s. mohammadreza alavizadeh

With the increasing number of older people worldwide, health and wellbeing concerns are becoming more crucial. Advances in science and medicine, along with longer life expectancy, are leading to higher longevity among older individuals (Koochakzadeh et al., 2021). The specific circumstances of women highlight the need to address health and physical activity issues in this demographic. Regular physical activity tailored for older adults can enhance and sustain their health. Exercise, including aerobic and balance routines, strengthens muscles, improves mobility, enhances physical performance, reduces the risk of chronic conditions like heart disease and diabetes, and enhances mental wellbeing in mobile older adults. Social support, perceived participation, sports, and physical and mental healthcare are all vital components. Engaging in sports and physical activities can help older individuals maintain their physical health, cognitive function, communication skills, and social connections (Chen et al., 2020; Contreras-Osorio et al., 2022). Furthermore, exercise can foster a sense of achievement and purpose, leading to increased self-esteem and overall life satisfaction (Chen et al., 2021). Support from family, friends, and the community also plays a significantrole in promoting healthy aging. Therefore, it is essential for communities to offer opportunities for older adults to engage in sports and social support networks to foster healthy aging.Various instruments are utilized to evaluate social support, with established psychometric properties in sports (Holt & Hoar, 2006) and social psychology (Haber et al., 2007). Examples include the Social Support Questionnaire (Sarason et al., 1983) and the Perceived Social Support Questionnaire (Brown et al., 1987). In the realm of sport psychology, instruments like the Social Support Scale (Santiago et al., 2023) and the Interpersonal Support Assessment List (Cohen & Hoberman, 1983) are commonly used. In Iran, various questionnaires have been employed, such as the social support questionnaire (Hooman & Livarjani, 2008), the social support scale in the medical outcome study (Mohammadzadeh et al., 2016), and the social support questionnaire (Vaux et al., 1986) in sports settings (Hosseini & Farzan, 2018). Given the significance of the issue, the existing challenges, the rise in the elderly population, and researchers' interest in supporting this demographic, this study aims to assess the psychometric properties of a specific sports instrument, explore the perception of available social support, and establish the factor structure, reliability, and validity of this instrument.

This study is a type of developmental research with an applied purpose in the field of sports social psychology research (Alavizadeh et al., 2020; 2021; Alavizadeh; Sepah Mansour et al., 2020). The statistical population of this study was older athletes in Tehran. The sample size was determined using a rule of thumb: 10 participants out of 160 for each item. The participants of this study were 147 older athletes (43 females and 104 males) out of 2022 who were selected through snowball sampling based on inclusion and exclusion criteria. Participants completed the Persian form of the Sport Social Support Perceptions Questionnaire (SSSP-Q). Exploratory factor analysis (EFA) was conducted in SPSS-26, and the results of confirmatory factor analysis (CFA), uni-dimensionality of indicators, composite reliability, and convergent and divergent (diagnostic) validity were also analyzed in SmartPLS-3 software.

The Kaiser-Meyer-Olkin test (KMO) indicated that the sample adequacy was appropriate (KMO = 0.71); additionally, the Bartlett test was statistically significant (χ2=874.742, p=0.01). Following orthogonal rotation using the varimax method, a four-factor model was derived. These four factors account for 64.67% of the total variance of the test. The subscales of self-esteem support, information support, emotional support, and tangible support also accounted for 17.13, 16.35, 16.17, and 15.03% of the total variance of the test, respectively.A) EFAThe Kaiser-Meyer-Olkin (KMO) test indicated that the sample adequacy is appropriate (KMO = 0.71); additionally, Bartlett's test was statistically significant (χ2=874.742, p=0.01). After orthogonal rotation using the varimax method, a four-factor model was derived. These four factors account for 64.67% of the total variance of the test. The sub-scales of self-esteem support, informational support, emotional support, and tangible support also accounted for 17.13, 16.35, 16.17, and 15.03% of the total variance of the test, respectively.B) CFAIn the second part, the construct validity of the P-SSSP-Q was assessed using CFA. The results indicate that the indicators for the goodness of fit of the P-SSSP-Q have an acceptable value (NFI=0.85, SRMR=0.08). Therefore, the data align statistically with the factorial and theoretical structure of the four latent variables (structure).Uni-dimensionality of the indicators: The standardized factor loading (λ) of all selected indicators for the desired structures is above average (greater than 0.45) and statistically significant at the one percent error level (Hair et al., 2019).Composite and internal reliability: The composite reliability of all research constructs exceeds 0.70, and their internal consistency with the Cronbach's alpha coefficient is also greater than 0.70. Therefore, all latent variables (structures) in the researchmeasurement model demonstrate very good reliability.Convergent validity: The results reveal that the average variance extracted (AVE) of all research constructs surpasses 0.50. Thus, all constructs in the research measurement model exhibit good convergent validity.Discriminant validity: Overall, the square root of AVE for each structure (0.813>AVE>0.771) exceeds the correlation between structures (0.690>AVE>0.310). This outcome confirms that the selected indicators for each construct share a significant portion of the common variance of that construct compared to others in the measurement model. Therefore, the discriminant validity of the constructs in the research measurement model is confirmed.

The results of the current study support the four-factor structure of the P-SSSP-Q. In the four-component model, factor loadings ranged from 0.46 to 0.54. The factor loadings of the questionnaire's dialects ranged from 0.67 for dialect number fifteen to 0.87 for dialect number five, and all dialects had acceptable factor loadings (Hair et al., 2019), so all dialects of the questionnaire were retained. The correlation between the four components of the questionnaire ranged from 0.31 to 0.69. Cohen et al. (1985) found that while social support can be conceptually categorized into specific dimensions, these dimensions are generally not independent in a natural environment. People who provide support may do so in different ways, such that an athlete who reports high levels of emotional support will be present on the P-SSSP-Q.This article presents initial evidence of the factor structure of the P-SSSP-Q. It suggests that developing and standardizing an instrument to accurately assess the availability of social support in sports can help answer important theoretical questions. The questionnaire also provides recommendations for social support instruments that are relevant to the target population and the context of the situation. The P-SSSP-Q can be used to explore the impact of perceived support in sports settings.

Anger is a basic emotion that it is known as popular phenomenon. Aggression is any verbal or physical behavior that proceed from anger and it has intentional or unintentional destructive dimension. These behavior can express to self or another object actively or passively. The aim of present study was development and validation of Sport Aggression Style Inventory (SASI). This instrument have developed based on Millon personality theory.

The sample include 99 participants that they randomly selected from 284 athletes which they selected in snowball sampling method, and they completed Sport Aggression Style Inventory (SASI) twice in two week. Data were analyzed in SPSS, AMOS and Smart-PLS environments.

The results of this study illustrate, the inventory has good internal consistency according to Cronbach's alpha for subscale as sadistic aggression style (external-active, ά=0.62), passive aggression style (external-passive, ά=0.84), masochistic aggression style (internal-active, ά=0.84), somatic aggression style (internal-passive, ά=0.82), and total score (ά=0.72); and good test-retest reliability in the SASI's subscales in a 2-week period (0.70-0.81). The Confirmatory Factor Analysis supported four factors model of SASI; and finally the results indicate that the SASI has acceptable convergent validity, discriminant validity, and composite reliability.

According to the present findings, The SASI has acceptable validity and reliability. Implications for research and clinical applications of the SASI in an Iranian athletic population is discussed.