinations in adolescents and risk for mental disorders in adulthood: Prospective evidence from the MUSP birth cohort study. Schizophrenia Research 176: 546–551.

De Leede-Smith

Barkus

(2013) A comprehensive review of auditory verbal hallucinations: Lifetime prevalence, correlates and mechanisms in healthy and clinical individuals. Frontiers in Human Neuroscience 7: 1–25.

De Loore

Gunther

Drukker

et al . (2011) Persistence and outcome of auditory hallucinations in adolescence: A longitudinal general population study of 1800 individuals. Schizophrenia Research 127: 252–256.

10.

DeVylder

Lehmann

Chen

(2015) Social and clinical correlates of the persistence of psychotic experiences in the general population. Schizophrenia Research 169: 286–291.

11.

Dhossche

Ferdinand

Van Der Ende

et al . (2002) Diagnostic outcome of self-reported hallucinations in a community sample of adolescents. Psychological Medicine 32: 619–627.

12.

Dolphin

Dooley

Fitzgerald

(2015) Prevalence and correlates of psychotic like experiences in a nationally representative community sample of adolescents in Ireland. Schizophrenia Research 169: 241–247.

13.

Dominguez

Wichers

Lieb

et al . (2011) Evidence that onset of clinical psychosis is an outcome of progressively more persistent subclinical psychotic experiences: An 8-year cohort study. Schizophrenia Bulletin 37: 84–93.

14.

Favaro

Caregaro

Tenconi

et al . (2009) Time trends in age at onset of anorexia nervosa and bulimia nervosa. Journal of Clinical Psychiatry 70: 1715–1721.

15.

Hafekost

Lawrence

Boterhoven

Haan

et al . (2016) Methodology of young minds matter: The second Australian child and adolescent survey of mental health and wellbeing. Australian and New Zealand Journal of Psychiatry 50: 866–875.

16.

Hafekost

Boterhoven

Haan

Lawrence

et al . (2017) Validation of the Adolescent Self-Esteem Questionnaire. Technical report, Telethon Kids Institute, Perth, WA, Australia (accessed on 15 May, 2017).

17.

Hielscher

DeVylder

Saha

et al . (2017) Why are psychotic experiences associated with self-injurious thoughts and behaviours? A systematic review and critical appraisal of potential confounding and mediating factors. Psychological Medicine 48: 1410–1426.

18.

Honings

Drukker

Groen

et al . (2016) Psychotic experiences and risk of self-injurious behaviour in the general population: A systematic review and meta-analysis. Psychological Medicine 46: 237–251.

19.

Kelleher

Connor

Clarke

et al . (2012) Prevalence of psychotic symptoms in childhood and adolescence: A systematic review and meta-analysis of population-based studies. Psychological Medicine 42: 1857–1863.

20.

Kelleher

Harley

Murtagh

et al . (2011) Are screening instruments valid for psychotic-like experiences? A validation study of screening questions for psychotic-like experiences using in-depth clinical interview. Schizophrenia Bulletin 37: 362–369.

21.

Kelleher

Keeley

Corcoran

et al . (2013) Childhood trauma and psychosis in a prospective cohort study: Cause, effect, and directionality. American Journal of Psychiatry 170: 734–741.

22.

Kendler

(2008) Why does psychiatry need philosophy. In: Kendler

(ed) Philosophical Issues in Psychiatry: Explanation, Phenomenology, and Nosology. Baltimore, MD: Johns Hopkins University Press, pp. 1–16.

23.

Koyanagi

Stickley

Haro

(2016) Psychotic-like experiences and disordered eating in the English general population. Psychiatry Research 241: 26–34.

24.

Kring

Alpert

Neale

et al . (1994) A multimethod, multichannel assessment of affective flattening in schizophrenia. Psychiatry Research 54: 211–222.

25.

Lawrence

Hafekost

Johnson

et al . (2016) Key findings from the second Australian child and adolescent survey of mental health and wellbeing. Australian and New Zealand Journal of Psychiatry 50: 876–886.

26.

Lee

Cho

et al . (2012) The relationship between psychotic-like experiences and sleep disturbances in adolescents. Sleep Medicine 13: 1021–1027.

27.

Léger

Beck

Richard

J-B

et al . (2014) The risks of sleeping ‘‘too much’’: Survey of a national representative sample of 24671 adults (INPES Health Barometer). PLoS ONE 9: e106950.

28.

Lin

Wigman

Nelson

et al . (2011) The relationship between coping and subclinical psychotic experiences in adolescents from the general population – A longitudinal study. Psychological Medicine 41: 2535–2546.

29.

Lui

(2004) Sleep and adolescent suicidal behavior. Sleep 27: 1351–1358.

30.

McCarthy-Jones

Trauer

Mackinnon

et al . (2014) A new phenomenological survey of auditory hallucinations: Evidence for subtypes and implications for theory and practice. Schizophrenia Bulletin 40: 231–235.

31.

McGee

Williams

Poulton

(2000) Hallucinations in nonpsychotic children. Journal of the American Academy of Child and Adolescent Psychiatry 39: 12–13.

32.

McGrath

Saha

Al-Hamzawi

et al . (2015) Psychotic experiences in the general population: A cross-national analysis based on 31,261 respondents from 18 countries. JAMA Psychiatry 72: 697–705.

33.

McGrath

Saha

Al-Hamzawi

et al . (2016) The bidirectional associations between psychotic experiences and DSM-IV mental disorders. American Journal of Psychiatry 173: 997–1006.

34.

Moreno

Nuevo

Chatterji

et al . (2013) Psychotic symptoms are associated with physical health problems independently of a mental disorder diagnosis: Results from the WHO World Health Survey. World Psychiatry 12: 251–257.

35.

Norman

Byambaa

et al . (2012) The long-term health consequences of child physical abuse, emotional abuse, and neglect: A systematic review and meta-analysis. PLoS Medicine 9: e1001349.

36.

Singh

Koyanagi

et al . (2016) Sleep disturbances are associated with psychotic experiences: Findings from the National Comorbidity Survey replication. Schizophrenia Research 171: 74–78.

37.

Poulton

Caspi

Moffitt

et al . (2000) Children’s self-reported psychotic symptoms and adult schizophreniform disorder: A 15-year longitudinal study. Archives of General Psychiatry 57: 1053–1058.

38.

Sawyer

Arney

Baghurst

et al . (2001) The mental health of young people in Australia: Key findings from the child and adolescent component of the national survey of mental health and well-being. Australian and New Zealand Journal of Psychiatry 35: 806–814.

39.

Scott

Martin

Bor

et al . (2009) The prevalence and correlates of hallucinations in Australian adolescents: Results from a national survey. Schizophrenia Research 107: 179–185.

40.

Scott

Welham

Martin

et al . (2008) Demographic correlates of psychotic-like experiences in young Australian adults. Acta Psychiatrica Scandinavica 118: 230–237.

41.

Shaffer

Fisher

Lucas

et al . (2000) Diagnostic interview schedule for children, version IV (NIMH DISC-IV): Description, differences from previous versions and reliability of some common diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry 39: 28–38.

42.

Silove

Austin

Steel

(2007) No refuge from terror: The impact of detention on the mental health of trauma-affected refugees seeking asylum in Australia. Transcultural Psychiatry 44: 359–393.

43.

Snell

Adam

Duncan

(2007) Sleep and the body mass index and overweight status of children and adolescents. Child Development 78: 309–323.

44.

Stanghellini

Langer

Ambrosini

et al . (2012) Quality of hallucinatory experiences: Differences between a clinical and a non-clinical sample. World Psychiatry 11: 110–113.

45.

van der Steen

Myin-Germeys

van Nierop

et al . (2018) ‘False-positive’ self-reported psychotic experiences in the general population: An investigation of outcome, predictive factors and clinical relevance. Epidemiology and Psychiatric Sciences 16: 1–12.

46.

van Os

Linscott

Myin-Germeys

et al . (2009) A systematic review and meta-analysis of the psychosis continuum: Evidence for a psychosis proneness-persistence-impairment model of psychotic disorder. Psychological Medicine 39: 179–195.

47.

Varghese

Scott

Welham

et al . (2011) Psychotic-like experiences in major depression and anxiety disorders: A population-based survey in young adults. Schizophrenia Bulletin 37: 389–393.

48.

Wolter

(2007) Introduction to Variance Estimation, 2nd Edition. New York: Springer.

49.

Yung

Lin

(2016) Psychotic experiences and their significance. World Psychiatry 15: 130–131.

50.

Yung

Nelson

Baker

et al . (2009) Psychotic-like experiences in a community sample of adolescents: Implications for the continuum model of psychosis and prediction of schizophrenia. Australian and New Zealand Journal of Psychiatry 43: 118–128.

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