Who Teaches Older Adults? Pedagogical and Digital Competence of Facilitators in Mexico and Spain

Abstract

Digital inclusion has become an essential component in ensuring the autonomy, social participation, and well-being of older adults. However, their learning of digital skills depends to a large extent on the quality of support provided by the facilitator, whose age, training, and experience directly influence teaching processes and how older adults relate to technology. This study compares the digital competences, and ICT skills of 107 facilitators of digital literacy programs, classified into three groups: peer educators (PEERS), young students without gerontological training (YOS), and young gerontology specialists (YGS). A quantitative design was used. Statistical analyses included non-parametric tests (Kruskal–Wallis, Mann–Whitney, Kendall’s Tau) and parametric tests (ANOVA, t-tests), to examine associations between socio-demographic variables, the level of digital competence, and ICT skills for teachers (technological and pedagogical). The results show clear differences between profiles. YOS achieved the highest scores in digital competence, especially in problem-solving and tool handling. The YGS achieved a balanced profile, combining competent levels of digital skills with pedagogical strengths linked to their gerontological training. In contrast, PEERS recorded the lowest levels of digital competence, particularly in security and information management; nevertheless, their role remains relevant for fostering trust and closeness in training processes among people of the same age. It was also found that educational level is positively associated with digital competence in all three profiles, while age showed a negative relationship only among PEERS. The findings highlight the importance of creating targeted training courses focusing on digital, technological, and pedagogical skills to ensure effective, tailored teaching methods for older adults.

1. Introduction

Over the past few decades, digitalization has become a fundamental aspect of social, economic, and cultural life due to changes in communication, citizen participation, and access to goods and services (Naik and Kakade 2024; Martínez-Alcalá et al. 2018). This process has given meaningful opportunities to foster personal autonomy and to broaden social inclusion (Rasi-Heikkinen and Doh 2023; Wanka et al. 2023). Nonetheless, it has evidently shown persistent inequalities affecting mainly older adults (Mubarak and Suomi 2022; Seifert et al. 2021). In this article, ‘older adults’ means people aged 60 and over who choose to take part in digital literacy courses. This group is highly heterogeneous in terms of age, educational level, work trajectories, previous digital experiences, motivations, functional abilities, and support needs. This diversity directly influences the types of pedagogical and technological strategies that facilitators should employ within digital literacy courses.

Research shows that this age group is most affected by the digital divide, a term used to describe a multidimensional phenomenon that spans multiple levels (Katey and Chivers 2025; Lee et al. 2020; Van Dijk 2020). This study considers three dimensions. First is the access divide, which relates to the availability of devices, infrastructure, and connectivity. Second, the use or ability divide refers to the capacity to use technology in an autonomous, critical, and significant way. The outcomes divide is ultimately linked to the transformation of technology into tangible benefits for everyday life. Together, these dimensions place digital training for older people within a broad framework of social inclusion (Van Deursen and Helsper 2015; Van Deursen and Van Dijk 2015; Van Dijk 2012).

It is more common to see older adults with devices and internet connections. However, many of them still face difficulties using them in their daily activities (Marimuthu et al. 2022; Martínez-Domínguez and Mora-Rivera 2020; Mubarak and Suomi 2022). Due to these limitations, their participation in tasks is essentially restricted nowadays. For instance, perform administrative tasks online, access digital health services, use electronic banking, or maintain communication with support networks (Fan and Zhang 2022; Hill et al. 2015). These complications are combined with a set of additional barriers, among them, trouble with accessibility derived from interfaces that are poorly adapted to the functional changes associated with aging (Lines et al. 2007; Ramdowar et al. 2024; Sayago and Blat 2009), lack of motivation linked to previous experiences of frustration, and ageist stereotypes that perpetuate the idea that “older people cannot learn” digital skills (Barrie et al. 2021; Holgersson and Söderström 2019; Seifert et al. 2018). To deal with this situation, it is crucial to teach digital skills. This will reduce inequalities and encourage older adults to play an active role in our growing digital world.

Digital literacy for older adults has been developed in formal and non-formal contexts (Martínez-Alcalá et al. 2018; Perim et al. 2025; Pihlainen et al. 2023). Nevertheless, the majority of digital learning among older adults takes place in non-formal contexts, where interaction is close and assistance is personalized, which is vital in the learning process. Most of them have access to digital support outside educational institutions or receive orientation from their family members (Rosales and Blanche-T 2022), volunteers (Elgamal et al. 2024), peer educator (Pizzul et al. 2024; Pizzul and Caliandro 2025), or community facilitators. Nonetheless, not everyone has close networks. Based on the aforementioned, organized programs in public libraries, community centers, civil associations, universities and intergenerational spaces constitute fundamental options to guarantee opportunities for accessible and continuous learning. Furthermore, research indicates that non-formal environments can effectively promote engagement and valuable learning. This means that adjustment of contents, rhythms, and didactic strategies to the concrete needs of the participants is allowed for (Ferreira et al. 2016; Pihlainen et al. 2023).

The role of the facilitator is therefore crucial. The facilitator’s experience, training, and support directly influence how older adults approach digital technologies and overcome technical, emotional, and attitudinal barriers (Flauzino et al. 2020; Vercruyssen et al. 2023). It should be noted that this study uses the term ‘facilitator’ to refer to anyone who teaches, supports, or leads the digital literacy process for older people, regardless of their academic training, age, or institutional role.

As highlighted in the previous paragraph, the importance of the support provided by the facilitators is clear. Further understanding of their role in the digital literacy process is necessary. The performance of the facilitators not only conditions the way in which older adults face technical, emotional, or attitudinal barriers, but also structures educational dynamics, defines learning opportunities, and models experiences of meaningful technology use (Arthanat et al. 2019; Chiu et al. 2019; Fields et al. 2020; Tomczyk et al. 2020). A particular set of pedagogical, digital, communicative, and socioemotional competences is required to teach digital abilities to older adults. These competences go beyond the mere transmission of content, requiring sensitivity, educational creativity, and mediation skills (Pihlainen et al. 2021).

Despite its relevance, research analyzing the role of facilitators in the digital literacy of older adults is still limited. The literature recognizes distinct types of facilitators, including peer educators (Pihlainen et al. 2021), young volunteers, university students (Elgamal et al. 2024) and facilitators with specialized training in gerontology and pedagogy (Martínez-Alcalá et al. 2021). Nevertheless, there is little evidence to compare and understand how these differences affect digital, pedagogical and socio-emotional competencies during the courses (Bhattacharjee et al. 2020). Furthermore, most research focuses on older adults’ experiences, neglecting the perspectives, training and educational practices of those delivering the training. This conceptual gap hinders our understanding of teaching and learning functions, as well as the factors that contribute to the success or limitations of the programs.

In this context, the purpose of this study is to analyze and compare three facilitators: peers educator (PEERS), young people without gerontological training (YOS), and young people with gerontological training (YGS); to examine how their sociodemographic characteristics, previous experiences, digital competences, and ICT skills are related to their teaching performance in programs of digital literacy for older adults. The study seeks to contribute to a more comprehensive understanding of the factors influencing teaching quality by providing comparative evidence of these profiles. It also aims to inform the training of facilitators and the design of more inclusive and effective programs for older adults.

1.1. Digital Inclusion in Mexico and Spain: Divide, Policies, and Structural Challenges

The present study is developed in two distinct contexts: Spain and Mexico, territories that share linguistic and cultural affinities but with significant contrasts in digital infrastructure, public policies, and access to training opportunities for older adults. These differences enable us to understand how structural factors influence facilitators’ labor, organizing digital literacy programs and participants’ learning experiences. It is crucial to note that the fieldwork was conducted in Sevilla (Spain) and Hidalgo (Mexico), which mirror the local aging patterns and technological access levels of the individuals within their respective national contexts.

Spain is one of the oldest countries in Europe, with 20.4% of its population aged 65 years or over, a proportion that could rise to 30.5% by 2055. Concerning the use of technology, 95% of people between 16 and 74 years use the internet regularly (INE 2025). Notwithstanding, the utilization of the device exhibits a decline among older adults. Between the ages of 74 and 79, the frequency diminishes to 80.5% among men and 79.3% among women. In Sevilla, this age group maintains similar levels close to 80%, which is evident in the high digital use, although age-related divides exist.

Mexico’s demographic structure is different due to 14% of its population being aged 60 or over (INEGI 2022). In 2023, 97 million people in the country had internet access (INEGI 2024). Additionally, internet usage decreases with age; within the 55–64 age group, for example, only 69.2% of people use the internet. In Hidalgo, 79.8% of the population use digital services, which is a level of connectivity similar to that observed in Seville. However, it still reflects significant disparities in usage among older adults at the national level.

Both territories have their own particularities, and data reveal a shared tendency. However, both countries demonstrate greater variations in the quality of teaching and the training of facilitators. In Spain, digital support is provided in public libraries, retirement associations, community centers, and intergenerational courses organized by municipalities and universities. Young volunteers and peer educators often promote mutual support and intergenerational learning strategies. On the other hand, in Mexico, community centers, universities, federal programs, and private initiatives offer the service. Most facilitators are young volunteers or professionals specialized in gerontology.

The diversity of profiles, training, and experience highlights the importance of analyzing their digital competencies and ICT skills (technological and pedagogical) to comprehend how they affect the efficacy of the training processes.

1.2. Educators’ Profiles in the Learning of the Elderly

Teaching digital skills to older adults is a task that not only entails transmitting technical knowledge but also adapting to specific concerns of this age group (Vercruyssen et al. 2023). In this context, facilitators’ profiles play an indispensable role as their definitions, characteristics, and pedagogical approaches can influence the efficiency of the training programs. The principal objective of this section is to identify and analyze the distinct facilitators’ profiles involved in teaching digital skills to older adults, including definitions and principal features.

A relevant aspect is that facilitators for older adults do not only teach technology, but also create learning environments that are suited to the emotional and cognitive needs of older adults. Seo et al. (2019) proposed that the success of educational programs depends predominantly on the characteristics of the facilitator, including their teaching style and personal attributes. Based on these authors, facilitators who earn the trust of learners and foster a safe and respectful environment where older adults feel free to ask questions significantly increase their chances of success in the programs. In this field, three main profiles of facilitators in digital literacy programs are commonly identified: peer educators, intergenerational educators, and facilitators with gerontological training.

Peer educators, for whom digital skills and knowledge have been acquired and shared with others of the same age. Older adults teach other older adults, drawing on their own experiences of learning about technology. On the other hand, they are one of the most frequently mentioned profiles in articles and studies on digital inclusion, highlighting their essential role in promoting digital literacy. Formosa (2018) emphasizes that peer teaching is one of the most effective learning methods during senior years. This teaching model is based on shared experience and empathy, which facilitates more equitable learning. The presence of tutors who understand the cognitive and technological limitations and difficulties of their peers of the same advanced age creates a less intimidating learning environment. Likewise, Pihlainen et al. (2021) emphasize that peer teaching promotes digital skills learning and facilitates a sense of community among participants, creating a socially enriching environment.

Another relevant profile is that of intergenerational educators, who are generally university students or volunteers, acting as guides for older adults in their learning process. Despite having less experience in teaching this age group, they are valuable resources due to their familiarity with technology and their ability to offer technical and emotional support. Breck et al. (2018) note that intergenerational mentoring programs enable older adults to improve their digital skills. At the same time, they promote a deeper understanding among generations, breaking stereotypes about aging and fostering empathy. These types of mentoring programs build two-way learning, in which both groups benefit from the exchange of knowledge and experiences. It is noteworthy that university students participate in these programs through projects arranged by their educational institutions, since they are part of the professional internships or social services required for their academic training. Meanwhile, volunteers are involved in initiatives promoted by non-governmental organizations (NGOs) and community associations. Not only do these facilitators teach the necessary technical skills, but they also provide emotional support to older adults, helping them to reduce their anxiety about technology. Arthanat et al. (2019) stressed that this type of profile is critical for creating an accessible environment where older adults feel comfortable and motivated to interact with technology.

Lastly, facilitators with gerontological training are educators with solid knowledge of aging, aging psychology, and andragogy. They are able to design strategies to adapt teaching to the cognitive, emotional, and psychological needs of older adults (Martínez-Alcalá et al. 2021). In some cases, these educators facilitate digital inclusion, ensuring that individuals acquire technological skills and feel included and autonomous in the digital environment. The adapted, learner-centered teaching approach is the main feature of this profile, enabling the design of strategies that promote gradual adaptation to technology and respect for the physical and cognitive limitations that some older adults may have (Seo et al. 2019). Pihlainen et al. (2021) highlight that the presence of gerontologists in the workshops allows a more personalized approach, since these professionals understand the unique aspects of aging and design programs that promote the inclusion of older adults in the digital environment.

Consequently, this approach assures that the teaching-learning process will be more accessible and responsive to participants’ abilities and expectations. Furthermore, these facilitators possess a deep understanding of the particularities of aging, thereby their teaching promotes digital autonomy and reduces psychological barriers related to learning new technologies. Hence, their intervention facilitates not only the acquisition of digital skills but also reinforces older adults’ confidence in their ability to navigate the digital world. As we can see, each facilitator profile has specific characteristics and competencies that enable them to address the cognitive and emotional barriers that older adults face when learning digital skills.

Nonetheless, most digital literacy programs for older adults tend only to have one type of facilitator, which can limit the effectiveness of the training process by not taking advantage of complementary approaches. For this reason, it raises questions about how differences in training, experience, and methodologies influence the teaching of digital skills to this age group. From this, the following research questions arise:

• How do facilitators perceive their level of digital skills?
• What is the level of digital competence of different facilitator profiles?
• What ICT skills for teachers (technological and pedagogical) distinguish the different facilitator profiles in teaching digital skills to older adults?

2. Materials and Methods

2.1. Study Design

A quantitative design was employed. We collected the variables using standardized instruments and analyzed them using descriptive and inferential statistical procedures. Two standardized instruments were applied to assess the associations between sociodemographic variables, digital self-perception, level of digital competence, and ICT skills for teachers. The study’s objectives are aligned with the quantitative approach, as it facilitates a systematic comparison of digital competence and ICT skills among different facilitator profiles. It also allows for the analysis of associations between these competencies and sociodemographic variables using robust statistical techniques.

It provides a comprehensive view of facilitators’ skills in different domains, allowing us to answer research questions about skill perception, level of digital competence, and differences between facilitator profiles (correlations with age, education, experience, and specific gerontology-related training).

2.2. Study Context

Respondents came from the states of Sevilla (España) e Hidalgo (Mexico), including urban, semi-urban, and rural areas, allowing for a wide range of socio-educational contexts to be captured. Additionally, institutions and programs that offered digital literacy courses to older adults were considered, such as community centers, universities, non-governmental organizations, and public and private initiatives.

2.3. Participants

Convenience sampling was used, selecting active facilitators in digital literacy programs for older adults who were willing to participate in the research. This approach proved to be the most efficacious for enlisting the participation of individuals within diverse communities and educational context. The facilitators in our study impart digital competencies to a range of older adult audiences, encompassing individuals with varying degrees of prior experience.

The study sample consisted of a total of 107 facilitators who were actively involved in digital literacy programs for older adults in Mexico and Spain. The participants were classified into three different profiles, defined in terms of their academic background, professional experience, and teaching methodology: peer educators (PEERS), young students with other studies (not related to gerontology), YOS; and gerontology specialists (young people with studies in gerontology, YGS). The ages of the three groups ranged from 17 to 74 years. Specifically, the PEERS were between 50 and 70 years old; the YOS were between 17 and 22 years old; and the YGS were between 22 and 33 years old. These age ranges were defined by following conceptual and practical criteria, ensuring that the diversity of generations and teaching experience of each profile was reflected, and also facilitating the comparison of teaching skills and styles. The sociodemographic variables for each group and the significant differences between the groups are presented in

Table 1. Means, standard deviations and independent ANOVA results for the variables of age and pedagogical skill of the three groups of Facilitators.

	Mean (SD)	Mean (SD)	Mean (SD)	Df = 2, 104
	PEERS	YOS	YGS	F	p
Age	59 (6)	19.51 (2)	24.77 (2)	1195.48	<0.001
Pedagogical skills	34 (3)	29 (9)	32.8(6)	10.90	<0.001

YOS, adolescent and young adults with other studies; YGS, young adults with gerontology studies. Df, degrees of freedom; SD, standard deviations. Numbers in bold indicate significant differences, p < 0.05.

and

Table 2. Summary of socio-demographic variables, experience, Digital Competence Scale (DCS) and Technological skills scores by facilitator group. (A) Medians and Kruskal–Wallis comparisons for age, years of education, and teaching experience. (B) Medians, distributions, and statistical comparisons of DCS and Technological Skills scores within groups.

A. Socio-Demographic measures and comparisons of the three groups of Facilitators *
				Intergroup		Intergroup
	PEERS n = 32	YOS n = 39	YGS n = 36	PEERS vs. YOS vs. YGS		PEERS vs. YOS		PEERS vs. YGS		YOS vs. YGS
	Median	Median	Median	χ2	p	z	p	z	p	z	p
Education (years)	17	13	16	48.28	<0.001	−4.9	<0.001	−0.2	0.78	−6.99	<0.001
Experience (years)	5.5	0.5	2	48.39	0.001	−6.49	<0.001	−3.8	<0.001	−4.13	<0.001
B. Scale measures and comparisons of the three group of Facilitators *
DCS	16	16	19	9.49	<0.001	−0.8	0.40	−2.8	<0.001	−2.32	0.02
Techn. skills	34.5	25	38.5	15.67	<0.001	−2.8	<0.001	−0.7	0.42	−3.7	<0.001

Medians of the three groups and statistical comparisons with Kruskal–Wallis and Mann–Whitney tests. Numbers in bold indicate significant differences, p < 0.05. YOS, young adolescents and adults with other studies; YGS, young adults with gerontology studies. Digital Competence Scale (DCS). Df, degrees of freedom; * at least one of the groups had not normal test distributions.

.

With the distribution by country and profile in mind, 32 facilitators of the PEERS profile and 29 of the intergenerational profile (YOS) were present in Spain. While in Mexico, 10 facilitators of the intergenerational profile (YOS) and 36 of the profile with training in gerontology (YGS) participated. This distribution reflects the diversity of contexts and profiles involved, making it possible to analyze the organizational and pedagogical particularities of digital literacy programs in both countries (See Appendix A—

Table A1. Sample distribution (N = 107) by country, facilitator role, and municipality.

Country	Role	Municipality	n	%
Spain (n = 61)	PEERS	Sevilla (Capital)	20	32.8%
	PEERS	Osuna	12	19.7%
	YOS	Sevilla (Capital)	20	32.8%
	YOS	Osuna	9	14.7%
Mexico (n = 46)	YOS	Pachuca de Soto	10	21.7%
	YGS	Pachuca de Soto	19	41.3%
	YGS	Mineral de la Reforma	10	21.7%
	YGS	Actopan	5	10.9%
	YGS	Omitlán	2	4.3%

). Due to the use of non-probabilistic sampling, the results cannot be generalized to all facilitators in Mexico and Spain; they should be interpreted as indicative trends within the programs analyzed.

2.4. Instruments

Data for this study were collected using two standardized instruments:

• Digital Competence Scale (DCS): Based on the European Digital Competence Framework for Citizens (DigComp 2.2, File S2), this instrument assessed the level of digital competence of the facilitators (Schwarz et al. 2024). Participants indicate their level of ability to perform a series of digital tasks, using the following options to reply: Yes, I can do it with help; Yes, I can do it on my own; Yes, I can help others; No, I cannot do it at all. Each item was highlighted, and the total amount allowed the classification of the participants into four levels of digital competency (

  Table 3. Scoring intervals and digital competency levels (DCS).

  Interval	Level
  0–6 points	No skills
  7–14 points	Basic
  15–22 points	Intermediate
  23–30 points	Advanced

  ):
• Survey on ICT skills for teachers (File S1): The objective of this survey was to identify the different types of ICT skills possessed by facilitators of digital literacy programs. The instrument was adapted from the UNESCO ICT Competency Framework for Teachers (UNESCO 2019) and was conceptually informed by previous research on teachers’ ICT competencies (Hernández Suárez et al. 2016; Prodromou et al. 2019). The instrument includes a self-perception question that asks participants to assess their level of digital skills using a 4-point Likert scale (Lower, Intermediate, Higher, and Highest). Furthermore, two specific areas of competence were evaluated: technological skills (15 items) and pedagogical skills (10 items), which provided a comprehensive overview of the facilitators’ skills relating to the use of technologies in their educational work. The scale for the competency items was as follows (

  Table 4. Scale values for technological and pedagogical ICT skills.

  Value	Description
  1	Not competent at all
  2	Not very competent
  3	Competent
  4	Very competent
  5	Fully competent

  ):

There is prior evidence of the validity and reliability of both instruments, which supports their suitability for assessing digital and ICT competencies in similar educational contexts.

2.5. Procedure

The study was conducted from May 2022 to August 2024, involving a series of two planned phases that enabled us to collect quantitative data from facilitators.

• Phase 1. Identification and contact with institutions and programs. During this phase, institutions and programs that offer digital literacy courses for older adults in Mexico and Spain were identified, including community centers, universities, non-governmental organizations, and public and private initiatives. Once the organizations were contacted, communication was established with their coordinators and facilitators, to whom the aim of the study was clearly explained, and they were formally invited to participate. The inclusion criteria considered facilitators of digital literacy programs for different ages who actively participated in teaching older adults.
• Phase 2: Application of instruments and data collection. Participants received standardized instruments to collect sociodemographic data and assess digital competence and ICT skills for teachers (technological and pedagogical). All instruments were administered remotely and asynchronously, in a fixed order, and took about 40 min to complete. Assistance was available for questions or technical difficulties. Responses were reviewed immediately after submission for completeness and consistency. Additionally, the instruments were distributed via a Google Forms questionnaire. In Spain, facilitators completed the survey using the institutional equipment they normally use for their training activities, while the groups of young people and gerontologists responded using their personal devices. The extended data collection period was justified by the need to coordinate the participation of multiple institutions in two countries. It was also due to the heterogeneity of the programs, contexts, and facilitator profiles. Over this time, there were no significant changes in program conditions that would affect data comparability. Therefore, all data were merged for further analysis.

2.6. Data Analysis

The primary objectives of the investigation included ascertaining the identities of the facilitators, examining their self-perceptions, assessing their DCS levels, evaluating their technological and pedagogical skills, and investigating the relationship between socio-demographic variables and the aforementioned levels. To this end, both intra- and intergroup analyses were deemed to be relevant.

We processed the data using Excel and SPSS v. 15. Frequencies, percentages, medians or means for each sociodemographic variable and for the categories of the Self-Perception, Digital Competence Scale, Technological and Pedagogical skills were obtained. We administered Kolmogorov–Smirnov tests to each group and variable, then performed the relevant statistical analyses according to their distribution. Compliance with normal parameters for the three groups led to an independent ANOVA when comparing the means. Independent Student’s t-tests were used for comparing two groups (MacFarland and Yates 2016; Ostertagova et al. 2014; Puka 2011).

Non-parametric statistics were used if at least one distribution was found to be not normally distributed for a group. Finally, we applied the Kruskal–Wallis test to compare the median values of the three groups and conducted Mann–Whitney tests for post hoc comparisons. Measuring ordinal associations between variables is the purpose of Kendall’s tau-b correlation, a non-parametric hypothesis test. Therefore, the performance of several Kendall’s Tau-B correlations analyses was carried out independently for each group for the two main variables of interest, age and educational level (in years), to decipher the association with the digital competence scales.

2.7. Ethics

All participants were informed in advance about the study objectives. Before participating, they all signed an informed consent form. This form guaranteed the confidentiality of their data and the right to withdraw from the study at any time without repercussions. Prior to analysis, all data were anonymized. There was no collection of names, email addresses, or other personal identifiers. Each participant was assigned a number by the database. This information was only shared with the research team. These measures ensured the confidentiality and ethical handling of the data throughout the analytical process. The study complied with all current ethical standards for educational research.

This research was part of a sabbatical project entitled Online Educational Scenarios for the Digital Inclusion of Older Adults, carried out during 2022–2023 in Seville, Spain. The study did not require evaluation by an ethics committee, as it did not involve experimentation or the manipulation of sensitive data.

3. Results

3.1. Socio-Demographic and Scale Results

Age

The distributions of the age and pedagogical skill scale variables were normal for all three groups. Therefore, parametric statistical analyses were calculated for them.

The ANOVA results showed significant differences considering all the groups (Table 3). The post hoc tests revealed significant differences with no assumption of equal variances between older and younger facilitators: PEERS vs. YOS (t(35) = 37.28, p < 0.001) and PEERS vs. YGS (t(40) = 31, p < 0.001). Similarly, for the two groups of younger facilitators, assuming similar variances, the post hoc test results showed that the ages were different (t(73) = −11.01, p < 0.001).

3.2. Self-Perception of Digital Skills

Using the Survey on ICT Skills for Teachers, participants’ self-perceived digital skill level was obtained, through a single Likert-type item with four response categories (lower, intermediate, higher, highest). These categories represent subjective self-assessments. They do not correspond to objective score ranges. Nor do they correspond to predefined numerical intervals. The categories and the frequencies converted to percentages for each group is shown in Figure 1. The percentages for each category were as follows: For the PEERS group: 9.37%, 34.37%, 50%, and 6.25%. For the YOS group: 28.21%, 41.03%, 17.95% and 12.82%. For the YGS group, the percentages were 27.78%, 52.78%, 11.11% and 8.33%. As observed, half of the group of PEERS considered they had a higher score. Almost all groups considered themselves as having intermediate levels of digital skills.

3.2.1. Descriptive Analyses for Socio-Demographic Variables and Scales

As stated above, the three scales administered were digital competence, technological skill, and pedagogical skill. Individual subjects within each group were classified on the DCS. For the PEERS group, the percentages for the basic, intermediate, and advanced levels were the following: 18.75%, 71.88%, and 9.38%, respectively. For the YOS group: 7.69%, 79.49%, and 12.82%; and for the YGS group: 11.11%, 55.56%, and 33.33%. According to the chi-square test = 9.76, p < 0.04, there were statistically significant differences in digital competency levels between the three groups. The YGS group had a proportionally higher number of participants with an advanced level (n = 12) compared to the PEERS group (n = 3) (z = −2.23, p = 0.02) (Figure 2A).

In further analyses concerning the DCS, in Figure 2A, the percentage of people from each group was categorized according to the DCS. It can be observed that the three groups are mostly intermediate (PEERS: 71.88%; YOS: 79.49% and YGS: 55.56%). Instead, few of them rated as having basic digital competences (PEERS: 18.75%; YOS: 7.69% and YGS: 11.11%). Few of them were also categorized as having advanced competence levels (PEERS: 9.38%; YOS: 12.82% and YGS: 33.33%). When obtaining the means of the DCS, only in the advanced level there was a significant difference between the level of the group of PEERS and the group of YGS (Figure 2B). Therefore, even when subjective self-reports position the group of PEERS as having high digital competences, objective studies rendered a different perspective. PEERS and YGS really differ when their advanced level of digital competence is compared, being the group of PEERS below the digital competence of the group of YGS.

3.2.2. Comparison of Medians for Years of Education and Years of Experience

For the variables of education and experience, non-parametric statistical analyses were performed (Table 2). In the case of digital competence and technological skills, the scales deviated from the normal distribution (Table 2).

According to the Kruskal–Wallis tests, the comparison of the medians of years of education and experience was significant for all three groups, as shown in Table 2 (17, 13, and 16 years for PEERS, YOS, and YGS, respectively). Post hoc tests revealed significant differences between groups, with the older group and the two groups of younger facilitators showing marked variations in almost all intergroup comparisons (years of education and years of experience). However, exceptions were found: the medians of years of education for PEERS and YGS (17 and 16 years, respectively) were not statistically different.

Regarding years of experience, notably, the older group had the highest median number of years of experience teaching older adults (5.5 years), whilst the YOS group had the lowest median of all groups, with 0.5 years of experience, and the YGS group had 2 years.

3.2.3. Comparison of Medians for the DCS

Another exception to the significant results within the comparison of means according to ANOVA and post hoc tests was the level of DCS for PEERS and YOS, as the level of YGS was the highest one. There were differences in the mean DCS scores for the three groups. The level of the PEERS and YOS groups was equivalent and did not reach statistical significance. While the comparisons between PEERS and YGS, and between YOS and YGS, showed they did differ (Table 2 and Figure 2B).

3.3. Technological and Pedagogical Skills

Regarding technological skills, medians were generally statistically different. When post hoc tests were applied, technological skills were equivalent between PEERS and YGS, but different between PEERS and YOS, and between YOS and YGS (Table 4 and Figure 3A).

Therefore, even when PEERS had more years of experience in teaching their contemporaries than younger groups, when years of education are contrasted, PEERS and YGS are similar. Also, PEERS resemble younger students without gerontology studies (YOS) in the DCS. However, PEERS’ technological skills are equivalent to those of the YGS.

As for pedagogical skills, the outcome of the ANOVA was significant (Table 1). Post hoc tests rendered statistically significant differences between almost all groups. Assuming different variances between the older and younger facilitators, both young groups had statistically different pedagogical profiles (PEERS vs. YOS, t(69) = 5.32, p < 0.001; YOS vs. YGS, t(50) = −3.74, p < 0.001). Interestingly, only PEERS and YGS had similar pedagogical skills (Figure 3B).

The results suggest that pedagogical skill does not follow the same pattern as technological skills in all profiles. This is because PEERS and YGS show comparable pedagogical strengths despite differences in age and training.

3.4. Correlations Between Socio-Demographic Variables and the DCS

Aside from the PEERS group, the youth groups showed positive and significant correlations between sociodemographic variables. YOS: age and education in years (rho = 0.87, p < 0.001); age and experience in years (rho = 0.54, p < 0.001); experience in years and experience teaching older adults (rho = 0.47, p = 0.002). YGS: age and education in years (rho = 0.41, p = 0.01); age and experience in years (rho = 0.67, p < 0.001); experience in years and experience in teaching older adults (rho = 0.60, p < 0.001).

3.4.1. Age and DCS Scores

Remarkably, there was a small but significant negative correlation between the DCS and age (Figure 4A) in the PEERS group (Kendall’s Tau = −0.30, p < 0.02). Predictably, both younger groups showed significant positive correlations (YOS: Kendall’s Tau = 0.40, p < 0.001; YGS: Kendall’s Tau = 0.36, p < 0.001).

3.4.2. Years of Education

Correlations between the DCS and years of education were positive for all groups. PEERS: Kendall’s Tau = 0.28, p < 0.04; YOS: Kendall’s Tau = 0.33, p < 0.01; YGS: Kendall’s Tau = 0.48, p < 0.001 (Figure 4B).

3.5. Correlations Between Socio-Demographic Variables and Technological and Pedagogical Skills

3.5.1. Age and Technological and Pedagogical Skills

The correlations between technological skill and age for the PEERS group were not significant (Kendall’s Tau = 0.11, p = 0.37) (Figure 5A). In contrast, the correlation between the younger groups showed significant positive correlations (YOS: Kendall’s Tau = 0.49, p < 0.001; YGS: Kendall’s Tau = 0.55, p < 0.001).

Correlations between pedagogical skill and age were positive but not significant for the group of PEERS (Kendall’s Tau = 0.19, p = 0.13). However, for the younger facilitators they were positive and significant (YOS: Kendall’s Tau = 0.77, p < 0.001; YGS: Kendall’s Tau = 0.48, p < 0.001) (Figure 5B).

3.5.2. Years of Education and Technological and Pedagogical Skills

The correlation between technological skill and years of education for the group of PEERS was negative although not significant (Kendall’s Tau = −0.19, p = 0.15). Nevertheless, for the group of young adolescents and adults, YOS, it was positive and significant, Kendall’s Tau = 0.41, p < 0.001); and also for the group of YGS: Kendall’s Tau = 0.53, p < 0.001.

The correlations between pedagogical skill and years of education were positive, although not significant for the group of PEERS (Kendall’s Tau = 0.22, p = 0.87). Nonetheless, these correlations were positive and significant for the adolescent, young adult group (YOS) (Kendall’s Tau = 0.67, p < 0.001) and for the YGS group (Kendall’s Tau = 0.50, p < 0.001) (Figure 5B).

3.6. Correlations Between DCS, Technological and Pedagogical Skills

Previously mentioned, the PEERS group presented non-significant negative or positive correlations between DCS scores and age. Similarly, this group shows little association with other scales. Although the relationship between DCS and technological skills is positive, low, and significant (Kendall’s Tau = 0.37, p < 0.001), the correlation disappears for DCS and pedagogical skills (Kendall’s Tau = 0.08, p = 0.52). However, it is again positive, low, and significant between technological and pedagogical skills (Kendall’s Tau = 0.31, p = 0.01) (Figure 6A).

Expectedly, associations between scales became stronger in younger facilitators. For the Young students group (YOS; facilitators aged 17–22 years) and the Young gerontologists group (YGS; facilitators aged 22–33 years), all correlations were positive and significant, particularly for the YGS group.

Specifically, for the YOS group, the association between DCS and technological skills was strong (Kendall’s Tau = 0.68, p < 0.001). The correlation between DCS and pedagogical skills was moderate (Kendall’s Tau = 0.41, p < 0.001), including technological and pedagogical skills. It was similar (Kendall’s Tau = 0.45, p < 0.001; see Figure 6B). YGS is between DCS and technological skills, Kendall’s Tau = 0.65, p < 0.001 is between DCS and pedagogical skills, Kendall’s Tau = 0.68, p < 0.001 is between technological and pedagogical skills, Kendall’s Tau = 0.75, p < 0.001 (Figure 6C).

4. Discussion

The results obtained show the distinct profiles of facilitators participating in digital literacy programs for older adults, revealing significant differences in their digital competencies level and ICT skills for teachers (technological and pedagogical). These profiles are also influenced by sociodemographic variables such as age, years of education, and experience in teaching older adults. These results highlight clear socio-demographic differences between the profiles of facilitators, especially in terms of education and teaching experience, which provide an important context for interpreting subsequent competency-related analyses.

Inputs and constraints to be considered to strengthen the quality of digital training older adults are identified.

The data show clearly differentiated patterns. These are related to the distribution by country and profile. In Spain, for example, there is a predominance of peer facilitators, along with a relevant group of young people without gerontological training. In Mexico, the most common profile is that of young people with specialized training, followed by a smaller number of young volunteers. These differences not only explain the composition of the sample but also influence the competences, perceptions, and pedagogical styles observed in each profile. This provides a comparative framework for interpreting the study results.

In terms of self-perception of digital abilities, the results demonstrate differences in how people value their own digital capacities. It is significant to acknowledge that these results are indicative of each profile’s self-perception, rather than its actual digital proficiency, which was independently gauged by the Digital Competence Scale (DCS). From this perspective, most PEERS are situated at a high level of self-perception, especially in the superior category, reflecting trust in their use of digital tools. By contrast, the young (YOS and YGS) exhibit an opposite pattern. Both groups focus on an intermediate level, indicating a more moderate view of their own competencies. Notably, the YGS group shows a strong tendency towards the intermediate level. Despite their proximity to technology, they are not perceived as highly competent users. This discrepancy between profiles underlines the subjective nature of self-perception and coincides with studies that document optimistic biases in respondents to digital surveys within familiar environments.

It has long been assumed that so-called ‘digital natives’ possess greater technological skills due to being born into a context surrounded by digital devices and constant technology (Kesharwani 2020). Nonetheless, recent studies suggest that not all young people fulfill this profile, and digital competence depends on factors such as accumulated experience, contextual use, and access to resources (Drabowicz 2017; Wilkin et al. 2017). The difference between ‘digital natives’ and ‘digital immigrants’ is not simple, as some peers’ educators prioritize digital skills, even if they are not as proficient as younger instructors. Despite this, the use of technology frequently and consistently results in improved performance (Nikou et al. 2019; Kirschner and De Bruyckere 2017). This study’s findings may be related to a person’s self-perception, specialized training, habitual interaction with digital tools, and, importantly, their chronological age.

The socio-demographic variables analysis revealed a negative correlation between age and digital competences. The older facilitators (PEERS) face more challenges in updating or maintaining their digital skills if they do not receive continuous training. This situation aligns with research that highlights age as a limiting factor in technological adoption, emphasizing the importance of adapted training to encourage digital inclusion among this age group (Arthanat et al. 2019; Mubarak and Suomi 2022). Notwithstanding, the experience and intrinsic motivation of pair facilitators should not be underestimated; even though they have technical limitations, they provide generational closeness and commitment that foster collaborative teaching and learning (Carrillo and Flores 2018; Pihlainen et al. 2021; Seo et al. 2019; Gates and Wilson-Menzfeld 2022). The accumulated experience is a valuable resource in the training process, particularly when it is aimed at significant learning for older people.

Since a positive relationship between age and digital competence rose, the opposite tendency was observed in younger groups (YOS and YGS). This suggests that YGS groups demonstrated a higher level of digital proficiency, likely due to the experience gained through their academic training and professional practice. Previous research has demonstrated generational closeness with technological environments, which facilitates learning and acquisition of digital competence. At the same time, academic and professional experience allow this consolidation (Arthanat et al. 2019; Seo et al. 2019).

In all three profiles, a positive relationship between level of education and the digital domain. Although this is more evident in the YGS group due to the combination of gerontological and academic training, enhancing their technological competencies (Gates and Wilson-Menzfeld 2022; Leedahl et al. 2019). Consequently, the development of digital abilities appears to be influenced not only by aging or generational proximity, but also by training and accumulated experience.

In terms of pedagogical skill, each profile offers specific advantages to the teaching and learning process in digital literacy programs. When PEERS share their life experiences with participants, they create an environment of trust and intragenerational closeness that facilitates horizontal learning and empathy towards the needs of older adults. Nevertheless, their technical limitations highlight the need for training support or collaboration with younger facilitators. Conversely, YOS are more proficient with technology, but sometimes struggle to translate their knowledge into pedagogically adapted strategies, relying on quick explanations or technical demonstrations that can result in less effective outcomes for older learners (Arthanat et al. 2019; Seo et al. 2019).

YGS’s gerontological training enables them to balance technological and pedagogical approaches, contextualizing digital learning in older adults’ daily lives and employing methodologies that foster autonomy and meaningful learning (Gates and Wilson-Menzfeld 2022; Leedahl et al. 2019). The digital skills taught to older adults are influenced by a range of factors, including technical, pedagogical, relational, and attitudinal domains. In this sense, the diversity of profiles is complementary. For example, there are PEERS who contribute to closeness and vital experience, YOS who offer technological expertise, and YGS who combine both dimensions with a sensible, structured approach. Therefore, efficient teaching relies on a combination of these competencies, pedagogical adaptation capacity, accumulated experience, and a willingness to generate meaningful connections. The results emphasize the importance of enhancing training and support for all profiles by promoting inclusive strategies and sustainable programs that are sensitive to both facilitators and learners.

In conclusion, a relevant aspect of this study is highlighted based on the results, specifically the need to design training strategies to each facilitator profile, considering their experience, previous training, and role during the courses. For PEERS, short, practical modules focused on the basic use of tools and the resolution of common problems are useful. In the case of YOS, strategies focusing on old-age didactics and pedagogical communication are required. There are also relevant opportunities for technological upgrading to complement the YGS’s gerontological training.

Moreover, given that a significant proportion of facilitators engage in community programs or volunteer activities, these endeavors must be pragmatic and sustainable, incorporating hybrid methodologies and concise certifications accessible from their professional environments. Whereas digital literacy in Spain and Mexico is developed mainly in libraries, community centers, open universities, municipalities and civil organizations, these same spaces are viable scenarios for implementing continuing training free of charge or at low cost, through programs promoted by local governments, educational institutions and community organizations.

When considered as a whole, these findings provide concrete evidence to guide digital literacy policies and programs with feasible impacts that are aligned with the current needs of facilitators and older adults.

5. Limitations

Several methodological limitations must be considered when interpreting the results. First, we used convenience sampling for practical reasons. This means that participation depended on whether there were active facilitators available in the programs during the data collection period. This approach, while common in exploratory studies, restricts the representativeness of the sample and consequently limits the generalization of findings to other contexts or regions.

Although the total sample size of 107 facilitators was considered small for a comparative analysis between two countries, the study’s findings are valuable. The size of the sample was determined by the actual possibilities of access to the programs that the facilitators agreed to participate in, rather than a formal estimate of the universe of facilitators. Moreover, it is challenging to calculate the total size of the target population precisely, as many programs are community-based, depend on volunteers and do not maintain systematic records of their training staff.

The data originates solely from two particular regions. Seville (Spain) and the state of Hidalgo (Mexico). While both regions have well-established digital literacy contexts, they do not reflect the full range of territorial and organizational diversity in both countries. Consequently, the results should be interpreted as representative of the programs analyzed, without assuming that they reflect the totality of digital inclusion initiatives for older adults.

Finally, as future research, it would be desirable to extend the study by using mixed methods, which integrate direct observation of pedagogical practices, deeper qualitative analyses, and more representative samples at the national level. Research that includes other types of programs, regions, and organizational models would also allow for a deeper understanding of the diversity of facilitator profiles and their impact on the digital inclusion of older adults.

6. Conclusions

The results of this study reveal significant variations in the digital competences and ICT skills for teachers of different facilitator profiles. Facilitators with experience (PEERS) and those with gerontology training (YGS) have pedagogical skills that are more suited to the cognitive and emotional needs of older adults. Similarly, specialized training and accumulated experience positively influence the effectiveness of teaching strategies and the integration of digital tools; however, experience alone does not guarantee proficiency in advanced digital skills.

The findings revealed that the links between sociodemographic variables and skills are more significant in young facilitators, particularly in YGS, indicating that integrating training and digital skills enhances effective teaching. In contrast, PEERS showed weaker associations, indicating the need for technological updates. The positive connection between digital, technological, and teaching skills in young facilitators shows the importance of developing all these skills to improve digital learning for older adults.

These findings clearly imply that professional training requires differentiated programs to enable PEERS to update their digital skills and YOS to acquire training in educational gerontology and adapted pedagogical strategies. Understanding these differences between profiles facilitates the design of more effective digital literacy programs. These programs promote autonomy, confidence, and active participation of older adults in the use of technology.