Introduction
Advances in scientific and healthcare technologies have increased the average lifespan while extending the period of old age. To promote a smooth transition into this period, increasing attention has been devoted to successful aging after midlife [
1]. A positive outlook on the aging process during midlife, which is a natural phase of the life cycle, is essential for successful aging and positive adaptation [
2]. Assessing the aging process is particularly important for middle-aged women, who may experience a sudden onset of physical and emotional symptoms following menopause [
3].
Successful aging involves not just physical health, but also psychological and social well-being, along with high life satisfaction [
4]. The selection-optimization-compensation (SOC) model has been applied to facilitate favorable aging from a multidimensional perspective [
5]. Designed for individuals who may feel isolated due to age, the SOC strategy involves choosing activities that suit their abilities (selection), working to perform these activities to the best of their ability (optimization), and using available resources to make up for limitations (compensation) [
4]. Accordingly, this strategy is focused on positively adapting to the physical and environmental changes associated with aging and maximizing one’s available abilities, rather than attempting to overcome changes or dwelling on diminished capacities [
6].
The SOC strategy scales used in South Korea (hereafter referred to as Korea) include a 48-item instrument developed by Baltes et al. [
7], which was adapted and validated by Eom and Chung [
8], along with a shortened 12-item version utilized by Song [
9] and an extended 20-item version created by Sohn [
10] that incorporated in-depth interviews with older adults. However, these tools employ dichotomous scales, presenting options as target and distractor items, which could lead to a polarized evaluation of respondent behavior. According to prior research, psychometric instruments assessing attitudes and behaviors should present individual situations and allow for selection based on specific circumstances [
11]. Consequently, instruments must be developed using a Likert-scale format; this enables individuals to rate the alignment of each option with their typical behavior in a nuanced manner, without referencing specific situations.
Furthermore, since current scales for SOC strategies were developed for the elderly, items must be added or modified to cover the late middle-aged population (aged 50 to 64 years), who are faced with the onset of aging. Accordingly, a scale should be developed to appropriately measure SOC strategies to support a successful transition from middle to old age. Recent research on aging suggests that preparations for old age should be approached from a life-cycle perspective [
12], and the outcomes and processes of successful aging must be measured during the period prior to old age. Middle age, a crucial period of preparation for successful aging, decisively influences the quality of life in later years [
13]. Middle age is often broadly defined as an age of 40 to 64 years; however, for women, the hormonal changes experienced during this time may necessitate distinct approaches between early and late middle age [
14]. Aging-related strategies likely differ between these stages.
The health crises, psychological changes, and coping behaviors of late middle-aged women during menopause represent key nursing concerns in the context of transitioning to old age [
2]. However, suitable instruments are lacking for evaluating SOC strategies in light of these characteristics. As aging accelerates with the onset of menopause, an objective assessment of SOC approaches in late middle-aged women is crucial to establish interventions that support successful aging. Therefore, this study was performed to develop a scale to measure SOC strategies in late middle-aged women, drawing on the model proposed by Baltes et al. [
7].
Results
General characteristics of the participants
The study included 299 participants with an average age of 53.44±3.56 years, ranging from 50 to 64 years. Most participants were employed (n=231, 77.3%), married (n=249, 83.3%), and religiously affiliated (n=266, 89.0%). The most frequent level of educational attainment was a bachelor’s degree (n=168, 56.2%), and the predominant economic status was the middle level (n=202, 67.5%). Overall, 183 participants (61.2%) reported having no chronic diseases, and 163 individuals (54.5%) rated their health status as average. Just over half of the participants (53.5%, n=160) expressed satisfaction with their lives, and 197 participants (65.9%) were postmenopausal (
Table 1).
Item analysis
The normality of the data collected for item analysis was confirmed by examining skewness and kurtosis values, which ranged from −1.06 to .01 and −.59 to 1.52, respectively. Since none of the items exhibited absolute values exceeding 3 for skewness or 7 for kurtosis, no items were excluded based on these criteria. Further analysis revealed that six items (items 3, 17, 25, 27, 28, 31) had correlation coefficients below .30, prompting their removal. After re-evaluating the correlations, the values obtained ranged from .31 to .82. Ultimately, 26 items were retained for exploratory factor analysis to assess construct validity.
Construct validity testing
Exploratory factor analysis was employed to assess the construct validity of the instrument developed to measure SOC coping strategies among late middle-aged women. The data’s suitability for factor analysis was previously established, evidenced by a KMO value of .90 and a Bartlett test of sphericity indicating significance (χ2=6,341.23, p<.001). Exploratory factor analysis was performed using maximum likelihood extraction and varimax rotation. Communalities for the individual items ranged from .43 to .82. Four items with communalities below .50 were excluded: items 5 (.47), 14 (.38), 26 (.43), and 29 (.45).
After eliminating these four items, a second-factor analysis was conducted. Items 4 and 32, which had respective communalities of .31 and .49, were excluded prior to a third-factor analysis. In this latter analysis, all remaining items had communalities greater than .50, resulting in a set of 20 items.
The third-factor analysis yielded four factors with eigenvalues exceeding 1.0, accounting for a cumulative variance of 66.4%. Item 21, however, exhibited a factor loading below .50 and was thus excluded from this analysis. A fourth-factor analysis was subsequently performed with the remaining 19 items, identifying four factors with eigenvalues of 1.0 or greater and explaining a cumulative variance of 66.9%. In this final factor analysis, factor 1 accounted for 20.1% of the variance, factor 2 for 18.7%, factor 3 for 18.0%, and factor 4 for 10.2% (
Table 2).
The exploratory factor analysis, conducted in three stages, resulted in the removal of seven items with communalities below .50. These items were: “I take the lead when making important life decisions,” “When I want to execute a plan, I consider the approaches of successful people,” “I obtain information on managing health changes from healthcare professionals,” “When things do not go well, I seek help or advice from others,” “If something no longer works like before, I try different methods until I achieve comparable results,” “If life is not going as well as it used to, I watch useful broadcasts or read books,” and “When things are unresolved, I continue trying different methods.”
Criterion validity testing
A significant correlation with the reference instrument was confirmed [
9], establishing the criterion validity of the SOC strategy scale (r=.30,
p<.001).
Reliability testing
To evaluate the reliability of the final 19-item scale developed in this study, we assessed the reliability of the subfactors and the entire item set, as well as Cronbach’s α value, when items were removed. The overall reliability of the items was .95, while the reliability scores for the individual factors were .90 for factor 1, .88 for factor 2, .90 for factor 3, and .90 for factor 4. These results confirmed the scale’s suitability for use. Furthermore, the removal of items did not significantly affect the reliability scores, indicating that no additional items required exclusion (
Table 3).
Finalization of the SOC strategy scale
After testing for validity and reliability, the SOC strategy scale developed for late middle-aged women consisted of 19 items. The items are grouped under four factors: factor 1, goal-oriented selection; factor 2, loss compensation; factor 3, outcome optimization; and factor 4, ability-based optimization (
Table 3). Each item is rated on a 5-point Likert scale, with total scores ranging from 19 to 95. Higher scores signify greater application of SOC approaches (
Supplementary Materials 1 [English version] and
2 [Korean version]).
Discussion
We developed and tested a scale measuring the application of the SOC strategy, specifically for late middle-aged women. This work was based on the SOC model proposed by Baltes and Baltes [
4]. The resulting instrument comprises 19 items divided into four factors: goal-oriented selection (four items), loss compensation (seven items), outcome optimization (six items), and ability-based optimization (two items).
Of the seven items removed due to communalities below .5 in the exploratory factor analysis, many share characteristics with SOC strategies commonly employed by older adults. These include seeking advice or assistance from others and turning to rest and physical care when confronted with limitations. Notably, middle age is a life stage marked by substantial roles and responsibilities, making individuals particularly susceptible to adverse life events and disabilities [
20]. Additionally, middle-aged people are charged with contributing to societal productivity and guiding the next generation, a concept known as generativity strivings [
21]. Consequently, productivity may facilitate a smoother transition for middle-aged individuals into a fulfilling old age. This pursuit can be viewed not as an event to be dreaded but rather as a proactive strategy to be embraced.
Factor 1, goal-oriented selection, includes four items and accounts for 20.1% of the observed variance. This factor relates to the methods used to pursue goals. In this context, “selection” is operationally defined as narrowing the scope of activities to areas in which high performance can be maintained, while disregarding other areas, as one grows older and experiences decline [
6]. In the elderly, selection typically involves emphasizing or identifying goals from available options in response to limited personal resources [
10]. However, unlike the elderly, who restrict their range of activities or exclude certain possibilities, late middle-aged women appear to opt to exhibit productivity through role fulfillment, while considering both present and future circumstances and setting priorities accordingly.
Factor 2, loss compensation, includes seven items and explains 18.7% of the variance. The items relate to approaches for addressing problems, such as difficulties in maintaining routine tasks. Compensation strategies include actions taken to mitigate the consequences of the biological and social impairments associated with aging [
6]. Research indicates that late middle-aged women also adopt compensatory actions in response to changes and losses [
22], and positive expectations about aging may alleviate aging anxiety among these women by addressing psychological elements. Factor 2 is characterized by various compensatory behaviors that individuals adopt to manage age-related changes. In Sohn’s research [
10], which developed the short form of the SOC strategy scale for the elderly, compensation strategies involved seeking help from others or relying on faith. However, the present study reveals that late middle-aged women are distinct in their proactive approach to achieving goals through various challenging behavior strategies, such as focusing on work, establishing an optimal environment, collaborating with others, and unflinchingly engaging in new attempts. Notably, the items identified in this study include social relationship elements, such as “When things do not go as before, I collaborate with people who share the same goals.” This departs both from previous research that used structural equations to analyze SOC strategy relationship factors, in which social relationship variables were not considered [
23], and from SOC strategy scales for the elderly that lacked social relationship items [
7,
9,
10]. Social activities have been identified as a key component of successful aging in elderly individuals, positively impacting adaptability and resilience during crises through interactions with others [
24]. For late middle-aged women facing the onset of aging, maintaining social activities and employing SOC strategies that involve social relationships are of even greater importance. This finding aligns with previous research [
25] indicating that sustaining social relationships based on one’s social network can support life satisfaction, improve well-being, and increase productivity during middle age.
Factor 3, outcome optimization, comprises six items and accounts for 18.0% of the variance. These items primarily concern the adjustment of situations or psychological attitudes, as well as physical responses, to achieve the best results possible. Demonstrating a positive attitude and effectively managing stress are considered essential during middle age. This life stage is characterized by tasks associated with developing self-confidence, building personal skills, and fostering competence and positivity through broad social experiences [
20]. The items pertaining to physical responses for outcome optimization suggest that adapting to physical changes is a key aspect for late middle-aged women. This finding corroborates research suggesting that cognitive function and functional health status are directly linked to successful aging in the elderly [
23]. Middle age is often portrayed as a time of crisis due to the onset of physical decline and a reduction in abilities, which are not encountered in earlier developmental stages [
13].
Factor 4, ability-based optimization, includes two items and explains 10.2% of the variance. This factor pertains to the strategic maximization of capabilities to fully realize one’s potential and maintain personal efficiency. The items include statements such as “I would like to further develop myself by learning the latest technologies along with the skills I already possess” and “I establish strategies to maximize my abilities.” These reflect the notion of ability-based optimization among late middle-aged women, as informed by their experiences.
This study has several limitations. First, the validity of the developed scale was assessed using exploratory factor analysis alone, without the support of confirmatory factor analysis. Second, the generalizability of the study results is limited, as participants were recruited through an online link posted on the websites of regional institutions. Therefore, follow-up studies are necessary to confirm the validity of the developed scale. Finally, this study focused on creating an SOC strategy scale tailored to late middle-aged women. Future research should aim to broaden the scope by developing measurement tools for various life stages and for both men and women.
The SOC strategy scale developed in this study facilitates an objective assessment of the aging process in late middle-aged women, who are experiencing menopausal symptoms and approaching old age. Furthermore, since SOC strategy scales for successful aging were previously available only for the elderly, this instrument can provide fundamental data supporting interventions to promote the successful aging of late middle-aged women.