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Abstract

With the global and national rise in aging populations, there is an increasing need for a comprehensive assessment of individuals’ readiness for aging. This concept spans multiple dimensions, including self-efficacy, social support, aging in place, financial preparedness, and health awareness. However, existing tools do not fully capture the multifaceted nature of aging. Therefore, this study aims to develop a comprehensive, psychometrically sound scale to assess readiness for aging. A mixed-methods approach with a sequential exploratory design, incorporating both qualitative and quantitative phases will be used. In Phase 1 (Qualitative Phase), a deductive content analysis of in-depth, semi-structured interviews will be conducted to define and conceptualize readiness for aging. In Phase 2 (Quantitative Phase), the findings from the qualitative phase will inform the development of a readiness for aging measurement tool, following the four-step Waltz and Bausell approach. The psychometric properties of the developed instrument, including face validity, content validity, construct validity, and reliability will be systematically evaluated. Given the lack of a specialized tool for assessing readiness for aging, this study develops a valid and reliable instrument that measures individual preparedness for later life providing a deeper understanding of the specific needs, challenges, and aspirations of older adults. By capturing these critical aspects, this tool can help create targeted interventions and support systems, ensuring that aging populations receive personalized resources and assistance to enhance their well-being and quality of life.

Keywords

readiness for aging psychometric properties validation older people

Introduction

The global aging population is growing rapidly, with projections indicating that the number of older adults will exceed 2 billion by 2025. Iran is experiencing a similar demographic shift, with estimates indicating that by 2050, individuals aged 60 and older will comprise 31.5% of the total population (Arjmand-sangani et al., 2024; Zanjari et al., 2024). Aging is accompanied by physiological changes that increase vulnerability to health conditions (Alvis & Hughes, 2015), highlighting the need to understand the challenges and needs faced by older people to develop effective interventions and policies (Frechman, Dietrich, et al., 2022; Savić et al., 2024).

The Iranian healthcare system faces several challenges in meeting the needs of its aging population, including insufficient knowledge, low self-efficacy, and inadequate self-care capacity (Samouei & Ageing, 2022). Additionally, older adults perceive that they have little control over their future and such a belief negatively impacts their quality of life (Lee et al., 2023). Psychological well-being in later life is closely tied to self-perception and attitudes toward aging, with positive aging perspectives being linked to better adaptation and overall well-being (Xu et al., 2024). The concept of readiness for aging offers a framework for understanding how individuals prepare for and navigate this life stage, encompassing various factors that influence their ability to adapt and thrive (Frechman, Dietrich, et al., 2022), encompassing psychological (Webster et al., 2018), physical (Avdeeva & Tulyakova, 2018), and social dimensions (Frechman, Buck, et al., 2022).

Several instruments have been developed to assess older adults’ preparedness in specific areas, such as advance care planning, financial readiness, and health management (Gao et al., 2024), health technology use (Ausserhofer et al., 2024), hospital discharge readiness (Mabire et al., 2015), mobility transition (Meuser et al., 2011), and independent living (Ardali et al., 2019). However, none of these instruments offer a comprehensive assessment of readiness for aging as a multidimensional construct. A recent concept analysis by Liang & Belza (2024) identified five key antecedents of aging preparedness: self-efficacy, social support, aging in place, financial preparedness, and health awareness (Liang & Belza, 2024).

Among these factors, self-efficacy—confidence in managing life transitions—is a key element in adapting to aging (Scult et al., 2015). Social support from family and community enhances resilience, while aging in place promotes independence and stability (Mayo et al., 2021). Financial preparedness ensures readiness for healthcare and long-term needs (Idárraga-Cabrera et al., 2020), while health awareness promotes overall well-being and supports healthier aging (Solhi, Pirouzeh, & Zanjari, 2022; Zanjari et al., 2024). Resilience, social connectedness, and future planning, collectively contribute to a higher quality of life, greater financial security, and better aging outcomes (Liang & Belza, 2024).

Although interest in readiness for aging is increasing, there remains a lack of a standardized, comprehensive instrument to assess this construct in current research. The Planning for Aging and Frailty Questionnaire is currently the only instrument specifically designed for aging preparedness; however, it has several limitations. While it evaluates various domains of aging planning, it primarily focuses on cognitive impairments, disabilities, and healthcare needs, rather than addressing key dimensions such as psychological resilience, self-efficacy, and financial security (Frechman, Buck, et al., 2022). Moreover, it does not offer a holistic assessment of an individual’s ability to navigate aging proactively, focusing instead on access to healthcare resources and disease management. Given these gaps, a more inclusive and multidimensional instrument is needed to assess readiness for aging in a comprehensive and integrated manner.

Another critical challenge in aging preparedness research is the role of culture in shaping individuals’ perceptions and experiences of aging. Cultural factors significantly influence attitudes toward aging, self-care practices, and expectations for later life, making it essential to consider these variations when developing tools for assessing aging readiness (Koo, 2011). In collectivist societies like Iran, family plays a central role in providing emotional, financial, and practical support for older adults, often serving as the primary source of care and assistance as individuals age (Peyman & Olyani, 2020). In contrast, in individualistic cultures, elderly care tends to rely more on formal social support systems and government institutions, with a greater emphasis on independence and self-reliance (Davey et al., 2005; Davey & Patsios, 1999; Kingston et al., 2018). A study by Shamsikhani et al. (2021) highlights the multiple dimensions of family support in Iran, emphasizing its critical role in shaping older adults’ well-being (Shamsikhani et al., 2021). Additionally, cultural beliefs about aging influence mental health and resilience, with positive perceptions associated with greater life satisfaction (Pashaki et al., 2015). Religious and spiritual beliefs also play significant roles in shaping health behaviors and end-of-life care preferences, further underscoring the need for a culturally relevant assessment tool (Faraji et al., 2023).

Given the distinct socio-cultural and healthcare landscape of Iran, existing Western-developed assessment tools may not fully capture the priorities and concerns of Iranian older adults. To ensure applicability and effectiveness, it is crucial to develop an instrument that aligns with the social and cultural dimensions of aging. Incorporating cultural sensitivity into the design of the Readiness for Aging Instrument (RAI) will enhance its relevance and utility, enabling more targeted interventions and policies to improve the well-being of the aging population. The aim of this study is to define the concept of readiness for aging, identify its dimensions, and develop and validate an instrument for assessing readiness for aging. The following research questions guide our study:

• How do older adults define their experience and perception of readiness for aging?

• What are the dimensions of readiness for aging?

• What are the content and face validity (both quantitative and qualitative) of the instrument measuring readiness for aging?

• What is the construct validity and internal consistency reliability of the instrument measuring readiness for aging?

• What is the absolute, relative stability, and test-retest reliability of the instrument measuring readiness for aging?

• How do the qualitative themes identified through directed content analysis inform the development of quantitative items in the readiness for aging instrument?

• To what extent do the quantitative results from the psychometric evaluation of the instrument align with the qualitative findings on older adults’ perceptions of readiness for aging?

• How can the integration of qualitative and quantitative data provide a more comprehensive understanding of the construct of readiness for aging?

• What discrepancies, if any, exist between the qualitative themes and the quantitative factor structure of the readiness for aging instrument?

• How can the mixed-method approach enhance the validity and reliability of the instrument in measuring readiness for aging across diverse populations?

Methodology

Study Design

A sequential exploratory mixed-methods design (QUAL → Quan), consisting of two distinct phases will be utilized. In the qualitative phase, in-depth interviews will be conducted based on the dimensions identified in previous international literature on preparedness for aging. These interviews will explore older adults’ experiences and perceptions of readiness for aging, providing rich qualitative data to inform the development of the instrument. The goal of the qualitative phase is to explore the perspectives of older people regarding their readiness for aging, using these insights to develop a questionnaire. In the quantitative phase, the key concepts and themes extracted from the qualitative data will be transformed into quantifiable items for this questionnaire. To ensure a thorough and nuanced understanding of the research question, both qualitative and quantitative data will be integrated during analysis and interpretation. This mixed-methods approach will enable the development of a comprehensive framework, fostering consensus on a standardized definition of readiness for aging (Johnson & Rasulova, 2017; Othman et al., 2020).

Rationale for Design

This study will adopt a mixed-methods approach to address the complex and broad challenge of developing a standardized and effective measure of readiness for aging (Bowen et al., 2017). Utilizing this approach allows for the integration of two distinct sampling strategies, combining qualitative insights with quantitative data to ensure a comprehensive and well-rounded assessment of the phenomenon (Mbuagbaw et al., 2013).

By incorporating both purposive and probabilistic sampling techniques, the study will ensure a comprehensive data collection process, capturing both depth and breadth (Mbuagbaw et al., 2013). The qualitative phase, consisting of individual interviews, will provide contextual understanding and elaborate on the findings from older people. Meanwhile, the quantitative phase will focus on assessing the psychometric properties of the RAI, validating its reliability and effectiveness. This integrated methodology will yield insights that would be unattainable through qualitative or quantitative methods alone. It will enhance the validity of the analysis, providing a more robust understanding of readiness for aging and contributing to the development of reliable, meaningful new knowledge (Fetters et al., 2013).

Study Timeline

Participant recruitment for the qualitative phase will begin in May 2025 and continue until August 2025. The synthesis of qualitative data will occur between August and October 2025. Insights gained from this phase will inform the development of a questionnaire, which will be distributed for data collection from November 2025 to February 2026. The final phase, involving the analysis of quantitative findings and integration of qualitative and quantitative data, will be completed between March and June 2026.

Phases of the Study

This study employs a mixed-methods design with a sequential exploratory approach, grounded in the pragmatism paradigm. By integrating qualitative and quantitative methodologies, this approach combines the strengths of both to deliver a more comprehensive and nuanced understanding of the concept under investigation—yielding insights that go beyond what a single-method approach can offer (Polit & Beck, 2010) (Figure 1). The research aims to develop and evaluate the psychometric properties of RAI. The study will be conducted in two phases, informed by content analysis, to establish a holistic, contextually relevant, and culturally adapted definition of readiness for aging.

Figure 1.

The Process of Instrument Development for Readiness for Aging

Phase 1: Qualitative Research

In the first phase, a qualitative content analysis approach will be used to derive an operational definition of readiness for aging and explore individual and socio-cultural factors influencing it. Antecedents, attributes, and consequences of readiness for aging will be identified, providing a theoretical foundation for the subsequent instrument development. Data analysis will be performed using the deductive content analysis method, as outlined by Hsieh and Shannon (2005) (Hsieh & Shannon, 2005). Accordingly, this study explores how existing theories and concepts apply within a specific context, refining established ideas through detailed, context-rich qualitative data. Drawing on a comprehensive review of the existing literature, the interview questions and key dimensions of readiness for aging will be identified. Subsequently, the concept and dimensions of readiness for aging will be examined in depth, and core items for a measurement tool will be derived using a deductive content analysis approach informed by the literature review findings. Therefore, it will be ensured that the instrument is grounded in both theoretical and empirical evidence, capturing the multifaceted nature of readiness for aging (Frechman, Buck, et al., 2022).

Participant Selection

Participants will be selected using purposeful sampling, targeting older adults who possess rich experiential insights and demonstrate a willingness to participate in the study. The first author will personally visit public spaces, such as mosques and parks—commonly frequented by older adults—to recruit participants directly from these settings. The inclusion criteria will encompass individuals aged 65 years and above, capable of articulating their experiences, and consent to take part in the study.

The study aims to capture diverse perspectives by ensuring maximum variation sampling in terms of age, gender, place of residence, education background, and socio-cultural context. This approach will help ensure that the findings reflect a broad range of experiences and contribute to the development of a comprehensive and inclusive instrument for assessing readiness for aging.

Data Collection

Data will be gathered through individual, face-to-face interviews, conducted either in person or virtually, as required. Interviews will continue iteratively until data saturation is achieved, meaning that no new or significant information emerges from additional participants.

To ensure a broad representation of experiences, interviews will be conducted in public spaces frequently visited by older adults, such as parks and community centers. Potential participants will be approached and after a detailed explanation of the study’s objectives, informed consent will be obtained from those willing to participate. Additionally, implicit consent will be secured for the audio recording of the interviews. The time and location for each interview will be chosen based on the participant’s preference to ensure comfort and privacy.

Interview Process

To foster a trusting and open atmosphere, interviews will begin with general, open-ended questions, allowing participants to express their thoughts freely. Once rapport is established, research questions will be introduced and probing questions will be employed to elicit deeper insights, clarify responses, and ensure comprehensive data collection. Interviews will continue until participants feel they have shared all relevant information. If necessary, follow-up sessions will be scheduled to address their fatigue or to gather additional details. After each interview, participants will be invited to share any additional reflections they may have overlooked. All interviews will be audio-recorded, and the researcher will also take field notes to document non-verbal cues, such as facial expressions, tone of voice, and gestures, to enhance the depth of qualitative analysis.

Directed Qualitative Content Analysis

A deductive content analysis approach will be used to examine readiness for aging systematically with the following steps:

(1) Identification and selection of relevant literature guided by established theories and prior research on preparedness for aging. The following key studies have been identified as foundational texts (Frechman, Buck, et al., 2022; Frechman et al., 2023; Liang & Belza, 2024; Solhi, Pirouzeh, Zanjari, et al., 2022). Also, a thorough review of empirical studies will be conducted to identify and define the core concepts and dimensions of readiness for aging. Interview questions will be designed based on these insights, covering essential domains of self-efficacy, social support, aging in place, financial readiness, health awareness, psychological resilience, social connectedness, quality of life, future-oriented planning, and leisure activities. (Table 1 of Supplemental file).

(2) Development of a conceptual matrix to organize the key concepts and dimensions identified in literature. This matrix will serve as a framework for data categorization during analysis.

(3) Designing an interview guide to ensure that all key concepts, definitions, and dimensions are systematically covered. This semi-structured guide will align with the theoretical framework and coding matrix.

(4) Selection of semantic units and code extraction so that the primary research question and defined theoretical concepts will guide the identification of semantic units in the qualitative data. Initial codes will be extracted based on participants’ responses.

(5) Code categorization within the conceptual matrix as the extracted codes will be systematically placed into the pre-defined categories within the conceptual matrix, ensuring alignment with theoretical constructs.

(6) Development of operational definitions as the key concept will be assigned a precise operational definition, based on the findings from the qualitative data analysis. These definitions will be compared with existing theoretical definitions to ensure consistency and conceptual refinement (Hsieh & Shannon, 2005).

This structured approach ensures a rigorous, theory-driven analysis, facilitating a comprehensive understanding of readiness for aging while maintaining scientific validity and reliability.

Trustworthiness

In qualitative research, the validity and reliability of data are assessed through five criteria: credibility, confirmability, dependability, transferability, and authenticity (Johnson & Rasulova, 2017). These criteria ensure the study findings’ accuracy, robustness, and trustworthiness. To enhance credibility, sufficient time has been allocated for data collection and in-depth analysis to achieve a comprehensive understanding of the research phenomenon. Data will be collected from multiple sources and analyzed using relevant theoretical frameworks to strengthen the validity of the findings. By recruiting participants from various geographic areas and different socio-demographic backgrounds, the variability of experiences is captured, enhancing the generalizability of the results. To ensure confirmability, a collaborating researcher, who has not been involved in data collection, will compare the interview transcripts with the original audio recordings to identify and correct any discrepancies. A subset of coded interviews will be returned to participants for verification, allowing them to confirm the accuracy and authenticity of their responses. The primary researcher remains aware of potential personal biases and actively works to prevent subjective interpretations from influencing the data collection and analysis process (Polit & Beck, 2010). While qualitative research does not seek direct generalization, transferability can be strengthened through strategic study design. Participants will be deliberately selected to represent diverse backgrounds, including differences in age, gender, education, and social status in line with maximum variation sampling. Detailed accounts of participants’ experiences and contextual factors will be provided, allowing future researchers and practitioners to assess the applicability of findings to similar populations (Pandey & Patnaik, 2014). It will be ensured that the study captures the full complexity of participants’ perspectives while fostering mutual understanding between the researcher and participants. Purposeful sampling will be employed to select participants with varied perspectives, ensuring a holistic representation of readiness for aging. The researcher will engage in dialogue with participants, allowing for the co-construction of meaning and ensuring that findings reflect genuine lived experiences rather than preconceived notions. Efforts will be made to minimize biases and accurately document all findings without distortion or selective interpretation (Carolyn Feher Waltz, Strickland, & Lenz, 2010). By integrating these trustworthiness strategies, this study ensures that its findings are rigorous, credible, and applicable while maintaining scientific integrity and transparency.

Phase 2: Questionnaire Development and Psychometric Evaluation

Findings from the qualitative phase will guide instrument development through:

(1) Conceptual Model Formation: An inductive approach will derive operational definitions from qualitative themes, ensuring theoretical and empirical coverage of readiness for aging.

(2) Measurement Objectives: Defined based on identified dimensions, these objectives align the tool with the concept’s theoretical foundation.

(3) Blueprint Design: Constructs will be mapped to measurable domains and associated items, grounded in qualitative insights.

(4) Instrument Construction: Items will be refined and scoring rules will be established (Carolyn Feher Waltz et al., 2010).

Item Extraction and Generation

Items will be developed through a deductive approach as items will be formulated based on existing theoretical frameworks; inductive approach as items will be extracted from codes identified in the qualitative phase. To enhance clarity, comprehensibility, and validity, participant verbatim responses will be incorporated into item wording whenever possible. The item development process will follow creating an initial item pool from qualitative findings; reviewing and refining items with input from the research team; eliminating redundant or conceptually similar items to ensure clarity and conciseness; finalizing the constructs and item set for further evaluation. This structured approach ensures that the RAI is conceptually grounded, empirically derived, and methodologically rigorous.

Psychometric Properties of the Instrument

This section outlines the methodological approach for assessing the validity and reliability of the RAI to ensure its scientific robustness and applicability.

Face and Content Validity

For face validity, ten participants will evaluate each item for clarity, relevance, and difficulty. Their feedback will guide revisions to improve item quality. Additionally, participants will rate item importance on a 5-point Likert scale. An impact score (Frequency × Importance) will be calculated, with items scoring above 1.5 retained (Pandey & Patnaik, 2014).

An expert panel of 10 specialists in aging and psychometrics will assess its content validity in terms of the instrument’s grammar, clarity, item phrasing, placement, and scoring. Revisions will be made accordingly. Quantitative content validity will be evaluated using:

(1) Content Validity Ratio (CVR): Based on the Lawshe’s method, items rated “essential” by experts must achieve CVR > 0.62 (Lawshe, 1975).

(2) Content Validity Index (CVI): Items will be rated on relevance (1–4 scale); I-CVI > 0.79 is accepted, 0.70–0.79 requires revision, < 0.70 causes rejection. S-CVI > 0.90 is acceptable.

(3) Modified Kappa (K): Used to adjust for chance agreement, with values > 0 indicating increasing inter-rater reliability.

Item Analysis

The loop method will be applied to refine items. First, the reliability coefficient for the overall questionnaire will be calculated. A pilot test involving 50 participants will be conducted. Items that do not meet correlation thresholds will be eliminated or revised. Items will be removed if their correlation with the total score is negative or if their correlation coefficient is below 0.3.

Construct Validity

Exploratory Factor Analysis (EFA) will be conducted to identify latent structures. Sampling adequacy will be assessed using the KMO test, and Bartlett’s test will confirm the suitability of the correlation matrix. Factors will be extracted by grouping items with strong intercorrelations (Sharma, 2022). A minimum sample size of five participants per item, as recommended by MacCallum et al. (1999) and Mokkink et al. (2010), will be ensured (MacCallum Rc, 1999; Mokkink et al., 2010). To evaluate construct validity, Confirmatory Factor Analysis (CFA) will be conducted following six key steps: (1) specifying a theory-based measurement model, (2) screening data for assumptions, (3) estimating the model and assessing fit via CFI, TLI, RMSEA, and SRMR, (4) verifying factor loadings (≥0.50) and convergent validity via AVE, (5) evaluating reliability (CR > 0.70) and discriminant validity, and (6) refining the model based on modification indices and theoretical considerations.

This rigorous approach ensures the reliability and validity of the measurement model, thereby enhancing the robustness of the study’s findings.

Reliability

The internal consistency and stability of the RAI will be evaluated using:

(1) Cronbach’s Alpha: Internal consistency will be assessed with a minimum acceptable alpha of 0.7 (Sharma, 2022).

(2) Test-Retest Reliability: Participants from the construct validity stage will re-complete the instrument 2–4 weeks after the initial test. Pearson’s correlation coefficient above 0.74 will indicate acceptable stability.

(3) Minimum Detectable Change (MDC) & Minimum Important Change (MIC): The MDC and MIC indices will be calculated to determine the smallest detectable and clinically meaningful differences.

Weighting of Items

After conducting exploratory factor analysis (EFA), factor loadings will be used to compute item weights. Each item’s factor loading will be multiplied by the proportion of variance explained by its corresponding factor to determine its relative contribution to the subscale. Finally, item weights will be standardized to ensure comparability across items.

Interpretability of the Instrument

Interpretability will be assessed based on three key criteria:

(1) Ceiling and Floor Effects: The proportion of participants scoring at the highest (ceiling) or lowest (floor) possible levels will be analyzed. A threshold of less than 20% is considered acceptable.

(2) Response Pattern Analysis: Missing data rates will be evaluated, and response distributions will be examined to identify potential biases or inconsistencies (Polit & Francis, 2016).

(3) Feasibility Assessment: The time required to complete the instrument, and the clarity of its items will be assessed to ensure ease of use and respondent comprehension.

Scoring

The items will be scored using a 5-point Likert scale. A linear transformation will be employed to standardize the scores on a 0–100 scale, as described in the following formula: Standardized Score = (Original Score - 1/4) × 100. In this scale, a score of 0 indicates no readiness, while a score of 100 represents maximum readiness (Polit & Francis, 2016).

Data Analysis

Data will be analyzed using SPSS using descriptive statistics, including the calculation of the mean, standard deviation, and frequency distribution. Also, exploratory Factor Analysis (EFA) involves the identification of latent dimensions and inter-item relationships (Kieffer et al., 2021). Confirmatory Factor Analysis (CFA) validates the factor structure through hypothesis testing. CFA is particularly preferred when the factor structure is already established (Brown, 2015).

Discussion

This study presents a protocol for a mixed-methods research study aiming at developing and validating the psychometric properties of the RAI. Given the rapid growth of the elderly population in Iran and the multifaceted nature of the aging process, there is a pressing need for a comprehensive, reliable, and culturally appropriate instrument to assess individuals’ preparedness for this stage of life.

Existing tools that measure aspects of aging readiness exhibit some limitations. For instance, the “Planning for Aging and Disability” instrument primarily focuses on disability-related aspects of aging while neglecting broader psychological and social dimensions (Frechman, Buck, et al., 2022). However, research suggests that aging readiness is a multidimensional concept, encompassing not only physical and financial preparation but also psychological resilience, self-efficacy, and awareness of the aging process—factors that are crucial to successful aging and quality of life.

The conceptual framework for this study is grounded in the “Analysis of the Concept of Readiness for Aging,” which delineates critical dimensions essential to understanding aging preparedness. These dimensions include psychological resilience, which refers to the capacity to effectively cope with stressors and maintain emotional equilibrium in the face of aging-related challenges; self-efficacy, defined as an individual’s confidence in their ability to manage the inevitable changes associated with aging; and awareness of the aging process, which encompasses an individual’s understanding of and preparedness for the physiological, social, and cognitive transformations inherent in aging. These dimensions collectively provide a comprehensive foundation for evaluating readiness for aging, offering a multidimensional approach to both the psychological and practical aspects of aging preparedness (Liang & Belza, 2024).

Despite their significant influence on the well-being and adaptability of older adults, dimensions such as psychological resilience, self-efficacy, and awareness of the aging process have not been systematically integrated into existing instruments. The omission of these factors leads to an incomplete assessment of aging readiness, which can limit the effectiveness of interventions and policy planning aimed at supporting older populations. Additionally, recognizing the cultural context and the vital role of family support in aging is crucial. Prioritizing the dignity and respect of older people (Shamsikhani et al., 2022), as well as assessing the level of familial support (Shamsikhani et al., 2021), can substantially improve aging preparedness and the quality of life of older adults (Shamsikhani et al., 2023). By considering these factors, this study seeks to address this gap and develop a comprehensive, psychometrically sound instrument that offers a more holistic measure of readiness for aging.

The findings from this research will have profound implications for public health planning, allowing policymakers to more accurately assess and address the needs of the aging population. Additionally, the study will guide clinical and gerontological interventions, helping to design targeted programs that enhance psychological resilience, self-efficacy, and well-being among older adults. The validated instrument developed in this study will also contribute to future research by providing a reliable tool that can be applied across diverse cultural and socio-economic contexts. Ultimately, the RAI represents a vital step toward improving the quality of life and well-being of older adults, ensuring they are better prepared for the challenges and transitions associated with aging.

Conclusion

A comprehensive and effective tool for assessing readiness for aging is crucial for precise and strategic planning aimed at enhancing the well-being of older adults. As the elderly population rapidly grows, maintaining their quality of life becomes increasingly important. The development of the RAI is essential for identifying individuals’ strengths and areas for improvement across key domains—such as physical and mental health, cognitive abilities, and social support. By doing so, the RAI can serve as a foundation for creating tailored educational and support programs that address the unique needs of everyone, ultimately contributing to a healthier and more fulfilling aging process. The implementation of such an assessment can lead to a variety of interventions, including life skills training, physical health promotion, strengthening social relationships, and enhancing psychological resilience. These programs empower older adults by increasing their awareness and knowledge, while also providing them with the resources needed to navigate the challenges of aging more effectively. A well-designed tool can further foster self-efficacy and confidence, enabling older adults to actively engage in society and maintain a sense of autonomy and purpose. Beyond the individual benefits, a comprehensive aging preparedness tool can be an asset for policymakers and planners. The insights gained from the RAI can guide the development of inclusive policies and programs that address the evolving needs of the aging population, ultimately promoting societal well-being and supporting sustainable aging.

Supplemental Material

Supplemental Material - Design and Psychometric Properties of an Instrument to Measure Readiness for Aging: Protocol of a Mixed-Methods Study

Supplemental Material for Design and Psychometric Properties of an Instrument to Measure Readiness for Aging: Protocol of a Mixed-Methods Study by Tahereh Bahrami, Fazlollah Ahmadi, Mitra Khoobi, Anoshirvan Kazemnejad, and Mojtaba Vaismoradi in International Journal of Qualitative Methods

Footnotes

Acknowledgments

This study is part of the PhD dissertation of the first author (T.B.) and is supported by Tarbiat Modares University (Decree Code: IR.MODARES.REC.1404.031). The authors express their sincere appreciation in advance to the older adults who will participate in this research and contribute valuable insights to the study.

ORCID iDs

Tahereh Bahrami

Mojtaba Vaismoradi

Ethical Considerations

This study was approved by the Research Ethics Committee (approval no IR.MODARES.REC.1404.031). The study will be conducted following the Declaration of Helsinki. Before participating, all participants will complete an informed consent form and receive a full briefing on the research objectives, as well as the measures taken to ensure anonymity and confidentiality. Interviews will be scheduled at a time and place convenient for the participants. They will be assured that their information will remain confidential and that they may withdraw from the study at any time. Participants will also provide permission for voice recording and notetaking during the interviews.

Consent to Participate

The informed consent form will be signed by the participants before taking part in the study.

Author Contributions

Study design and conceptualization: TB, FA, MKH, AK, MV; data collection: TB; data analysis and interpretation: TB, FA, MKH, AK, MV; manuscript writing: SR, FA, MKH, AK, MV; study supervision: FA, MKH, MV. All authors have fully participated in the design and conceptualization of the study and have read and approved the draft version of the article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article.

Data Availability Statement

The developed guideline will be available from the corresponding author upon reasonable request.*

Supplemental Material

Supplemental material for this article is available online.

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