angelo.psychosis characteristics (thesis)may25th2015 (final version) (1)

Discrimination Race Gender amp APPS 1

Discrimination may contribute to a higher endorsement of Attenuated Positive Psychotic Symptoms (APPS) in black compared to white college students irrespective of gender

Angelo Laine

Mentor Deidre Anglin PhD

Department of Psychology

City College of New York

May 25th 2015


Abstract

Background Studies have shown that psychotic disorders are part of a spectrum

meaning that their symptoms extend to the general population in attenuated forms Both

clinically psychotic individuals and attenuated forms of the disorders are subject to the same risk

factors

Currently we know that the incidence of schizophrenia is gendered and that ethnic

minorities are at increased risk for psychosis Ochoa et al (2008) found a 14 rate ratio male to

female in the incidence of schizophrenia but studies are inconclusive at finding similar results in

the prodromal phase of psychosis Ethnic minorities have been found to be at a higher risk for

psychosis and a higher endorsement of attenuated positive psychotic symptoms in the presence

of discrimination

Objective The study had two main aims first a women to men difference in APPS

should be present in blacks as long as it is sufficiently mediated by discrimination since

discrimination is a gendered experience secondly due to discrimination such gender difference

in APPS in the black group should be significantly higher than the ones that may be found in

white individuals

Methods amp Results A sample of 1633 young adults who self-identified as black or

whites were recruited from two US Northeast colleges They completed self-report

questionnaires of APPS experiences of discrimination Our results showed that black individuals

irrespective of gender reported more discrimination endorsed more APPS and distressing APPS

than white individuals We also found a gender difference among black individuals in term of

APPS categories and discrimination However discrimination may only partially mediate the

relation between race and gender in regard to APPS in the black sub-sample


Psychosis characteristics

Psychotic disorders including schizophrenia are disorders exhibiting symptoms in at

least one or more of the following domains ldquodelusions hallucinations disorganized thinking

(speech) grossly disorganized or abnormal motor behavior (including catatonia) and negative

symptomsrdquo (American Psychiatric Association [APA] 2013 p 87) Delusions and hallucinations

are also known as positive symptoms which are considered to be excess in onersquos normal

behavior (Sims 2002) The definition of delusion is to firmly hold onto beliefs that are

contradictory to reality and to counterevidence (APA 2013) Such beliefs may appear in

different forms Persecutory delusions are the beliefs that one is under the constant threat of

harm harassment and so on from individuals organizations or other groups (APA 2013)

Grandiose delusions are an exaggerated sense of self in regard to onersquos abilities wealth or fame

(APA 2013) Somatic delusions are excessive preoccupations in regards to onersquos health (APA

2013) Referential delusions refer to the beliefs that gestures comments made by people objects

or even environmental cues are actually directed to oneself (APA 2013) Hallucinations refer to

auditory or visuals experiences reported by psychotic individuals that happen in the absence of

stimulus from the environment

Negatives symptoms which are comprised of avolition asociability anhedonia blunted

effect and alogia refer to deficit in normal behavior (Sims 2002) Such symptoms are more

common in schizophrenia than other psychotic disorders (APA 2013) Psychotic individuals

may for example regress from their daily hygiene routine from work or school work also

known as avolition They may speak very little or not speak at all for an extended amount of

time a symptom known alogia They may lose their interests in social activities and interactions


such as losing contact with friends which results in their own isolation also known as

asociability They experience less pleasure and express less expression emotion known as

blunted effect and anhedonia

Disorganized thinking refers to onersquos incoherent and incomprehensible speech pattern

Grossly disorganized or abnormal motor behavior refers to onersquos inability to conform to

community standards Those behaviors are varied One group of such behaviors catatonia for

example is defined by a ldquomarked decrease in reactivity to the environmentrdquo (APA 2013 p 88)

Catatonic behaviors can be a ldquoresistance to instructions or negativismrdquo the ldquomaintenance of a

rigid or inappropriate posturerdquo known as mutism the ldquocomplete lack of verbal and motor

responsesrdquo known as stupor finally ldquopurposeless and excessive motor activity without obvious

causesrdquo also known as catatonic excitement (APA 2013 p 88) But abnormal motor behaviors

can also be very ldquochildlike to unpredictable agitationrdquo that may interfere with their daily

activities (APA 2013 p 88)

Schizophrenia and the psychotic spectrum

Schizophrenia is a brain disorder that ldquoinvolves a range of emotional cognitive and

behavioral dysfunctionsrdquo (APA 2013 p 99) According to the 5th and latest edition of the

diagnostic statistical manual for mental disorders (APA 2013) the diagnostic criteria belonging

to schizophrenia are as follow the patient should exhibit symptoms belonging to two or more of

the psychotic domains for a significant amount of time during a 1 month period At least 6

months of marked decrease in level of functioning in one or more major areas like work or

interpersonal relationships should be present Finally none of the symptoms can be explained by

any other disorders Persecutory delusions and auditory hallucinations are the two most


commons schizophrenic symptoms (Sartorius Shapiro Jablonksy 1974) Currently in the

United States about 03 to 07 of the population suffers from schizophrenia (APA 2013)

Schizophrenia is surprisingly a very costly disease In the year 2002 in the United States

Wu et al (2005) estimated that schizophreniarsquos financial impact to be at 627 billion US dollars

(USD) from data collected from privately and publicly insured patients Similar results were

found in other countries Phanthunane Whiteford Vos Bertram (2012) estimated from data

collected in 2008 that schizophreniarsquos financial impact in Thailand was 925 million USD

Magalore amp Knapp (2007) estimated schizophreniarsquos cost to be 67 billion pounds in England for

the 20042005 year It should be noted that in all three studies indirect costs consisted the

majority of the financial impact Wu et al (2005) only attributed 225 billon USD of direct costs

associated to the disease in term of medications treatments and else while Magalore amp Knapp

(2007) attributed 2 billion of the financial costs of the disease to direct cost Phanthumane et al

(2012) said that unemployment was the biggest culprit in the total financial costs in Thailand

It is possible to predict someonersquos risk The most well-known way to predict the risk of

schizophrenia in individuals is through their family history Indeed it has been shown that

schizophrenia has a strong genetic component While the general population lifetime risk to

develop schizophrenia is less than 1 children whose at least one of their parents has

schizophrenia have a 13 chance to develop it too (McGuffin Gottesman Farmer 1987) The

risk is higher in fraternal and identical twins with a 17 and 48 risk respectively (Mc

Gruffin et al 1987)

Furthermore schizophrenia and other psychotic disorders are part of the psychotic

spectrum The psychotic spectrum refers to the continuum of distressing or non-distressing


subclinical psychotic symptoms experienced by the general population that may in turn progress

to the full blown clinical symptoms diagnosed in psychotic disorders ((Dhossche et al 2002

Hanssen et al 2005 Wiles et al 2006 Dominguez et al 2011) In other words the diagnosis of

prodromal symptoms in an individual does not mean he will be psychotic in the future As a

matter of fact subclinical psychotic symptoms are actually common in the general population A

recent systematic meta-analysis found a median prevalence of 5 and a median incidence rate of

3 for prodromal psychotic symptoms and 75-90 of those symptoms disappeared over time

(van Os Linscott Myin-Germeys Delespaul and Krabbendam 2009) To reflect the uncertain

transient nature of subclinical psychotic symptoms a group of researchers proposed the term at

ldquorisk for mental staterdquo to imply that the individuals in the early phase of the disorder may never

fully develop the disorder They preferred their term to the word ldquoprodromerdquo which they stated

was a medical term that refers to the early signs of a disease and therefore alluded that the

disease will soon follow up (Yung et al p286) Indeed ldquofalse false positiverdquo individuals are

people who ldquowould have the same vulnerability markers as the true positives who do progress

from an at-risk mental state to psychosis but because of resilience or protective factors do not

make the transitionrdquo ( Yung et al 1996 p 288) Only a small amount of people with prodromal

symptoms makes the conversion to psychosis Yung et al (1996) found that only 212 of their

small sample (N=33) of at-risk for psychosis patients transitioned within 12 months In another

study about 40 of the high risk patients transitioned to clinical psychotic disorders within 12

months (Yung et al 1998)

The development of subclinical psychosis and its transition to clinical psychosis is

dependent on many factors After determining the amount of patients who transitioned to

psychosis Yung et al (2003) determined what were the highly predictors of psychosis of their


sample (N=49) They have found that individuals who have been experiencing the prodromal

symptoms for a long amount of time before diagnosis who were functioning poorly at intake and

expressed severe psychotic symptoms were at a significant risk to transition to psychosis

Subsequently the risk factors associated with the developing schizophrenia are the same as for

developing its milder symptoms Van Os et al (2009) did a systematic review of 1558 papers

published in the past 5 years at the time of the publication of their article They reported the same

risk of developing schizophrenia were also in its prodromal symptoms We can infer from those

information that the development of subclinical psychosis is heavily dependent onersquos level of

exposure to psychotic risk factors (van Os et al 2009) which in turn may transition to clinical

psychosis due to the length and severity of the symptoms experienced causing a decrease in the

level of functioning in the individual (Yung et al 1998)

Diagnosis of Subclinical Psychotic Symptoms

There are many instruments that can be used to diagnose prodromal symptoms in

individuals and the Structured Interview for Prodromal Syndromes (SIPS) is one of those

instruments (McGlasan et al 2001 Miller et al 2003 Rosen et al 2002 Miller et al 1999) A

trained professional expecting to use the SIPS will find the following measures the scale of

prodromal symptoms (SOPS) the schizotypal Personality Disorder Checklist based on the DSM

IV the family history questionnaire and the global assessment of functioning scale (Miller et al

2003) The family history section assesses the patientrsquos socio-demographic background

Information regarding a personal or family history of psychosis trauma and substance use is also

gathered there The Schizotypal personality disorder assesses the presence of the disorder in the

patient Five or more of the symptoms as listed in the DSM IV must be met for a full diagnosis

The SOPS is a 19 item questionnaire used to assess the severity onset and frequency of


psychotic symptoms in the patients When investigating the presence or non-presence of

symptoms in positive negative disorganized and general symptoms a trained professional rates

the items on a 0 to 6 point scale along with their frequency and date of onset A score of 0-2

means that symptoms are normal or absent A score of 3-5 means that the symptoms are

prodromal and a score of 6 means psychotic Of course a trained professional should always

note of the onset of the symptoms and indicate whether they have aggravated in the last 12

months (McGlashanWalshWood 2010) The Global Assessment of functioning assesses the

level of functioning of the patient over the past 12 months The assessment is scored on 10

categories of 10 scores ranging from 1 to 100 The patient receives two score based on its present

and 12 month prior level of functioning (McGlashanWalshWood 2010)

After the interview information gathered on the measures is analyzed based on two main

criteria the presence of psychotic syndrome (POPS) and the Criteria of psychosis risk

syndromes (COPS) (Miller et al 2003 Miller et al 2010) On the one hand the Information

meeting POPS criteria mean that the individual has been experiencing symptoms for a while and

currently meet the criteria for psychosis On the other hand informationrsquos meeting COPSrsquo

criteria can be categorized in one of the following three categories brief intermittent psychotic

symptom (BIPS) attenuated positive symptom (APPS) and genetic risk and deterioration

(GRD) All three symptom categories were first identified by Yung et al (1996 1998) Miller et

al (2003) defines each COPS symptom as follow BIPS is defined by the psychotic symptoms

have been experienced in the past three months but are too brief and too infrequent to be

considered at risk for a full psychosis syndrome GRD is for individuals who experienced a 30

decreased in GAF scored meet the criteria for schizotypal personality disorder or have a first

relative who has the disorder APPS is defined by the mild positive psychotic symptoms that


occurred at least once a week in the past month and which severity have worsened in the past

year that put the patient at risk to form a fully diagnosable psychotic disorder The SIPS was

modeled after Yung et al criteria of prodromal psychotic symptoms (Miller et al 1999) A

validity study found that 50 of prodromal patients who were diagnosed with the SIPS

transitioned to clinical psychosis within a 12 month period of time (Miller et al 2003)

Schizophrenia Gender and Prodromal phase

Extensive research on schizophrenia revealed some definitive gender differences in terms

of characteristics of the disorder such as age of onset premorbid condition symptomatology

characteristics course of illness and comorbidity of substance use (Ochea S Usall J Labad

X Kulkarni J 2012) An earlier age of onset is seen in men but seems to disappear in the

presence of family history in schizophrenia (Goldstein Tsuang Faraone 1989 Gureje 1991

Galderisi bucci Ucok Peuskens 2011 Ochoa et al 2006 Albus et al 1994 Peraumllauml

Kuoppasalami Partonen Kieseppauml 2007) For example Galderisi et al (2011) found the age of

onset in men was around 22 years and around 24 years in women Men report a higher

comorbidity of cannabis alcohol cocaine and hallucinogen use than women (Galderisi et

al2011 Cotton et al 2009 Wade Harrigan Edwards Burgess Whelan McGorry 2006 Foti

Kotov Guey Bromet 2010 Rodriguez-Jimenez et al 2008) Also while many studies did not

find gender differences in symptomatology (Addington Addington Patten 1996 Lindstrom

Knorring 1994 Hayashi Igarashi Yamashina Sunda 1995) those that did find a difference

reported more negative and disorganization symptoms in men than women (Galderisi et al

2011 Morgan Castle Jablensky 2008 Abel Drake Goldstein 2010) Women are found to

have had better premorbid condition and course of illness than men (Shatasel Gur Gallacher


Heimberg Gur1992 Morgan Castle Jablensky 2008Uggerby Nielsen Correll Nielsen 2011

Usall Araya Ochoa Busquets gost Marquez 2001)

Yet it is widely regarded that no gender difference exists in the prevalence of

schizophrenia (Mc Grath Saha Chant Welham 2008 Saha Chant welham Mc Grath 2005)

Indeed Mc Grath et al (2008) conducted a meta-analysis of 383 studies in regard to prevalence

incidence and mortality risks and found no gender difference in the prevalence of schizophrenia

But he and his team (2008) found a 14 male to female rate ratio in the incidence of

schizophrenia Such results were consistent with other research also demonstrating a higher

incidence of schizophrenia in men (Saha Chant welham Mc Grath 2005 Alerman Kahn

Selten 2003 Abel Drake Goldstein 2010) Furthermore the number of research finding a

higher male incidence in schizophrenia vastly outnumber those studies that find the inverse (Mc

Grath Saha Welham Saadi MacCauley amp Chant 2004)

An attempt at understanding such discrepancy in the research could be made by looking

at the definition of the two words According to Mc Grath et al (2008) incidence measures the

amount of new cases of a disorder in a population during a specific period of time while

prevalence relates to the measure of proportion ldquoof surviving individuals who manifest a disorder

at a specific time or during a specific periodrdquo (p68) From the definition of the words a higher

mortality risk in men seems to be the answer to the discrepancy For example Galderisi et al

(2012) found that males significantly abuse alcohol more than women Rodriguez-Jimenez et al

(2008) found a higher consumption of cocaine and hallucinogen and cannabis in men While

women are more likely to attempt suicide (Austad Joa Johannessen Larsen 2013) men are

more likely to succeed in their suicide attempt (Test Burke Wallisch 1990 Silvia 2010) But

Mc Grath et al (2008) seem to refute such hypothesis by reporting that they did not find a sex


difference in the mortality risk for all causes of mortality More research is needed to determine

if health related issues in regard to substance use and suicide risk are enough in explaining the

discrepancy in the gender difference in incidence and in prevalence research

In the prodromal phase very few studies have looked at the gender difference in

incidence premorbid condition and so on Of those studies results found so far are mixed As it

was explained previously psychosis is part of a spectrum In other words gender difference

found in clinical psychotic disorders should also be found in subthreshold symptoms It is with

this assumption that Barajas Ochoa Obiols Lulucats-jo (2015) decided to conduct a literature

review on the gender difference in at-risk individuals They were able to find only 12 studies

Some of those studies results were consistent with gender differences in clinical psychosis some

were not Results that are consistent with current gender research in psychosis are that men

exhibit more severe negative symptoms worst level of functioning than women (Barajas et al

2015) While women receive more social support and exhibited more affective symptoms than

men (Barajas et al 2015) In terms of incidence Barajas et al (2015) found some studies that

show a higher male to female incidence (eg Von Os et al 2009) others found the inverse or no

difference Due to the low amount studies examined Barajas et al (2015) said that their results

could not be generalized

Race amp Psychosis

Many studies have shown that ethnic minorities especially blacks living in

predominantly white developed countries are at a higher psychosis risk (Fearon et al 2006

Bhugra et al 1997 Mc Neil 2005 Hutchinson et al 1996 Spronton amp Nazroo 2002 Sohler amp

Bromet 2003 Bresnahan et al 2007 Johns amp Von OS 2000) Three large sample incidence


and prevalence studies from UK and the US illustrate the high risk for psychosis in ethnic

minority groups The Aetiology and Ethnicity of Schizophrenia and Other Psychosis (AESOP)

was a study conducted by Fearon et al (2006) across three psychiatric centers in the UK for two

years The study examined the psychotic incidence rate for different ethnic groups (N=568) with

an age range of 16 to 54 Potential participants could only participate to the study once and

should exhibit psychotic symptoms in delusions hallucinations thought disorders and negative

symptoms that characterized them as at-risk individuals (Fearon et al 2006) Participants also

identified themselves as African-Caribbean Black African Asian Mixed White British and

white other The results show that when adjusted for sex and age all the categorical groups were

at an increased incidence rate ratio (IRR) for psychosis compared to white British But the IRR

for psychosis in Black Caribbean (67 95 confidence interval (CI) = 54-84) and Black

African ( 41 CI=32-53) were the highest in comparison to white British Two things can be

inferred from this study The first is that being an immigrant is linked to an increase risk of

developing schizophrenia The second is that being a black immigrant makes you more likely

than the rest of the population to develop psychotic symptoms

The Ethnic Minority Psychiatric Illness Rates in the Community (EMPIRIC) is a

community-based prevalence study in the UK that was conducted by Spronton amp Nazroo (2002)

The different ethnic groups of the study were Indian Pakistani Bangladeshi Black Caribbean

Irish and White British Researchers calculated the age-adjusted risk ratio of different ethnic

groups (N=4281) They found that African Caribbean were at a higher odds (184 CI= 111-

303) of expressing psychotic symptoms than whites Similarly as AESOP onersquos race and

minority status matter in the development of psychosis The difference to the AESOP study is

that the risk here is milder and only one ethnic black group was examined


In the US Breshnan et al (2007) looked at the incidence rate of schizophrenia for

African American and white in birth cohort To be eligible for the study the participantrsquos mother

should have been enrolled during pregnancy at the Alemada County Kaiser Permanente Medical

Care Plan clinics between the years 1956-1966 Only one offspring per family was allowed to

participate in order to eliminate siblingsrsquo correlated observations (Breshman et al 2007)

Selected participants (N=6636) were followed during the years 1981-1997 The results found

that African-American were two times more likely to develop schizophrenia than white after

adjustment for socio-demographic variables (Breshman et al 2007) Breshman et al (2007) is

one the few incidence studies in psychosis conducted in the US The fact that the participants and

their mothers are US-born put this study at a significant advantage over the other two It allows

to look at the risk to develop schizophrenia based solely on race From what we see just like in

other two studies being black constitutes a significant risk factor in relation to schizophrenia

which further support that minorities are in increased risk of psychosis

Unsurprisingly the risk for psychosis decreases when an ethnicity is no longer a minority

(Bhugra et al 2000 Hickling amp Rodgers-Johnson 1995 Mahy et al 1999 Boydell et al 2001)

First-onset studies for psychosis that were conducted in Trinidad (Bhurga et al 1996) Jamaica

(Hickling amp Robertss-Johnson 1995) and Barbados (Mahy et al 1999) found similar incidence

rate ratio across them (236 in Jamaica 32 in Barbados and 22 in Trinidad) Those rates are

much lower than the ones found in African Caribbean living in the UK (Mahy et al 1999 Fearon

et al 2006) Velinget al (2008) found that immigrants living in low-ethnic density

neighborhood were at significantly increased adjusted rate ratio for psychosis (236) than those

who live in neighborhood with high-ethnic density neighborhood (136) Boydell et al (2001)


found that black individuals living in neighborhood where they were a minority were at a higher

risk of schizophrenia than those who lived in neighborhood where they were better represented

Racial discrimination psychosis amp Black

According to Cater (2007) racial discrimination is a type of racism which role is to create

a distance whether intentionally or not between the dominant racial group members and the

minority racial groups through behaviors thoughts policies and strategies Following this

definition it is logical to infer that racial discrimination can be experienced in a wide range of

real life setting as long as it enables members of the dominant group to ostracize minorities That

is why the self-report questionnaire Experiences of Discrimination (EOD) (Krieger Smith

Naishadam HartmanBadeau 2005) ask both the place and the frequency where discrimination

is experienced People can be discriminated at work school hospital courts and other places

overtly or perniciously

The discrimination that someone receives may be gender-specific Sexism is the word

used for discrimination to the opposite-sex Although the word gives the impression of going

both ways it is mostly expressed toward women After all discrimination is mostly expressed by

the dominant group and in the US men are the dominant sex For example women may be

barred from specific position or income because of their gender a process known as the glass

ceiling The US census Bureau (2011) reported that women in general earn 23 percent less than

men in 2010

Sexism is worse in ethnic minorities Women from ethnic minorities have to deal with

negative perceptions related to their raceethnicities along with negative perceptions related to


their gender leaving them extremely disadvantaged In the same income example presented

before women typically earn less than their men counterpart within the same raceethnicity

African American women earn 111 percent less than African American men Hispanic women

earn 223 percent less than Hispanic men and Asian Women earn 87 percent less than Asian

men (US census Bureau 2011)

Once experienced racial discrimination is highly personal and painful (Delgado 1982

Landrine amp Klonoff 1996) and can lead to a series of negative physical psychological

responses and even worse health behaviors in the individual (Pascoe amp Richman 2009 William

amp Mohammad 2009 Brown et al 2000 Krieger et al 2013) Black individuals who

experienced discrimination are more likely to exhibit psychological distress anxiety depression

than those who do not experience discrimination (eg Brown et al 2000) In turn the

consequences of racial discrimination differ based on gender Black women who experience

discrimination are more likely than men to express symptoms of depression and psychological

distress (eg Brown et al 2000 Lambert English amp Ialongo 2014)

In the literature racial discrimination represents a major link between the risk of

psychosis and the ethnic minority status of an individual For example Anglin Lighty

Greenspoon and Ellman (2014) conducted a series of self-report questionnaires based on

attenuated Psychotic Positive Syndromes (APPS) discrimination depression and anxiety among

a US based young adults ethnic minorities population (N=650) Participants self-identified as

Hispanic Asian Black White and other They reported that ethnic minorities endorsed racial

discrimination more than white in the sample They also found that racial discrimination was

associated with all of the domains of APPS and individuals exposed to racial discrimination were

more likely to endorsed eight or more distressing APPS symptoms meaning that they are likely


to be at a high risk for psychosis (Anglin et al 2014) In a follow up study to the EMPIRIC

study they found that discriminatory exposure to racist insults (odd ration (OR=23 95

CI=14- 34 plt0001) and unfair treatment at work (OD=21 CI=13-34 P=0004) put someone

at the highest risk of mental disorders Black individuals in particular were at increased risk of

mental disorders when they were unfairly treated at work (OD=29 CI=12-73 p=002) (Bhui et

al 2005)

In addition the frequency with which someone is exposed to discriminatory situations is

also an important link to psychosis Veling Selten Susser Laan Mackenbach Hoek (2007)

conducted a study in the Netherlands on different ethnic minorities They found that the risk for

psychosis was positively linked to the level (very low low medium high) of perceived

discrimination reported among ethnic minorities (Veling et al 2007) For example a very low

report of discrimination was associated with an incidence rate ratio (IRR) of psychosis equals to

12 (CI=081-190) after adjustment for age and gender While a high report of discrimination

was associated with an IRR = 400 (CI=300-535)

Current Study

We know so far that psychosis is a spectrum that shares the same risk factors regardless if

itrsquos clinically diagnosed or still in its sub-threshold stage (Von Os et al 2009) At least in the

level of clinical psychosis convincing gender differences were found in serval aspects of the

disorder The rate ratio of men to women was 14 meaning that close to three men compared to

two women are newly clinically diagnosed for psychosis at any point in time (McGrath et al

2008) Ethnic minorities especially black individuals (Fearon et al 2006) are a population at a

higher risk to psychosis associated to the type and frequency of discrimination they are exposed


to (Velin et al 2007 Bhui et al 2005) At the subthreshold level discrimination was associated

to APPS a category of prodromal symptoms for ethnic minorities (Anglin et al 2014)

Subsequently it can be inferred from the information presented above that first a women to

men difference in APPS should be present in blacks as long as it is sufficiently mediated by

discrimination since discrimination is a gendered experience secondly due to discrimination

such gender difference in APPS in the black group should be significantly higher than the ones

that may be found in white individuals

To test those assumptions we tested the following hypotheses

1- Black individuals will be more discriminated against than white individuals

2 We will find a gender difference in the discrimination reported by black individuals

3- A gender difference will be found in black individuals in the report of APPS

4- APPS will be higher in black than white individuals

5- Black individuals will be more likely to endorse high level of distressing positive

symptoms than white individuals

6- Discrimination will mediate the relation between APPS and gender in the black

population

Methods

Participants and Procedure


Our study sample was drawn from data collected from two large Northeast Universities

(N= 2539) Data collected from one of the universities was composed of primarily emerging

young adults (19 to 29 years old) from ethnic minorities Participants from this particular

university had to self-identify as African-AmericanBlack African Descent or as an immigrant

(first or second generation) in an online subject pool to maximize the number of young ethnic

minorities possessing characteristics of high psychosis risk (Anglin Lee Yang amp Opler 2010)

Data collected from the other university was non-selective of the undergraduate students

recruited from another online subject pool across various interdisciplinary courses All

Participants completed a series of self-report questionnaires in the laboratory computer of their

respective universities The protocol was approved by the institutional review board of each

university Participants signed written consent forms and received course credit for their

participation in the study For the purpose of the study only data from black and white

individuals were analyzed (N= 1633)

Measure

APPS To assess the Attenuated Positive Psychotic Symptoms (APPS) each participant

was required to complete the Prodromal Questionnaire-Likert ( PQ Likert) ( Loewy Bearden

JohnsonRaine amp Cannon 2005 Loewy Bearden amp Cannon 2007) which is a 92-item self-

report measure of subclinical psychotic symptoms experienced in the absence of alcohol drugs

and other medications Participants mentioned whether they had experienced the PQ items in the

past month and whether they found them distressing or not The PQ Likert is composed of four

subscales scores of which the positive symptoms (APPS) (45 items eg unusual thought content

and perceptual abnormalities) have been found to have the strongest predictive value (Loewy et

al 2005)


The PQ scale is not a clinical assessment tool However Loewy et al (2007) noted that

self-report questionnaires are reliable and valid Endorsing 8 or more of positive PQ items

predicted a SIPS diagnosis (prodromal or clinical) with 90 sensitivity and 49 specificity

(Loewy et al 2005) The endorsement of 8 or more distressing APPS in the PQ scale suggest

that the individual may be at a high risk of psychosis (Loewy et al 2007) For the purpose of

the study a dichotomous variable that compared High (8 or more positive symptoms) vs Low (4

or less positive symptoms) levels of endorsement of Distressing Positive PQ was created We

also created a dimensional variable to look at the score of number of APPS endorsed for each

participant (0-45)

Self-reported Experiences of Discrimination (EOD) were determined using the EOD

Instrument (Kriegeret al 2005) a questionnaire which assess the location of the experienced of

the discrimination and its frequency The nine locations assessed are as follow school getting a

job work getting medical care getting service in a store getting credit or a loan on the street

and from the police or the courts The frequency of occurrence of each situation was endorsed on

a three point scale by each participant (1-3) where 1 equates to once and 3 equates to four or

more times (Krieger et al 2005) Two new variables were created for our study First a

dimensional variable called ldquoEODfreqrdquo was created to get for each participant the sum all of

the frequencies of occurrence of experienced discrimination (0-27) The second variable was also

a dimensional variable called ldquoEODscalerdquo to get into a singular number the sum of all the

different discriminatory items domains endorsed by each participant (0-9)

Sociodemographic data Sociodemographic data collected from the participants were

their age (years) gender (female male) immigration status raceethnicity proficiency in

English Raceethnicity was determined in the question ldquochoose one category that best captures


how you see yourselfrdquo and given several options Responses were grouped into several

categories Black white Hispanic Asian Participants also say whether they were born in the

US or not A ldquoWhitevsblackrdquo binary was created for the purposes of our analyses where the

white group would serve as the reference group Black and white individuals were put in the

same categorical variable since only those two groups are of interest for our study Two other

variables combining gender and race were created A 4 level variable called ldquoracegenderrdquo was

created and contained the different combination of gender and race possible such as white male

white female black male black female Finally a ldquosexXrace interactionrdquo variable was created

by multiplying the variables whitevsblack and gender in order to look at the possible interaction

of sex and race on the endorsement of APPS

Statistical analyses

Mean groups differences in gender race and in gender in combination with each race

separately in the endorsement of PQ positive symptoms frequency and type of discrimination

were assessed using one factor and two factors ANOVA A crosstab Chi square of PQ levels

High vs Low by ldquoracegenderrdquo was performed in order to determine if there was a difference in

the endorsement of PQ positive distressing symptoms in the whole sample Lastly we did a two-

step linear regression analysis of APPS in terms of gender and EODfreq for the black population

of the sample to assess whether discrimination mediated the relation between race and gender in

regard to endorsement of APPS Gender was in in the first step while EODfreq was added in the

second step


Results

Sample characteristics

The overall demographic sample is described in Table 1 The majority of the sample was

female (729) white (686) and US born (875) The average age was 2021 (SD=204)

years old with a range of 18 to 29 years old Mean APPS was 41 (SD=566) with the majority

of the sample (719) endorsed one or more positive symptoms But mean APPS-distress

(M=172 SD=308) was lower with a majority (583) endorsing no distressing symptoms

In term of discrimination the mean of domain of discrimination reported was very low

(M=120 SD150) with 551 of our sample reporting one or more domains The mean of

frequency of discrimination was much higher (M=226 SD=319) with 548 of the sample

reporting to have been discriminated against at least once

APPS analyses

A two factor (2X2) ANOVA of race by gender in regard to endorsement of APPS

showed several significant results First there was a significant main effect of gender on the

amount of APPS endorsed F(11627)= 2051 plt0001 Males reported more APPS than

females Mdiff=147 95 confidence Interval (CI) (083 ndash 211) plt0001 There was also a

significant main effect of race on the amount of the APPS endorsed F (1 1627) = 18032

plt0001 Black endorsed more APPS than whites Mdiff= 436 95 Confidence Interval (CI)

(372 - 500) plt0001 There was a significant interaction between gender and race on the

amount of APPS endorsed F (11627)=803 plt0001 In order to interpret the significant


interaction 4 groups captured in the raceXgender interaction term were analyzed using one way

ANOVA

The One way ANOVA revealed a significant difference in APPS across the 4 racegender

groupings As expected from the two factor ANOVA there was main effect in the racegender

grouping (racegender) variable to the amount of APPS endorsed F(31627)=69505 plt0001All

the mean APPS to the racegender variable are reported in figure 1 Tukey post hoc test revealed

that Black males endorsed significantly more APPS than Black females (Mdiff=239 CI(098 ndash

38) plt0001) White males (Mdiff=528 CI (383 ndash 672) plt0001)) and White females

(Mdiff=583 CI (451 ndash 713) plt0001) It also revealed that Black females endorsed more APPS

than White males (Mdiff= 289 CI (186 ndash 391) plt0001) and White females( Mdiff= 344 CI

(260 ndash 428) plt0001) Finally White male endorsed slightly more APPS than white female

but it was not significant Mdiff= 055 95 CI (-3496-145) pgt005

Racegender and High vs Low endorsement of distressing APPS

A chi-square of ldquoracegenderrdquo by High vs low risk of psychosis shows a significant

relationship between the two X2(3 N=1520) =448 plt0001 Black females and males were

more likely to be in the high risk category (11 and 18 respectively) than white males and

females (27 and 48) See figure 2 for percentage of high and low endorsement of distressful

APPS for every combination of racegender

Racial Discrimination

See figure 3 for the complete report of the mean of frequency of discrimination for each

combination of racegender One way ANOVA of the racegender variable and frequency of

discrimination reported a main effect of the racegender variable on the frequency of


discrimination endorsed F (3 1627) = 16003 plt0001 Tukey post hoc test showed where the

significant differences lie Black males significantly endorsed a higher frequency of

discrimination than black females (Mdiff= 092 CI(021 ndash 165) p=0005) white female (Mdiff=

384 CI(316 ndash 451) plt0001 white male (Mdiff= 381 CI(307 ndash 455) plt0001) Black female

significantly endorsed a higher frequency of discrimination than white female (Mdiff= 291

CI( 248 ndash 334) plt0001) and white male (Mdiff= 289 CI(236 ndash 342) plt0001) White male

did not significantly endorse more frequency of discrimination than white female (Mdiff= 0020

CI(-044 ndash 048) pgt005)

Just like for frequency of discrimination the One way ANOVA analysis of racegender

and EODscale showed a main effect of racegender combination on the domain of

discrimination endorsed F (3 1627)= 20285 plt0001 Tukey post hoc test further clarified

where the difference lied Black males did not significantly endorse more domains of

discrimination than black female (Mdiff= 031 CI(-017 ndash 064) p=007) but did endorse more

domain of discrimination than white female (Mdiff= 186 CI(156 ndash 217) plt0001) and white

male (Mdiff= 186 CI(152 ndash 219) plt0001 It also showed that black female significantly

endorsed more domain of discrimination than white female (Mdiff= 155 CI (135 ndash 175)

plt0001) and white male (Mdiff= 154 CI(130 ndash 178) plt0001) White males had a negligible

and insignificant rise in endorsed domain of discrimination than white female (Mdiff= 0008 CI(-

022 ndash 020) pgt005) The complete mean of endorsed domain of discrimination for each

genderrace combination can be seen in figure 4


Frequency of Discrimination Black individuals and APPS

Two linear regression models were conducted to determine whether the effect of gender

on APPS in the Black subsample may be partly explained by exposure to racial discrimination

The first unadjusted model compared genderrsquos relation to APPS and found a significant relation

(b=239 standard error(se)= (075) p=0001) In the second model mean frequency of racial

discrimination was added to the unadjusted model and was significant (b=21 se (0077)

p=0005) Notably the beta coefficient for gender in this adjusted model was slightly decreased

but remained significant b=219 (se (0077) P=0003) Those results and more are reported in

table 2

Discussion

Aims

The study had two main aims first a women to men difference in APPS should be

present in blacks as long as it is sufficiently mediated by discrimination since discrimination is a

gendered experienced secondly due to discrimination such gender difference in APPS in the

black group should be significantly higher than the ones that may be found in white individuals

The first aim was partially supported by our results Black man reported a higher frequency of

discrimination more endorsement of APPS and more endorsement of distressing APPS than

black females (see fig 1 2 3 amp4) The two models of linear regression lines of frequency of

discrimination gender in the endorsement of APPS found a significant relation between

frequency of discrimination and the level of APPS reported However discrimination did not

mediate the relation of gender and race in the black population (see table 2)


Our second aim was also partially supported Black participants especially black males

endorsed more discrimination than white participants regardless of their gender (see fig 3 amp 4)

Subsequently Black participants especially black males reported a higher endorsement of

APPS and distressing APPS than white males and females participants However as reported in

the paragraph above discrimination is not the main link explaining those differences across race

Study implications

The gender difference in perceived discrimination reported by our black sample is in line

with the literature One might have expected black females to have reported more instance of

discrimination due to the dual effect of sexism and racism Black women have to deal with

certain discrimination in regard to their sexuality level of work intelligence femininity that

black men do not experience (Shorter-Gooden amp Jones 2003) But there are two main reasons

for our current results first discrimination needs to be recognized in order to be reported by an

individual second black men are more overtly discriminated against in the US Shorter-Gooden

amp Washington (1996) reported that race is more salient than gender in black individuals For

example in a series of survey that they conducted (Shorter-Gooden Jones 2003) among US

black women (N=333) only found 69 of them who reported at least one instance of

experienced discrimination Surprisingly when interviewed later many of the ones who did not

report an instance of discrimination shared personal discriminatory stories related to unequal

pay harassment sexual violence Shorter amp jones (2003) concluded that black women are not

sensitized enough to recognize those forms of discrimination Furthermore studies have shown

that black men are more frequently the target of racial stereotypes than females that picture them

as more threatening and violent (Krieger amp Sidney 1996 Williams amp Mohammed 2009)


Our results support the idea that there is a gender difference in risk of psychosis

especially in ethnic minorities (Ochoa et al 2008 Ochoa et al 2004 Alerman et al 2005

Veilin et al 2006) Ochoa et al (2008) found a higher incidence of schizophrenia in men than

women Our results showed men generally endorsed more APPS than women (Mdiff=147 95

confidence Interval (CI) (083 ndash 211) plt0001) Further analyses showed that race modified the

relationship between gender and APPS which is in line with Veling et al (2006) study in the

Netherlands In term of ethnicity Veling et al (2006) reported that Moroccan men second and

first generation immigrants were at an increased risk for schizophrenic disorders compared to

both Moroccan woman second and second generation and white Dutch irrespective of the

gender Similarly our results showed that black men endorsed more APPS than black female

(plt0001) white males (plt0001) and white female (Plt001) (see fig 1) Even white men

endorsed more APPS than females even though it was not significant (pgt005) (fig 1) Black

men were also more likely to endorse more distressing APPS than everyone else (see fig 2)

Veling et al (2006) reported Moroccan encounter great difficulties in their process of

acculturation such as more perceived discrimination social defeat and else Likewise our study

showed that black men are more discriminated against than anyone else in our sample (see fig 3)

Extraneous factors

Other factors must be working in sync with discrimination to produce the results found in

the study since it may only partially mediate the relation between race and gender in the black

subgroup A look at table 1 shows that a higher proportion of black (242) participants were

first generation immigrants than the white sample (72) Studies have shown that immigration

is an important risk factor in the development of psychotic disorders (eg Fearon et al 2006)

Both the AESOP and EMPIRIC studies showed that black immigrant groups were at higher


incidence rate ratio to develop schizophrenia than the white natives (Fearon et al 2006 Spronton

amp Nazroo 2002) Immigrants whether new or not have to handle a lot of stressful situation

such adapting to a new culture learning a new language lack of financial and social support and

even xenophobia The degree to which they adapt to their new environment is link to psychosis

(Vega Sribney Miskimen Escobar and Aguilar-Gaxiola 2006) In the same train of thought

children of first generation immigrants also known as second-generation immigrants have been

found to have higher risk of developing a psychotic disorder than their parents (Veiling et al

2006 Cantor-Graae ampSelten 2005) Further analysis is needed to confirm the extent of the effect

of immigration has on the endorsement of APPS on top of discrimination in our sample

Socio-demographic variables such as income neighborhood onersquos living in and

traumatic life experiences are also important factors linked to psychosis (eg Von Os et al 2009

Boydell et al 2001 Beards et al 2013Fisher et al 2009) Beards et al (2013) found that adults

who were exposed to traumatic life events were several times more likely to develop psychotic

experiences than those who do not Anglin Polanco-Roman amp Lui (2015) found that

dissociation mediated the relation between traumatic life experiences and APPS But such

relation was dependent upon onersquos ethnicity Notably full mediation was only present in the

black subgroup partially present in Hispanics and not found in Asians In term of gender

difference Fisher et al (2009) found that severe physical or sexual abuse in childhood is linked

to later psychosis in women more than men Boydell et al (2007) found individuals living in

neighborhood where they were ethnically well-represented were at lower risk for psychosis than

those who live in neighborhoods where they were minorities Furthermore people of lower

socio-demographic who see societyrsquos continuously hinder their efforts to move up the socio-

economic ladder may fall into social defeat (Cantor-Graae Selton 2005) Selton amp Cantor-Graae


(2005) hypothesized that social defeat which they defined as a positon of submission or be an

outsider may be a link to schizophrenia As evidence they cited a series of animal experiments

which showed that constant exposure to social defeat leads to a hyperactivity of the dopamine

mesolimbic system In humans the dopamine mesolimbic system is oversensitive in

schizophrenic individuals Therefore they suggested that just like in animals socially defeated

humans may have sensitive mesolimbic dopamine system which may heighten their descent to

psychosis Further research could indicate the level of social defeat trauma and the type of

neighborhood associated to the black sample of our study and how they work with discrimination

to explain their high endorsement of APPS and APPS distress

Limitations

There are several limitations in our study The first of our limitations is our reliance to APPS

through the PQ scale Loewy et al (2005 2007) accentuated that the PQ is not a clinical

assessment tool Instead it should be taken as a tool that pinpoints those who may be found at

risk of psychosis when assess through clinically valid interviews The second of our limitations

is that endorsing APPS alone through the PQ scale is not indicative of risk of psychosis Peoplersquos

hunger fatigue concentration culture religion may all affect the way they respond to the

questionnaire For example people who are hungry and tired may not pay as much attention to

the questionnaire and falsely answer a series of items Alternatively their understanding of

hallucinations or other positive psychotic symptoms may be skewed through their cultural and

religious understanding People also could have other disorders which influence their responses

David et al (1999) showed that Latinos with PTSD were more likely to endorse psychotic

symptoms in self-report questionnaires The third of our limitations is the sample used All of our

participants are college based The results may lack the external validity needed to extend the


findings to the general population Lastly data was collected on a single point in time for each

participant making this study not as strong as a longitudinal study which could have shown the

progression of the symptoms in the participants

Reference List

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of Psychiatry 22(5) 417-428 http doi 103109095402612010515205

AddingtonD AddingtonJ amp PattenS (1996) Gender and affect in schizophrenia Canadian

Journal of Psychiatry 41(5) 265ndash268

Albus M Scherer J Hueber S et al (1994) The impact of familial loading on gender

differences in age at onset of schizophrenia Acta Psychiatrica Scandinavica 89 (2) 132ndash134

Aleman A Kahn R S and Selten J P (2003) Sex differences in the risk of schizophrenia

evidence from meta-analysis Archives of General Psychiatry 60(6) 565ndash571

American Psychiatric Association [APA] (2013) Diagnostic and Statistical Manual of Mental

Disorders (Fifth ed) Arlington VA American Psychiatric Publishing

Anglin DM Polanco-Roman L Lui F (2015) Ethnic variation in whether dissociation

mediates the relation between traumatic life events and Attenuated Positive Psychotic

SymptomsJourmal of Trauma amp Dissociation 16 68-85

Anglin DM Lighty Q Greenspoon M Ellman LM (2014) Racial discrimination is

associated with distressing subthreshold positive psychotic symptoms among US urban ethnic


minority young adults Society Psychiatry and Psychiatric Epidemiology Retrieved from

httpdoi 101007s00127-014-0870-8

Austad G Joa I Johannessen J O Larsen T K (2013) Gender differences in suicidal

behavior in patients with first-episode psychosis Early Intervention in Psychiatry Retrieved

online httpdoi 101111eip12113

BarajasA OchoaS Jordi E O and Lalucat-Jo LL (2015) Gender Differences in Individuals

at High-Risk of Psychosis A Comprehensive Literature Review The Scientific World Journal

2015 1-13 Retrieved from httpdxdoiorg1011552015430735

Beards S Gayer-Anderson C Borges S Dewey M E Fisher H L amp Morgan C(2013)

Life events and psychosis A review and meta-analysisSchizophreniaBulletin39 740ndash747 doi

101093schbulsbt065

BhuiK Stansfeld S McKenzie K Karlsen S Nazroo J Weich S (2005) RacialEthnic

Discrmination and Common Mental Disorders among workers Findings from the EMPIRIC

study of Ethnic minority Groups in the United Kingdom Journal of Public Health 95(3) 496-

501

Bhugra D Hiwig M Hossein B Marceau H Neehall J Leff J et al (1996) First-contact

incidence rates of schizophrenia in Trinidad and one-year follow-up British Journal of

Psychiatry 169 587-592

Bhugra D Leff J Mallett R Der G Corridan B Rudge S (1997) Incidence and outcome

of schizophrenia in whites African-Caribbean and Asians in London Psychological Medicine

27 791-798


BhugraD HilwigM Mallett R Corridan B Leff J Neehall J amp Rudge S (2000)

Factors in the onset of schizophrenia a comparison between London and Trinidad samplesActa

Psychiatria Scandinavica 101 135-141

Boydell J Van Os J McKenzie K Allardyce J Goel R McCreadie RG et al (2001)

Incidence of schizophrenia in ethnic minorities in London ecological study into interactions with

environment British Medical Journal 323 1336-1338

Breshnahan M Begg M D Brown A Shafter C Sohler N Insel B et al (2007) Race

and risk of schizophrenia in a US birth cohort another example of health disparity

International journal of Epidemiology 36 751-758

Brown T N Williams D R Jackson J S Neighbors H W Torres M Sellers S L

Brown K T (2000) ldquoBeing Black and Feeling Bluerdquo The mental health consequences of racial

discrimination Race amp Society 2(2) 117-131

Carter R T (2007) Racism and Psychological and Emotional Injury Recognizing and

Assessing Race-Based Traumatic StressThe Counseling Psychologist 35(13) 13-105 httpdoi

1011770011000006292033

Cantor-Graae ESelten JP (2005) Schizophrenia and migration a meta-analysis and review

American journal of Psychiatry 162 12-24

CottonS M Lambert M Schimmelmann B G et al (2009) Gender differences in premorbid

entry treatment and outcome characteristics in a treated epidemiological sample of 661 patients

with first episode psychosis Schizophrenia Research 114 (1ndash3) 17ndash24


DeNavas-Walt C Proctor B D and Smith JC (2011) Income Poverty and Health Insurance

Coverage in the United States 2010 In US Census Bureau Current Population Reports (pp

60-239) Washington DC US Government Printing Office Retrieved from

httpwwwcensusgovprod2011pubsp60-239pdf

Fearon P kirkbrideJ MorganC DazzanPMorgan K LLoyd T et al(2006) Incidence of

schizophrenia and other psychoses in ethnic minority groups results from the MRC AESOP

Study Psychological Medicine pp 1541-1550 doi101017S0033291706008774

Fisher HMorganC DazzanP Craig T K MorganK Hutchinson G et al (2009) Gender

differences in the association between childhood abuse and psychosis The British Journal of

Psychiatry 194 (4) 319-325 httpdoi 101192bjpbp107047985

Foti D J Kotov R Guey L T and Bromet E J (2010) Cannabis use and the course of

schizophrenia 10-year follow-up after first hospitalization American Journal of Psychiatry

167(8) 987ndash993

GalderisiSBucci P UccedilokA PeuskensJ (2012) No gender differences in social outcome in

patients suffering from schizophrenia European Psychiatry 27 406-408 Retrieved from

httpdoi101016jeurpsy201101011

Goldstein J M Tsuang M T Faraone S V (1989) Gender and schizophrenia implications

for understanding the heterogeneity of the illness Psychiatry Research 28(3) 243ndash253

Gottesman II McGuffin P amp Farmer AE (1987) Clinical genetics as clues to the ldquorealrdquo

genetics of schizophrenia a decade of modest gains while playing for time Schizophrenia

Bulletin 13 23-47


GurejeO(1991) Gender and schizophrenia age at onset and sociodemographic attributes Acta

Psychiatrica Scandinavica 83(5) 402ndash405

Hayashi N Igarashi Y Yamashina M Suda K (2002) Is there a gender difference in a

factorial structure of the positive and negative syndrome scale A test by structural equation

modeling Psychopathology 35 (1) 28ndash35

Hickling FW amp Rodgers-Johnson P (1995) The incidence of first contact schizophrenia in

Jamaica British Journal of Psychiatry 167 193-196

Johns LC amp Van OS J (2001) The continuity of psychotic experiences in the general

population Clinical Psychology Review 21 1125-1141

Krieger N amp Sidney S (1996) Racial Discrimination and blood pressure The CARDIA study

of young black and white adults American Journal of Public Health 86 1370-1378

Doi102105AJPH86101370

Krieger N Smith K Naishadham D Hartman C Barbeau E M (2005) Experiences of

discrimination validity and reliability of a self-report measure for population health research on

racism and health Soc Med 61(7) 1576-1596

Lambert SF English D Ialongo NS (2014) Longitudinal Associations between Experienced

Racial Discrimination and Depressive Symptoms in African Americans Adolescents

Developmental Psychology 50(4) 1190-1196

Leung A Chue P (2000) Sex differences in schizophrenia a review of the literature Acta

Psychiatry Scandinavica Supplementum 4013-38


Lindstrom E amp Von Knorring L (1994) Symptoms in schizophrenic syndromes in relation to

age sex duration of illness and number of previous hospitalizations Acta Psychiatrica

Scandinavica 89 (4) 274ndash278

Loewy RL Bearden CE Johnson JK Raine A Cannon TD (2005) The prodromal

questionnaire (PQ) Preliminary validation of a self-report screening measure for prodromal and

psychotic syndromes Schizophrenia Research 79 117-125

Loewy RL Bearden CE Cannon TD (2007) Self-report of Attenuated Psychotic

experiences in a college Population Schizophrenia Research 93 (1-3) 144-151

Mahy GE Mallett R Leff Jamp Bhugra D (1999) First-contact incidence rate of

schizophrenia on Barbados British Journal of Psychiatry 175 28-33

Mangalore R1 Knapp M (2007) Cost of schizophrenia in EnglandJournal of Mental Health

policy and economic10(1) 23-41

McGlashan TH Miller TJ Woods SW Hoffman RE and Davidson L (2001) A scale

for the assessment of prodromal symptoms and states In Miller TJ Mednick SA

McGlashan TH Liberger J and Johannessen JO (Eds) Early Intervention in Psychotic

Disorders Dordrecht The Netherlands Kluwer Academic Publishers pp 135-149

McGlashan T H Walsh B C Woods S W (2010) Structured Interview for Psychosis-Risk

Syndromes (5th version) Prime Research Clinic Connecticut In print

McGrath J Saha S Chant D and Welham J (2008) Schizophrenia a concise overview of

incidence prevalence and mortality Epidemiologic Reviews 30(1) 67ndash76


Miller T I McGlashan T H Rosen J L Cadenhead K Ventura J Farlane W hellip Woods

S W (2003) Prodromal Assessment with the Structured Interview for Prodromal Syndromes and

the Scale of Prodromal Symptoms Predictive validity Interrater validity and Training to

Reliability Schizophrenia Bulletin 29 (4) 703-715

Miller TJ McGlashan TH Woods SW Stein K Driesen N Corcoran CM Hoffman

R and Davidson L (1999) Symptom assessment in schizophrenic prodromal states Psychiatric

Quarterly 70 273-287

Morgan V A Castle D J and Jablensky A V (2008) Do women express and experience

psychosis differently from men Epidemiological evidence from the Australian National Study

of Low Prevalence (Psychotic) Disorders Australian and New Zealand Journal of Psychiatry 42

(1) 74ndash82

Ochoa S Usall J Cobo J Labad X Kulkarni J (2012) Gender differences in

schizophrenia and First-Episode Psychosis A Comprehensive Literature Review Schizophrenia

Research and treatment 2012 Retrieved from httpdxdoiorg1011552012916198

OchoaS UsallJ Villalta-Gil V et al (2006) Influence of age at onset on social functioning in

outpatients with schizophrenia European Journal of Psychiatry 20(3) 157ndash163

Pascoe EA Richman LS (2009) Perceived discrimination and health a meta-analytic review

Psychology bulletin 135(4) 531-554 httpdoi101037A0016059

Peraumllauml J SuvisaariJ Saarni S I et al (2007) Lifetime prevalence of psychotic and bipolar I

disorders in a general population Archives of General Psychiatry 64(1) 19ndash28


Phanthunane P Whiteford H Vos T Bertram M (2012) Economic burden of schizophrenia

empirical analyses from a survey in ThailandJournal of Mental Health policy and

economic15(1) 25-32

Rodriacuteguez-Jimeacutenez R Araguumleacutes M Jimeacutenez-Arriero M A et al (2008) Dual diagnosis in

psychiatric inpatients prevalence and general characteristics Investigacion Clinica 49 (2)195ndash

205

Rosen JL Woods SW Miller TJ and McGlashan TH (2002) Prospective observations of

emerging psychosis Journal of Nervous and Mental Disorders 190133-141

Saha S Chant D Welham J McGrath J (2005) A systematic review of the prevalence of

schizophrenia PLoS Med 2(5) doi 101371journalpmed0020141

Sartorius N Shapiro R amp Jablonsky A (1974) The international pilot study of

schizophrenia Schizophrenia Bulletin 2 21-35

Shorter-Gooden K Washington NC (1996) Young Black and female The challenge of

weaving an identityJournal of Adolescence 19 465-475

Shorter-Gooden K Jones C (2003) Shifting The double Lives of Black Women in America

New York NY HarperCollins Publishers

Shtasel D L Gur R E Gallacher F Heimberg C and Gur R C (1992) Gender differences

in the clinical expression of schizophrenia Schizophrenia Research 7(3) 225ndash231

Silvia C (2010) The Gender Paradox in Suicide Suicide and Life Threatening Behavior 28

(1) 5 doi101111j1943-278X1998tb00622x


Sims A (2002) Symptoms in the mind an introduction to descriptive psychopathology

Philadelphia W B Saunders

Singh T amp Rajput M (2006) Misdiagnosis of Bipolar Disorder Psychiatry (Edgmont) 3(10)

57ndash63

Sproston K Nazroo JY (2002) Ethnic Minority Psychiatric Illness Rates in the Community

(EMPIRIC)London England The Stationery Office

Uggerby P Nielsen R E Correll C U Nielsen J (2011) Characteristics and predictors of

long-term institutionalization in patients with schizophrenia Schizophrenia Research 131(1ndash3)

120ndash126

Usall J Ochoa S Araya S Maacuterquez M (2003) Gender differences and outcome in

schizophrenia a 2-year follow-up study in a large community sample European Psychiatry

18( 6) 282ndash284

Van Os J Linscott R J Myin-Germeys I DelespaulP and Krabbendam L (2009) A

systematic review and meta-analysis of the psychosis continuum evidence for a psychosis

pronenessndashpersistencendashimpairment model of psychotic disorder Psychological Medicine 39

179-195 doi101017S0033291708003814

Veilin W Selten JP Veen N Laan W Blom JD amp Hoen HW (2006) Incidence of

schizophrenia among ethnic minorities in the Netherlands a four-year first-contact

studySchizophrenia Research 86 189-193


Veling W Selten JP Susser E Laan W Mackenbach JP Hoek HW (2007) Discrimination

and the incidence of psychotic disorders among ethnic minorities in The Netherlands

International Journal of Epidemiology 36(4) 761-768 doi 101093ijedym085

Veling W Susser E van Os J Mackenbach JP Selten JP Hoek HW (2008) Ethnic density of

neighborhoods and incidence of psychotic disorders among immigrants Am J psychiatry 165

66-73

Williams DR amp Mohammed S A (2009) Discrimination and racial disparities in health

Evidence and needed researchJournal of Behavioral Medecine 32 20-47

Doi101007s10865-008-9185-0

Wu EQ1 Birnbaum HG Shi L Ball DE Kessler RC Moulis M Aggarwal J (2005) The

economic burden of schizophrenia in the United States in 2002 Journal of Clinical Psychiatry

66(9) 1122-1129

Yung AR Phillips LJ Yuen HP Francey SM McFarlane CA Hallgren M McGorry PD

(2003) Psychosis prediction 12 month follow up of a high risk (ldquoprodromalrdquo) group

Schizophrenia research60 (1) 21-32

Yung A R McGorry P D McFarlane C A et al (1996) Monitoring and care of young

people at incipient risk of psychosis Schizophrenia Bulletin 22 283ndash 303

Yung A Phillips L J McGorry P D et al (1998) A step towards indicated prevention of

schizophrenia British Journal of Psychiatry 172 (33) 14ndash20


Table 1- descriptive information of the sample on gender race and endorsement of APPS

and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)

Age (years) mean (SD) [range] 2021 (204) [18-29]

205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----

Immigrant Status n ()

US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)

APPS mean (SD) [range]41 (566)[0-40] 675(73) [0-31] 289 (396) [0-

40]

APPS-distress mean (SD) [range] 172 (308) [0-23] 248 (382)[0-23] 135 (254)[0-19]

Frequency of Discrimination mean (SD) [range]

226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]

Domain of Discrimination mean (SD) [range]

119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]

APPS = Attenuated Positive Psychotic Symptoms


Table 2- Unadjusted regression lines of EODfreq gender to APPS for the black

subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]

Figure1- APPS means by Racegender

Black male Black female white female white male0

1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S


Figure2- high vs low endorsement of APPS-distress by racegender

black male black female white man white female0

20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow

combination of racegender

hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress


Figure 3- Mean frequency of discrimination by racegender combination

black male black female white male white female0

05

1

15

2

25

3

35

4

45

5

474

382

091 093

frequency of discrimination

combination of race and gender

mea

n fr

equn

cy o

f disc

rimin

ation


Figure 4- Mean of endorsed domain of discrimination by racegender combination

Black male Black female White female White male0

05

1

15

2

25

234203

0478 0486

Mean domain of discrimination endorsed


Abstract

Background Studies have shown that psychotic disorders are part of a spectrum

meaning that their symptoms extend to the general population in attenuated forms Both

clinically psychotic individuals and attenuated forms of the disorders are subject to the same risk

factors

Currently we know that the incidence of schizophrenia is gendered and that ethnic

minorities are at increased risk for psychosis Ochoa et al (2008) found a 14 rate ratio male to

female in the incidence of schizophrenia but studies are inconclusive at finding similar results in

the prodromal phase of psychosis Ethnic minorities have been found to be at a higher risk for

psychosis and a higher endorsement of attenuated positive psychotic symptoms in the presence

of discrimination

Objective The study had two main aims first a women to men difference in APPS

should be present in blacks as long as it is sufficiently mediated by discrimination since

discrimination is a gendered experience secondly due to discrimination such gender difference

in APPS in the black group should be significantly higher than the ones that may be found in

white individuals

Methods amp Results A sample of 1633 young adults who self-identified as black or

whites were recruited from two US Northeast colleges They completed self-report

questionnaires of APPS experiences of discrimination Our results showed that black individuals

irrespective of gender reported more discrimination endorsed more APPS and distressing APPS

than white individuals We also found a gender difference among black individuals in term of

APPS categories and discrimination However discrimination may only partially mediate the

relation between race and gender in regard to APPS in the black sub-sample



































































Gruffin et al 1987)












































































































































Race amp Psychosis







































































men in 2010

































al 2005)









Current Study
























population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




































































Gruffin et al 1987)












































































































































Race amp Psychosis







































































men in 2010

































al 2005)









Current Study
























population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486











































































































































Race amp Psychosis







































































men in 2010

































al 2005)









Current Study
























population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




































































men in 2010

































al 2005)









Current Study
























population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486
































al 2005)









Current Study
























population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486


















population

Methods
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486
















Measure









al 2005)










participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486











participant (0-45)



































second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486






















second step


Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486



Results











APPS analyses











ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




ANOVA





























CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486










CI(-044 ndash 048) pgt005)






















table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486











table 2

Discussion

Aims

















Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486








Study implications


































Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486



















Extraneous factors









































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




































Limitations


















Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486






Reference List


















httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




httpdoi 101007s00127-014-0870-8









101093schbulsbt065




501






27 791-798
















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486

















1011770011000006292033



















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486















167(8) 987ndash993








Bulletin 13 23-47













Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486














Doi102105AJPH86101370









































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486


































(1) 74ndash82













economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486





economic15(1) 25-32



205














(1) 5 doi101111j1943-278X1998tb00622x





57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486






57ndash63





120ndash126



18( 6) 282ndash284




179-195 doi101017S0033291708003814










66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486








66-73



Doi101007s10865-008-9185-0



66(9) 1122-1129










and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




and discrimination

Overall Sample (n =

1633)Black ( n=512) White (n=1121)

Demographics

Female n () 1189 (729) 387 (756) 802 (715)


205 (24) [18-29]

2007 (183) [18-29]

Race n ()

Black 512 (314) --- ----

White 1121 (686) --- ----


US Born 1426 (873) 386 (758) 1040 (928)

US foreign 204 (125) 123 (242) 81 (72)


40]



226(319) [0-25] 404(416)[0-23] 092 (168)[0-14]


119 (150) [0-9] 21 (188)[0-9] 048 (08)[0-5]




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486




subsample

APPS b(se)[p-value]

Step 1 Step 2

Gender 239 (075) [p=0001] 219 (075)[p=0003]

EODfreq 0215 (0077) [p=0005]

Constant 618 (0368)[plt0001] 536 (0469) [plt0001]

Unadjusted R2 020 [p=0001] 035[p=0005]



1

2

3

4

5

6

7

8

9

857

618

386476M

ean

endo

rsem

ent o

f APP

S




20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486





20

40

60

80

100

120

18 11127

48

82 889972 952

Highlow


hi

gh v

s low

end

oers

emtn

of A

PPS-

dist

ress




05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486





05

1

15

2

25

3

35

4

45

5

474

382

091 093



mea

n fr

equn

cy o

f disc

rimin

ation




05

1

15

2

25

234203

0478 0486





05

1

15

2

25

234203

0478 0486


angelo.psychosis characteristics (thesis)may25th2015 (final version) (1)

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