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Abstract

Cybersecurity has been identified as a potentially strong career for some autistic individuals who possess systemising traits and special interests in technology. Using a strengths-based approach, career education and training for adolescents may increase confidence and motivation for future employment. The present study recruited 16 autistic adolescents with an interest in technology to determine the feasibility of a co-produced cybersecurity program, delivered as a the three-day in-person workshop supported by post-graduate cybersecurity mentors. Participants completed a feedback survey, as well as pre- and post-program questionnaires relating to self-determination and self-efficacy. Demand for the program was sufficient, with more than 20 expressions of interest within a three-week recruiting period. Participant survey responses provided general support for the acceptability and expansion of the program, and key learnings were identified, with a strong theme relating to the types of cybersecurity jobs and career pathways. Comments relating to adaptation and practicality included, ‘it was a bit too long each day’, ‘too many videos’, and ‘[questions] needed more explanation’. Assessment of preliminary efficacy revealed significant increases in self-efficacy within some cybersecurity domains. Positive demand and acceptability support the need for further feasibility testing, using themes drawn from the surveys to improve practicality and implementation of the program.

Keywords

autism education adolescents technology transition to adulthood strengths-based cybersecurity self-determination self-efficacy positive youth development

Introduction

In Australia, ∼1.1% of the population has been diagnosed with autism (Australian Bureau of Statistics, 2022), a condition marked by differences in social communication and interaction skills, and restricted, repetitive behaviours that can make navigating mainstream society challenging (American Psychiatric Association, 2013). The prevalence of autism has increased by more than 40% since it was reported at 0.8% in 2018, which may be attributed to broadening criteria, increased awareness, and improved diagnostic tools (Australian Bureau of Statistics, 2022; Bölte et al., 2019a). Regardless of the cause, the rising prevalence generates an increased need for support services and tools to improve adult outcomes for Australian autistic youth. This is evident in the historically low employment rates of working-age autistic adults, reported lower than both those without disability and those with disabilities other than autism (Australian Bureau of Statistics, 2022). Despite possessing the skills and desire to find employment, autistic adults report issues due to limited opportunities, educational and skill gaps, communication challenges, and a lack of accommodations by employers (Hatfield et al., 2017).

Strengths-Based Approaches to the Transition to Adulthood

Traditional transition supports for autistic adolescents often look to address the difficulties faced by these individuals, which can inadvertently overshadow their capabilities (Acevedo, 2020). Recent evidence suggests approaches that identify and leverage individual strengths and interests can significantly enhance autistic adolescents’ experiences in school and the transition to adulthood (Hatfield et al., 2018; White et al., 2023). Such strengths-based approaches are grounded in the positive psychology framework (Park & Peterson, 2008), which posits that focusing on an individual's strengths rather than their limitations can lead to better adult outcomes (Lee et al., 2020; Scott et al., 2018). For adolescents, positive youth development (PYD) aims to provide opportunities to participate in meaningful activities which allow adolescents to see themselves as capable individuals with the potential to succeed (Larson, 2006; Ramey & Rose-Krasnor, 2012). Unlike approaches to preventing or correcting maladaptive behaviour, PYD provides a sense of purpose and creates opportunities for adolescents to build on their strengths (Shek et al., 2019; Yuen et al., 2022), leading to the development of skills, attitudes, and values necessary for success in adulthood (Bowers et al., 2010).

Importantly, strengths-based approaches account for the diverse abilities and potential contributions of autistic individuals, recognising their unique skills, talents, and interests, and use these as a foundation for developing tailored strategies for employment and independent living (Carter et al., 2015; Jones et al., 2022; Scott et al., 2018). Research indicates this approach can lead to improved employment outcomes by fostering greater self-efficacy, job satisfaction, and career stability (Bölte et al., 2021; Hatfield et al., 2018; Lee et al., 2020). For example, when autistic individuals are encouraged to pursue careers aligned with their strengths, whether in areas such as technology, detail-oriented tasks, or creative fields, they are more likely to experience higher levels of job satisfaction and engagement (Bölte et al., 2021). Furthermore, these approaches facilitate the development of personalised vocational training and support systems, creating more inclusive and accommodating work environments, which are critical for overcoming the barriers to employment (Mawhood & Howlin, 1999). Supporting career pathways that align with an individual's interest and fostering accommodating environments also promotes the development of sustainable careers, characterised by long-term employability and personal fulfilment (De Vos et al., 2020).

Self-Determination and Self-Efficacy

Self-determination refers to an individual's capacity to engage in self-directed behaviour and actively pursue goals and aspirations that are personally meaningful (Wehmeyer, 1998, 2005). Higher self-determination has been linked to positive adult outcomes for individuals with disabilities, including higher post-secondary education rates, a greater chance of employment, and higher quality of life (Kim, 2019; Petcu et al., 2017; Shogren et al., 2015; Wehmeyer et al., 2010; Zalewska et al., 2016). However, autistic adolescents have been reported to have lower self-determination than neurotypicals without a disability (Shogren et al., 2018b) and those with other disabilities (Chou et al., 2017; Kim, 2019; Shogren et al., 2018a). Self-determination theory (SDT) proposes that self-determination increases when individuals experience autonomy, competence, and relatedness—the three basic psychological needs that support intrinsic motivation (Deci & Ryan, 2000). Autonomy, in particular, is viewed as a fundamental human need, and evidence suggests it is a key factor contributing to job satisfaction in autistic adults (Pfeiffer et al., 2018). For autistic young adults, a major employment barrier is the perceived lack of opportunities aligned with their skills and interests, limiting their ability to make self-determined choices about their future (Goldfarb et al., 2019; Nicholas & Klag, 2020). Strengths-based programs can address this by fostering autistic adolescents’ belief in their capabilities, promoting autonomy, and, in turn, increasing the likelihood of better adult outcomes.

Similarly, self-efficacy, defined as one's belief in their capability to succeed, significantly influences an individual's task engagement and persistence (Bandura, 1977), and is a crucial factor in overcoming job barriers and planning for future success (Pinquart et al., 2003). This concept is well-supported by research, showing a strong correlation with job performance, job satisfaction, and academic success in neurotypical individuals (Judge & Bono, 2001). Similarly, for autistic individuals, higher self-efficacy is linked to improved life satisfaction and quality of life (Lorenz et al., 2016). However, autistic adults generally have lower self-efficacy compared to their neurotypical counterparts (Chou et al., 2017; Lorenz & Heinitz, 2014). Notably, those employed in supported roles exhibit higher self-efficacy than unemployed autistic individuals and those employed in roles without autism-specific supports in place (Lorenz et al., 2016; Lorenz & Heinitz, 2014). Successfully performing tasks and positive appraisal are considered the most effective ways to enhance self-efficacy (Bandura, 1997; Kulakow, 2020; Ward & Esposito, 2019), leading to the theory that autistic individuals in supported roles may experience more successes and recognition. Therefore, another important target for strengths-based programs should be to provide autistic individuals with opportunities to learn and practise skills which will translate to employment or further education, building their self-efficacy and confidence for post-secondary school opportunities (Lorenz & Heinitz, 2014).

Cybersecurity

One area where autistic strengths align well with employment opportunities is in the field of cybersecurity. Some of the cognitive and perceptual traits associated with autism, such as attention to detail, pattern recognition skills, and ability to focus on complex tasks for extended periods, are valuable in technical roles (Cope & Remington, 2022; de Schipper et al., 2016; Spek & Velderman, 2013). Cybersecurity professionals are often required to identify subtle anomalies in data, detect and analyse patterns of suspicious online behaviour, and solve intricate software problems (Dawson & Thomson, 2018). A framework developed by the National Initiative for Cybersecurity Education (NICE) emphasises the importance of recognising and nurturing diverse skill sets in cybersecurity, promoting a broad spectrum of skills and competencies, including attention to detail, analytical thinking, and problem-solving (Dawson & Thomson, 2018; Newhouse et al., 2017). Not only might autistic people possess these skills, but they often have special interests in areas of cyber and technology too, creating motivation towards employment (Dunn et al., 2015; Jones et al., 2021).

By integrating strengths-based approaches with the competencies outlined in the NICE framework (Newhouse et al., 2017), we can better align training and employment opportunities with the natural abilities of autistic individuals, thereby enhancing their career prospects in this critical field. An example of this integration is the online course Genius Armoury (Untapped, 2021), which was co-produced with neurodivergent adults to support autistic individuals in exploring their potential interest and suitability in a career in cybersecurity. The introductory syllabus offers insight into the role of a cybersecurity professional and the nature of their work, including the current cybercrime landscape, common attack methods, core technologies, and potential career pathways. Throughout the course, the diverse skills considered valuable in the field are emphasised with the objective of helping participants identify how their own strengths may align with cybersecurity roles.

The present study aimed to develop and evaluate the feasibility of a strengths-based program for autistic adolescents, designed to foster skills and interest in pursuing a future in the cybersecurity workforce. The Genius Armoury (Untapped, 2021) course was selected to deliver technical skills and knowledge, and was supplemented by three additional modules focused on exploring autistic identity and character strengths. Together, these components formed the Cybersecurity Education and Training (CyberSET) program. CyberSET was designed to foster an inclusive and supportive learning environment that leverages the strengths of autistic adolescents while offering opportunities for skill development and achievement. Prior to this study, neither Genius Armoury nor the identity and strengths modules had undergone formal evaluation with autistic adolescents. The current study piloted the program as an out-of-school bootcamp to assess its feasibility for delivery to autistic adolescents, further hypothesising that the program would enhance participants’ self-determination and self-efficacy.

Methods

Design

This research is based upon the first two steps of the Medical Research Council framework for developing complex interventions (Skivington et al., 2021), which covers development and feasibility testing. Development of the program involved identifying the appropriate cybersecurity course for autistic participants and adapting this to ensure an adolescent-friendly strengths-based approach. To assess the feasibility of CyberSET, eight areas of focus were evaluated: acceptability, demand, implementation, practicality, adaptation, integration, expansion, and preliminary efficacy (Bowen et al., 2009). A definition of each area of focus and its application in this study is outlined in Table 1.

Table 1.

Feasibility Areas of Focus (Bowen et al., 2009) and Their Application to the CyberSET Evaluation.

Area of focus	Definition	Application to CyberSET evaluation
Acceptability	Participants’ satisfaction with the intervention	Qualitative approach with data collected via participant surveys
Demand	The demand for intervention within the autistic population	Qualitative approach with data obtained via participant surveys and a quantitative approach with recruitment and retention rates
Implementation	How the intervention is delivered	Quantitative approach with data collected via facilitator fidelity report
Practicality	Ability to deliver the intervention with available resources	Qualitative approach with data collected via participant surveys
Adaption	Modifications made to the intervention	Qualitative approach with data collected via participant surveys
Integration	Changes required to integrate the intervention into existing health and community infrastructure	Qualitative approach with data collected via participant surveys
Expansion	Consideration as to how the intervention could be increased in scale or applied to a different population/setting	Qualitative approach with data collected via participant surveys
Limited efficacy	Preliminary efficacy testing and evaluation of the measurement framework	Quantitative evaluation through adolescent-reported pre- and post-test outcome measures

Approval was obtained from the Human Research Ethics office (HRE2023-0035) at Curtin University, Perth, Western Australia. Participation in the research was voluntary, and participants could choose to drop out of the research at any time.

Phase 1: Program Development

Based upon research surrounding the components of existing strengths-based programs (Rumsa et al., 2025), CyberSET was developed with the following essential components: (1) personalised strengths profiling; (2) career exploration and skill matching; (3) skill development; and (4) individualised goal setting. Supplemental Appendix A maps these ingredients, as well as others, to research surrounding PYD (Ramey & Rose-Krasnor, 2012), SDT (Deci & Ryan, 2000), and self-efficacy (Bandura, 1977). The course involved nine modules comprised of a combination of video content, written content, reflective questions, technical quizzes, and worksheets, across two online platforms.

The first three modules, housed on the Global Challenge Platform (Global Challenge, 2025), were designed to encourage adolescents to reflect on their identity and strengths, building confidence prior to the technical content. The modules were developed by the first author in collaboration with a reference group of five autistic young adults. Although not a requirement to participate, each member of the group was enrolled in tertiary education, across a range of fields, including computer science, psychology, and commerce. Across two meetings, the reference group workshopped content, information delivery methods, and reflection activities to ensure the material was relevant, engaging, and aligned with the experiences and preferences of autistic adolescents.

One key recommendation from the reference group was to provide participants with a tangible representation of their personal strengths. To achieve this, the authors developed a questionnaire assessing character strengths aligned with both the NICE framework (Newhouse et al., 2017) and existing literature on common strengths among autistic individuals (Bölte et al., 2019b; Kirchner et al., 2016; Warren et al., 2021). Using a Likert-scale from 0 (not at all like me) to 4 (very much like me), the questionnaire included statements such as ‘I find it easy to pay attention and give tasks my full focus’ (attentive), and ‘If I see something that needs to be done, I do it without being told’ (proactive). Each participant received a personalised visual summary of their strengths profile (e.g., Supplemental Appendix B) and the opportunity to explore cybersecurity job profiles matched to their strengths.

The subsequent introductory cybersecurity education, delivered through the Genius Armoury platform (Untapped, 2021), consisted of six modules: (1) introduction to cybersecurity; (2) threats and exploits; (3) computer networking; (4) digital forensics; (5) programming; and (6) governance. To provide real-world insight, the program also incorporated career talks from three independent industry professionals, one of whom identified as neurodivergent, who shared their job roles, industry experiences, and educational pathways. Students listened to each speaker for 15–20 min and then had ∼10 min to engage in questions.

Phase 2: Feasibility

Participants

The program was advertised through the Autism Academy for Software Quality Assurance (AASQA) CoderDojo clubs and a number of social groups using a recruitment flyer distributed via email and on social media. Primary recruitment through AASQA ensured pre-existing interest in cyber and technology. Within a three-week recruiting period, expression of interest was received from 22 potential participants. For this study, participation was capped at 16 students, due to the accessibility of resources, such as mentors and laptops, to accommodate the group size. Participants were registered in chronological order of their contact with researchers until capacity was reached. Prior to registration, information sheets were provided to both adolescents and their parents. They were given the opportunity to ask questions and discuss the study to ensure understanding. Written informed consent was obtained from the parent or guardian, and written assent was obtained from the adolescent when they chose to participate. Two participants dropped out of the program after the first day due to personal reasons, and one participant failed to complete the quantitative post-test outcome measures. Therefore, the final number of program participants was 14, of which 13 completed all outcome measures.

Inclusion criteria for adolescents were (a) aged between 12 and 18 years, (b) having a diagnosis of autism spectrum disorder from clinical child mental health services according to DSM-5, (c) following a mainstream school curriculum, and (d) able to read and converse in English. The self-reported diagnosis was confirmed using the Social Responsiveness Scale – Second Edition (SRS-2; Constantino & Gruber, 2012). The SRS-2 comprises 65 items which assess the severity of autistic traits, including social awareness, social cognition, social communication, social motivation, restricted interests, and repetitive behaviour. The measure was reported to have strong reliability and cross-cultural validity in studies with school-age children in clinical settings (Bölte et al., 2008; Bruni, 2014).

The socio-demographics of adolescents and their parents are detailed in Table 2. Adolescents ranged in age from 11 to 15 years, the majority of whom were male (78.6%). Most adolescents demonstrated high autistic traits (M = 79, SD = 9.12) according to the SRS-2 (Constantino & Gruber, 2012), with ADHD as the most coming cooccurring condition (57.1%). The majority of parents providing the parent-report data were female (85.7%), with the most common level of completed education being tertiary education (92.9%).

Table 2.

Sociodemographic and Clinical Information of Adolescent Participants of the CyberSET Program, as Reported by Their Parent.

Characteristic	CyberSET (n = 14)
Child age, mean (SD) (years)	13.36 (1.28)
Child age range (years)	11–15
Child gender, n (%)
Male	11 (78.6%)
Female	1 (7.1%)
Other	2 (14.3%)
SRS-2 T-score, n (%)
Within normal limits (30–59T)	0
Mild (60–65 T)	2 (14.3%)
Moderate (66–75 T)	2 (14.3%)
Severe (76 T or higher)	10 (71.4%)
Other medical conditions reported, n (%)
NA	3 (21.4%)
Anxiety	3 (21.4%)
ADHD	8 (57.1%)
Other (e.g., dyslexia, dysgraphia, and sensory processing disorder)	5 (35.7%)
Schooling, n (%)
Public	3 (21.4%)
Private	7 (50%)
Other (incl. home school)	4 (28.6%)
Parent age, mean (SD)	47.57 (4.73)
Parent age, range	37–52
Parent gender, n (%)
Female	12 (85.7%)
Male	2 (14.3%)
Parent highest education, n (%)
Secondary school	1 (7.1%)
Tertiary degree	13 (92.9%)

CyberSET = Cybersecurity Education and Training; SRS-2 = Social Responsiveness Scale – Second Edition; ADHD = attention deficit hyperactivity disorder.

Program

The program was delivered in a bootcamp style, consisting of three 5-hour days, providing structured, intensive sessions while allowing for breaks to manage sensory and cognitive load. Delivered on campus at Curtin University, each student had their own device to complete the course at their own pace, facilitating a personalised learning experience. Adjacent to the main classroom, several smaller rooms were available for students who would prefer to complete the program in a quieter space.

To further support student's needs and maintain focus throughout the day, the schedule included breaks for morning tea and lunch, as well as the option to take breaks whenever needed. To supplement break times and encourage social interaction between students, researchers provided a range of leisure activities such as boardgames and drawing materials. In addition to the first author being present as the primary facilitator, four postgraduate cybersecurity students from Curtin University were present each day as mentors to support students with technical questions throughout the course and provide relief supervision if students needed a break. All participants were welcome to bring a support person with them, of which two were accompanied by their parent at each session.

Data Collection

Prior to the program, participant's parents were emailed a link to a sociodemographic survey (age, gender, educational background, and diagnosis) to be completed alongside the SRS-2 (Constantino & Gruber, 2012). Parents were also emailed a link to an online survey containing a suite of outcome measures, comprised of four questionnaires, to be completed by the adolescent participant at home. The same suite of measures was competed pre-test, prior to the first day of the program, and post-test, within a week after the program finished.

Attendance and Fidelity. The first author attended each session as the primary facilitator and was responsible for ensuring sessions were conducted according to the design. A fidelity report (Supplemental Appendix C) was completed each session, consisting of a participant attendance tracker and a ‘yes’/‘no’ checklist for achieving the contextual active components listed under the following headings: session preparation, introduction, online program, breaks, career talk, and overall experience. Where a component was checked ‘no’, a reason was to be provided for why it was not achieved in the session.

Feedback Surveys. Following completion of the program, as part of the post-test assessment, a survey was conducted to gain participant perspectives on a range of areas of focus. This survey was completed during the last session, with a researcher present to elaborate on the questions if the student was unsure. Consisting of 13 broad, open-ended questions, the survey evaluated six areas of focus: acceptability, demand, practicality, adaptation, integration, and expansion. For example, what did you enjoy the most/least? What was missing from the program which you would have liked to learn or practice? What do you think were the barriers to you benefitting from the program?

Outcome measures. The AIR self-determination scale (AIR-SD; Wolman et al., 1994) student report form, comprising 24 questions on a 5-point Likert scale, measures an adolescent's perception of how they go about getting what they want or need (Garrels & Granlund, 2018). The measure consists of several subscales: Things I Do, How I Feel, What Happens at School, and What Happens at Home. Higher scores are indicative of higher self-determination and are calculated by adding together all responses, or those of specific item numbers, for the subscales. The measure has previously been regarded as suitable for use in assessing students with disabilities (Shogren et al., 2008), and the strong reliability demonstrated in the current study (Cronbach's α = .95) further endorses its use with autistic adolescents.

The Basic Psychological Need Satisfaction Scale–Autonomy Subscale (BPNSS–A; Deci & Ryan, 2000; Gagné, 2003) uses self-report to quantify autonomy in decision making. Autonomy is defined as feeling free to decide how to live one's own life and is recognised by SDT as a key component of intrinsic motivation (Deci & Ryan, 2000). The subscale consists of seven items on a 7-point Likert scale, three of which are reverse scored. The overall score is calculated by finding the mean of the corrected scores, with higher scores indicating greater satisfaction in the participant's experience of autonomy. The measure demonstrated good predictive validity and adequate reliability in its development (Gagné, 2003), as well as good internal consistency in a recent study of college students with disabilities (O'Shea et al., 2023), but had not previously been evaluated with autistic adolescents. The current study found the scale to have good reliability (Cronbach's α = .81).

The Generalised Self-Efficacy Scale is a self-report measure of overall self-efficacy and problem solving, involving 10 items on a 4-point Likert scale (Schwarzer & Jerusalem, 1995). The scores are summed to give a total score, with higher scores indicating a greater sense of self-efficacy. Originally in German, the English translated scale has been found to have high internal consistency in general adult samples from Canada and the USA (Scholz et al., 2002). The measure has demonstrated adequate reliability in autistic adult samples (Connor et al., 2020; Lorenz et al., 2016), and in the current autistic adolescent sample (Cronbach's α = .88).

A Domain Specific Self-Efficacy Scale surrounding distinct behaviour outcomes in relation to participating in the CyberSET program was developed by the researchers according to the guide for constructing self-efficacy scales (Bandura, 2006). The self-report measure consisted of 35 items on a 100-point scale, ranging in 10-unit intervals from 0 (not at all confident) to 50 (slightly confident), to 100 (absolutely confident). The scale involved seven domains relating to CyberSET: Participating in the Program, Personal Strengths and Skills, Cybersecurity Careers, Cyber Threats, Data Communication, Data Structures, and Programming. Five items assessed each domain, which were developed and refined in collaboration with a reference group of autistic adults. The total score and domain scores were calculated by summing individual item scores, with higher scores indicating higher self-efficacy. The measure (Supplemental Appendix D) was found to have high internal consistency in the current sample (Cronbach's α = .92).

Data Analysis

A directed qualitative content analysis was conducted by the first author on the participant feedback survey responses (Assarroudi et al., 2018). Using a deductive approach, the responses were coded into a predetermined matrix informed by the feasibility Areas of Focus (Bowen et al., 2009; Hsieh & Shannon, 2005). Supplemental Appendix E illustrates the mapping of survey questions to their corresponding Areas of Focus, which formed the top-level categories for the content analysis. The matrix was unconstrained, meaning that codes within each category were not predefined. Instead, ad-hoc grouping was used to capture all data, rather than restricting analysis to content that strictly fit the predetermined matrix (Elo & Kyngäs, 2008). Codes within the categories were then thematically clustered into themes and subthemes. Two co-authors subsequently reviewed the coding framework and thematic interpretations to validate the analysis and resolve any ambiguities.

Quantitative data from pre-test and post-test measures were analysed by the first author using the Statistical Package for Social Sciences 28.0 (SPSS; IBM Corp., 2021). Considering the small sample size (n = 13), a non-parametric comparison of means was performed. Descriptive statistics were also used to quantify the demand and implementation of the program using data from the facilitator fidelity report and recorded recruitment rates.

Results

Fidelity

The facilitator fidelity report tracked participant recruitment and retention rates, as well as adherence to the program. Within a three-week recruitment period, more than 20 expressions of interest were received, and 16 participants were enrolled in the study, satisfying the target sample size (Moore et al., 2011). A total of 14 participants completed the study (87%), due to two participants withdrawing during the program. One participant withdrew because the content was too easy, and the other cited personal reasons. Only one absence was recorded, resulting in an average participant attendance of 97%.

Overall fidelity to the program was satisfactory, with 92% adherence across the three sessions (Borrelli et al., 2005). Two components of the Introduction (modelling introductions and participants introducing themselves) were not achieved in sessions two and three, as participants preferred to skip formal introductions after the first session. Session Preparation achieved 83% in the first session due to the room not being free of distractions, which required some adjustments for participants. This was improved to 100% in the following sessions.

Qualitative Findings

Direct content analysis of the post-program survey responses produced a total of 14 themes across the areas of focus. This involved three themes for acceptability (content difficulty, gained knowledge, and enjoyable aspects), two themes for demand (increased interest in cyber and no increased interest in cyber), two themes for practicality (platform logistics and program logistics), three themes for adaptation (content suggestions, videos, and worksheets), two for integration (length of program and length of sessions), and two for expansion (career talks and interest in mentoring). All themes are outlined in Table 3.

Table 3.

Qualitative Themes Linked to Feasibility Areas of Focus (Bowen et al., 2009).

Area of focus	Themes	Subthemes with the number of codes
Acceptability	Content difficulty	Not too easy or too difficult k = 7Too difficult k = 1Too easy k = 1
	Gained knowledge	Cyber topics k = 17General k = 6Jobs k = 7Self-awareness k = 7Soft skills k = 3
	Enjoyable aspects	Good resources k = 2Had fun k = 8Made friends k = 6
Demand	Increased interest in cyber	General interest k = 4Greater understanding of jobs k = 5Helpful knowledge k = 2
Demand	No increased interest in cyber	Focused on other field/s k = 4Not sure about cyber prospects k = 1
Practicality	Platform logistics	Website k = 1Worksheets k = 2
Practicality	Program logistics	Breaks k = 4Mentors k = 3Device k = 2Room conditions k = 12Timing k = 6
Adaptation	Content suggestions	Clearer information k = 6Introducing terms k = 1More about specific topics k = 2More careers information k = 2No suggestions k = 8
	Videos	Too long k = 6Too many k = 6
	Worksheets	Logistics k = 2Wording k = 3
Integration	Length of program	As is (3 days) k = 9Less days k = 1More days k = 2
Integration	Length of each session	Longer sessions k = 1Shorter sessions k = 4
Expansion	Career talks	Hearing about real experiences k = 3learning about options k = 2
Expansion	Interest in mentoring	No k = 8Yes k = 5

Acceptability

The theme of content difficulty was developed around subthemes drawn from participants’ comments regarding the ease of the modules. The majority of comments reflected satisfaction with the content, with one participant noting, ‘it seemed more to teach you what you wanted. The difficulty depended how much effort you put in and listened to what the videos were saying’ suggesting that the program allowed for individualised learning based on engagement. However, one student expressed dissatisfaction due to confusion, stating ‘I didn't understand the worksheets, so I didn't get to properly learn those topics’, indicating a need for clearer guidance or scaffolding in some areas. While another participant felt that ‘the global challenge modules were too easy’, highlighting the variation in perceived difficulty among learners.

Participants also expressed satisfaction in what they learned across a range of topics, forming the theme of gained knowledge. Some participants made general comments about ‘learning a lot’, while others referred to specific cyber topics, such as ‘encryption’, ‘networking’, and ‘python’, as well as learning ‘about the types of jobs’ and being introduced to ‘career pathways’. In addition, some participants reflected on learning about themselves, including developing self-awareness around ‘what my goals should be’ and practicing soft skills such as ‘how to allocate resources to certain things and time management’.

Other notable aspects mentioned in the surveys included participants’ satisfaction with the opportunity to ‘make friends’ and be ‘with like-minded people’, as well as generally having ‘fun’ and ‘enjoying it’. Additionally, the program resources were directly commended by two participants, who stated that ‘the first modules were really good’ and ‘it was well explained in videos and instructions’. This positve feedback relating to enjoyment, social connection, and quality of the resources contributed to the theme of enjoyable aspects.

Demand

Demand for the program was primarily evaluated through participants’ interest in the topic. This was gauged through comments of a general nature, such as ‘I think it's more interesting now than before’, as well as more specific remarks about the field of work, including that they were ‘interested to see the statistics … it seems like a good idea to work in cybersecurity’. While some participants were not interested in pursuing a career in cybersecurity, they still acknowledged its relevance, noting that learning about cybersecurity ‘will be helpful regardless because everything is on technology these days’. These comments were grouped under increased interest in cyber and were considered to demonstrate demand for the program.

On the other hand, some participants indicated that cybersecurity was not of interest to them, as they were already set on a different field of work, such as ‘teaching’, ‘IT (information technology)’, and ‘engineering’. One participant also expressed concern about the prospects of a cybersecurity career in the future, stating that ‘AI (artificial intelligence) will be able to do everything’. Feedback of this nature was grouped under no increased interest in cyber and was considered indicative of a lack of demand.

Practicality

Participants feedback regarding the practicality of navigating the online CyberSET course revealed some issues in ‘navigating the genius armoury website’ and, more specifically, with the worksheets because ‘they had to be downloaded and uploaded’ and some participants ‘couldn't install python to do [that] worksheet’. Given the logistical nature of these challenges, they were grouped under the theme of platform logistics, highlighting areas that require attention to enhance the participant experience.

Another theme regarding the practicality of CyberSET was program logistics, which referred to the method of delivery and physical environment in which participants engaged with the program. Feedback within this theme included positive endorsement of the self-paced nature of the course, with participants stating they ‘liked being able to do it in my own time’ and could ‘take breaks when I needed to’. They also appreciated being able to complete the program ‘on my computer’ because ‘I work better and faster in my own environment’. Participants were also pleased with the support provided by mentors, noting that they were ‘very helpful and answered questions when they could’ and they ‘were very friendly’, which contributed to a supportive and encouraging learning environment.

The conditions of the room also emerge as a point of feedback, with participants commenting on the ‘bright lights’, ‘the air vents’, and that the ‘room was a bit cramped’, suggesting there should have been ‘less people in one room’ or that it ‘should have been a bigger room’. Some participants found the group atmosphere ‘too noisy sometimes which made it hard to concentrate’ and expressed a preference for ‘a more focused group’. This was particularly notable at the beginning of the program, with two participants specifically saying the atmosphere of the first day was ‘distracting’, reflecting the importance of a calm and sensory-considerate environment. In terms of timing, one participant felt the sessions were ‘a bit too long each day’ while several others noted that the sessions were ‘too early in the morning to focus’ and suggested it ‘would be better in the afternoon’. These responses indicate that adjustments to the physical setting and schedule could further enhance the accessibility and comfort of the program.

Adaptation

Analysis revealed three themes relating to how the program may be adapted: content suggestions, videos, and worksheets. Despite eight participants having no explicit suggestions for adaptations to the content when asked directly, several expressed a desire for supplementary written material to complement the video content because the videos were ‘hard to follow’ and ‘needed more explanation’ and ‘if it was written down, I could have the information there to look at again’. Some also found the worksheet questions challenging, with comments that ‘the wording was confusing’ or ‘too vague’. In addition, some participants wanted more in-depth information on specific topics such as ‘digital forensics’ and ‘different threats’, as well as expanded career-related content, including ‘an option to discover certain careers in more detail if you want to’ and ‘how they get scouted or how to apply’. These responses suggest that increasing the clarity and accessibility of content, as well as offering optional extension material, could enhance the learning experience.

Many comments about the videos specifically were that they were ‘too long’, there were ‘too many’, and ‘I was glad [when] there were no more videos’. The issues appeared to affect engagement, with one participant commenting, ‘I skipped a lot of them and so did others’. This indicates that video length and quantity may need to be reduced or made more interactive to sustain attention and interest throughout the program. Similarly, some participants did not complete the worksheets because they ‘couldn't figure out how to do the worksheets’ and ‘some of the questions didn't make sense’. These difficulties point to the need for clearer instructions and possibly more guided support to help participants successfully complete the activities and reinforce their learning.

Integration

Two key themes emerged in relation to the potential for integration of the program: length of the program and length of each session. When asked explicitly about the three-day workshop structure, nine participants responded positively, stating ‘I like the three days’. However, there were mixed reviews about the overall duration. One participant said, ‘it could even be two days’, while two others expressed a preference for ‘more days’ and that ‘it would be better if it was longer’. These differing views were echoed in comments regarding the length of each session. Several participants felt that the individual sessions were ‘a bit too long each day’ and recommended that they be ‘shorter sessions’, suggesting that while the program's total duration may have been appropriate for some, the length of each session impacted engagement and comfort. Only one participant expressed a preference for extended sessions, noting they would ‘rather have the longer days’. Overall, the feedback highlights a need to balance the number of days with the daily schedule to accommodate participant preferences.

Expansion

In exploring ways to expand the program, participants were asked about their interest in continuing their cybersecurity learning beyond the online component through mentoring by an industry expert. Five participants expressed interest, with one commenting ‘yes, very interested’. Meanwhile, eight of the participants said they would not be interested in mentoring, citing reasons such as ‘I don't see myself doing that as a career’, ‘I don't think I should make any big decisions about this’, and ‘not right now’. These responses suggest that while mentoring may appeal to a subset of participants, it may not be broadly applicable without more targeted alignment to individual interests or career aspirations.

Notably, responses to the career talks delivered by industry experts were overwhelmingly positive, forming another theme within expansion. Participants commented that ‘I learned a lot from the people that came in to talk to us’ and noted the value of real-world insight, saying it ‘helps you to know what you could do’ and that ‘the way that they talked about their experiences made it seem more possible’. This feedback highlights a strong interest in hearing directly from professionals and suggests that expanding the program's career exploration components could enhance its relevance and motivational impact for participants.

Preliminary Feasibility

Participants showed a significant increase in overall Domain Specific Self-Efficacy scores from pre-test (median = 2150, IQR = 1600–2420) to post-test (median = 2830, IQR = 2575–3065), as indicated by a Wilcoxon signed rank test (z = −3.18, p < .001). This suggests an improvement in overall self-efficacy relating to the program, which was further investigated within each domain. The significant increase in was observed in the domains of Data Communication (z = –3.19, p < .001), Data Structure (z = –3.02, p < .05), and Programming (z = –2.67, p < .05). Despite a lack of significance in the AIR-SD and BPNS scales, participants’ post-test scores showed a positive trend. Table 4 illustrates the statistical outcomes for each measure and subscale.

Table 4.

Wilcoxon Signed-Rank Tests Results of Quantitative Participant Outcomes (n = 13).

Outcome measure	Domain	Pre-testMedian (IQR)	Post-testMedian (IQR)	z	p	ES
AIR-SD	Total	81 (75–86)	85 (77–93.5)	–.86	.39	.17
	Things I do	21 (17–22)	22 (19.5–23)	–67	.51	.13
	How I feel	20 (18–22.5)	23 (18–23.5)	−.79	.43	.15
	What happens at school	18 (12.5–21.5)	19 (13–23)	−.55	.58	.11
	What happens at home	24 (20.5–26)	24 (18.5–25.5)	−1.55	.12	.30
	Think	27 (24–30.5)	29 (24.5–30.5)	−.67	.50	.13
	Do	27 (25–28)	28 (25–30.5)	−.59	.55	.12
	Adjust	27 (22.5–29)	29 (25.5–30.5)	−.89	.37	.18
BPNS	Total	32 (25.5–36)	33 (27–37.5)	–.42	.67	.08
GSE	Total	30 (24.5–31.5)	29 (25–30.5)	–35	.72	.07
DSE	Total	2150 (1600–2420)	2830 (2575–3065)	–3.18	.001*	.62
	CyberSET	330 (260–350)	380 (260–410)	–88	.38	.17
	Strengths	390 (320–415)	340 (295–410)	–71	.48	.14
	Careers	290 (230–340)	320 (285–350)	–1.61	.11	.32
	Threats	320 (155–400)	340 (300–395)	–1.65	.10	.32
	Communication	220 (130–300)	340 (290–390)	–3.19	.001*	.62
	Structure	250 (180–345)	370 (275–390)	–3.02	.003*	.59
	Programming	370 (200–405)	410 (340–445)	–2.67	.008*	.52

AIR-SD = American Institutes for Research Self-Determination Scale; BPNS = Basic Psychological Needs Scale; GSE = General Self-Efficacy Scale; DSE = Domain-Specific Self-Efficacy Scale; IQR = interquartile range; ES = effect size; CyberSET = Cybersecurity Education and Training.

*p < .05.

Discussion

This study described the co-production of CyberSET, a cybersecurity education and training program for autistic youth, and aimed to assess the feasibility of the program when delivered in an out-of-school setting, as well as its potential to increase self-determination and self-efficacy in autistic adolescents. The feasibility assessment framework (Bowen et al., 2009) focused on eight key areas: acceptability, demand, implementation, practicality, adaptation, implementation, expansion, and preliminary efficacy. A strengths-based approach and the PYD framework were used to guide the analysis, with particular attention to how the program created opportunities for participants to engage in meaningful activities, demonstrate their strengths, and develop skills relevant to future employment (Larson, 2006; Ramey & Rose-Krasnor, 2012).

Acceptability

Qualitative data collected through participant surveys after completing the program revealed three themes relating to participants’ acceptability of the program. The first theme reflected overall satisfaction with the difficulty of the content, with most participants reporting that it was neither too easy nor too difficult. While two participants provided contrasting reviews regarding difficulty, it is important to consider that the sample included participants covering four school year groups, and some variation in perceived difficulty was therefore anticipated (Schneider, 2008). Notably, most concerns about difficulty were linked to confusion rather than content level, which is addressed further under adaptation.

Participants also expressed satisfaction with what they learned from the program, covering a range of topics including career pathways, self-awareness, and soft skills, in addition to cybersecurity-specific knowledge. This aligns with the principles of strengths-based approaches for autistic adolescents, which emphasise the importance of providing opportunities to build on and demonstrate skills, increasing self-efficacy and confidence (Jones et al., 2022; Lorenz & Heinitz, 2014; Rumsa et al., 2025). Furthermore, career-specific preparation has been identified as a predictor for post-secondary success (Mazzotti et al., 2021; Test et al., 2020), suggesting that CyberSET holds potential as an effective transition support program for those interested in cybersecurity.

The findings are consistent with other strengths-based, interest-driven programs for autistic adolescents, which also report high levels of enjoyment and engagement when content is aligned with participants’ interests (Jones et al., 2021; Kaboski et al., 2015). In particular, the opportunity to connect with like-minded peers has been similarly recognised as a contributor to program satisfaction and social development, forming an important secondary outcome for strengths-based practices for autistic adolescents (Diener et al., 2016b; Jones et al., 2022; Winter-Messiers, 2007).

Demand

Recruitment efforts yielded more expressions of interest than the target sample size, with 16 participants enrolling in the program, followed by high retention (87%) and attendance (97%). High retention and attendance are frequently cited as key indicators of program feasibility and demand (Bowen et al., 2009), and are particularly notable in interventions with autistic youth, where factors such as social anxiety or sensory environments can often influence participation (Vasilevska Petrovska et al., 2019). As such, these rates provide quantifiable support for the demand and acceptability of the CyberSET program among its target audience.

Qualitative feedback also reflected a clear interest in the topic, with some participants beginning to consider cybersecurity as a potential career, and others recognising the relevance of cybersecurity knowledge even outside of the field. However, those who did not report increased interest tended to be committed to other career paths or expressed concerns about job stability due to AI. These findings suggest that while CyberSET has the greatest demand from participants already inclined toward tech fields, future iterations could broaden appeal by more explicitly connecting cybersecurity concepts to a wider range of professions. Emphasising the general applicability of cybersecurity knowledge, and addressing evolving industry trends, may help strengthen the program's relevance for all end-users of digital technology (Ferdousi, 2024).

Implementation

The program delivery was aligned with best-practice recommendations for autistic adolescents, providing each participant with a personal workspace, access to quiet rooms, communal fidget tools, and individual devices with Wi-Fi and login credentials (Cooperative Research Centre for Living with Autism, 2016). A U-shaped seating arrangement fostered an open, social environment, similar to other strengths-based programs (Diener et al., 2016a; Dunn et al., 2015), which appeared to support social connection, as evidenced by participants feedback that they made friends and enjoyed spending time with like-minded peers.

Fidelity tracking after the first session identified two key adjustments to reduce distractions and boost engagement: first, participants needed explicit reminders at the start of each session that they could use the quiet rooms whenever the main classroom felt overwhelming (Leonards et al., 2024); second, they preferred to forgo repeated self-introductions, initially modelled by facilitators and mentors, to begin working immediately in subsequent sessions (Shernoff, 2012). In line with evidence that the social-skills components of strengths-based programs should align with autistic participants’ actual goals (Rumsa et al., 2025), the session plan was revised to incorporate these changes, thereby enhancing both comfort and productivity.

Practicality

Practicality was evaluated through participants’ post-program feedback, highlighting both logistical and environmental adjustments needed to optimise the program. Platform-related challenges, such as difficulties accessing worksheets or needing to install software, created barriers to full participation. Similar issues have been documented in other digital-skills programs for autistic learners (Jones et al., 2021, 2023), where simplified digital access was suggested to improve engagement. For future iterations, CyberSET could implement cloud-shared materials and online coding tools to eliminate technical friction and improve accessibility. In addition, incorporating environmental preferences, including smaller groups, later start times, and flexible lighting, would enhance the practicality of CyberSET in alignment with the adaptable, strengths-based approach (Rumsa et al., 2025).

Adaptation

Qualitative feedback from participants identified several adaptations to improve CyberSET, the most prominent being the addition of written material to complement video content. Participants noted that the videos were difficult to follow, or lacked sufficient explanation, and expressed a desire for accessible reference material. Interestingly, this diverges from feedback in other strengths-based programs for autistic adolescents where a preference for visual over written content was reported (Genova et al., 2023). This contrast highlights the need for multi-modal learning options to accommodate individual preferences and enhance accessibility (Wilson et al., 2018).

Several participants also noted specific topics they found particularly interesting and would have liked further learning in, such as digital forensics and threat identification. Similarly, there was a suggestion that the course lacked detail on the specific entry pathways for various roles within cybersecurity. CyberSET was designed as an introductory syllabus, meaning in-depth coverage of certain topics would be beyond the scope of the program and may not align with the interests of all participants. However, these learning areas have the potential to be included in a follow-up program and are discussed further under Expansion.

Integration

Overall, the bootcamp style design of the program, consisting of three five-hour sessions, was well received by the participants, and considered viable for integration as an extra-curricular program. However, several participants’ feedback was that the bootcamp sessions were too long, indicating a preference for a greater number of shorter sessions. A longer program that aligns with a school term may be more appropriate for participants who prefer this method and supports the need to evaluate the feasibility of delivering the program in other contexts.

Expansion

The opportunity to explore career pathways has been identified by autistic adults as a valuable feature of transition programs (White et al., 2024), and this was reflected in participants’ positive feedback about the industry expert talks. Adolescents appreciated hearing real-life experiences and having the chance to ask questions. By fostering early exposure to cybersecurity and linking to real-world applications, CyberSET contributes to sustainable career development among autistic adolescents (De Vos et al., 2020). As CyberSET expands, one-on-one mentoring with industry experts could support students seeking deeper, specialised learning. This aligns with participants’ interest in more detailed information about specific cybersecurity roles and application processes. Importantly, career-specific preparation has been identified as a predictor of post-secondary success (Mazzotti et al., 2021; Test et al., 2020), reinforcing the value of incorporating such elements into future program iterations.

Preliminary Efficacy

The present study also assessed the potential of the CyberSET program to increase self-determination and self-efficacy in autistic adolescents. This was evaluated through several quantitative outcome measures and analysed using Wilcoxon signed-rank tests. Participants showed non-significant increases in self-determination and autonomy, which may be attributed to the small sample size and should not be interpreted as an indication of poor feasibility (Tickle-Degnen, 2013). Given the variability among participants in prior knowledge, interest, and understanding of the program concepts, these findings may warrant investigation using more individualised outcome measures. For example, Goal Attainment Scaling has recently gained traction in research with autistic youth, as it allows for the measurement of personally meaningful goals (Lee et al., 2022).

The scale of general self-efficacy, which measured participants overall belief in their capabilities, showed a non-significant decrease in post-test scores. This may be due to the narrow focus of the program, which targeted specific technical skills rather than broader personal competencies (Bandura, 1997, 2006). However, a significant increase was observed in the domain-specific self-efficacy measure, which highlights the program's ability to enhance self-efficacy in cybersecurity topics. Specifically, significant increases in self-efficacy were found in the domains of Data Communication, Data Structure, and Programming. These domains are part of the core knowledge required for work in the cybersecurity field (Dawson & Thomson, 2018; Newhouse et al., 2017). Therefore, this finding supports the potential success of the CyberSET program in equipping adolescents with confidence in their cybersecurity technical skills.

Limitations

The significant limitations of this study are the lack of a control group and the lack of long-term follow-up. Although these components are a purposeful part of the pilot feasibility design, they must be considered when interpreting the results and drawing causal assumptions. The only certain conclusion that may be drawn from the present study is the justification for further testing. Future designs could include a passive control in which another group of adolescents participate in a hobby activity, such as playing video games or reading books, or an active control in which another group of adolescents participate in an established form of career planning.

As this study aimed to assess feasibility through rich qualitative feedback, and recruitment feasibility was not a primary focus, sample size was determined in balance with practicality (Julious, 2005; Moore et al., 2011). However, this presented some limitations in the interpretation of quantitative measures. As noted, further investigation may benefit from incorporating more individualised outcome measures that are sensitive to the unique progress and experiences of each participant.

Additionally, the qualitative data was limited to the responses of autistic adolescent participants in their post-program survey, missing feedback from other key stakeholders such as parents and program facilitators. This pilot study was facilitated by the first author, who was unable to provide unbiased feedback. Future iterations should include non-researcher facilitators who can provide feedback on the program from a different perspective.

Conclusions

This pilot study provides valuable feedback on the CyberSET program for autistic adolescents through the feasibility testing outlined by Bowen et al. (2009). Overall, the program shows promising feasibility that justifies further testing in a wider population. This includes evaluation of the expansion into a school context, following adaptations to improve the acceptability, practicality, and integration as suggested throughout the discussion. Finally, the program has shown the potential for increasing self-determination and self-efficacy in cybersecurity skills for autistic adolescents, positioning CyberSET as a budding strengths-based transition program.

Supplemental Material

sj-docx-1-ndy-10.1177_27546330251370656 - Supplemental material for Strengths-Based Cybersecurity Education and Training Program for Autistic Adolescents: A Feasibility Study

Supplemental material, sj-docx-1-ndy-10.1177_27546330251370656 for Strengths-Based Cybersecurity Education and Training Program for Autistic Adolescents: A Feasibility Study by Sophie Rumsa, Bahareh Afsharnejad, Elinda Ai Lim Lee, Sven Bölte, Tele Tan and Sonya Girdler in Neurodiversity

Footnotes

Acknowledgements

The authors would like to express deep gratitude to all the participants in this study. Their time, effort, and willingness to share their experiences were invaluable in contributing to the success of this research. Similarly, to the mentors and industry experts, without their support, this program would not have been possible. We are sincerely thankful for their cooperation and their openness to engage in this project. This research was supported by funding from the Australian Government Department of Industry, Science and Resources under the Cyber Security Skills Partnership Innovation Grant, Round 2. The authors would like to acknowledge the Department’s support in enabling this work.

ORCID iDs

Sophie Rumsa

Bahareh Afsharnejad

Elinda Ai Lim Lee

Sven Bölte

Tele Tan

Sonya Girdler

Ethical Considerations

Consent to Participate

Informed written and verbal assent was obtained from all participants, as well as informed written consent from a parent or carer, prior to the adolescent partaking in the research.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Department of Industry, Science and Resources (grant number CSSIII000020). The authors acknowledge the financial support of Curtin University to Sophie Rumsa through Australian Government Research Training Program (RTP) Scholarship. The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Contributing authors Sonya Girdler and Sven Bölte are on the editorial board for Neurodiversity. The remaining authors have no conflicts to declare.

Data Availability Statement

The data that support the findings of this study are available from the authors upon request.

Supplemental Material

Supplemental material for this article is available online.

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