Background and Objectives: In spite of the aging of the Iranian population, the real needs of the elderly as a vulnerable group have not been given much attention, so they need serious consideration of the authorities for their comprehensive exposure. Therefore, in this study we tried to identify the priorities of active aging policy making for planning so that it can meet all their needs. So, factors affecting large-scale managerial policies could be a good aging predictive factor in the coming years. Material and Methods: The method of this project is a qualitative content analysis study. The statistical population of this study consisted of 287 elderly managers in organizations related to the provision of active aging services. The research tool was a questionnaire which was developed by the researcher. Quantitative assessment was done using content validity ratio (CVR) and content validity index (CVI). Data were analyzed using descriptive statistics, one sample t-test and SPSS software. Results: According to the findings of this study, nutrition, housing, leisure planning, income security, urban planning and spaces, mental health, community attitudes and health literacy, lifelong learning and employment are effective in prioritizing active aging policy and nutrition with 0.512 factor loading has the most important factor and "lifelong training" with 0.820 factor loading is the least in defining the factors of active aging in prioritizing. Conclusion: If government and related organizations make policy-making based on priorities, and need-based policy-making becomes coherent and integrated, significant results are expected to improve the condition of the elderly.

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Objective: Active ageing constitutes one of the guiding perspectives on policies, but the factors influencing ageing have not received considerable attention. The present study aimed to identify the factors affecting active ageing management in Iran. Design: Drawing on quantitative data gathered through a questionnaire filled out by 287 participants and an interview with 20 experts. Main outcome measures: The instrument was a questionnaire based on the five-point Likert scale. Questions with CVR>0.49 and with CVI>0.7 were accepted. To assess the reliability of the questionnaire, Cronbach's alpha coefficient was (0.92) used. The adequacy of the sample size was estimated at 0.952, based on the Kaiser-Meyer-Olkin (KMO) index. The collected data were analyzed by SPSS Ver 22. An exploratory factor analysis was used to explore and evaluate the dimensions of the model through a mathematical approach. Also, confirmatory factor analysis was utilized to verify the model, using AMOS 24 software. Results: Eight factors were identified as effective factors in active ageing management in Iran, which include: Organizational structure (0/83), services (0/80), control (0/74), financing (0/72), government grants (0/71), policy making (0/68), selected area to focus (0/65), members (0/63). Organizational structure and member components had the most and least significant effects. Conclusions: Establishing a High Council with the presence of the President's representative, allocating a specific budget for the elderly, determining the responsibilities of the government and the related organizations, determining the responsibility and providing suitable services can lead to the effective management of active ageing.

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