https://doi.org/10.24016/2023.v9.366
ORIGINAL ARTICLE
Development and psychometric properties of the Attitudes Towards
Intellectual Disability Scale in the workplace
Desarrollo
y propiedades psicométricas de la Escala de Actitudes hacia la Discapacidad
Intelectual en el trabajo
Alicia Boluarte Carbajal1*,
Martin Salazar-Conde1, Arantxa N. Sánchez Boluarte2,
Danilo Sánchez Coronel1, Brian Norman Peña-Calero3,4
1 Universidad César
Vallejo, Lima, Peru.
2
University of Washington, Department of Global Health, Washington, United
States.
3
Advances in Psychological Measurement Study Group, Lima, Peru.
4 Universidad Nacional
Mayor de San Marcos, Lima, Peru.
* Correspondence: alyboluarte@gmail.com
Received: 19 October, 2023 | Revised: 02 November, 2023 | Accepted:
14 December, 2023 | Published Online: 20 December, 2023.
CITE IT AS:
Boluarte, A.,
Salazar-Conde, M., Sánchez, A., Sánchez, D., & Peña-Calero, B. (2023). Development
and psychometric properties of the Attitudes Towards Intellectual Disability
Scale in the workplace. Interacciones, 9,
e366. https://doi.org/10.24016/2023.v9.366
ABSTRACT
Background: A new instrument was designed to measure attitudes towards intellectual
disability in the workplace. This tool provides the opportunity to identify
underlying cognitive and emotional patterns that may influence people's
interaction and performance in such environments. Objective: To construct, validate, and ensure the reliability of a scale measuring
attitudes towards intellectual disability, establishing its suitability in
labor inclusion programs. Method: A psychometric design was used that
incorporated qualitative techniques, such as focus groups and cognitive
interviews, in the instrument construction phase. The content validation of the
items involved the participation of 15 experts in the field, which resulted in
a reduced version with 10 items distributed in two dimensions: Perception and
Social Distance. Subsequently, both the validity of the internal structure and
the reliability of the instrument were evaluated in a sample of 255
individuals, composed of 35% (n=88) women and 66% (n=167) men. Result: The
third-factor model evaluated with confirmatory factor analysis (CFA) was the
one that demonstrated excellent fit indices (CFI= .991; TLI=.988; RMSEA= .076;
SRMR =.038), with an adequate inter-factor correlation (0.82) and adequate
consistency coefficients (α=0.825; ω=0.916). Conclusion: A tool of
invaluable value is presented for planning public health programs aimed at reducing
stigma and promoting the socio-labor inclusion of people with intellectual
disabilities.
Keywords: Attitudes, Intellectual Disability, Validity, Reliability, Public
Health.
RESUMEN
Introducción: Se diseñó un nuevo instrumento para medir las
actitudes hacia la discapacidad intelectual en el lugar de trabajo. Esta
herramienta brinda la oportunidad de identificar patrones cognitivos y
emocionales subyacentes que pueden influir en la interacción y el desempeño de
las personas en dichos entornos. Objetivo: Construir, validar y asegurar la fiabilidad
de una escala que mide las actitudes hacia la discapacidad intelectual,
estableciendo su idoneidad en programas de inclusión laboral. Método: Se utilizó un diseño psicométrico que
incorporó técnicas cualitativas, como grupos focales y entrevistas cognitivas,
en la fase de construcción del instrumento. La validación de contenido de los
ítems contó con la participación de 15 expertos en la materia, lo que resultó
en una versión reducida con 10 ítems distribuidos en dos dimensiones:
Percepción y Distancia Social. Posteriormente, se evaluó tanto la validez de la
estructura interna como la confiabilidad del instrumento en una muestra de 255
individuos, compuesta por 35% (n=88) mujeres y 66% (n=167) hombres. Resultados:
El tercer modelo factorial evaluado con análisis factorial confirmatorio (AFC)
fue el que demostró excelentes índices de ajuste (CFI= .991; TLI=.988; RMSEA=
.076; SRMR =.038), con una adecuada correlación interfactorial
(0.82). y coeficientes de consistencia adecuados (α=0,825; ω=0,916). Conclusión: Se presenta una herramienta de invaluable valor para la planificación de
programas de salud pública dirigidos a reducir el estigma y promover la
inclusión sociolaboral de personas con discapacidad intelectual.
Palabras claves: Actitudes,
Discapacidad Intelectual, Validez, Confiabilidad, Salud Pública.
BACKGROUND
The concept of disability was interpreted based on religious principles
(Martin & Ripolles, 2008) that justified mental
retardation as a divine punishment. Subsequently, a rehabilitative medical
model emerged that considered that the cause of disability had its origin in
biological patterns and could be overcome if they were rehabilitated (Velarde
Lizama, 2012). They were confined in specialized centers, psychiatric hospitals
and orphanages, accentuating segregation, and social exclusion, facing barriers
that limited their participation in daily life, education and employment
(Palacios, 2008). This conceptualization lasted until the mid-twentieth
century, when the medical model of disability began to be questioned, demanding
compliance with the rights of social integration and equal opportunities
(Belmonte Almagro & García Sanz, 2014). These changes allowed, in turn,
that the concept of disability should not be interpreted from a medical
perspective, but rather from a social one (Maldonado, 2013).
Despite progress in research and policy implementation in several
countries, people with intellectual disabilities (PWID), in contrast to other
forms of disability, continue to be victims of discrimination, prejudice and
social exclusion (Gurdián-Fernández et al., 2020).
This has threatened their fundamental rights and dignity, a problem that has
been exacerbated during the COVID-19 pandemic and has hindered their access to
the (global/national?) labour market (Silván & Quifes, 2020). Faced
with this problem, the International Labor Organization (ILO) has established
international standards necessary to promote labor opportunities for people
with intellectual disabilities (ILO, 2017). However, the lack of research on
this issue and the absence of policies to promote the labor inclusion of this
social group are worrying. In this context, it is important to develop
diagnostic studies to understand the socio-labor problems of people with
intellectual disabilities, through measurement tools that allow the assessment
of intellectual disability from a social perspective focused on labor
inclusion. This issue has motivated researchers to explore perceptions of
intellectual disability in different contexts (Valentini et al., 2019; Shahidi
et al., 2023).
The social model recently implemented in the construction of instruments
for measuring attitudes seeks to understand that disability is no longer a
personal characteristic, but rather a social construct that requires adopting a
philosophy of non-discrimination and equality (García-Sanz et al., 2022b).
In order to identify existing instruments, Palad et al., 2016, conducted
a review on the scope of instruments measuring attitudes towards disability,
finding 31 instruments of which only 6 were associated with the measurement of
attitudes towards disability: Attitude to Disability Scale ADS-ID (P) applied
to PWID and ADS-ID (G) to General population (Power & Green, 2010),
Attitudes Towards Intellectual Disability Questionnaire (ATTID) (Morin et al.,
2013), Challenging Behavior Perception Questionnaire (CBPQ) applied to service
providers to people with intellectual disabilities (Williams & Rose, 2007),
Community Living Attitudes Scale , Mental Retardation Form (CLAS-MR) (Henry et
al., 1996a), Intellectual Disability Literacy Scale (IDLS) (Scior & Furnham,
2011), Mental Retardation Attitudes Inventory (MRAI-R) (Hampton & Xiao,
2008).
Table 1. Instruments measuring
attitudes towards intellectual disability.
|
Nº |
Authors (year)/journal |
Instrument |
Dimensionality |
Sample |
Internal structure |
Reliability evidence |
|
1 |
Henry et al. (1996) / Mental Retardation |
Community Living
Attitudes Scale, |
4 sub-scales:
Empowerment; Similarity; Exclusion; Refuge (40 items). Likert of 6 points. |
n=355 |
CFA (GFI=.92 / RMS=.09)
Confirmed a 4-factor solution. Adequate fit indexes. |
Internal consistency: |
|
2 |
Williams y Rose (2007)
/Journal of Intellectual Disabilities |
Challenging Behavior
Perception Questionnaire (CBPQ) |
6 dimensions: Customer of
consequences; Consequence caregiver; Control caregiver; Chronology;
Chronic/acute; Episodic chronology; Emotional representation (19 items). Likert of 5 points. |
n=51 |
They explain 26% of the
variance. |
Internal consistency: |
|
3 |
Hampton y Xiao (2008)
/Research in Developmental Disabilities |
Mental Retardation
Attitudes Inventory-Revised (MRAI-R) in a Chinese population. |
4 sub-scales:
Integration-segregation (INSE); Social distance (SDIS); Private rights
(PRRT); Subtle Derogatory Beliefs (SUDB) (29 items). Likert of 4 points. |
n=420 |
AFE (x2/ gl =3.24) accounted for 25% of the variance. |
Internal consistency: |
|
4 |
Power y Green (2010) /
Journal of Intellectual Disability Research |
Attitude to Disability
Scale - ADS-ID (P) and ADS-ID (G) |
4 sub-scales: Inclusion;
Discrimination; Earnings; Perspectives (16 items). Likert of 5 points. |
n=3772 |
AFE: ACP |
Internal consistency: |
|
5 |
Scior y Furnham (2011)
/Research in Developmental Disabilities |
Intellectual Disability
Literacy Scale (IDLS) |
4 sub-scales: Contact
subscale; Causal belief subscales; Intervention subscales; Social distance
subscale (52 items) |
n=1376 |
AFE: |
Causal Beliefs Subscales α = .84. |
|
6 |
Morin et al. (2013) /
Journal of Intellectual Disability Research |
Attitudes Toward
Intellectual Disability Questionnaire (ATTID) |
5 factors: Discomfort;
Knowledge of capabilities and rights; Interaction; Sensitivity and
Compassion; Knowledge of the causes of DI67 items. Likert of 5 points. |
n=1605 |
AFE: ACP |
Internal consistency -
General Scale α=.92 / Per factor: |
Note. EFA= exploratory factor
analysis, CFA= confirmatory factor analysis, PCA= principal component analysis
In the analysis of the psychometric properties of the mentioned
instruments (Table 1), a diversity of statistical techniques used without
sufficient theoretical support is observed, which could lead to imprecise
conclusions, jeopardizing data-based decision making (Power & Green, 2010;
Morin et al., 2013; Henry et al., 1996); Scior & Furnham, 2011; Hampton
& Xiao, 2008; Williams & Rose, 2007). On the other hand, the lack of
updated reviews on the psychometric properties of the aforementioned tests
raises doubts about their validity. It is suggested that these reviews be
conducted at least every 5 to 7 years, based on recommendations from the
American Educational Research Association, the American Psychological
Association, and the National Council on Measurement in Education (2014).
Likewise, in Singapore, the Attitude Scale towards People with
Intellectual Disabilities (Boo & Nie, 2018) was designed considering the
cultural particularities of the local population. At the same time, in Spain,
the Invisible Barriers Scale: Attitude towards People with Intellectual
Disabilities and the Goratu – PG Questionnaire
(García-sanz et al., 2022) (Gómez et al., 2022)
emerged, both specifically applied in school environments.
Principal Component Analysis (PCA) is a versatile tool that finds
applications in various fields, for instance in situations where the bivariate
distribution is linear, and the observations are independent (Jolliffe, 2002).
Nevertheless, a methodological limitation has been identified in Likert-type
scales that measure attitudes towards intellectual disability. It is generally
chosen to use PCA rather than Exploratory Factor Analysis (EFA), as evidenced
by countless studies (Power and Green, 2010; Morin et al., 2013; Scior and
Furnham, 2011; Energy and Green, 2010). However, this preference has led to
uncertainties regarding the accuracy of the obtained results. It is generally
believed that EFA is more appropriate for exploring the underlying structure of
latent variables, such as the measurement of attitudes (Lloret et al., 2017).
Most of the instruments available to evaluate attitudes towards
intellectual disability are framed in a multidimensional perspective that
encompasses affective, cognitive, and behavioral components (Whittaker, 2007).
This approach seeks to comprehensively measure what people think, feel, and do
in relation to intellectual disability (Antonak &
Livneh, 2000) (Olson & Zanna, 1993). This is
fundamental to understand the impact on educational, social, and labor support
systems.
On the other hand. It has been shown that attitudes can be modified
through cognitive-behavioral processes and social interaction, supported by the
principle of neuroplasticity (Rees, 2016) (Lubrini et
al., 2018). The establishment of neural networks generates brain changes in
their configuration, as well as applying environmental enrichment
interventions, significantly improves the adaptation of people with
intellectual disabilities (PCDI) (Novak & Morgan, 2019). Increasing
participation through inclusion programs facilitates social acceptance
(Seccombe, 2007) and optimizes inclusion processes in compliance with their
fundamental rights.
In this context, it is important to develop diagnostic studies to
understand the socio-occupational problems of people with disabilities, using
measurement tools that allow their condition to be assessed from a social
perspective focused on labor market integration. Therefore, the objective of
the present study is the construction, validity, and reliability of a scale of
attitudes towards intellectual disability, to establish its suitability in
programs to support labor inclusion.
METHOD
Design
The research employed a psychometric design, involving the creation and validation of the psychometric attributes of the assessment instrument (Ato et al, 2013).
Participants
The determination of the sample size was grounded on the Comparative Fit Index (CFI) adjustment index (CFI) established by Kim, according to specific statistical criteria that included a mean factorial loading of 0.6, mean factorial correlation of 0.7, a significance level of 0.05, and expected statistical power of 0.80. Consequently, a minimum sample size of 251 participants was considered essential. Furthermore, various factors were taken into consideration to mitigate the probability of committing a type II error. As an illustration, approximately 20 observations were made for each variable, as advocated by Lloret-Segura et al. (2014). Additionally, the participants engaged in the study were adults devoid of any health conditions. Moreover, a concise scale consisting of 12 items was utilized, which was devised to have two well-defined factors.
The sample comprised 255 laborers, with 35% (n=88) being females and 65% (n=167), males. The average age was 39.17 (SD 11.72). Furthermore, 67.8% (n=173) originated from public establishments, while the remaining 32.2% (n=82) came from private establishments.
Instruments
An analysis of the scientific literature was carried out to
conceptualize the study variable. The Focus Group technique (Nassar-McMillan
& Dianne Borders, 2002) with the participation of 7 people who worked in
various institutions made it possible to validate the emerging dimensions and
generate items.
Based on the qualitative procedures used, the underlying theory that
supports the understanding of attitudes towards intellectual disability was
identified. From a social perspective, it is recognized that the socio-labor
inclusion of people with intellectual disabilities can be influenced by the
presence of subtle prejudices. In this context, two dimensions were identified
in relation to attitudes towards intellectual disability in a work environment:
Perception and Social Distance (see Table 2), which have given rise to the
formulation of a set of 12 items derived from the indicators.
Table 2. Specification Matrix.
|
Dimensions |
Definition |
Indicators |
|
Perception |
The way in which
employers and co-workers perceive and evaluate the work behavior of a person
who has an intellectual disability in the context of their employment. |
Respect, clear
instructions, cleanliness and order, autonomy, productivity, expression of
opinions. |
|
Social distance |
Willingness to interact
positively or negatively with a person with intellectual disabilities in the
work context. |
Social support, teamwork,
patience, comfort. |
After developing the instrument, rounds of cognitive interviews were
carried out (Estefania & Zalazar-Jaime, 2018) to check the level of
understanding and comprehension of each item. Next, the content validity
procedure was carried out by expert judgment (Escobar-Pérez &
Cuervo-Martínez, 2008).
Procedure
The data collection process was executed by utilizing a form in KoBo Toolbox, owing to the challenges encountered in
accessing the internet. This form included the provision of Informed Consent.
The type of participants' selection was intentional non-probabilistic,
utilizing the snowball technique (Biernacki and Waldorf, 1981). This technique
facilitated the expansion of the sample size by utilizing contacts and
references, thus satisfying the inclusion criteria: individuals employed by
either a public or private organization, possessing a minimum work experience
of 6 months.
Data analysis
A descriptive analysis of the items was carried out to analyze the
behavior and distribution of the scores. To assess asymmetry and kurtosis, it
is being considered that their values do not deviate beyond the range of +-1.5,
which may suggest the absence of univariate normality (Forero et al., 2009;
Shield & Cartwright, 2005). Concerning the corrected homogeneity index that
is reported, a value equal to or greater than 0.30 is deemed an acceptable
minimum, thereby indicating that the items pertain to and adequately measure
the corresponding factor (Kline, 2005). Additionally, the commonality of the
items is reported, which denotes the extent to which the factor explains the
variability, with a minimum threshold of 0.40 being deemed ideal for an item
(DeTrinidad, 2016; Nunnally & Bernstein, 1994). For the Confirmatory Factor
Analysis (CFA), the weighted least squares estimator with adjusted mean
variance (WLSMV) was used, an estimation method suggested when the measurement
scale is ordinal with a sample greater than 200 (Forero & Maydeu-Olivares, 2009). Various fit indices of the data to
the theoretical model were tested (Xia & Yang, 2019), such as the
Comparative Fit Index (CFI) where the values closest to one indicate to what
extent the specified model is better than the null model, accepting values
above .90 (Hu & Bentler, 1998). The Tucker-Lewis index (TLI) was found,
relevant to generally distinguish the estimated model from the null model that
indicates independence between the variables studied. The literature indicates
that it is optimal if the value is greater than .90. Likewise, the RMSEA
statistic was used, which is the root mean square error of approximation whose
value must be less than .05 to be determined optimal (Lai, 2020) and
Standardized Root Mean Square Residual (SRMR) whose score must be less than 05
with RMSEA confidence intervals (RMSEA CI 90%) less than .08. Reliability was
analyzed using the internal consistency method, considering the model that had
greater theoretical and empirical coherence, using the omega coefficient for
multidimensional and ordinal categorical scales (Flora, 2020; MacDonald, 1999).
The free access program RStudio (R Core Team, 2016) was used, using the
libraries "psych" (Revelle, 2023), "lavaan",
"EFAtools" (Rosseel, 2012).
Ethics Aspects
The study obtained the approval of the Cesar Vallejo University's
Research Ethics Committee (EO41-2022-03) and was carried out following strict
research ethics guidelines. During the application of the scale, each participant
provided prior informed consent, respecting their wishes and the
confidentiality of the information collected.
RESULTADOS
Descriptive analysis
In
the descriptive analysis procedure of the items, no response option exceeded
80% marking, indicating that there is an adequate variability. The mean
indicates that the frequency of responses is between option 3 and with a
standard deviation between .72 and .99. On the other hand, the asymmetry (g1)
and kurtosis (g2) coefficients did not exceed the value of ±1.5, except for
items 1-2-8-9-10-11 and 12, which is evidence that the data are far from
univariate normality.
In
relation to the corrected homogeneity indices (CHI), the values were ≥ .30,
which indicates the contribution of each item in the measurement of the
construct (see Table 3). Likewise, the communalities exceeded the cut-off point
(0.40) showing adequate shared variance. However, item 2 did not meet the
criterion.
Table 3. Descriptive analysis of the
items.
|
Factors |
Items |
% |
M |
SD |
CHI |
H2 |
||||
|
1 |
2 |
3 |
4 |
5 |
||||||
|
Perception |
1 |
4.55 |
12.66 |
65.58 |
4.55 |
12.66 |
4.63 |
0.95 |
0.70 |
0.51 |
|
2 |
2.75 |
2.75 |
3.92 |
38.82 |
51.76 |
4.34 |
0.90 |
0.41 |
0.19 |
|
|
3 |
3.14 |
2.35 |
6.67 |
43.14 |
44.71 |
4.24 |
0.91 |
0.73 |
0.65 |
|
|
4 |
2.75 |
1.57 |
13.33 |
38.43 |
43.92 |
4.19 |
0.92 |
0.76 |
0.70 |
|
|
5 |
2.35 |
3.14 |
11.76 |
44.71 |
38.04 |
4.13 |
0.91 |
0.79 |
0.77 |
|
|
6 |
2.75 |
7.45 |
28.24 |
38.82 |
22.75 |
3.71 |
0.99 |
0.60 |
0.44 |
|
|
Social distance |
7 |
2.35 |
1.18 |
1.96 |
32.94 |
61.57 |
4.50 |
0.80 |
0.79 |
0.66 |
|
8 |
2.30 |
0.38 |
23.37 |
71.65 |
2.30 |
4.66 |
0.72 |
0.88 |
0.82 |
|
|
9 |
2.67 |
0.76 |
18.32 |
75.57 |
2.67 |
4.69 |
0.75 |
0.89 |
0.83 |
|
|
10 |
1.96 |
0.39 |
3.14 |
27.84 |
66.67 |
4.57 |
0.75 |
0.89 |
0.83 |
|
|
11 |
2.30 |
3.07 |
32.18 |
60.15 |
2.30 |
4.51 |
0.77 |
0.83 |
0.73 |
|
|
12 |
3.04 |
4.18 |
26.62 |
63.12 |
3.04 |
4.51 |
0.85 |
0.88 |
0.82 |
|
Note. M=mean, SD=standard
deviation, CHI=corrected homogeneity index, H2=commonality.
Analysis of the internal structure
Table
4 represents the results of the Exploratory Factor Analysis, identifying the
consensus of the parallel method, Kaiser criterion and optimal coordinates,
which coincided in the presence of two factors. The minimum residual estimation
method was used since these are ordinal variables and oblimin
rotation, the 2-factor structure explained 70% of the variance and the
inter-factor loading was .63. In Factor 2 there is a Heywood case (item 8) “I
would help him/her if he/she had difficulties” whose intention is similar to
item 7.
Table 4. Exploratory Factor Analysis
of the EADI Scale.
|
Items |
λF1 |
λF2 |
|
1. They deserve respect
just like other workers. |
0.76 |
|
|
2. They need a detailed
explanation of their functions. |
0.68 |
|
|
3. They can keep their
workspace clean and tidy. |
0.66 |
|
|
4. They give important opinions. |
0.64 |
|
|
5. They comply with labor
productivity. |
0.85 |
|
|
6. They can perform their
work without support. |
0.84 |
|
|
7. I would accept his/her
help if I needed it. |
0.73 |
|
|
8. I would help him/her
if he/she were having difficulties. |
1.02 |
|
|
9. I would stand up for
him/her if he/she were mistreated. |
0.9 |
|
|
10. I would form a work
team with him (her). |
0.73 |
|
|
11. I would be patient
with him/her. |
0.74 |
|
|
12. I would feel
comfortable working with him/her. |
|
0.75 |
|
Inter-factor loadings (ϕ) |
|
|
|
F1 |
1 |
- |
|
F2 |
0.63 |
1 |
|
% Explained variance |
0.44 |
0.7 |
Note. F1: Perception towards
intellectual disability; F2: Social distance towards intellectual disability
The
instrument's structure was assessed using confirmatory factor analysis. We
adjusted the model specification through successive corrections. A total of
three models were evaluated, and their adjustment indices are presented in
table 5. The first model, retaining the original structure of the instrument,
demonstrated excellent values in terms of its CFI and TLI indices.
Additionally, it displayed an adequate value in SRMR. However, the RMSEA value
was significantly higher than the acceptable minimum (0.10).
Subsequently,
a re-specification of the original model was examined, considering the removal
of two items with the lowest performance in both their factorial loading and
corrected homogeneity index. This re-specified model is referred to as model 2.
The second model exhibits notable enhancements across all its indices,
demonstrating exceptional values in CFI, TLI, and SRMR. Although the RMSEA has
already fallen below the prescribed minimum threshold, it remains comparatively
high.
Consequently,
a second re-specification is undertaken, drawing upon the modification rate and
a careful examination of item content within the second model. As a result, in
the third model, item 1 was relocated to the second factor representing social
distance. This adjustment ultimately yields a final factorial model
characterized by exceptional values in its adjustment indices and a tolerable
RMSEA.
Table 5. Validity evidence based on
the internal structure of the EADI scale.
|
|
X² |
df |
CFI |
TLI |
RMSEA |
CI 90% |
SRMR |
|
|
Model 1 |
260.27 |
53 |
0.965 |
0.957 |
0.124 |
0.109 |
0.139 |
0.078 |
|
Model 2 |
111.13 |
34 |
0.986 |
0.982 |
0.095 |
0.075 |
0.114 |
0.05 |
|
Model 3 |
84.45 |
34 |
0.991 |
0.988 |
0.076 |
0.056 |
0.097 |
0.038 |
Note. Model 1 = Original model; Model 2 = Model 1+ ítem 2 y 6
removed; Model 3 = Model 2
+ item 1 relocated to second factor.
The
alteration in the standardized factorial loading of the items in the models are
shown in Table 6. Within the initial model, items 2 and 6 possess significantly
lower coefficient values in comparison to the other items, which may impede the
evaluation of the instrument itself. Furthermore, upon excluding the items
(model 2), the coefficients for the remaining items bear a resemblance to those
demonstrated in the preceding model.
Despite
the presence of three items in the initial factor, the third model demonstrates
that the standardized factorial loading of these items experiences a slight
increase and maintain values that are near one another. This phenomenon serves
to reinforce a consistent evaluation of the factor by its corresponding
indicators. Furthermore, the first item exhibits good performance when it is
relocated to the second factor. Concerning factorial correlations, elevated
values are observed across all three models, with a marginal decrease in the
final model. This trend represents an ideal manifestation.
Table 6. Factor solutions of the 3
evaluated models of the EADI scale.
|
Factors: Items |
Model 1 |
Model 2 |
Model 3 |
||||
|
|
|
λest [IC 95%] |
SE |
λest [IC 95%] |
SE |
λest [IC 95%] |
SE |
|
F1: Perception |
Item 1 |
0.86 [0.78 -
0.94] |
0.04 |
0.86 [0.78 -
0.93] |
0.04 |
||
|
Item 2 |
0.53 [0.43 -
0.63] |
0.05 |
|||||
|
Item 3 |
0.79 [0.73 -
0.84] |
0.03 |
0.78 [0.72 -
0.84] |
0.03 |
0.80 [0.75 -
0.86] |
0.03 |
|
|
Item 4 |
0.86 [0.81 -
0.91] |
0.02 |
0.86 [0.81 -
0.91] |
0.02 |
0.89 [0.84 -
0.93] |
0.02 |
|
|
Item 5 |
0.84 [0.79 -
0.89] |
0.02 |
0.82 [0.77 -
0.88] |
0.03 |
0.84 [0.79 -
0.89] |
0.03 |
|
|
|
Item 6 |
0.61 [0.53 -
0.69] |
0.04 |
|
|
|
|
|
F2: Social distance |
Item 1 |
0.79 [0.72 -
0.86] |
0.04 |
||||
|
Item 7 |
0.82 [0.77 -
0.88] |
0.03 |
0.81 [0.76 -
0.87] |
0.03 |
0.81 [0.76 -
0.87] |
0.03 |
|
|
Item 8 |
0.90 [0.87 -
0.94] |
0.02 |
0.90 [0.87 -
0.94] |
0.02 |
0.90 [0.86 -
0.93] |
0.02 |
|
|
Item 9 |
0.91 [0.87 -
0.95] |
0.02 |
0.91 [0.87 -
0.95] |
0.02 |
0.91 [0.87 -
0.95] |
0.02 |
|
|
Item 10 |
0.93 [0.90 -
0.96] |
0.01 |
0.93 [0.91 -
0.96] |
0.01 |
0.93 [0.91 -
0.96] |
0.01 |
|
|
Item 11 |
0.86 [0.81 -
0.90] |
0.02 |
0.85 [0.81 -
0.90] |
0.02 |
0.85 [0.81 -
0.90] |
0.02 |
|
|
|
Item 12 |
0.92 [0.89 -
0.96] |
0.02 |
0.92 [0.89 -
0.96] |
0.02 |
0.92 [0.89 -
0.96] |
0.02 |
|
Correlation: F1*F2 |
0.85 [0.80 -
0.90] |
0.03 |
0.86 [0.81 -
0.91] |
0.03 |
0.82 [0.77 -
0.88] |
0.03 |
|
Internal
consistency was evaluated with the factor loadings obtained through
Confirmatory Factor Analysis (CFA). To establish adequate comparability, 3
decimal values in coefficients Alpha and Omega were used in table 7. The
variations are most evident in the alpha coefficient, where the values in its
coefficient increased in the first and second factor, until the second model.
As for the omega coefficient, a more conservative behavior is observed, in
which factor 1 has barely a negative variation in one thousandth, while in the
second factor there is a positive variation in 4 thousandths. All values in the
reliability coefficients are considered adequate.
Table 7. Reliability estimates for
factor models of the EADI scale.
|
Model |
Factors |
Alpha |
Omega |
|
Model 1 |
F1: Perception |
0.825 |
0.926 |
|
F2: Social distance |
0.829 |
0.912 |
|
|
Model 2 |
F1: Perception |
0.834 |
0.926 |
|
F2: Social distance |
0.836 |
0.912 |
|
|
Model 3 |
F1: Perception |
0.856 |
0.925 |
|
F2: Social distance |
0.825 |
0.916 |
DISCUSSION
The results obtained through the application of the Attitudes towards
Intellectual Disability Scale (EADI) were consistent with the underlying
theory. However, it required certain modifications. The initial adjustments
were centered around eliminating items 2 and 6, which consistently demonstrated
insufficient performance in evaluating the instrument, both in terms of
factorial loading and the descriptive indices provided. The second edition was
implemented in Model 3, entailing the relocation of the initial element
("They deserve respect just like other workers") to the second
variable of social separation. Theoretically, this adjustment is rooted in the
reciprocal essence of "respect" within an interpersonal bond.
Consequently, its placement within the realm of social distancing holds
significance.
Despite undergoing two re-specifications resulting in the evaluation of
three factorial models, the original configuration of the instrument has
predominantly been preserved. Moreover, the assessment of reliability
coefficients reinforces the notion that the re-specifications have contributed
to an enhancement in the form of the instrument, and that the exclusion of
items has not impacted the statistical evaluation of the instrument.
From a theoretical standpoint, each item symbolizes the quantification
of variables in a pertinent manner. On one hand, the Perception variable
concentrates explicitly on performance within a professional setting:
maintaining a tidy and organized work area, providing constructive feedback,
and contributing to labor efficiency. Furthermore, adequacy is ensured in the
quantification of a variable through the utilization of a minimum of three
items (Abad, 2011). Furthermore, it is evident that in the third model, the
associations between the variables are below 0.85, which is the customary
threshold to eliminate potential issues regarding the overlap of the
measurement and/or the lack of differentiation among the variables (Brown,
2015).Despite the existence of various instruments that evaluate attitudes
towards intellectual disability, most are aimed at the general population
(Henry et al., 1996) (Scior & Furnham, 2011) (Morin et al., 2013) (Power
& Green, 2010) or health workers (Williams & Rose, 2007). It is important
to highlight that none of these instruments are specifically designed to
measure attitudes in the work environment.
Moreover, other studies on attitudes towards people with intellectual
disabilities were carried out in a school context (García-sanz
et al., 2022) (Gómez et al., 2022), further highlighting the lack of tools
oriented to labor contexts. In contrast, the Scale of Attitudes towards
Intellectual Disability (EADI) focuses exclusively on the evaluation of
attitudes in the workplace, with the aim of promoting the socio-labor inclusion
of this group.
It has been observed that the tests that assess attitudes towards
intellectual disability, apart from their lengthy nature, reveal disparities in
the factorial structure when compared to the original theoretical proposal
(Morin, 2013; Lena Song, 2017; Scior, 2011). The existing body of literature
suggests the adoption of concise investigative tests, aiming to optimize the
efficiency of data collection, minimize participant fatigue, and reduce
irrelevant response patterns (Johnson, 2005). All of these considerations are
methodological in nature and have an impact on the instrument's reliability (Tavakol & Dennick, 2011).
We identified the existence of nine instruments that evaluate
discrimination towards people with intellectual disabilities through attitude
scales. Of these instruments, seven are in English and come from the following
countries: the United Kingdom (ADS - PG and DI) (Power & Green, 2010),
Canada (ATTID - PG) (Morin et al., 2013), the USA (CLAS-MR) (Henry et al.,
1996a), USA (CBPQ) (Williams & Rose, 2007), China (MRAI-R) (Hampton &
Xiao, 2008), USA (IDLS) (Scior & Furnham, 2011) and Singapore (APID) (Boo
& Nie, 2018). Two instruments were found in Spanish, both of which were
utilized in Spain: The Goratu Questionnaire – PG
(Gómez et al., 2022), the Invisible Barriers Questionnaire – PG (García-Sanz et
al., 2022).
In light of the literature, a methodological gap has been identified
with respect to the psychometric procedures used in previous studies. These
problems range from the omission of relevant information to the application of
statistical techniques that are not relevant to the psychometric analysis of
latent variables. Several authors used Principal Component Analysis (PCA) as
the technique of choice for latent factor analysis (Power & Green, 2010;
Scior & Furnham, 2011; Morin et al., 2013 and Boo & Nie, 2018).
Technique considered inadvisable for the identification of the factor structure
of latent variables (Lloret-Segura et al., 2014).
Although the confirmatory factor analysis demonstrated consistency with
the underlying theory through its fit indices, other studies (Hampton &
Xiao, 2008; Power & Green, 2010; Boo & Nie, 2018) did not report the
estimators to calculate the parameters of the model, nor did they fit them to
the observed data. On the contrary, assessments assessing attitudes toward
intellectual disability show a wide range and report differences in the
structural composition compared to the original theoretical proposal (Morin,
2013; Lena Song, 2017; Scior, 2011). The existing literature suggests the
adoption of brief survey assessments to optimize the efficiency of data
collection, mitigating participant fatigue, and reducing the occurrence of
irrelevant response patterns (Johnson, 2005). All of these considerations have
methodological implications that affect the reliability of the instrument (Tavakol & Dennick, 2011). However, the assessment of
attitudes toward intellectual disability in the workplace environment involves
various components that cannot be quantified by a single instrument. The
measurement scale presented in the current research only suggests two factors
that have a sufficient level of theoretical clarity. These factors are derived
from a nomological network rooted in the social model of intellectual
disability proposed by the World Health Organization in 2001. In the field of
discrimination, the first factor that exerts an influence is the level of
understanding we have of the condition of disability and its defining
characteristics (Scior, 2011). This research focuses on aspects directly
related to these characteristics. To understand the efficient dynamics of
interaction and communication that can be cultivated in a professional
environment, the dimension of social distance proves to be crucial.
Limitations
We encountered several limitations, such as the limited sample size,
which could potentially affect the generalizability of the findings to a
broader population. The presence of response bias resulting from how the
instrument was administered, where there was a lack of control over the
circumstances in which participants completed the survey, undermines the
validity of the findings. In addition, selection bias arises from complications
in accessing the sample, thereby compromising the ability to apply sampling
techniques. Finally, sociodemographic differences within the study cohort may
influence the observed variations in the variable of interest. Therefore, it is
imperative to exercise caution in interpreting the results and to take them
into account in future research.
Implications for working environments
This brief instrument will facilitate inclusion in the work environment.
A high rating on the instrument implies a higher degree of acceptance, while a
lower rating may imply varying degrees of non-acceptance. These forms of
assessment are essential for the identification and ongoing monitoring of work
interactions, promoting improvements in the standard of professional existence
and organizational effectiveness. Based on the quality standards established by
the organization and by ISO 10667, it is essential to regularly carry out valid
and reliable assessments to evaluate the performance and well-being of
employees (Muñiz, 2015). In this context, the use of this scale proves
beneficial in identifying discrimination in the workplace and in implementing
educational interventions that promote an inclusive and healthy work
environment. Consequently, the scale not only fulfills the quality expectations
of the ISO 10667 standard but also assumes an important role as a valuable tool
for continuous improvement in human resource management. Measuring attitudes
towards the PCDI will allow us to identify areas of prejudice and stigma that
need intervention, and help us to identify and prevent maladaptive behaviors in
the social work environment. Its approach requires the collaboration of
professionals including psychiatrists, neurologists, rehabilitators,
technologists, teachers, psychologists, sociologists, anthropologists, social
workers as well as mental health institutions.
Conclusion
The EADI is a brief and accurate tool for measuring attitudes that is
valuable in the evaluation of programs and policies aimed at understanding
inclusion and equal opportunity. Further studies are recommended that allow for
full invariance analysis to generate robust normative data and ensure the
applicability of the results to a wider population.
ORCID
Alicia Boluarte
Carbajal: https://orcid.org/0000-0002-8316-8065
Martin
Salazar-Conde: https://orcid.org/0000-0002-9507-0938
Arantxa N. Sánchez
Boluarte: https://orcid.org/0000-0003-0876-7196
Danilo Sánchez Coronel: https://orcid.org/0000-0003-0697-7683
Brian Norman
Peña-Calero: https://orcid.org/0000-0002-1073-9306
AUTHORS’ CONTRIBUTION
Alicia Boluarte Carbajal: study design, writing
of the manuscript, funding acquisition.
Martin Salazar-Conde: data collection, manuscript writing.
Arantxa N. Sánchez Boluarte: data analysis,
critical revision of the manuscript.
Danilo Sánchez Coronel: data collection, manuscript writing.
Brian Norman Peña-Calero: data analysis, manuscript writing.
All the authors approved the final version.
FUNDING
SOURCE
This work was
subsidized by CONCYTEC through the PROCIENCIA program within the framework of
the “Applied Research Projects in Social Sciences” contest, according to contract:
ID: PE501078008-2022.
This research is
derived from a bachelor’s thesis in Psychology at the Cesar Vallejo University.
CONFLICTO DE
INTERESES
The authors declare that they have no conflict of interest.
ACKNOWLEDGMENTS
Not applicable.
REVIEW
PROCESS
This study has been reviewed by external peers in double-blind mode.
The editor in charge was Renzo Rivera. The review process is included as
supplementary material 1.
DATA
AVAILABILITY STATEMENT
The database is included as supplementary material.
STATEMENT ON
THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE
No artificial
intelligence-generated tools were used in the creation of the manuscript.
DISCLAIMER
The authors are responsible for all statements made in this article.
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