Participants Over-Estimate How Helpful They Are in a Two-Player Game Scenario Toward an Artificial Confederate That Discloses a Diagnosis of Autism

Abstract

Research on how autistic people are perceived by neurotypical people indicates that disclosing a diagnosis leads to a positive discriminatory bias; however, autobiographical autistic accounts indicate that diagnostic disclosure often results in negative discriminatory behavior. We report on an exploratory study to compare people’s self-reported helping behavior with their actual helping behavior toward an assumed autistic collaborator. We led 255 participants to believe that they were interacting online with a real person to play Dyad3D, a maze navigation game where players must work together to open doors, and complete the levels. However, participants were actually playing with an artificial confederate (AC) that is programmed to behave the same way across all interactions. This design enabled us to manipulate the diagnostic status of the AC that participants received prior to collaboration across three conditions: no disclosure, dyslexia-disclosure, and autism-disclosure. We use this method to explore two research questions: (1) is Dyad3D viable in creating a simulated interaction that could deceive participants into believing they were collaborating with another human player online? and (2) what are the effects of disclosing an autism diagnosis on social perception and collaboration? Combined with a post-game questionnaire, we compared differences between diagnostic conditions and differences between self-reported behavior and actual behavior in the game. Our findings show that Dyad3D proved to be an efficient and viable method for creating a believable interaction (deception success rate >96%). Moreover, diagnostic disclosure of autism results in the AC being perceived as more intelligent and useful, but participants also perceived themselves to be more helpful toward the AC than they actually were. We evaluate the strengths and limitations of the current method and provide recommendations for future research. The source code for Dyad3D is freely available (CC-BY-NC 4.0) so that the study is reproducible and open to future adaptation.

Full text

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ORIGINAL RESEARCH
published: 11 June 2019
doi: 10.3389/fpsyg.2019.01349
Edited by:
Stefan Kopp,
Bielefeld University, Germany
Reviewed by:
Marco Fyfe Pietro Gillies,
Goldsmiths, University of London,
United Kingdom
Radoslaw Niewiadomski,
University of Genoa, Italy
*Correspondence:
Brett Heasman
b.heasman@ucl.ac.uk
Specialty section:
This article was submitted to
Human-Media Interaction,
a section of the journal
Frontiers in Psychology
Received: 06 November 2018
Accepted: 23 May 2019
Published: 11 June 2019
Citation:
Heasman B and Gillespie A (2019)
Participants Over-Estimate How
Helpful They Are in a Two-Player
Game Scenario Toward an Artificial
Confederate That Discloses
a Diagnosis of Autism.
Front. Psychol. 10:1349.
doi: 10.3389/fpsyg.2019.01349
Participants Over-Estimate How
Helpful They Are in a Two-Player
Game Scenario Toward an Artificial
Confederate That Discloses a
Diagnosis of Autism
Brett Heasman1*and Alex Gillespie2
1Centre for Research in Autism and Education, UCL Institute of Education, London, United Kingdom, 2Department
of Psychological and Behavioural Science, London School of Economics and Political Science, London, United Kingdom
Research on how autistic people are perceived by neurotypical people indicates that
disclosing a diagnosis leads to a positive discriminatory bias; however, autobiographical
autistic accounts indicate that diagnostic disclosure often results in negative
discriminatory behavior. We report on an exploratory study to compare people’s self-
reported helping behavior with their actual helping behavior toward an assumed autistic
collaborator. We led 255 participants to believe that they were interacting online with a
real person to play Dyad3D, a maze navigation game where players must work together
to open doors, and complete the levels. However, participants were actually playing
with an artificial confederate (AC) that is programmed to behave the same way across
all interactions. This design enabled us to manipulate the diagnostic status of the AC
that participants received prior to collaboration across three conditions: no disclosure,
dyslexia-disclosure, and autism-disclosure. We use this method to explore two research
questions: (1) is Dyad3D viable in creating a simulated interaction that could deceive
participants into believing they were collaborating with another human player online?
and (2) what are the effects of disclosing an autism diagnosis on social perception and
collaboration? Combined with a post-game questionnaire, we compared differences
between diagnostic conditions and differences between self-reported behavior and
actual behavior in the game. Our findings show that Dyad3D proved to be an efficient
and viable method for creating a believable interaction (deception success rate >96%).
Moreover, diagnostic disclosure of autism results in the AC being perceived as more
intelligent and useful, but participants also perceived themselves to be more helpful
toward the AC than they actually were. We evaluate the strengths and limitations of the
current method and provide recommendations for future research. The source code for
Dyad3D is freely available (CC-BY-NC 4.0) so that the study is reproducible and open to
future adaptation.
Keywords: online game, diagnostic disclosure, helping bias, positive discrimination, negative discrimination,
autism, confederate study, double empathy
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INTRODUCTION
There is a growing interest in the role non-autistic people play
in shaping social opportunities for autistic people (Milton et al.,
2018). While the abilities of autistic people to understand the
perspectives of neurotypical others has been well documented,
typically developing people have been shown to experience
difficulties in interpreting autistic perspectives (Sheppard et al.,
2016;Heasman and Gillespie, 2018b;Jaswal and Akhtar, 2018),
which can potentially have longer-term consequences for social
opportunities for autistic people (Sasson et al., 2017). To date a
number of studies have explored how autistic expressions and
behavior are perceived by non-autistic people through vignettes
and thin-slice judgements (e.g., utilizing video, image, and
audio), showing that disclosing a diagnosis of autism significantly
improves evaluations (e.g., Chambres et al., 2008;Faso et al.,
2014;Brosnan and Mills, 2016). However, reports from autistic
people indicate that disclosure of a diagnosis can also result in
stigma and negative discrimination (Davidson and Henderson,
2010;Powell and Acker, 2016;Treweek et al., 2018), resulting in a
gap in the literature in connecting self-reported perceptions with
actual behavior.
We examined the effect of the label “autism” on social
perception and behavior on 255 participants through an
online collaborative video-game, where the participants believed
they were interacting with a human partner to navigate
through a maze, when in fact they were interacting with an
artificial confederate (AC), programmed to behave the same
way for all participants. The impetus for selecting a video-
game as a medium for studying interaction was primarily
methodological rather than ecological; it provided a controlled
environment for manipulating the variable (i.e., the disclosure of
a diagnosis), measuring subsequent behavior (i.e., co-operative
or uncooperative movements in the game), and repeating the
interaction for all participants. In addition to testing the viability
of the method, we were curious to see if diagnostic disclosure,
even in a primarily goal-orientated logical task, led to any
pervasive differences in social perception, and behavior. We
therefore examined social perception and behavior of participants
in three conditions, (1) a no disclosure condition, (2) a dyslexia-
disclosure condition, and (3) an autism-disclosure condition.
Studies of How Autistic People Are
Perceived by Non-autistic People
Research on how autistic people are perceived by non-autistic
people has found evidence of both positive and negative
discrimination when a diagnosis of autism is disclosed. Using
a variety of stimuli (still images, audio, and video), evidence
suggests that when no diagnostic information is provided, autistic
people are perceived as more socially awkward (Grossman,
2015), idiosyncratic (Brewer et al., 2016), less attractive and
less likeable resulting in reduced intention to pursue social
interactions (Sasson and Morrison, 2017). These judgments
can form very quickly (e.g., based on brief exposure to video:
Grossman, 2015) and show little change with increased exposure
to stimulus (Sasson et al., 2017). Studies which have manipulated
the diagnostic status of stimuli presented to participants have
shown that a diagnosis of autism can result in significantly
more positive social evaluations (Chambres et al., 2008) and
improved affective attitudes (Brosnan and Mills, 2016). However,
such effects are shaped by a number of contextual factors, such
as the gender (Chambres et al., 2008) and the identity of the
perceiver (Gernsbacher et al., 2017), in addition to the medium
in which the stimulus is presented (e.g., audio-visual stimulus vs.
a speech transcript: Sasson and Morrison, 2017). Moreover, even
with knowledge of a diagnosis, ratings have been shown to lag
behind those of typically developing targets who were mislabeled
as autistic (Sasson and Morrison, 2017). Thus, knowledge of a
diagnosis only partially corrects for negative interpretations of
autistic behavior and, moreover, positive effects are not always
consistently observed.
Autistic reports also indicate that autistic people are
misunderstood by non-autistic others resulting in stigma
(Dekker, 1999;Chell, 2006;Chown and Beardon, 2017;Treweek
et al., 2018). Moreover, media representations have largely
focussed on autism as an illness that is a burden to others
(Clarke, 2011;Huws and Jones, 2011;Sarrett, 2011;Brownlow
et al., 2015), framing autism in terms of a deficit rather
than a difference from a neurotypical majority norm (Smukler,
2005;Ortega, 2009;Kapp et al., 2013;Ridout, 2017). In turn,
this has contributed to stigma experienced by autistic people
in interpersonal relationships (Hacking, 1999;Heasman and
Gillespie, 2018b). There is therefore a gap in terms of connecting
the self-reported positive discriminatory behaviors observed in
research using vignettes, and the actual behavior of non-autistic
people toward autistic people. Yet exploring this perception-
behavior gap presents a methodological challenge in terms
of establishing a standardized interaction so that comparisons
across groups can be observed.
Methods for Simulating Interactions
Studies of how autistic people are perceived have traditionally
used vignettes. Vignettes are passages of text, images, or other
types of stimuli (e.g., video) which present a hypothetical
situation to participants to elicit a response, either observed,
or self-reported (Hughes and Huby, 2004;Grbich, 2013). They
are a common technique used in social research to elicit data
and can be used to incorporate a variety of detail about social
situations; from abstract pictures and short text which impose low
cognitive demand, to more elaborate immersive video and audio
which draw upon participants’ own experiences (Kinicki et al.,
1995). Vignettes can be used to explore automated and intuitive
psychological processes, for example Heider and Simmel’s (1944)
classic attribution paradigm, where participants observe shapes
moving around a scene, and explores how participants impute
human social behavior to abstract entities.
Although vignettes provide a controlled way to present
context to participants, they remain limited because they do not
replicate the pressures of real social life (Hughes and Huby, 2004).
In particular, vignettes lack a key social psychological feature
involved in human behavior: understanding Self from the social
position of Others (Mead, 1934). In vignette studies, participants
are not active in the social field they evaluate; rather they evaluate
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psychological targets knowing that the targets themselves do not
perceive them in return. Moreover, while participants passively
observe vignettes presented to them, they remain active social
agents in the research setting. Thus behavior can be subject to
a response bias in light of what participants believe researchers
want to observe (Furnham, 1986;McCarney et al., 2007).
It is possible to place participants within an active, yet
controlled, social field. Confederate-based studies aim to situate
the participant in a controlled social setting where they are
interacting with a confederate (i.e., a participant who is actually
working for the researcher). This type of design has been
classically illustrated, for example through Asch’s (1956) study
of conformity, where participants were led by the majority
of confederates to report an incorrect answer in judging the
lengths of a line, and Milgram’s (1963) study of obedience, where
participants were led to believe that they were causing harm to
a participant (the confederate) in another room. The advantage
of confederate-based studies is that they minimize the impact
of potential response biases by focussing more on observed
behavior than self-reported data. However, confederate studies
require additional methodological considerations, including
formalized procedures for interaction, and extensive training
to ensure consistency of behavior participants are exposed to
(Corti and Gillespie, 2015).
An alternative approach to simulating interactions is through
virtual environments, which enable interactions to be replicated
while immersing the participant within a social world or scenario
(Blascovich et al., 2002;Gillespie et al., 2018). Instead of using
the actual presence of others, virtual environments use computer-
generated avatars to represent human interactants (Blascovich
et al., 2002;Bailenson et al., 2004). Virtual environments allow
researchers to decouple rendered behavior from actual behavior
through controlling audio-visual perceptual channels (Bailenson
et al., 2004;Yee et al., 2009). Moreover, they are adaptable,
facilitating research into abstract or more socially complex
scenarios. For example, Cyberball (Williams et al., 2000) is a
virtual ball tossing game used to examine social ostracism,
whereby participants are led to believe they are playing with
others online, when in truth they play with a virtual agent that
is programmed to deliberately exclude the participant from the
game. This minimalist format has the advantage of providing a
gradable way to manipulate the independent variable of levels of
ostracism. Alternatively, virtual environments can encompass a
high degree of social complexity (Gillespie et al., 2018), both in
terms of the identity that avatars portray, and the communication
systems used between avatars (Evans, 2012). “Second Life” is
an example of a massively multiplayer online role-playing game
(MMORPG) used in psychological research, where users have no
task-specific focus other than their own interest in exploring and
socializing (Boelstorff, 2008;Evans, 2012). Building on such ideas,
we developed Dyad3D as a tool that could be used to simulate
interactions with participants while controlling an independent
variable of diagnostic disclosure.
Dyad3D Design
To explore how disclosing a diagnosis of autism affects social
perception and behavior of non-autistic people, we adapted
Heider and Simmel’s (1944) social attribution paradigm, which
involves two-dimensional geometric shapes moving around a
box, into a three-dimensional computer game. The participant
plays using a sphere-shaped avatar which moves around a maze
and must work with another sphere-shaped avatar, an AC, that
participants believe to be human. Since the AC follows the same
path regardless of participants’ actions, it is possible to create
the illusion of a collaborative computer-mediated task and thus
create a standardized experience of interacting which is the same
for all participants.
Combined with a questionnaire administered after the game,
this format allows us to examine (1) variation between self-
report perception and actual in-game behavior; and (2) variation
between groups of participants who have received different labels
for the AC. Since we were interested in understanding the
effects of disclosing a diagnosis of autism prior to the task,
we accordingly grouped participants into an “autism-disclosure”
condition (i.e., where participants are led to believe they are
playing with an autistic participant) and a control condition
(i.e., where no information about a diagnosis is disclosed).
We also included an additional group with another diagnosis,
dyslexia, to observe whether differences in comparison to the
control condition were specific to the label of autism or a
diagnostic label in general. Dyslexia was chosen since it is a well-
known label to describe difficulties in processing information,
there are no associated physical indicators, and like autism it can
involve difficulties in planning and organization (Gooch et al.,
2011) which are relevant to the nature of the game in which
participants must handle multiple tasks (exploring, navigating,
and coordinating action).
While advances in graphics and immersive virtual
environments provide the opportunity for replicating detailed
social situations, we based our study on the minimalist paradigm
of Heider and Simmel which uses basic geometric shapes.
For practical reasons a minimalist abstract design provided
a baseline for testing the viability of the procedure. Further
advantages were that using geometric shapes enabled control
over different modalities of interaction (e.g., there are no
non-verbal interpersonal cues) which meant that differences
in perception and behavior could be attributed to the label
disclosed and not other social psychological characteristics that
have previously been observed to affect interpersonal perception
of autistic people (e.g., eye gaze: Sasson et al., 2017). We also
did not attempt to replicate any “autistic” behaviors through
the geometric shapes. Autism covers such a broad range of
abilities and behaviors (Heasman, 2018), and replication would
be unrepresentative and potentially uncomplimentary because
there are few options to highlight positive autistic behaviors
through the simplistic game task. Rather, our intention was
to present participants with a misunderstanding within an
interaction, since misunderstandings are common across all
relationships (Laing et al., 1966) including those involving
autistic people (Heasman and Gillespie, 2018b). We wanted to
examine how participants made sense of the misunderstanding,
and the extent to which they used the partial knowledge of their
perceived online partner (i.e., their diagnostic status) to explain
their behavior. Moreover, we wanted to observe the potentially
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pervasive effects of disclosing a diagnosis of autism, in this case
whether it would affect participants’ perceptions and behaviors
in an extremely abstract and predominantly logical game task.
The simplistic use of shapes was also pragmatic: it provides a
platform for game development to introduce deeper levels of
ecological complexity, thus the source code is freely available to
researchers at: https://bitbucket.org/enghoff/dyad3d.
The design process for Dyad3D was iterative over 18 months
involving 183 participants, with interviews and focus groups after
pilot sessions feeding into further developments of the game.
The structure of the game (described with associated pictures
below) involves navigating through a maze with an AC that
behaves the same way for every participant. Dyad3D ostensibly
requires collaboration (hence the name “Dyad”), because some
doors in the maze can only be opened by the player, and other
doors can only be opened by the AC. However, the game is
configured so that the participant progresses successfully in
the initial levels before a misunderstanding occurs where the
AC deliberately goes the wrong way in the maze and leaves
the participant trapped in a prison which severely reduces the
participant’s overall score. This perceived “misunderstanding”
provides a reference point for participants to discuss and evaluate
what went wrong given the partial information they have about
their partner. Every participant has the same experience of the
interaction unfolding because the AC is programmed to follow
a specific path.
Manipulation of the independent variable (i.e., the diagnostic
disclosure) is achieved through an option at the start of
the game where participants are invited to reflect on their
performance in the tutorial of the game through typing a message
that is sent to the “online partner.” Diagnostic disclosure is
contained in the message participants receive from the AC, with
participants randomly assigned to one of three conditions: a no
diagnostic disclosure condition, a dyslexia-disclosure condition,
and an autism-disclosure condition. Behavior in the game was
recorded and a post-game questionnaire examined self-reported
perception of the collaboration. The research aims were as
follows: (1) to examine whether Dyad3D was viable in creating
a simulated interaction that could deceive participants into
believing they were collaborating with another player online,
and (2) to examine the effects of disclosing an autism diagnosis,
both in terms of (2a) comparing self-reported social perception
scores with actual behavior in the game, and (2b) examining
the qualitative explanations provided by participants about their
experience of participation.
MATERIALS AND METHODS
Ethics Statement
BPS and APA procedures regarding informed consent and
ethical guidelines were followed, with ethical approval granted
by the researcher’s university ethics committee (ref: 000674).
Participants were briefed about the nature of the study (i.e., they
were informed that they would be navigating through a series
of mazes with an online collaborator) and were informed of
their right to withdraw at any time. All participants stated in
the debrief that they were happy for further participants to
experience the same deception and to take part in the study.
Materials and Measures
Dyad3D Game
Dyad3D involves navigating through four mazes of increasing
complexity by opening doors to reach a rotating gold cube at
the end of each level. The participant plays as a 3-dimensional
virtual ball and navigates by using arrow keys on the keyboard.
To successfully complete the mazes the participant must work
with another ball, the AC, to open a series of doors, and
to free each other from a prison at the start of each level.
Some doors can be unlocked by the player, and some can be
unlocked by the AC.
The game is structured into three parts. In Part 1 the
participants completed a tutorial where they were systematically
introduced to different elements required to complete a level (e.g.,
Figure 1A). The tutorial lessons included: (1) navigating to move
and “collect” gold cubes by colliding with them; (2) learning how
to search for hidden buttons to open doors and collect the gold
cubes; (3) learning that some doors can be opened by the red
player (participant), and some opened by the silver player (AC),
thus collaboration is required; (4) learning how to free the other
player from a prison (same process as unlocking doors); and
(5) familiarizing with a full game scenario including receiving a
score based on time remaining in the level.
In Part 2, participants had the opportunity to reflect on their
progress in the tutorial and send a message to their online
partner (Figure 1B). Ostensibly, this aimed to aid collaboration
by sharing information about strengths and weaknesses. After
sharing information, participants were taken to an artificial
loading screen and waited for 14 s to be “paired” with another
available partner online (in truth, the AC). This was designed
to further the illusion that participants were playing with other
humans (and thus need to be coordinated) and not directly with
an AC. In the next scene, participants were informed they had
been successfully paired with a “partner” (Figure 1C). They then
received a message from the AC, in which information about
the diagnostic status of the AC was manipulated. We chose
a statement that offered both positive and negative feedback,
indicating difficulty with organizational skills but a strength in
navigational ability. For participants in the autism-disclosure
condition, the information received was: “I found balancing
multiple tasks tricky since I am autistic but my control is
good.” For participants in the dyslexia-disclosure condition,
the information included “since I am dyslexic” as substitute.
Participants in the control condition received: “I found balancing
multiple tasks tricky but my control is good.” To further the
strength of the deception, fake 24-digit identification numbers
were created which matched the style of the participants own
anonymous ID (as administered by Prolific). These IDs were
displayed at the top of all subsequent screens in the game along
with the information shared by the player and AC (Figure 1D).
Part 3 involved playing the game, where participants
progressed through four levels of mazes (Figure 1D). At the
start of each level the dyad had 1000 points which decreased by
eight points a second, with the time stopping when both players
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FIGURE 1 | (A) Starting Part 1, involving tutorial training for movement. (B) Starting Part 2, where participants are invited to reflect on the tutorial and send this
information to their online partner (the AC). (C) The information received from the AC in the control condition. (D) Starting Part 3, where the participant must navigate
through the maze. The AC is the silver ball and the human participant is the red ball. (E) A leaderboard providing a score and ostensible ranking which is shown after
every level. (F) Level 3 misunderstanding where the AC, despite immediately unlocking the participant from the prison, chooses instead to take an incorrect route
through the maze wasting valuable time. (G) The leaderboard after Level 3 which reflects a sharp drop in ranking to last position, 10th. (H) Level 4 where the
participant is faced with the option of collecting a gold cube before helping the AC, or freeing the AC first.
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picked up their respective gold cubes. In addition, the player and
AC alternated in terms of who started the level in a prison and
required support from the other to be freed.
The game was designed so that the first two levels were
completed very easily and the AC appeared cooperative in terms
of efficiently moving and opening doors, freeing the player from
the prison, and picking up the gold cube at the end of the level.
A fake leaderboard was provided after each level which provided a
ranking for performance, ostensibly based on the last ten dyads to
complete the game (Figure 1E). The inclusion of the leaderboard
was designed to ensure all participants had an equal impression
of their collaborative success. In the third level, however, the AC
deliberately took the wrong path through the maze and ignored
the participant waiting to be freed from the prison (Figure 1F).
This negatively impacted the score for the level resulting in a low
ranking (Figure 1G).
In the final level of the game, participants were presented with
a choice between collecting their own gold cube before freeing
their partner from prison (thus reciprocating the experience
of themselves being trapped and ignored by the AC in the
previous level), or freeing their partner from the prison and then
proceeding to collect the gold cube (Figure 1H). This choice was
designed to understand behaviorally how participants responded
to the misunderstanding that occurred in the prior level.
Since the scores in the game were aggregated for the levels,
participants continued to be ranked last (e.g., 10th) after the
fourth level despite their efforts. The leaderboard thus provided
a benchmark about the severity of the misunderstanding
experienced in the third level. Each participant therefore
experienced the same ranking of performance: after level 1, they
were ranked 4th out of the last ten dyads to register a score;
level 2, 3rd; level 3, 10th ; and level 4, 10th.
Behavioral Measures
Dyad3D records 11 variables of user input (Table 1). It records
the score; calculates mean distance between the player and AC for
each level (spatial proximity); mean time difference between the
player and AC collecting their respective gold cubes at the end of
the level (cube coordination); and mean keystrokes by the user for
each level. In addition, it also calculates the number of keystrokes
made by the user when they are trapped in the prison on the
third level and ignored by the AC (measure of frustration), and
the mean duration of each keystroke in time. In the fourth level,
it records whether participants free their partner from prison
before collecting their own gold cube (termed altruistic behavior),
or whether they collect the gold cube before freeing their partner
from prison (termed selfish behavior).
Questionnaire
Qualtrics was used to administer a post-game questionnaire
for participants. Given the priority of first impressions in
forming judgements about autistic people (Sasson and Morrison,
2017), we asked participants if they found the information
supplied by their partner as useful through a closed-ended
question. We further invited participants to explain why
they found the information useful or not useful. We also
asked participants whether they believed the information
TABLE 1 | List of behavioral measures from the Dyad3D game.
Measure Levels Description
Points score 1–4 A score calculated for the tutorial and for each
level in the game. 8 points = 1 s. Each level
starts with 1000 points and reduces continually
into minus figures
Mean distance
(spatial proximity)
1–4 The average distance between the Player and
the AC for each level. Measured after the Player
or AC are freed from prison and thus working
together to complete the level. Unit
measurement based on Player diameter
Cube coordination 1–4 Calculates the time difference between the
Player and the AC collecting their respective
gold cubes
Leadership 1–4 Identifies who picks up the gold cube first, the
Player or the AC
Keystroke count 1–4 Counts the number of times the Player hits an
arrow button during the levels of the game
Mean keystroke
duration
1–4 Calculates the mean duration a key is held
down during the game
Bump count 1–4 Counts the number of times the Player and the
AC make contact for each level
Prison keystroke
count
3 Calculates the number of times the Player
presses a keyboard button when trapped in the
prison during the 3rd level misunderstanding
Mean prison
keystroke duration
3 Calculates the mean duration a key is held
down while the payer is trapped in the prison
during the 3rd level misunderstanding
Priorities (prosocial
or selfish)
4 Identifies whether the Player chooses to free
the AC from prison first before collecting a gold
cube (prosocial behavior) or whether they
choose to collect their own gold cube before
freeing the Player
Response time 4 Measures the time between the Player
unlocking the AC from prison to when they
actually free the AC from prison
provided by their partner affected their own behavior in
the game to understand participants’ perceptions about the
relationship between diagnostic disclosure and its impact on their
behavior in the game.
Additionally, we wanted to understand if there were
differences in how participants explained the interaction, thus
an open-ended question invited comments on the following
points: (1) what worked well in your collaboration? (e.g., useful
information shared, hunting for hidden buttons, freeing from
prisons, opening doors, deciding which route to take, and
dividing up search areas); (2) What could have been improved
in your collaboration? (3) Is there anything you could have done
differently to support your partner? (4) Is there anything your
partner could have done differently to support you? (5) What
impressions do you think your partner has of you through their
experience of playing the game?
The Interpersonal Perception Method
In addition to exploring the effects of diagnostic disclosure,
we included rating scales to explore additional perspectives
on the task, since social interactions typically comprise
multiple perspectives on Self, perspectives on Other, and
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perspectives on how one is being perceived by others (Mead,
1934;Ichheiser, 1943;Heasman and Gillespie, 2018b). The
Interpersonal Perception Method is a way of systematically
analyzing the relations between these perspectives (Laing
et al., 1966) and has most typically been methodologically
operationalized into rating scales (Kenny, 1988;Gillespie et al.,
2010;Moore and Gillespie, 2014).
When identifying items to rate we considered criteria from
previous studies of social perception of autism. However, we
were also limited by the nature of the interaction through the
video-game where there is no facial or auditory dimension
of engagement. Chambres et al. (2008) used three evaluative
dimensions of cognitive, social and emotional items for assessing
vignettes of a 6-year-old autistic child’s behavior that participants
were either informed or uninformed about their diagnosis.
We accordingly included items of “intelligence” (cognitive),
“helpfulness” (social), and “frustration” (emotional). We also
included “skill,” since the game is dependent on the ability to
interact with the computer which participants may feel was a
critical factor in the collaboration.
Participants
A total of 183 participants took part in the pilot study phase to
help iteratively develop the game. Participants for the pilots were
sourced from the participant pool of the research lab belonging
to the researchers’ university. Since the pilot phase exhausted
available participants in the participant pool, the full study
sourced participants online through a paid participant service
provided by Prolific.
A total of 347 participants took part in the full study online.
All participants were recruited via Prolific and were paid £5
for 30 min participation. To ensure sample validity through the
online recruitment process, we used multiple inclusion/exclusion
criteria. First, a demographic restriction was applied given the
cross-cultural variation in identifying and understanding autism
(Mandy et al., 2014;Obeid et al., 2015). We therefore recruited
participants who had English as a first language. Following
recruitment, additional inclusion/exclusion criteria were applied.
We included an attention check by embedding a closed-ended
question within the post-game rating scales that had to be false
(“were you unable to finish the game with your partner?”).
Participants who failed the attention check were removed from
the sample (n= 42). A manipulation check was also included to
see if participants were aware of the information provided. Those
that claimed they did not receive any information or that they
did not remember the information shared (n= 23) were removed
from the analysis. We conducted a deception check through
analyzing the free text provided by participants in response to
a question which asked them to explain their experience of the
study. Participants who mentioned the belief that they were
playing with a computer and not a human were excluded (n= 9).
Additional criteria for exclusion included participants who:
did not complete the game or the questionnaire (n= 5), who
copied and pasted unintelligible text for open-ended questions
(n= 3), rated artificially (e.g., the same score for all items in the
questionnaire) (n= 5), and had technical problems during the
study (n= 5). In total 92 participants met the exclusion criteria,
with 255 participants included in the study, to which all results
and findings relate.
Participants were randomly assigned through the survey
software Qualtrics to one of three conditions: (1) a control
condition (where no diagnostic information was disclosed);
(2) a dyslexia-disclosure condition (where a dyslexia diagnosis
was disclosed); and (3) an autism-disclosure condition (where
an autism diagnosis was disclosed). In the debrief, participants
reported that they were happy for other participants to go
through the same process, while two participants voluntarily
contacted the researchers after the study to express their
enjoyment of playing the game, and their surprise that they were
playing with an AC and not a human.
Method of Analysis
To explore RQ1 (how viable is Dyad3D in creating a simulated
interaction that could deceive participants into believing they
were collaborating with another player online?), we asked
participants in the post-game questionnaire to rate the quality
of the deception on a six-point scale, from not believable at
all (=0) to very believable (=5). Additional checks included:
(1) the qualitative responses provided by participants were
examined to see if any reference was made to the AC which
questioned whether it was actually human; (2) we examined
whether attributions of intentionality to the AC were made by
participants; (3) participants were asked in the debrief whether
they would consent to other participants taking part in the study;
and (4) we categorized feedback volunteered by participants who
contacted the lead researcher after the study was complete.
To address RQ2a (comparing self-reported social perception
scores with actual behavior in the game) one-way ANOVAs
were run to explore the effect of condition (no disclosure vs.
dyslexia-disclosure vs. autism-disclosure) on survey responses
and behavioral data from the game. For ordinal data, non-
parametric Kruskal-Wallis one-way ANOVAs were used. Where
significant effects were observed, post hoc tests with Bonferroni
correction examined specific differences between conditions.
To address RQ2b (examining the qualitative explanations
provided by participants to understand the role of diagnostic
disclosure on their experience of participation) we analyzed
participants’ text responses. Specifically, we analyzed participants’
statements about why the information supplied by the AC
was useful or not useful with a process of iterative coding
(Neale, 2016). Iterative coding involves open-coding participants’
responses, before sorting codes into categories based on the
links between codes (Heasman and Gillespie, 2018b). Four
main categories resulted from this process, e.g., the category
of “tolerance” was formed from statements where participants
said the AC information led to lower expectations, higher
confidence, greater patience, and increased empathy. The
category of “redundant” emerged from statements about the
shortcomings of the AC, since some participants deemed
the information shared as superfluous, inaccurate, unhelpful,
and misleading. The category of “explained misunderstanding”
covered statements that specifically linked the AC information to
the misunderstanding experienced in the third level of the game
(thus no iteration required). Finally, the category of “ambiguous”
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included statements that were merely descriptive (e.g., “he said
how he did the tutorial”), provided tangential information (e.g.,
“we couldn’t pick the color”), and statements which did not
provide meaningful context, (e.g., “yes it did”).
RESULTS
Table 2 highlights that there were no statistically significant
associations between groups in terms of gender χ(4) = 0.729,
p= 0.948, nationality χ(4) = 0.260, p= 0.992, gaming
experience χ(4) = 6.09, p= 0.193, or ratio of group disclosing
a diagnosis χ(2) = 2.27, p= 0.321. A one-way ANOVA further
investigated the effect of gaming experience on performance in
the game, finding no significant association between mean time
for completing the tutorial between groups, [F(2,252) = 0.310,
p= 0.734], suggesting participants were of comparable ability
to play the game.
RQ1: How Viable Is Dyad3D in Creating a
Believable Interaction?
Ratings of the quality of the deception were strong with an overall
mean score of 3.83 on a 0–5 Likert scale (0 = not believable at
all; 5 = extremely believable), and a one-way ANOVA showed
TABLE 2 | Participant details.
Control Dyslexia Autism χ2p
(n= 80) (n= 83) (n= 92)
Gender 0.729 0.948
Female 45 45 47
Male 34 36 43
Unspecified 1 2 2
Nationality 0.260 0.992
United Kingdom 50 52 58
United States 25 23 27
Other 5 8 7
Diagnoses
disclosed by
participants1
2.27 0.321
Depression 4 3 1
Anxiety 4 6 2
Autism 1 1
OCD 0 1
Epilepsy 1 0
PTSD 1
Borderline personality
disorder
1
Chronic fatigue
syndrome
1
Gaming experience 6.085 0.193
Experienced 30 41 32
Intermediate 36 34 49
Novice 14 8 11
1Significance measured as difference in proportion of participants with a
diagnosis in each group.
no significant difference between groups [F(2,252) = 0.066,
p= 0.936]. Nine participants believed they were playing with a
computer and not a human representing <4% of participants
who had passed all other inclusion/exclusion criteria. Moreover,
all participants made attributions of intentionality to the AC,
as shown by references to the AC’s mental states, emotions and
skill/experience, and showing their assumption of human traits.
All participants also indicated that they would consent to others
taking part in the study, thus the nature of the deception did not
result in significant discomfort for participants. Taken together,
these data indicate that Dyad3D was predominantly successful
in creating a believable interaction, but there is still scope for
improvement (see section “Discussion”).
RQ2a: Differences Between
Self-Reported and Behavioral Measures
Table 3 summarizes the differences between groups on self-
reported and behavior measures. Kruskal-Wallis Htests
showed a statistically significant difference between groups
regarding the extent to which information provided by the
collaborator was perceived as useful, H(2) = 12.74, p<0.002,
with a mean rank score higher for the autism-disclosure
(autismusefulness_of_info = 140.81) and dyslexia-disclosure
(dyslexiausefulness_of_info = 133.38) groups than for the control
(controlusefulness_of_info = 107.69) group. Post hoc pairwise
comparisons showed a significant difference between the
control and autism-disclosure groups (p= 0.002) and the
control and dyslexia groups (p= 0.028). The results suggest
disclosing a diagnosis significantly increased the extent to
which participants found the information supplied by the
AC as useful.
There was a significant difference between groups in reporting
perceived helpfulness toward the AC because of the information
shared, H(2) = 8.02, p= 0.018, with a mean rank score higher
for the autism-disclosure (autisminfo_affected_helpfulness = 135.96)
and dyslexia-disclosure (dyslexiainfo_affected_helpfulness = 131.36)
groups than for the control (controlinfo_affected_helpfulness = 113.81)
group. Post hoc pairwise comparison with Bonferroni correction
showed a significant difference between the control and autism-
disclosure groups (p= 0.020) but not the control and dyslexia-
disclosure groups (p= 0.109). The results suggest disclosing a
diagnosis increased the extent to which participants perceived
they acted more helpfully during the game, but only significantly
for the autism-disclosure and not the dyslexia-disclosure group.
However, although participants in the autism-disclosure
group showed a greater tendency to prioritize their partner’s
interest (freeing their partner from prison before collecting
their own gold cube) than prioritizing their own interests
(picking up the gold cube before releasing their partner from
prison) compared with the control and dyslexia-disclosure group
(mean ranks: controlpriorities = 138.59; autismpriorities = 117.88;
dyslexiapriorities = 129.01), this difference was not significant
H(2) = 5.13, p= 0.077. Further Chi-square comparisons showed
no significant association between perceiving oneself to be helpful
with actual helping behavior χ(1) = 0.185, p= 0.667. These
findings compare with parametric one-way ANOVAs which
found no significant differences between groups for mean time
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TABLE 3 | Kruskall-Wallis comparison between groups on self-reported and behavioral measures.
Post hoc pairwise
df Mean rank H comparisons (Adj Sig.)
Dyslexia- Autism- Control- Control- Autism-
Control disclosure disclosure autism dyslexia dyslexia
Was AC information seen as useful? 2 107.69 133.38 140.81 12.74∗0.020∗0.028∗1.00
Did AC information result in increased self-reported helpfulness? 113.81 131.36 135.96 8.02∗0.020∗0.109 1.00
Did participant prioritize partner over Self? 138.59 117.88 129.01 5.13
Desire to collaborate with the AC again? 119.23 127.98 134.27 3.12
Rating AC intelligence 111.61 128.60 140.33 7.45∗0.019∗0.351 0.788
Rating AC skill 125.35 134.02 123.55 1.08
Rating AC helpfulness 126.06 126.90 129.29 0.10
Rating AC frustration 131.79 124.16 126.74 0.48
Rating dyad spatial coordination 133.03 121.10 128.40 1.15
Rating dyad calmness 128.06 125.23 129.03 0.13
Rating dyad efficiency 124.60 128.18 129.41 0.20
Rating dyad understanding 128.58 126.50 127.45 0.03
Rating self intelligence 136.13 122.26 124.67 2.00
Rating self skill 131.50 126.68 124.75 0.41
Rating self helpfulness 141.24 119.79 122.43 4.58
Rating self frustration 132.77 126.75 123.59 0.71
∗p<0.05.
to complete levels [F(2,252) = 0.811, p= 0.446], mean spatial
proximity between the participant and their other player across
the levels [F(2,252) = 0.654, p= 0.521], or mean frustration
(measured as the mean time participants hold down a keyboard
key while trapped in the prison), [F(2,243) = 2.770, p= 0.65].
These results suggest that despite participants in the autism-
disclosure group believing they were more helpful compared
with participants in the control group, they did not significantly
differ from the control group when it came to actual helping
behavior in the game.
There was a significant difference between groups in
participants rating AC intelligence, [H(2) = 7.452, p= 0.024] with
participants in the autism-disclosure group rating their partners
higher than the control or dyslexia-disclosure group (mean rank
scores: autismintelligence_other = 140.33 controlintelligence_other =
111.61 dyslexiaintelligence_other = 128.60). Post hoc pairwise
comparison with Bonferroni correction showed a significant
difference between the control and autism-disclosure groups
(p= 0.019), but no significant difference between the control
and dyslexia-disclosure groups (p= 0.788). This result was
consistent when analyzing the differences between rating
one’s own intelligence and rating their partner’s intelligence
[H(2) = 8.327, p= 0.016], with post hoc pairwise comparison
showing significant differences between the autism-disclosure
and control groups (p= 0.023). The results suggest a difference
in effect between diagnostic labels, with a disclosure of autism
leading to significantly higher perceptions of intelligence than a
disclosure of dyslexia when compared with the control group.
Criteria where no significant differences between groups were
observed include: participants rating the AC’s skill [H(2) = 1.080,
p= 0.583], helpfulness [H(2) = 0.097, p= 0.953], and frustration
[H(2) = 0.475, p= 0.789]; perceived ratings by the AC in terms
of intelligence [H(2) = 5.605, p= 0.61], skill [H(2) = 0.407,
p= 0.816], helpfulness [H(2) = 1.151, p= 0.563] and frustration
[H(2) = 0.568, p= 0.753]; perceptions of teamwork in terms of
calmness [H(2) = 1.363, p= 0.506], efficiency [H(2) = 0.845,
p= 0.655], or understanding [H(2) = 0.285, p= 0.867]; desire
to collaborate again with the AC [H(2) = 3.12, p= 0.210];
and participants rating their own intelligence [H(2) = 2.002,
p= 0.368], skill [H(2) = 0.406, p= 0.816], helpfulness
[H(2) = 4.584, p= 0.101] or frustration [H(2) = 0.705, p= 0.703].
Taken together, these results indicate that disclosing a diagnosis
results in positive discrimination in terms of higher perceptions
of intelligence, finding information provided by the AC as more
useful and resulting in greater tolerance, and more positive
perceptions of being helpful toward the AC. However, in each
case these effects were significant for the autism -disclosure group
in comparison to the control group, but not so for the dyslexia-
disclosure group (where participants were only significantly
different from the control group in terms of finding the
information provided by the AC as more useful). This suggests
that positive discrimination observed due to the disclosure of an
autism diagnosis is specific to autism and not the wider presence
of a label in general.
RQ2b: Explanations Provided by
Participants About Their Perception
and Behavior Toward the AC
Explanations provided by participants about the utility of
the AC information was categorized into three types (see
Table 4), which accounted for 80% of all participants.
These categories included: (1) participants who felt that
the information supplied was redundant or inaccurate and
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TABLE 4 | Frequency and distribution of coded statements from participants
about the information received from the AC.
No. of coded statements Kruskall-
(% of participants) Wallis
Dyslexia- Autism-
Control disclosure disclosure
(n= 80) (n= 83) (n= 92) H
Information redundant 37 (46%) 33 (40%) 28 (30%) 3.456
Information explained
misunderstanding
4 (5%) 8 (10%) 12 (13%) 3.137
Information led to
greater tolerance
14 (18%) 23 (28%) 44 (48%) 12.169∗
Ambiguous statements 26 (33%) 22 (27%) 15 (16%) 1.642
∗p-value <0.05. Post hoc pairwise comparisons with Bonferroni correction
showed a significant difference only between participants in the autism condition
and the control condition (p = 0.002).
of no use to facilitating the game collaboration (termed
“information redundant”); (2) participants who claimed that
the information provided helped them to make sense of
why they were left in prison by their partner (termed
“information explained misunderstanding”); and (3) participants
who claimed that the information provided led to greater
tolerance, either because it led to greater confidence in
themselves, prepared them to be more patient, or incentivised
them to help more (“information led to greater tolerance”). The
remaining comments (20% of participants) were ambiguous,
either because they did not provide an explanation, made
tangential comments not related to the question, or ignored the
question altogether.
Table 4 and Figure 2 summarize the frequency and distri-
butions of the coded statements. It highlights a trend in
which participants in the autism-disclosure group were less
likely to see the information they received from the AC as
redundant and significantly more likely to claim that it led to
greater tolerance in comparison with the control group (autism-
disclosure group = 48%, control group = 18%). The dyslexia-
disclosure group showed a similar trend but it was not significant
compared with the control-disclosure group.
The finding that participants in the autism condition are
significantly more likely to report that the AC information
led to greater tolerance compares with increased perceptions
of behaving in a more helpful way (reported above). It is
also noticeable that diagnostic disclosure aids interpretations
about the misunderstanding experienced, with 13% of parti-
cipants in the autism condition linking the diagnosis to the
misunderstanding compared with only 5% of participants
in the control condition, although this is not significant at
α<0.05. Thus diagnostic disclosure of autism leads to
increased perceptions of tolerance and increased likelihood that
it will help to explain the misunderstanding experienced in
the game. However, we also found that the same disclosure
of a diagnosis can potentially have the opposite effects, being
perceived as redundant information. Table 5 illustrates the range
of statements provided by participants.
Thus, although disclosing a diagnosis of autism generally
results in more positive perception (seeing disclosure from the
AC as useful, perceiving oneself to be more helpful) it can also
lead to negative perceptions (seeing the disclosure as redundant
and useless). These differing reactions help to explain why
disclosing a diagnosis may arouse anxiety for autistic people,
because it is a cost-benefit decision which autistic people in
particular may find especially hard to evaluate given that it would
require a nuanced social reading of others. Moreover, the lack
of an association between participants perceiving themselves to
be helpful and helpful behavior suggests a bias in overestimating
one’s own prosocial behavior toward autistic people.
FIGURE 2 | Comparison of participants’ perceptions about the information provided by the AC.
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TABLE 5 | Illustrative examples of reasons provided by participants for finding the information useful.
Illustrative example
Category Control Dyslexia-disclosure Autism-disclosure
Information redundant The information was so generic as to be
useless in trying to formulate a strategy
They stated they were dyslexic, but I
didn’t find that to be particularly useful
information. It tells me nothing of their
ability to perform the task
They just said they were autistic, which
wasn’t really relevant
While I understood what they was trying to
share it was not useful to me
I guess it was useful but I’m not sure
what being dyslexic has to do with
rolling a ball through a maze
I did not know how to alter my playstyle
through the information they shared with
me, such as them being autistic
Information explained
misunderstanding
They said they were not good at multitasking,
which may explain why they did not notice
my gate could have been unlocked
My partner shared they were dyslexic
and had trouble with multiple tasks,
and that might have explained why
during one game they navigated
through half the maze but failed to
rescue me from the prison?
My partner explained that he was autistic
which made it difficult for him to multi-task
which explained why perhaps he forgot to
do things in one of the games
A little, he said he wasn’t good at
multi-tasking (probably why he forgot to let
me out as soon as he was able to) but he
was good at maneuvering the ball
It tempered my frustration when my
partner forgot to let me out of prison in
one of the games
It was useful because I can somewhat
understand how they performed the way
that they did
Information led to
greater tolerance
They told me they were good at steering,
which they were, and they told me they
weren’t great at multitasking which I had in
mind when they forgot to free me until the end
It allowed me to be more empathic to
the person controlling the other ball,
and told me I didn’t need to worry
about their control of the ball
He said as he was autistic he was not very
good at focusing on multiple tasks at once,
which made me more patient when I was
locked in prison and only he could move
I think I had left him confident and calm, so
that we could play this game at our best
they said they were dyslexic but still
good at following orders, I was ready to
give them a bit more help of needed
but they navigated just fine
They mentioned that they struggled to juggle
multiple tasks at once due to suffering with
autism. This was useful to know and was
evident in some of the games that we
played. As a result I tried to work as quickly
as I could to complete my sections of the
games, in order to compensate for times
where my partner may have struggled to
cope with multiple scenarios in the game
DISCUSSION
The first research aim (RQ1) was to create a simulated interaction
for exploring the psychological effects of labels exposed to
different groups of participants. Dyad3D, combined with a
post-game questionnaire, proved to be a very efficient means
of gathering simulated interactional data. Participants found
the interaction highly believable, with an average quality of
deception rating of 3.83 out of 5, with only 9 participants (3.4%
of participants passing all other inclusion/exclusion criteria)
explicitly expressing doubt about whether the AC was human.
All sampled participants also made attributions of intentionality,
including mental/emotional states when describing the behavior
of the AC showing that participants were psychologically
orientated to the AC as another human player. The nature of
the deception was also successful with participants providing
feedback that it was efficient, believable, and enjoyable. Thus
Dyad3D was broadly successful in creating an efficient, believable
and controlled interaction that could be used to generate
insights about the differential effects labels produce on social
perception and behavior, although there remains scope for
improvement especially in terms of introducing ecological
complexity into the task (discussed further below). Further
studies are required to help explore the viability of the method,
thus a key contribution of the present study is to make the
source code for the game freely available at: https://bitbucket.org/
enghoff/dyad3d.
The second research aim examined the effects of disclosing
a diagnosis and was split into two parts. RQ2a compared self-
reported data in the post-game questionnaire with behavior
recorded in the game. Our findings concur with existing
reports that the label of autism has a broad positive effect
on social perception (Sasson et al., 2017), resulting in higher
perceptions of intelligence of the AC, and perceiving information
communicated by the AC as having more utility. However, there
is also evidence to suggest that such effects are temporary, rather
than enduring. Although participants find diagnostic disclosure
about autism useful, they are less likely to believe it impacts
their own ability to provide help in the task. In addition, there
was no significant association between participants who believed
that the AC diagnostic disclosure made them more helpful
compared to whether they were actually helpful during the game.
These findings help to explain why diagnostic disclosure, despite
enhancing social perceptions by others, can still result in negative
discrimination in terms of behavior as reported by autistic people
themselves (Davidson and Henderson, 2010;Powell and Acker,
2016;Treweek et al., 2018).
RQ2b further highlighted why diagnostic disclosure is not
straightforward, since there were varied reactions toward the
information supplied by the AC. Although most participants
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found the information to be useful, they were less likely to
articulate why. Many participants felt that the diagnosis of autism
explained the misunderstanding experienced in the game, yet
a smaller number of participants also felt that the diagnostic
disclosure was redundant information. These varied reactions
highlight why diagnostic disclosure is a risky decision for
autistic people. The label of autism can ameliorate confusion
associated with a misunderstanding, but it can also potentially
exasperate underlying frustrations depending on the cognitive
frame of the perceiver.
These findings contribute to understanding the double
empathy problem, a term used to describe the differences
in mutual understanding which arise between autistic and
non-autistic people on account of their different dispositional
outlooks (Milton, 2012;Milton et al., 2018). Interactions between
autistic and non-autistic people are subject to bias, such as
higher perceptions of awkwardness associated with autistic facial
expressions (Faso et al., 2014;Brewer et al., 2016), or non-autistic
people negating autistic social achievements in light of their
diagnostic label (Heasman and Gillespie, 2018b). While to date
research has focussed on how the label of autism affects the way
autistic people are seen by others, the contribution of this study
is to highlight that the label of autism also affects how others see
themselves, specifically that they see themselves as more helpful
than they actually are. Over-estimating one’s own helpfulness
is understandable, since it protects the positive identity of the
perceiver and brings their self-perception into line with their ideal
Self as presented in the research. However it could lead to seeing
less validity in the claims made by autistic people that such efforts
toward them are not helpful; or, due to the paradoxical effects of
helping (or even perceiving that one is being helpful: Gillespie
and Hald, 2017), this bias may even lead to expectations that
autistic people should be grateful.
Potential evidence of a “helping bias,” where participants
perceive themselves to be more helpful toward autistic people
than they actually are, has a number of real-world implications
for autistic people. In a caregiving context, such findings
align with other research on communicative disabilities where
caregivers, and care-receivers have differing ideas about the levels
of support being provided in the relationship (Goodwin, 2004;
Moore and Gillespie, 2014). A helping bias would mean that
caregivers are potentially less responsive to providing support if
such support is seen by caregivers as surplus to the caregiving
efforts already made. Within the context of employment,
adjustments to the workplace can have a great impact on
accessibility for autistic employees (Baldwin et al., 2014) and
in many countries (e.g., the United Kingdom) it is a legal
requirement to make reasonable adjustments for people with
disabilities. However, the extent to which adjustments are seen
as reasonable is subjective from the perspective of line-managers
and HR professionals; a helping bias may be a contributory
factor in explaining reports about why adjustments are rejected
(Heasman, 2017), because managers, and HR professionals may
already believe they are providing adequate support.
The study therefore highlights that diagnostic disclosure
remains a risky decision for autistic people. The label of autism
can lead to some improved perceptions of intelligence but
also create additional mistaken beliefs about how helpful one
actually is toward the autistic individual, which could become
problematic in future interactions where levels of support are
negotiated. Further research is required to understand how
diagnostic disclosure can lead to more consistent and sustained
positive effects on social perception and behavior. In particular,
the relationship between autism knowledge and the psychological
effects of disclosing a diagnosis of autism is receiving increasing
attention (Gillespie-Lynch et al., 2015;Sasson and Morrison,
2017;Crane et al., 2018). It is possible that such effects may
be associated with increased self-awareness of one’s own taken-
for-granted assumptions toward others with a diagnosis, which
raises the question as to whether knowledge of the effects of
a helping bias could potentially serve to correct the effects of
such a bias? It also remains to be seen whether these effects
would be observed in interactions between autistic people, which
have rarely been studied but have been shown to exhibit more
complimentary features of interaction (Heasman and Gillespie,
2018a). Additionally, beyond those that perceived themselves
to be helpful, future research should also explore further lay
understanding of autism, since some participants reported that
the diagnostic disclosure was irrelevant information for the
purposes of collaboration.
In summary, this study has helped to illustrate both
positive and negative discrimination resulting from a diagnostic
disclosure of autism, with social perception more favorable
than actual social behavior. Future research using simulated
interactions can further differentiate the factors affecting social
perception and behavior of non-autistic people toward autistic
people, and in doing so potentially evolve the current design
into an intervention for correcting biases that contribute to the
double empathy problem. A central contribution of the study is
therefore to make the source code for Dyad3D freely available.
The study is reproducible and opens up the possibility for future
studies to implement more ecological features into the game (e.g.,
varying the form in which the stimulus is presented which has
been shown to shape social perceptions: Sasson et al., 2017), and
to improve the sensitivity and diversity of behavioral measures.
LIMITATIONS
Limitations pertaining to RQ1, the viability of the deception, stem
from the use of a computer-mediated task which is contingent on
people’s ability to interact with others via a computer interface.
While this provides a means for replicating the experience
of an interaction efficiently, it also raises questions about the
validity of the interaction, because the identity of the AC is
not open for questioning. The internet, and the development of
networked virtual worlds, have created multiple opportunities
for the same individual to present their identity in different
ways (Gillespie et al., 2018) and consequently people are aware
that virtual interactions may be risky and not authentic (Evans,
2012). Thus there may be levels of doubt associated with the
authenticity of the interaction studied even if it is not explicitly
mentioned or reported by participants when asked to rate the
quality of deception. Moreover, such doubts may be furthered
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because of a lack of ability to see, hear or verbally interact with
the AC which means such concerns about validity cannot be
questioned. This means that there remains a question about the
generalizability of such findings to other ecological contexts. It is
possible, for example, that other modalities of interaction such
as body language and physical appearance could alter whether
positive or negative aspects of a diagnostic label become salient
in social perception and behavior. As discussed previously, we
deliberately limited the modalities of interaction in order to
explore the viability of the process before iteratively introducing
future ecological elements. Yet enhancing the strengths of the
deception may itself be achieved through the introduction of
further interactivity such as the ability to send messages in the
game (which has since been added as a configurable option
to the current game setup). Further structural improvements
are also possible, such as improving collaborative basis of
the game (e.g., the player and AC could share resources or
empower each other’s abilities), or by changing the way in which
the stimulus is presented (e.g., a pre-recorded webcam of the
“online” player).
Limitations pertaining to RQ2a, which compares self-report
and behavioral data, highlight concerns about the social aspects
of the game and what it reveals about interpersonal dynamics.
In the present study we deliberately presented a minimalist
situation to see what knowledge participants would import to the
disclosure of a diagnosis, particularly since in real life discovering
someone’s diagnosis may not always be associated with adequate
auxiliary information about the diagnosis. Thus it was interesting
to find that even in a predominantly cognitive task with minimal
information about the diagnosis, disclosure resulted in positive
evaluations of the ACs’ intelligence, and utility of information
shared. However, in this context there is no reason not to be
generous in social perceptions. Perceptions might change if the
consequences were higher (e.g., job hiring) where there was a
major investment in the outcome of the interaction.
Another challenge of the present design is that Dyad3D is a
primarily goal-orientated activity which may supersede the social
obligation to help one’s partner. Although a social component
exists in the game in terms of freeing the other player from prison
and having to share responsibility for opening different doors in
the game between player and AC, it is still possible to play the
game in a primarily strategic way. Revising structural aspects of
the game and associated behavioral measures should therefore
be explored to build a more ecologically valid understanding of
social interaction. For example, there could be individual scores
for each player which are then aggregated to form an overall
score for the dyad. This could help boost an understanding
of teamwork and collective identity. Likewise, there could be a
reward system which benefits the dyad if close spatial proximity
is maintained. No significant differences were observed in
mean distance between players, mean time to complete levels,
mean time between collecting gold cubes, mean keystrokes,
or mean keystroke duration. These null results indicate that the
significant behavioral differences observed should be interpreted
with a degree caution and highlight room for improving the
way behavioral measures operationalized in the game detect
meaningful action.
Limitations pertaining to RQ2b, understanding the expla-
nations provided by participants, highlight a potential bias
in terms of memory retrieval. In-game activity may deplete
attentional resources required to accurately report on one’s
interaction, although there were no significant differences obser-
ved when comparing gaming experience with helpfulness or
recognizing the information shared as useful. Moreover, Dyad3D
used deliberately simple and intuitive input controls of the arrow
keys, yet even this can place a demand on users not familiar with
computers or navigation via keyboard inputs, which represents
another potential distraction from accurate reporting. The ability
to ostensibly exchange messages (i.e., a chatbot interface) could
represent more valuable qualitative data, as instead of asking
participants to report on the interaction in hindsight, one can
observe their actual attempts at communication to build a social
understanding of the situation. To help address this challenge, a
configurable chat interface option has already been included in
the existing source for the game.
Finally, within the protocol we examined success in terms
of whether participants believed they were interacting with a
human. However, deception arguably also involves a second
component, which is whether participants believe in the
diagnosis that was disclosed. In our data, no participants gave
an indication that they did not believe in the diagnosis from
their verbal explanations of the interaction, but further studies
may want to explicitly ask this question post-deception reveal.
Additionally, we did not assess levels of autism knowledge since
there are conflicting findings about whether there is a relationship
between knowledge and attitudes in understanding autism
(White et al., 2016), and the cross-cultural bias of such tools
has been questioned (Harrison et al., 2017). Nevertheless, further
studies could benefit from implementing an autism knowledge
questionnaire, particularly as it could help to understand
more about why there are both positive, and negative aspects
of discrimination associated with disclosure as observed in
the present study.
ETHICS STATEMENT
This study was carried out in accordance with the recommenda-
tions of The Research Ethics Code, The London School of
Economics Research Ethics Committee with written informed
consent from all subjects. All subjects gave written informed
consent in accordance with the Declaration of Helsinki. The
protocol was approved by the London School of Economics
Research Ethics Committee (REC approval ref.: 000674).
AUTHOR CONTRIBUTIONS
BH designed and wrote the code for Dyad3D, recruited the
participants, conducted the pilots, gathered and analyzed the
main study data, and wrote the manuscript. AG provided the
intellectual guidance in developing the research throughout,
including through discussions, and commentary on aspects of the
written manuscript.
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Heasman and Gillespie The Effects of Disclosing an Autism Diagnosis Online
FUNDING
This work was supported by a Ph.D. studentship from the
Economic and Social Research Council (ESRC)
(Grant no. ES/J500070/1).
ACKNOWLEDGMENTS
We would like to thank Tamara Ansons, Lars Wicke, Seth Lusic,
Giovanna Rossin, Denise Zimmerman, and the Behavioural
Research Lab, LSE.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
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