Conceptualizing the Active Ageing Index (AAI): A Systematic Literature

Review of Frameworks and Supporting Digital Tools

Mar

ıa In

es Acosta-Urig

uen

1,3 a

, Juan Pablo Holgu

ın-Carvajal

2 b

, Mateo Sebasti

an Zea-Paredes

Juan Fernando Lima

1 c

, Alexandra Bermeo

1 d

, Javier D

ıaz

3 e

and Ivana Harari

3 f

Computer Science Research & Development Laboratory, Universidad del Azuay, Av. 24 de mayo, Cuenca, Ecuador

Facultad de Medicina, Universidad del Azuay, Av. 24 de mayo, Cuenca, Ecuador

Facultad de Inform

atica, Universidad Nacional de la Plata, Av. 7 N° 776, Buenos Aires, Argentina

ﬂ

Keywords:

Active Ageing, Older Adults, Literature Review, Frameworks, Digital Tools.

Abstract:

Currently, due to the growth of cities, a sedentary lifestyle, and increase in life expectancy, multiple approaches

are being analyzed on caring for the well-being of older adults. As part of these efforts, initiatives have been

developed to measure full aging. The active ageing index (AAI) proposed by the United Nations (UN) is one

of the most relevant measures; it was constructed using several lifestyle features. However, it is relevant to

identify whether the initiative of AAI is being adopted around the world, emphasizing the frameworks and

technological instruments for its execution, thus this work presents a Systematic Literature Review (SLR)

for collecting data related to AAI’s adoption by means of a qualitative analysis. The results reinforced that

the UN index is the one with the greatest impact; however, other countries and organizations are proposing

other approaches. On the other hand, the European Union countries are at the forefront in the development,

speciﬁcally since 2015. A qualitative analysis demonstrated that speciﬁc features have a greater impact on

its calculation, highlighting participation in society, people’s educational achievements, and access to health

services. Finally, the review shows insights for an analysis stage, but not yet the implementation phase.

1 INTRODUCTION

The older adult population is constantly growing, and

is expected to reach 15.9% of the total population by

2050 (United Nations, 2019). Taking this into consid-

eration, it has become important to deﬁne strategies

and tools to support this segment of the population.

Here is where the concept of active aging (AA) comes

into light, which is deﬁned by the World Health Orga-

nization (2002), as the process of maximizing health,

engagement, and safety to improve the overall quality

of life during the ageing process. It enables individu-

als to explore their capacity for physical, social, and

psychological well-being. Furthermore, this concept

strives to ensure appropriate safeguarding, security,

and assistance for elderly individuals when needed.

https://orcid.org/0000-0003-4865-2983

https://orcid.org/0000-0002-6844-3962

https://orcid.org/0000-0003-3500-3968

https://orcid.org/0000-0002-2697-7528

https://orcid.org/0000-0002-4225-3829

https://orcid.org/0000-0001-6350-7739

Various approaches have been proposed around

the concept of active aging that seek to measure it

based on several aspects or features of lifestyle. The

active ageing index (AAI), proposed by the United

Nations (UN) is most relevant approach among them;

however, other organizations and governments have

proposed extensions of AAI, such as the Development

of Self-Active Aging Index (S-AAI) among rural el-

derly in lower northern Thailand classiﬁed by age and

gender (Keeratisiroj et al., 2023), or simply have pro-

posed new methods such as the active aging-wellness

index (AAWB) (Fritzell et al., 2021).

However, AAI is based on main pillars: partici-

pation, health, and security (World Health Organiza-

tion, 2002), which are the basis for the policy making

when referring to older adults. Using these character-

istics within the three pillars. It is necessary to ﬁnd a

way to measure the fulﬁlling or lack of them; then the

measurement of the AAI has emerged as a signiﬁcant

research topic in recent times. This provides insight

into the potential of older adults and assists decision-

makers in enhancing policies to include them promot-

ing healthy living (Dugarova et al., 2017).

276

Acosta-Urigüen, M., Holguín-Carvajal, J., Zea-Paredes, M., Lima, J., Bermeo, A., Díaz, J. and Harari, I.

Conceptualizing the Active Ageing Index (AAI): A Systematic Literature Review of Frameworks and Supporting Digital Tools.

DOI: 10.5220/0012722000003699

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2024), pages 276-283

ISBN: 978-989-758-700-9; ISSN: 2184-4984

There are different technologies and methodolo-

gies that could be used in beneﬁt of the older pop-

ulation and in the creation of an AAI. For instance,

the work by Haque and Afrin (2022), who studied the

construction of an active ageing index speciﬁcally for

Bangladesh, with satisfactory results. The work of Ko

and Yeung (2018), who created a framework for the

population of China, which could assist in the deﬁni-

tion of policies for community based long term care.

And lastly, Mik¸elsone et al. (2023) created a Healthy

Ageing Index using and comparing data from Latvia

and Iceland. Based on these speciﬁcations, the main

question is ”What are the frameworks that have been

implemented for the conceptualization of the active

ageing index?”. It gives opening to a deep analysis

about the conceptualization of the active ageing, in-

cluding the demographic situation, frameworks and

digital tools used in the measurement.

Seeking to address and cover the review, this work

is structured as follows: Section 1 presents the intro-

duction to the topic, followed by the Related work on

Section 2. The methodology which was followed to

perform this systematic literature review is presented

on Section 3, while Section 4 present the obtained Re-

sults and the discussion, it includes the qualitative and

quantitative analysis. Finally, the conclusions are pre-

sented.

2 RELATED WORK

Active ageing refers to the quality of life that an

older adult should have, which includes daily activ-

ities within the home, work and job environment, and

social activities that they are capable to execute. An-

other important area where older adults also are able

to perform is in politics, due to their preparation,

knowledge, and mainly, experience . Therefore, it is

important to search the manner to calculate the AAI

focused on our society, reaching towards the improve-

ment of their quality of life. In this context, there are

different methods to perform this calculation, how-

ever, this research performs a systematic literature re-

view (SLR) of previous works related to methodolo-

gies, tools, and frameworks, to then analyze and in-

terpret the data obtained.

The research developed by S

anchez-Gonz

alez

et al. (2020) identiﬁes a political framework of active

ageing, through the study of strategies and programs

carried out on the subject in Spain, Europe and the

global context. Also, in the study carried out by Pe-

queno et al. (2020), the researchers identify the qual-

ity of life assessment instruments used in population

studies in older adults around the world. In Naah et al.

(2020), the authors identiﬁed 3 key facets of active

ageing: employment, community support and hous-

ing. A gender bias was identiﬁed in active ageing,

with income having a signiﬁcant impact. This study

suggests that policies should incorporate a gender per-

spective and income options for older adults.

Related to literature reviews on this topic, in the

study by Badache et al. (2023), the researchers con-

ducted a SLR about the perspectives of older adults

aged 75 and over on what it means to age successfully.

Summarizing the results, the authors selected 15 stud-

ies of the 4661 proposed for research, as a conclusion

to this, they identiﬁed that theories should continue

to be developed, using the perspectives of understud-

ied populations. In the work developed by Menichetti

et al. (2016), the researchers conduct a review with the

objective of mapping health promotion interventions

aimed at promoting active and healthy ageing among

older adults. As a result, they found that different rec-

ommended interventions promoted for active ageing

are effective in improving health and quality of life,

despite this, no study has undertaken a holistic study

that improves long-term results.

Related to technology, the work by Rocha et al.

(2019), the researchers identify relevant applications

to promote active ageing, with the type of technolo-

gies that have been applied in the studies. As a result,

in these studies they identiﬁed that different types of

detection devices were developed for smart cities to

promote active ageing, which allows older adults to

fully participate and integrate into society. In Berde

and Kuncz (2019), the role of the internet in older

people is focused and increasing the weight given to

internet use when calculating the AAI, and comparing

different weighting systems. Furthermore, this study

recommends including a more sophisticated indicator

on the internet use in the AAI, added to this, they ver-

iﬁed that older citizens of the European Union have

increased their use of the internet, becoming increas-

ingly relevant as basic literacy.

Related to frameworks for the analysis of AAI, in

Xu et al. (2022), the quality of life of the older peo-

ple in China is evaluated under the framework of ac-

tive ageing. For this, they used security, participa-

tion and health information data from various statis-

tical sources, from 2000 to 2016, showing that be-

tween 2005 and 2015 the quality of life improved in

terms of security, participation and health . To im-

prove the quality of life, this study proposes reducing

the socioeconomic gap between regions, strengthen-

ing family support and improving social services for

the elderly.

Another way to analyze the AA is proposed by

Lak et al. (2020), who carried out a study based on the

Conceptualizing the Active Ageing Index (AAI): A Systematic Literature Review of Frameworks and Supporting Digital Tools

277

concept of “active ageing”, where they tried to under-

stand and apply the concept in a more effective way,

for this the researchers identiﬁed 15 key aspects, rang-

ing from personal characteristics to social health, with

this, the researchers brought together these aspects

using a 5P model (person, processes, place, princi-

pal, policy formulation), concluding that it is recom-

mended to apply these aspects when addressing the

topic of active ageing.

Related to features of living environment, the re-

search carried out by Wood et al. (2022), they indi-

cate how human characteristics could support active

and healthy ageing, for this the researchers identiﬁed,

deﬁned facilitators and barriers in various domains,

such as sociocultural, personal, environmental, politi-

cal and economic. The researchers mapped their ﬁnd-

ings with the WHO List of Essential Characteristics

of Age-Friendly Cities (World Health Organization,

2007), highlighting the need and relevance of taking

into account transcultural and migrant communities.

In addition to this, the researchers used the Citizen

Science Evaluation Tool, which was used to rate the

quality of participatory approaches.

Related to the application of the AAI across the

word, the study by Przybysz and Stanimir (2023a)

performed a comparison study between countries of

the European Union (EU), based on a subjective eval-

uation of the activities related to active ageing, for

this, they made use of the database of the European

Social Survey, in order to obtain a result close to real-

ity. Moreover, they developed analyzes based on gen-

der and age groups, as a result of this, they identiﬁed

recurring patterns based on behavior corresponding to

active ageing; also, they were able to verify that these

results were the same in different countries in which

this study was replicated. In Przybysz and Stanimir

(2023b), researchers discuss the importance of active

ageing and how activity in different areas can trans-

late into a better quality of life. This study as a basis

compares the quality of life of older Polish inhabi-

tants with others countries of the European Union to

identify the causes of inactivity. To do this, they de-

ﬁned an original indicator of active ageing, examining

the impact that various activities had on older adults,

in terms of their life satisfaction, using a comparative

analysis and a classiﬁcation method.

In Robbins et al. (2018), they carried out a system-

atic review in order to emphasize the importance of

promoting active ageing and how affordable and scal-

able these can become, through the use of digital ini-

tiatives such as e-health and telemedicine. Therefore,

the researchers demonstrated a wide range of thera-

pies that are available internationally, through an ap-

proach based on community and technological meth-

ods, despite this, the lack of depth of the studies they

carried out resulted in limitations such as the small

number of samples, restricted statistical analyzes and

variability of measurements in the results. Also, the

study indicates that research approaches (technolog-

ical, conventional) should be included, in controlled

trials, with the purpose of improving the quality of

the information used to educate policymakers, health

professionals, communities and individuals about ac-

tive ageing efforts.

3 METHODOLOGY

This paper follows the guidelines proposed by

Kitchenham and Charters (2007), which is a system-

atic and iterative process for literature reviews, based

on three stages: planning, conducting, and reporting

the results. The planning stage is focused on deﬁne

the protocol including the research question and sub-

questions (RQs), databases, inclusion and exclusion

strategies, and data extraction criteria. The execu-

tion stage, where the primary studies are collected and

coded, the initial number of articles are decreased due

to the application of inclusion and exclusion strate-

gies. And ﬁnally, the reporting stage, which is pre-

sented by means of charts and descriptive analysis

addressing the discussion of the ﬁndings, this stage

is shown in the section of results.

3.1 Planning the Review

The systematic review protocol is the base to perform

a successful systematic literature review, therefore, in

this subsection, the main features related to the proto-

col are shown. As a ﬁrst activity, a research question

needs to be estblished, for the purpose of this work

is ”What are the frameworks that have been imple-

mented for the conceptualization of the active ageing

index?”, then, there is needed to deﬁne the research

sub-questions (RQs), which will help to address the

main research question. Following are presented each

of the research sub-questions:

• RQ1. What frameworks, tools and applications

have been implemented to capture, process, and

analyze information related to the AAI?

• RQ2. What conceptualization methods have been

applied in research on the AAI?

• RQ3. What is the state of research in the ﬁeld of

frameworks used in the conceptualization of the

AAI?

Once the RQs have been deﬁned, it is necessary to

deﬁne the digital databases (digital libraries) which

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278

Table 1: Data extraction criteria.

RQ Extraction criteria Collected features

RQ1

EC01: Framework active aging-wellness index (AAWB), active aging index AAI), self-active

aging index(S-AAI), other.

EC02: Analysis type development, research, other.

EC03: Framework

variables

age, sex. region, internet service, academic level, independent life, health

services, ﬁnance indicators, society participation, other.

EC04: Screaning

instruments

surveys, interviews, statistical data, historical data, others.

EC05: Analysis

features

age range, region classiﬁcation, virtual environments, seg, others.

EC06: Analysis

process

mathematical models, mapping of local policies, Djurovic’s coefﬁcient,

others.

RQ2

EC07: AAI health surveys, participation surveys, security surveys.

EC08: AAWB social indicators, application domain.

EC09: S-AAI WHO’s frameworks, age and gender classiﬁcation, surveys, explorative

factorial analysis, others.

EC10: Data collection UE’s income and lifestyle survey (EU-SILC), Lifestyle European survey

(EQLS), prior projects.

RQ3

EC11: Phase(s) in

which studies are based

analysis, design, implementation, testing.

EC12: Type of

validation

proof of concepts, survey, experiment, quasiexperiment, prototype, case

study, others.

EC13: Approach scope industry, academy.

EC14: Methodology new, extension.

EC15: Country

EC16: Year

allow to collect a high quantity of primary studies

related to the main topic; these libraries were se-

lected because they have technical and medical arti-

cles. Each library has different ways to obtain the

articles, such as ﬁlters, reports, and search strings.

The search strings are the best approach to get articles

based on a query, the query is a set of words (quo-

tation marks for literal searches), logical connectors

(AND, OR, NOT), and wildcards (asterisk as word

competition) that allow a user to reﬁne a search of ar-

ticles. Table 2 shows the search string for each library,

and the quantity of articles returned by itself.

Table 2: Search string results by library.

Library Search string Result

WoS

”active ageing”

AND (index OR framework)

211

Scopus

”active ageing”

AND (index OR framework)

486

Embase

”active ageing”

AND (index OR framework)

159

The deﬁnition of strategies to guarantee that the

selected primary studies is the key to carry out a

proper systematic literature review, the initial strate-

gies are part of the exclusion and inclusion criteria,

these aspects allow to deﬁne whether a study will be

part or not of the analysis. In this work, those were

deﬁned as follows:

• Inclusion Criteria: observational studies, ran-

domized clinical trial, randomized controlled

trial, language (only English, Spanish, Por-

tuguese).

• Exclusion Criteria: books, book chapters, work-

shops, reviews or systematic reviews, duplicate

reports of the same study in different sources,

short works with less than 5 pages.

Data extraction strategy is based on providing a

set of data extraction criteria that allows to systemati-

cally collect data, in addition, mark answers for each

criterion were provided to facilitate the data collec-

tion process. Also, metadata will be collected from

the sources, such as: conference, magazine, article,

digital library, year of publication, country of origin

and authors. Table 1 shows the extraction criteria of

the primary studies, classiﬁed by the research ques-

tion, with an identifying code and its classiﬁcation.

Conceptualizing the Active Ageing Index (AAI): A Systematic Literature Review of Frameworks and Supporting Digital Tools

279

3.2 Conducting the Review

In this phase, the activities declared in the planning

stage are executed with the following structure: col-

lecting the primary studies, applying the inclusion and

exclusion criteria, executing the data extraction strat-

egy, and ﬁnally, the data synthesis (see results and dis-

cussion). To improve the trace among each step, ini-

tially, in each digital library, the articles were ﬁltered

using the search string proposed above, after that each

article was stored for revision, with a total of 446 ar-

ticles obtained from this initial search.

In the selection of primary studies, the articles that

were relevant were selected by reading their abstract

and title, using the platform ”Covidence”, which is

a platform for improving and tracing a SLR. In addi-

tion, the exclusion and inclusion criteria were applied,

which helped for the selection of the required articles.

Also, a quality assessment for each article was done,

it was rated with ”yes” for any research that agrees

with the topic being addressed, otherwise it was rated

with ”no”, resulting in 149 articles chosen for analy-

sis. Figure 1 shows each stage and number of articles

for each stage.

Begin

Identification

End

Screaning

Elegibility

Included

446 articles

149 articles

158 articles

430 articles

Figure 1: Stages and number of articles in stage 3.2.

For data extraction by means of each extraction

criteria (EC), the studies were classiﬁed with 0 and 1

for each criterion. The ﬁrst step was to tabulate the

date of publication, digital library, country of origin

and the criteria for data extraction. Following this, a

count and cross-relation between variables was car-

ried out, thus allowing a demographic study, trends

and new lines of research to be obtained.

4 RESULTS AND DISCUSSION

The results of this review are structured on 3 stages:

Demographic analysis, which is focused on under-

standing when and where the AA initiative is being

adopted. After that, a quantitative analysis, which al-

lows to identify and represent the reality of each ex-

traction criteria. And ﬁnally, qualitative analysis, fo-

cused on answer the main research questions.

4.1 Demographic Analysis

The demographic analysis was tackled where primary

studies show that 56 countries are developing research

related to the active ageing. The Figure 2 shows a

summary of the top 20 countries and their percentage

of studies, which were determined with the data col-

lected from the RSL. Then, the descriptive analysis

shows that Spain, United Kingdom, and China are the

top three countries where this topic and its research is

widely addressed due to the amount of articles. On

the other hand, even though the active ageing is a re-

ality in some countries, the true is that the rest 36 of

countries, out of the ﬁgure, are tacking the quarter of

primary studies collected showing a less than one per-

cent for each of them.

Figure 2: Top 20 countries and percentage of studies related

to active ageing.

Regarding the years when the initiative was de-

veloped, Figure 3 shows that, starting in 2020, the

trend tends to increase in terms of publications of ac-

tive ageing, being this time in which the most studies

were carried out.

Figure 3: Trend of adoption of AA over the years.

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280

4.2 Quantitative Synthesis

For this subsection, the analysis quantitative is shown

by means of text, the percentage for each feature (re-

lated to the extraction criteria) is represented by one

or two representative article(s).

EC1. Framework: there are 1% of studies re-

lated to the topic of the Active Ageing Wellbeing In-

dex (AAWB) [SA106]; however, for the Active Age-

ing Index (AAI) there are 43% of studies that are

related to that topic, in addition to this, 55% of the

other frameworks were noted, highlighting [SA03],

[SA14].

EC2. Type of framework: On the one hand, 35%

of the studies are related to the use of the type of

analysis framework, having as important examples

[SA02], [SA04] and [SA08]. Furthermore, 11% re-

garding the types of frameworks of conceptual scope,

relating studies such as [SA07], [SA21]. Added to

this, there is 54% that refers to frameworks related to

research [SA148], [SA149], [SA150]. Lastly, there is

only a 1% for studies with other types of frameworks

[SA23].

EC3. Variables: 17% of studies related to

age, highlighting studies such as [SA154], [SA158].

Added to this, 9% for studies related to the region, the

most representative being [SA135], [SA142]. Also,

there are a 14% of studies that focus on the item

about sex [SA113], [SA112]. For employment rates,

a percentage of 7%, covering investigations such as

[SA145], [SA138]. For Educational Achievement the

9% [SA158], [SA148]. For Access to health services,

7%, with research such as [SA141]. In relation to

ﬁnancial indicators, 6% [SA136]. Independent liv-

ing 7% [SA149], participation in the company 10%

[SA142].

EC4. Tools: Surveys 34% [SA158], Statistics 7%

[SA154], Historical data with 5% [SA156], and Other

with 34% [SA157].

EC5. Analysis: Age ranges with 29% [SA117],

[SA111]. Virtual Environment 3% [SA116], Sex with

26% [SA112], Other 22% [SA110].

EC6. Process: Structural Equations for data anal-

ysis with 5% [SA144], Map local policies for each

region with 6% [SA150], coefﬁcients calculated by

Djurovic formulation with 2% [SA74], and Other

with 87% [SA69 ].

EC7. AAI: Health surveys with 39% [SA122],

Participation surveys with 33% [SA128], and Safety

surveys with 28% [SA133].

EC8. AAWB: with a percentage of 49% [SA144],

and domains with 51% [146].

EC9. S-AAI: Framework approved by the WHO

with 50% [SA126], Classiﬁcation by age and gen-

der for the study 24% [SA127]. Questionnaires, 16%

[SA135], Exploratory factor analysis, 8% [SA71].

Another with 1% [SA121].

EC10. Data Collection: EU Survey of Income

and Living Conditions (EU-SILC) with 11% [SA48],

[SA13]. Based on projects previously carried out by

organizations or researchers, 69% [SA03]. and Other

with 1% [SA68].

EC11. Phase(s) in which the studies are based:

The most concurrent study phase was the analysis

phase with a percentage of 72%, followed by the test

study phase with a percentage of 11%.

EC12. Type of Validation: The types of valida-

tion most used in the study were, ﬁrst, experimenta-

tion with a percentage of 29%, followed by proof of

concepts with a percentage of 22%, and in third place

was the type of validation. of case study with a total

percentage of 21%.

EC13. Approach scope: It has been identiﬁed that

7% correspond to an industrial scope and the remain-

ing 93% refers to academic scope studies.

EC14. Methodology: 38% of the studies imple-

ment a new methodology and the remaining 62% are

the studies that are based on previous studies.

4.3 Qualitative Synthesis

The extraction criteria (EC), and their collected fea-

tures from the 152 studies were classiﬁed, based on a

heatmap, which was created answering each research

question (RQ) formulated in the methodology, high-

lighting the following statements:

In the case of RQ1, a comparison between EC3

and EC1, where for the AAI framework variables

such as age, sex and participation in society were

used, in addition to this, the use of another type of

framework is detailed which presented the frequent

use of variables such as , age, other and sex.

Figure 4: Evaluating the RQ1 by means of EC1 y and EC3.

In the case of RQ2, the comparison was made be-

tween EC3 and EC11, where it could be noted that

Conceptualizing the Active Ageing Index (AAI): A Systematic Literature Review of Frameworks and Supporting Digital Tools

281

in terms of the studies that focused on the analysis

study phase, they used more the variables that have

been referents regarding the socio-economic charac-

teristics. Demographic features such as: age and sex,

the graph also details the use of other types of vari-

ables, in addition to those already used in the studies.

Figure 5: Evaluating the RQ2 by means of EC11 y and EC3.

In the case of RQ3, EC1 and EC11 were com-

pared, where it can be noted that the tendency of the

studies has indicated the use of other types of frame-

work with regard to the present question and with a

tendency to be in the analysis study phase, followed

by this, another framework that has been implemented

is the active aging index (AAI), in which it was found

that the most used study phase was also the analysis

phase.

Figure 6: Evaluating the RQ3 by means of EC11 y and EC1.

5 CONCLUSIONS

In the context of this study, we have focused on an-

swering three research questions formulated for this

research. Subsequently, these were tackled by means

of quantitative and qualitative analysis. Thus, in re-

lation to the ﬁrst research subquestion, it has been

identiﬁed that the framework that has been used the

most was the one that was related to the Active Ag-

ing Index (AAI), in addition to other types of frame-

works used for the other investigations, all of them in

the same amount of AAI. For the RQ2, it was found

that the studies which were in the analysis phase, the

Sociodemographic variables used were age, sex, and

also, the use of other types of variables is highlighted.

Regarding to subquestion 3, we have that in the sense

of the frameworks used, the majority are related to the

analysis study phase, focusing especially on the use of

frameworks such as AAI, among others.

It can be concluded that the frameworks that have

been dealt with the most in the selected studies are

related to other types of frameworks. In addition, it

was found that apart from this, one of the most used

frameworks was the AAI. Many of these studies were

related to the use of demographic variables such as

age, sex and most of them were related to studies re-

lated to the analysis study phase, thus answering the

questions formulated above. Moreover, the study is

outlined so that in the future a framework related to

our environment will be implemented based on the

present research.

Moreover, after executed the systematic literature

review, it was determined that, around the world, there

have been identiﬁed many different types of indexes,

which are used to calculate the level of active age-

ing among older adults. However, once studiyng the

used variables, it has been clear that they constantly

repeat across all found indexes. Therefore, said vari-

ables could be deﬁned to, further, create and apply an

active ageing index adapted to a latinoamerican real-

ity.

ACKNOWLEDGEMENTS

This research is supported by Vice-rectorate for Re-

search of Universidad del Azuay contestable grant

2023-0130. In addition, the authors wish to thank the

teachers from the Facultad de Inform

atica of the Uni-

versidad de la Plata by their expertise on the ﬁeld.

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APPENDIX

The list of articles that were used in this literature

review can be found at the following URL: https:

//drive.google.com/file/d/1--XzV8Gi8wmLzvzle

NXTYk-RYI8bw7Ex/view?usp=drive

link.

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