Activities of daily living (ADL) encompass essential tasks that individuals must perform independently to function in daily life.¹⁾ These assessments cover a range of routine physical activities, including eating, dressing, bathing, transferring, toileting, and personal hygiene.²⁾ Evaluating an individual’s capacity to perform ADLs is crucial for determining their functional independence, overall health, and potential care needs, particularly among older adults or people with disabilities.^3,4)

This field has attracted considerable attention for several reasons. First, the increasing proportion of older adults worldwide has made the maintenance and improvement of functional independence a pressing social concern.⁵⁾ Second, the growing number of people with chronic illnesses and disabilities underscores the importance of establishing robust systems to assess and support their functional abilities in everyday activities.^6,7) Furthermore, as healthcare systems evolve toward a prevention-oriented and patient-centered model, ADLs have emerged as central indicators for guiding personalized treatment and rehabilitation.⁸⁾ Advancements in digital health, such as wearable devices, artificial intelligence (AI), and remote monitoring technologies, also support the collection and analysis of ADL data.^9,10) For instance, these innovations enable real-time monitoring, personalized interventions, and comprehensive data analysis, which enhance the accuracy and efficiency of ADL assessments.¹⁰⁾ As a result, ADLs have a crucial role in enhancing quality of life and enabling effective healthcare delivery, making their assessment a topic of continued interest.¹¹⁾

This study aims to provide a comprehensive review of ADL assessment methods, highlighting their evolution, current challenges, and potential for technological integration. By addressing these issues, we aim to propose a framework for the future development of ADL tools that support individualized care plans and improve the quality of life for various populations.

ADL includes a range of everyday tasks necessary for individuals to maintain their independence and quality of life.¹²⁾ ADL refers not only to basic self-care but also to functional activities that promote social engagement and overall well-being.¹³⁾ This idea extends beyond basic survival and represents a set of skills essential for autonomous and fulfilling living in society.¹⁴⁾ ADL is typically categorized into three core groups: basic ADL (BADL), instrumental ADL (IADL), and extended ADL (EADL)/higher-order ADL.^15,16)

BADL involves fundamental self-care tasks that individuals must complete independently each day.¹⁷⁾ These essential activities, including bathing, dressing, eating, transferring, toileting, and managing continence, are vital for physical well-being and daily bodily functions.^17,18) BADL serves as a primary measure of functional independence, particularly for older adults, individuals undergoing rehabilitation, and those with chronic health issues.^19,20) Evaluating BADL provides valuable insights into a person’s current abilities, supports the development of effective rehabilitation goals and treatment plans, and assists in forecasting the likelihood of recovery and return to independent living.²¹⁾ Additionally, BADL assessments clarify the level of assistance an individual may need with daily activities, helping outline the necessary scope of care services.²²⁾

The term “IADL” involves more complex tasks that support independent living within both home and community settings.²³⁾ Requiring greater cognitive function and advanced skills than BADL, IADL is a crucial indicator of an individual’s social independence and overall quality of life.²⁴⁾ Core IADL activities include meal preparation, shopping, housekeeping, transportation, financial management, communication, medication management, and engaging in leisure activities.²⁵⁾ IADL, which is closely tied to cognitive health, serves as an important marker for early dementia detection and is an indicator of social independence.²⁶⁾ IADL assessments inform personalized rehabilitation plans and care services and can support policy efforts aimed at improving quality of life and fostering social participation among older adults in aging societies.²⁷⁾

EADL encompasses higher-level complex tasks that individuals undertake to fully engage in society and enhance their life satisfaction.²⁸⁾ Unlike BADL and IADL, EADL emphasizes activities that are integral to fulfilling social roles, achieving personal growth, and improving the quality of life.²⁹⁾ Core aspects of EADL include occupational tasks, leisure and hobbies, social interactions, cognitive and learning activities, psychological and spiritual development, and involvement in the community.²⁸⁾ Evaluating EADL provides a comprehensive picture of an individual’s social, mental, and physical abilities, supporting the design of individualized programs aimed at enhancing quality of life.³⁰⁾ Additionally, assessing EADL can help identify and manage mental health concerns, such as isolation and depression, at an early stage. This information can also contribute to policies that support active social participation among older adults within aging populations.³¹⁾

The three categories of ADL (BADL, IADL, and EADL) serve as a framework for assessing the daily activities crucial for independence and overall well-being.^17,28,32) By evaluating an individual’s ability to perform these activities independently, the necessary level of support can be identified, guiding the development of appropriate care or rehabilitation plans. Together, these categories relate closely to physical, cognitive, and social health, exerting a substantial influence on the quality of life and social involvement.

In summary, the three ADL categories (BADL, IADL, and EADL) represent varying degrees of self-care, independence, and social engagement, collectively forming the basis for an individual's overall quality of life and social involvement.

In this context, ADL is of considerable clinical and research significance. They can be used to assess an individual’s medical care requirements, capacity to maintain fundamental daily living activities, formulate rehabilitation objectives, and develop care plans.¹¹⁾ Additionally, ADL evaluation contributes to individuals’ life satisfaction and social inclusion.³³⁾ ADL assessments are widely used in fields, such as medicine, nursing, rehabilitation therapy, social services, and community support programs.^34,35) They are instrumental in assessing abilities related to mental health, social psychology, gerontology, and vocational rehabilitation.^36,37) For older adults, ADL assessments help determine support requirements by evaluating performance in BADL and IADL, identifying early cognitive decline through reduced IADL capabilities, and assessing fall risk.^38-40) By comprehensively evaluating an individual’s ability to perform these activities, clinicians can identify the areas of need, implement targeted interventions, and monitor progress over time. As technology continues to advance, the integration of digital tools and data-driven approaches into ADL assessments holds great potential for improving the accuracy, efficiency, and personalization of care.

A range of tools are available today to assess ADL, with some of the most commonly used for BADL being the Katz Index, Barthel Index, Functional Independence Measure (FIM), and Psychogeriatric Dependency Rating Scale (PGDRS).

The Katz Index uses a binary scoring method to evaluate each activity for independence.¹⁷⁾ This tool includes six essential tasks that allow for a quick and straightforward assessment; has been widely adopted in clinical settings with studies supporting its reliability and validity.⁴¹⁾ Additionally, the Katz Index is easy to administer to healthcare providers as it requires no specialized equipment or training.⁴²⁾ However, the tool has limitations in tracking changes in patients with milder conditions or those recovering from illness, and may not adequately capture cultural variations in task performance.^43,44) For example, the Katz Index has been validated in neuropathological studies, which demonstrated high reliability for assessing BADL retrospectively, with a strong Cronbach's alpha (α=0.93) and standardized item-total correlations exceeding 0.90.⁴⁵⁾ While some item redundancy (correlations >0.85) was observed, likely owing to informant bias, the scale remains a reliable tool for evaluating ADL performance even in individuals with cognitive decline.⁴⁵⁾ Subsequent revisions should address multicollinearity to enhance precision.⁴⁵⁾

The Barthel Index assigns scores to 10 items, and the total score reflects overall independence.⁴⁶⁾ This tool is frequently used in rehabilitation settings as an effective method of monitoring changes in function and recovery.⁴⁷⁾ Numerous studies have validated the reliability and accuracy of the Barthel Index.⁴⁸⁾ However, their use in geriatric settings may lead to inconsistent ratings, particularly when conducted by untrained nursing staff.⁴⁹⁾ The assessment process is also more time-intensive than the Katz Index and may be less reliable for cognitive aspects.^50,51) Proper training of raters is essential for accurate assessments. For instance, the present study employed Rasch analysis to assess the suitability of the Barthel Index for evaluating BADL in patients with dementia. The study's key findings revealed that the Barthel Index is compromised by issues such as person-item mistargeting, redundant and misfitting items (e.g., "mobility" and "stairs climbing"), and cultural measurement bias. The study further underscored the impact of specific neuropsychiatric symptoms, such as disinhibition and agitation, particularly Barthel Index item scores, thereby emphasizing the necessity for dementia-specific ADL assessment tools. The authors recommended refinement of the Barthel Index to address these limitations, particularly within the context of dementia care settings.⁵²⁾

The FIM covers 18 items, including physical and cognitive functions, and offers a comprehensive assessment of an individual’s abilities.⁵³⁾ As a standardized tool, it is suitable for various clinical environments.⁵³⁾ However, the extensive number of items requires more time, and the scoring process can be challenging for new users, making the rater training essential.^54,55) We et al.⁵⁶⁾ developed and evaluated as a home-based rehabilitation management program for elderly stroke patients using the FIM score as a guide. A controlled trial compared 290 participants with the intervention group using FIM-based tailored exercises and the control group following standard home rehabilitation instructions. The results showed significant improvements in motor function, self-care ability (Barthel Index), and cognitive function (Mini-Mental State Examination) in the intervention group at 4 and 8 weeks, with lower levels of disability (modified Rankin Scale scores). These results support the efficacy of the FIM-guided approach for personalized stroke rehabilitation.

The PGDRS is designed to assess levels of functional dependence in older adults, particularly those with psychiatric or cognitive conditions such as dementia.⁵⁷⁾ This scale is effective in evaluating physical, psychological, and social dependencies through assessments based on observations and reports conducted by trained professionals, including nurses, occupational therapists, and doctors.^58,59) The PGDRS includes two subscales: physical dependency (PGDRS-P) and behavioral dependency (PGDRS-B). The PGDRS-P assesses physical independence and evaluates daily tasks, such as bathing, dressing, eating, transferring, and toileting.⁶⁰⁾ Conversely, PGDRS-B focuses on identifying behavioral issues associated with dementia or other mental health conditions, covering factors such as social interactions, anxiety, aggression, and behavior-related dependencies.⁶¹⁾ While PGDRS-P does not address cognitive or behavioral issues, PGDRS-B has limitations in evaluating physical function. Thus, using both scales together provides a more complete assessment of the patient’s functional and dependency status. For example, Adams et al.⁵⁷⁾ evaluated the PGDRS to determine its factor structure and assess its utility in measuring the efficacy of antipsychotic treatments for dementia-related behavioral and psychological symptoms (BPSD). Factor analysis identified four core dimensions—disruptive overactivity, thought/communication disorder, interpersonal aggressiveness, and destructiveness—which accounted for approximately 60% of the total variance. Among the medications tested, olanzapine showed superior efficacy in reducing interpersonal aggressiveness compared with haloperidol and risperidone, although no significant differences were observed for other factors. These findings confirmed that the PGDRS is a reliable multidimensional tool for assessing BPSD and tailoring treatment strategies for dementia care.

Table 1 summarizes the key features of BADL assessment tools.

Several tools are available for evaluating IADL, including the Lawton-Brody IADL Scale, Direct Assessment of Functional Abilities (DAFA), Assessment of Motor and Process Skills (AMPS), and Alzheimer’s Disease Cooperative Study-activities of daily living scale (ADCS-ADL).

The Lawton-Brody IADL Scale includes eight tasks that measure the ability to perform activities independently, such as telephone use, meal preparation, shopping, housework, transportation, laundry, financial management, and medication management.^62,63) It is known for its simplicity and ease of administration, and widely used to evaluate functional ability in older adults and reflects gender differences in activity performance.^64-66) However, adjustments to the scale may be necessary in cultures where activity roles vary by gender, as this can influence the responses.⁶⁷⁾ Additionally, because the scale relies on self-reporting, it may be subject to bias and may not effectively differentiate between higher and lower levels of functioning.²⁷⁾ For individuals with cognitive impairment, self-reporting may limit the accuracy.⁶⁸⁾ Some studies have sought to address the limitations of the previous research. Siriwardhana et al.⁶³⁾ adapted and validated the Sinhala version of the Lawton IADL Scale to assess functional independence among older adults in Sri Lanka. A psychometric evaluation involving 702 participants revealed excellent internal consistency (Cronbach's alpha=0.91) and substantial inter-rater reliability (intra class correlation [ICC]=0.57–0.91). Factor analysis confirmed the scale’s unidimensional structure (comparative fit index [CFI] = 0.98), and moderate convergent validity was demonstrated through its correlation with the Barthel Index (ρ=0.61). The presence of significant score variations across age groups supports the divergent validity. The Sinhala Lawton IADL scale has been demonstrated to be a reliable and valid instrument that provides an effective method for evaluating instrumental activities of daily living in aging populations, for both research and healthcare applications.

The DAFA assesses functional skills directly through tasks that mimic real-life scenarios, ensuring reliability and addressing activities with significant cognitive demands.⁶⁹⁾ However, the assessment process can be lengthy, potentially causing fatigue or stress in the patients.⁶⁹⁾ The DAFA also requires specific materials and settings, often necessitating a clinical environment, and its effectiveness depends largely on the expertise of the assessor.⁶⁹⁾ In a study of 43 participants, the DAFA demonstrated excellent reliability (r=0.95, p<0.01) and revealed a significant overestimation of abilities in individuals with dementia, particularly for tasks requiring awareness and comprehension. The informant ratings were more accurate with minimal underestimation.⁶⁹⁾ The DAFA’s ability to objectively assess functional impairment makes it a valuable tool, particularly for identifying preclinical disabilities in dementia. It is less prone to bias than self-reporting, ensuring an accurate assessment of functional status.

The AMPS examines a person’s ability to perform ADL by analyzing motor and process skills, which support detailed assessment and the creation of tailored intervention plans.⁷⁰⁾ However, the AMPS requires trained assessors, is expensive and time-intensive, and may not be fully adaptable across different cultural contexts.⁷¹⁾ Darragh et al.⁷¹⁾ examined the influence of familiar (home) versus unfamiliar (clinic) environments on IADL performance in adults with acquired brain injury. Using the AMPS, researchers assessed both motor and process skills in these settings. The key findings showed no significant differences in motor skills between home and clinical settings, but process skills were significantly better in the home setting. Scatter plot analyses revealed meaningful performance differences for a subset of participants, highlighting the role of environmental familiarity in task performance. These findings suggest that rehabilitation should prioritize home-based assessments and therapy to ensure accurate assessments and functional improvements tailored to real-life settings.

ADCS-ADL was designed to measure daily functional independence in people with dementia, including those with Alzheimer’s disease, and to track disease progression.⁷²⁾ Key areas of assessment included money and medication management, meal preparation, phone use, and shopping, with ratings based on feedback from the primary caregiver.⁷³⁾ However, this tool relies on subjective caregiver assessments, is less effective in identifying small changes, and does not account for cultural differences or behavioral symptoms.^74,75) To address these limitations, using additional assessment tools in combination with the ADCS can provide a more comprehensive evaluation. For instance, ADCS-ADL was validated in a study involving 769 patients with amnestic MCI over 36 months. The scale exhibited strong reliability, as evidenced by a Cronbach’s alpha of 0.64 at baseline and 0.87 at month 36, and demonstrated good test-retest reliability, as indicated by an ICC of up to 0.73. The scale effectively distinguished between different levels of disease severity, thereby demonstrating known-group validity and exhibiting moderate-to-strong correlations with related clinical measures, such as the Clinical Dementia Rating Sum of Boxes (CDR-SB), thereby supporting its convergent validity. This scale demonstrates sensitivity to detecting functional changes over time, indicating responsiveness to disease progression. These findings confirm that ADCS-ADL-MCI is a reliable and valid tool for assessing functional abilities in mild cognitive impairment (MCI) populations, making it suitable for clinical and research applications.

Table 2 highlights the key features and scoring methods of prominent IADL assessment tools discussed in this study.

Several tools are available for evaluating EADL, including the Nottingham Extended Activities of Daily Living Scale (NEADL), Frenchay Activities Index (FAI), Community Integration Questionnaire (CIQ), Reintegration to Normal Living Index (RNLI), Assessment of Life Habits (LIFE-H), WHO Disability Assessment Schedule 2.0 (WHODAS 2.0), and Occupational Self-Assessment (OSA).

The NEADL was designed to assess EADLs in older adults and individuals recovering from stroke.⁷⁶⁾ It includes 22 items, each scored based on the task performance frequency.⁷⁷⁾ NEADL is widely used to evaluate functional independence and social involvement.⁷⁷⁾ However, as a self-report tool, it may introduce response bias, and certain items may lack relevance in varying cultural or social contexts.^78,79) Additionally, those with cognitive impairments might struggle with accurate self-reporting.⁸⁰⁾ The NEADL scale was examined in patients with stroke to assess its validity, reliability, and concordance with other scales, including the Barthel Index and FAI.⁸⁰⁾ The NEADL exhibited a symmetrical distribution devoid of substantial floor or ceiling effects, a distinction from the Barthel Index and FAI. The NEADL demonstrated stronger concordance with the Barthel Index than with the FAI, thereby substantiating its capacity to appraise EADL in conjunction with fundamental ADL. The predictors of functional outcomes included stroke severity, as quantified by the National Institutes of Health Stroke Scale (NIHSS), and cognitive status, as gauged by the Abbreviated Memory Test. The NEADL was found to be a sensitive and reliable instrument, particularly because of its capacity to assess EADL. Its integration with acute-stage NIHSS scores may facilitate patient outcome prediction and rehabilitation planning.

The FAI was primarily developed to assess the social and leisure activities of stroke survivors.^81,82) It consists of 15 items that examine the frequency of engagement in activities over the past three months, covering physical tasks, instrumental activities, and certain aspects of disability.⁸³⁾ This tool offers valuable insights into activity participation and aids in setting rehabilitation goals.⁸⁴⁾ However, it was specifically designed for patients with stroke, which limits its generalizability to other populations.⁸³⁾ The FAI is a reliable instrument for evaluating lifestyle activities in patients with stroke.⁸⁴⁾ In conjunction with other assessment tools such as the Barthel Index, the FAI provides a comprehensive evaluation of daily activities. In a study involving 45 stroke patients, the FAI exhibited excellent inter-rater reliability, with an overall ICC of 0.90 (95% confidence interval, 0.82–0.94) and substantial agreement (kappa>0.60) on 11 of its 15 items. However, the reliability of three items—namely, "local shopping," "social occasions," and "actively pursuing a hobby"—was suboptimal owing to the ambiguity of the provided scoring instructions. This study underscores the FAI’s efficacy in outpatient rehabilitation contexts and puts forward recommendations for the refinement of scoring guidelines, to enhance its consistency and clinical relevance.

The CIQ assesses the degree of community integration in patients with traumatic brain injury (TBI) by measuring social participation and role fulfillment across 15 items.⁸⁵⁾ The CIQ has been widely used by researchers and healthcare providers to assess reintegration into society.⁸⁵⁾ Nonetheless, as it was developed with TBI patients in mind, it may not be suitable for other groups, and there is a risk of varied interpretations among patients owing to subjective question phrasing.^86,87) Additionally, the CIQ demands cognitive skills to understand and respond to complex items, which may affect the reliability of responses for correlation analysis.^88,89) Gerber et al.⁸⁹⁾ assessed predictors of community integration and health-related quality of life (HRQoL) in individuals with acquired brain injury (ABI) using the CIQ. The results indicated that the Disability Rating Scale (DRS) was the strongest predictor of community integration and HRQoL. However, the CIQ exhibited limitations, including insufficient evaluation of cognitive and emotional aspects and reliance on self-reported data. To address these limitations, this study proposes a two-pronged approach: first, the incorporation of additional measures to capture cognitive and emotional factors; and second, the enhancement of the CIQ’s validity through cultural adaptation. These findings underscore the necessity of targeting both physical and psychosocial factors in rehabilitation to enhance the integration and quality of life of ABI patients, ensuring a more comprehensive assessment of community reintegration.

The RNLI measures an individual’s reintegration into daily life after illness or disability, using items that assess social involvement, physical mobility, and recreational activities.⁹⁰⁾ This scale includes 11 items that cover social, psychological, and physical dimensions based on patient self-reports and provides a quick assessment of the quality of life.^91-93) While the RNLI is a valuable measure, it can be subject to self-reporting biases, lacks specificity in certain areas, and may not account for cultural differences. Therefore, it is often best used alongside other objective tools.^90,94) The present study focuses on the cross-cultural adaptation and validation of the RNLI for Igbo-speaking individuals with mobility disabilities in Southeast Nigeria.⁹⁴⁾ The study adhered to the guidelines established by the American Association of Orthopaedic Surgeons for adapting the English version of RNLI into Igbo. The validation results demonstrated excellent concurrent validity, as indicated by correlation coefficients ranging from 0.81 to 0.95, and internal consistency, as indicated by Cronbach’s alpha of 0.84. These findings suggest that the tool is reliable in this cultural context. Principal component analysis revealed two key domains thereby ensuring structural validity. The adapted RNLI is a valuable and reliable tool for assessing community reintegration in Igbo-speaking populations, emphasizing the importance of culturally appropriate instruments for disability rehabilitation.

The LIFE-H measures life habits and social participation across 12 domains, assessing both performance and satisfaction levels.⁹⁵⁾ It is a comprehensive tool suitable for individuals across different age groups with diverse types of disabilities, making it useful for intervention planning to enhance the social engagement of people with disabilities.^96-98) However, the assessment process is time-consuming and may lead to fatigue and reduced patient attention.⁹⁵⁾ The LIFE-H is a valid and reliable instrument for the assessment of social participation among individuals with physical disabilities.⁹⁷⁾ Its strong test-retest reliability (ICC=0.71–0.95) and adequate concurrent validity with the Barthel Index are notable findings in this regard. However, the administration time of LIFE-H is a significant limitation, as it can lead to reduced attention and engagement, particularly in participants with cognitive or physical fatigue. To address this challenge, this study proposes a series of recommendations, including simplification of the assessment process through the prioritization of key items and implementation of adaptive testing methods to minimize the respondent burden. Additionally, the integration of interactive features into the digital version of the tool enhances participant engagement and streamlines data collection. Despite these limitations, the LIFE-H remains a crucial instrument for the evaluation of social participation, with the potential for further improvements to enhance its efficiency and usability.

The WHODAS 2.0 is an internationally standardized instrument that evaluates health conditions and disability across 36 items divided into six domains, including interpersonal interactions, cognition, self-care, life activities, mobility, and participation.⁹⁹⁾ WHODAS 2.0 was designed for cross-cultural and multilingual adaptability, enhancing its applicability.⁹⁹⁾ However, this requires assessor training and a structured system for data handling and analysis, particularly in large populations.^100,101) For example, the Functioning Disability Evaluation Scale-Adult Version (FUNDES-Adult), derived from the WHODAS 2.0, was developed for use in Taiwan’s disability evaluation system to assess activity limitations and participation restrictions.¹⁰⁰⁾ The study validated FUNDES-Adult’s reliability (Cronbach's alpha, 0.89–0.97) and its five-factor structure for performance and capability dimensions, encompassing cognition, mobility, self-care, participation, and life activities. Notwithstanding its strengths, the instrument encountered limitations, including substantial ceiling and floor effects in certain domains as well as deficiencies in responses for culturally sensitive items. To address these concerns, the authors underscore the necessity of enhanced data management systems, rigorous evaluator training programs, and adaptations for diverse cultural contexts. The FUNDES-Adult demonstrates its utility; however, further research is imperative to enhance its usability and accuracy in large-scale disability assessments.

Finally, OSA assesses an individual’s ability to perform roles and the perceived importance of these roles.¹⁰²⁾ It is frequently used in client-centered occupational therapy and helps design personalized interventions.^103,104) However, interpreting subjective results objectively for intervention purposes requires experience, and accurate assessment may be challenging if patients lack motivation or uncooperative during the evaluation.^104,105) Jo and Kim¹⁰⁵⁾ evaluated the impact of home environment modifications and assistive device training, guided by the OSA framework, on occupational participation, self-awareness, and activity limitations in people with disabilities, compared to a standard home exercise program. The OSA-guided interventions significantly improved the time spent on ADLs and participants’ self-awareness of occupational competence. However, no significant reduction in activity limitation was observed in the intervention group, suggesting the need to combine environmental modifications with exercise programs to enhance their effectiveness. This study underscores the importance of the OSA framework in implementing client-centered approaches to promote occupational participation and self-awareness. The limitations of this study include its small sample size and the lack of long-term follow-up, emphasizing the need for further research to validate these findings and refine OSA-based interventions.

Table 3 summarizes the key features of EADL assessment tools, including their scoring methods, number of items, and specific applications for evaluating extended activities.

Accurate evaluation of ADL is critical for understanding an individual’s functional independence, identifying areas that require intervention, and formulating effective care plans. ADL assessment tools are essential instruments in clinical practice, rehabilitation, and public health to track functional changes over time and guide decision-making. Despite its importance, acknowledging the limitations of ADL assessment is essential. First, the cultural limitations of ADL tools have been demonstrated in studies such as Yen et al.¹⁰⁰⁾ This study highlighted the challenges associated with adapting the WHODAS 2.0 for non-Western populations, citing variations in daily activities and social norms as key factors. Second, subjectivity and variability in assessment outcomes, as noted by Almazan-Isla et al.,¹⁰¹⁾ stem from the assessors’ experience and judgment, often leading to inconsistent results without adequate rater training. Third, environmental factors, such as lack of adequate home accessibility or family support, are often overlooked in traditional tools, but significantly impact functional performance Federici et al.⁹⁹⁾ Psychological factors, including depression and motivation, also play critical roles in ADL performance.¹⁰⁶⁾ However, traditional tools fail to assess these dimensions, limiting their utility in identifying barriers to daily functioning. Furthermore, the time-consuming nature of certain assessments such as the LIFE-H, as articulated by Desrosiers et al.,⁹⁸⁾ can lead to fatigue and diminished accuracy. This underscores the need for streamlined instruments that strike a balance between comprehensiveness and efficiency.

Digital technologies such as remote monitoring systems and virtual simulations are imperative for addressing the limitations of traditional tools, which are subjective and inconsistent. For instance, wearable sensors can monitor daily routines in real time, whereas smartphone applications can complement IADL evaluations by providing task-specific reminders and tracking adherence.¹⁰⁷⁾ Furthermore, virtual reality environments offer opportunities to simulate real-world scenarios, thereby enhancing the accuracy of social and occupational skill evaluations in EADL assessments.¹⁰⁸⁾ Multidisciplinary collaboration is vital to standardize evaluator training and harmonize scoring systems across diverse settings, as emphasized by the WHODAS 2.0 framework.¹⁰⁰⁾ Finally, it is imperative to acknowledge the influence of psychological and environmental factors on ADL evaluation. Depression, anxiety, and family support have been demonstrated to exert a substantial impact on ADL performance.¹⁰⁴⁾ The integration of complementary tools such as OSA, which emphasizes patient-centered feedback, is crucial for addressing these factors and enhancing the precision of ADL assessments. By integrating technological innovation, cultural adaptability, and comprehensive psychological assessments, evaluations of ADL, IADL, and EADL can become more precise, inclusive, and impactful.¹⁰⁹⁾

Emerging digital tools and online platforms are shaping the future of ADL assessment. Primary technologies poised for broader use include: wearable devices, smartphone applications, sensor-based systems, computerized assessment tools, virtual & augmented reality technologies, telehealth and remote monitoring systems, and AI & machine learning (ML)-based assessment tools. Each technology offers distinct features for evaluating ADL performance.¹⁰⁹⁾

Wearable devices collect data on physical activity through sensors embedded in wearable technology such as wristbands, smartwatches, and smart glasses.¹¹⁰⁾ These devices can track steps, distance, burned calories, heart rate, blood pressure, and sleep patterns, thereby providing a continuous overview of daily activity levels and health metrics.^111,112) Wearable devices allow for constant monitoring and is user-friendly, as individuals can gather data simply by wearing the device.¹¹³⁾ Wearable sensors have emerged as promising tools for monitoring bathroom activities among older adults, offering significant privacy advantages over traditional methods such as cameras and audio-based systems.¹¹⁰⁾ Research indicates high accuracy in activity recognition, such as 95% for toileting. However, a limited number of studies and controlled experimental settings hinder their broader applicability. The challenges associated with these sensors include small sample sizes, lack of real-world testing, and complexity of multisensor systems, which can reduce user compliance. To address these limitations, future efforts should focus on large-scale real-world studies and the development of simplified, user-friendly devices optimized for long-term use. Additionally, integrating advanced ML algorithms can enhance the accuracy and scalability of wearable sensor applications in daily living environments.

Smartphone applications leverage smartphone sensors and features to help users monitor their functional status using self-assessment questionnaires and activity tracking.¹¹⁴⁾ Functions include medication reminders, exercise goals, and activity prompts.¹⁰⁷⁾ Owing to the widespread use of smartphones, smartphone applications are highly accessible and offer easy connectivity to healthcare providers, thereby facilitating real-time communication.¹¹⁵⁾ Roy et al.¹¹⁴⁾ investigated the integration of smartphones and ambient sensors to enhance the recognition of ADLs in multi-inhabitant smart environments. The authors proposed a hybrid approach that utilizes smartphones for individual-specific microactivities and ambient sensors for location-specific data, achieving a 30% higher classification accuracy than methods that use smartphones exclusively. This study identifies challenges such as distinguishing activities in shared environments and ensuring computational efficiency in multi-user scenarios. This study underscores the necessity of integrating individual and environmental context data to enhance ADL classification. Future research should focus on refining activity recognition algorithms and leveraging additional smartphone sensors to facilitate more comprehensive data collection.

Sensor-based systems employ sensors and Internet of Things devices placed within the home to detect and evaluate user activities.^116,117) Devices such as motion detectors, pressure sensors, door sensors, and electricity monitors, collect data on movement and activity patterns.^118,119) Sensor-based systems enable non-intrusive monitoring, providing continuous data on daily activities and allowing for early detection of any irregularities without disrupting the user’s routine. Cahill et al.¹¹⁷⁾ reported several key findings. First, the use of sensors to monitor residents’ physical activities, environment, and care delivery processes is recommended. Second, the system demonstrates the potential to improve daily life experiences by providing predictive risk management, real-time monitoring, and streamlined communication among residents, caregivers, and family members. Third, the study identifies challenges to be addressed, including ensuring user acceptability, maintaining privacy, and preventing a reduction in human interaction. To address these challenges, this study proposes the implementation of ethical guidelines, refinement of system design to enhance usability, and training of care staff to integrate technological solutions with person-centered care approaches.

Computerized assessment tools use digital platforms to assess ADL capabilities by simulating everyday tasks in a controlled, virtual environment.¹²⁰⁾ These assessments often focus on cognitive functions such as attention and memory by mimicking daily tasks.^121,122) Computerized assessment tools provide objective, consistent evaluations that can be standardized, saved, and systematically analyzed, making it an efficient tool for longitudinal monitoring of ADL performance.¹²³⁾ The 2013 study on computerized adaptive testing (CAT) for assessing ADL presented a novel, efficient approach for evaluating functional independence in stroke outpatients.¹²³⁾ The CAT system was developed using an item bank of 44 ADL tasks and was later refined to 34 items after rigorous psychometric evaluation. The key findings include the following. First, the CAT demonstrated an average reliability of 0.93, exhibiting strong correlations with established measures such as the Barthel Index and the FAI. Second, the CAT required only one-fifth of the administration time of traditional methods. However, the study also identified two significant challenges: first, the CAT’s limited generalizability to inpatients and second, the need for broader cultural validation. To address these issues, future studies should expand the CAT’s application to diverse patient populations and incorporate items tailored to specific cultural contexts.

Virtual and augmented reality technologies create realistic environments for evaluating ADL performance in simulated settings.^108,124) For instance, tasks such as shopping in a virtual grocery store can be used to assess skills relevant to behavioral training and cognitive rehabilitation.^125,126) This method offers a risk-free environment and can be tailored to various scenarios, while the interactive and immersive design can enhance user motivation and engagement.¹²⁷⁾ Buele and Palacios-Navarro¹²⁷⁾ examined the potential of VR-based cognitive-motor interventions to support IADL in older adults with MCI or dementia. It highlights the potential of virtual reality to improve executive function, memory, and visuospatial orientation while fostering independence and quality of life. Key challenges include the need for personalized interventions tailored to the participants’ physical and cognitive conditions and addressing the digital divide for equitable access. Future applications should integrate adaptive task difficulties, provide real-time feedback, and ensure usability across diverse populations to enhance long-term engagement and effectiveness. This comprehensive approach has the potential to transform rehabilitation strategies for older adults by promoting independence and cognitive resilience.

Telehealth and remote monitoring systems utilize telecommunication technology to allow healthcare providers to remotely monitor and assess a patient’s ADL capabilities through video conferencing.¹²⁸⁾ This approach enables direct observation and guidance in performing daily activities with patient activity data shared with healthcare teams for evaluation and consultation.¹²⁹⁾ By eliminating geographic barriers, telehealth and remote-monitoring systems offer healthcare services without requiring frequent in-person visits, resulting in time and cost savings.¹³⁰⁾ The patient’s activity data can then be shared with a healthcare team for evaluation and consultation, thereby enabling the delivery of healthcare services without the constraints of distance and reducing the need for in-person visits. This approach has the potential to save both time and money.^131,132) The study developed and evaluated a remote health monitoring system designed to prevent frailty and support physical activity (PA) in chronic obstructive pulmonary disease patients.¹²⁹⁾ The system, which included an app for patients and support staff, demonstrated a significant improvement in PA duration and daily steps for one participant, although the results varied across individuals. A key limitation was the reliance on manual data entry, which risks errors and incomplete data. To address this limitation, the integration of automated data collection tools such as advanced sensors and seamless connectivity features, was proposed. This approach can be complemented by providing tailored health education to enhance patient self-management. The findings underscore the reliability of personalized technology-enabled interventions in the management of chronic conditions while concurrently mitigating the risks associated with frailty.

AI and ML-based assessment tools apply AI to analyze ADL data, assess an individual’s functional abilities, and identify potential irregularities.¹³³⁾ AI and ML-based assessment tools can detect early signs of functional decline or risk factors, anticipate changes in functional status, and support preventive strategies.^134-136) With the capacity to process extensive data efficiently, AI and ML-based assessment tools deliver precise assessments and assist in creating personalized intervention plans tailored to the individual’s unique characteristics.^134,137) Graham et al.¹³⁵⁾ are investigating the application of AI, with a focus on ML and natural language processing, in predicting and detecting cognitive decline among the older adult population. AI techniques employ extensive datasets encompassing sociodemographic information, clinical assessments, and neuroimaging data to identify early indications of neurocognitive disorders. Although AI has exhibited reliable accuracy and scalability, it is confronted with challenges such as bias, ethical considerations, and interpretability. Addressing these challenges requires interdisciplinary collaboration, extensive data sets, and a clear regulatory framework. Additionally, enhancing clinician engagement and transparency in AI models can facilitate their integration into healthcare services and ensure ethical and equitable utilization.

Table 4 summarizes the contents of emerging digital tools and online platforms.

The use of digital tools and online platforms for ADL assessment offers several advantages. These technologies enhance objectivity by providing more accurate and data-driven evaluations than subjective assessments. Continuous monitoring enables real-time feedback, interactive features increase user engagement, and organized data management allows longitudinal analysis to identify trends. However, this study has some limitations. Privacy and security concerns arise because of the potential for unauthorized access to personal and health data, and technological accessibility gaps may hinder individuals who are less familiar with digital devices. Moreover, the high cost of some technologies can restrict accessibility, and the complexity of data interpretation requires specialized expertise.^109,138) Despite these challenges, digital ADL assessment tools address several limitations inherent in traditional methods, enabling more accurate and efficient evaluations that ultimately contribute to enhancing individuals’ functional independence and quality of life.¹³⁹⁾

This study emphasizes the critical role of ADL assessment tools in evaluating functional independence and guiding personalized care strategies. Despite their widespread use, the current tools exhibit limitations, including cultural biases, reliance on subjective judgment, and insufficient consideration of psychological and environmental factors. Our findings underscore the importance of addressing these challenges through technological advancements such as AI, remote monitoring systems, and sensor-based tools, which offer opportunities to enhance accuracy, inclusivity, and efficiency. The integration of multidisciplinary collaboration and culturally adaptive frameworks is recommended to enhance the relevance and impact of these tools. By aligning technological innovations with the diverse needs of populations, ADL assessments can evolve into powerful instruments for improving health outcomes, fostering independence, and enabling meaningful societal participation.