ABSTRACT
Objective:
Elderly people’s success in attaining rehabilitation goals may be heavily dependent on their achievement motive, but research has not identified the factors that impact on achievement motive or suggested any effective interventions to enhance it. This study demonstrated the effects of personality traits, theories of intelligence, and other factors on achievement motive among community-dwelling elderly people.
Methods:
The dataset consisted of questionnaire responses from 281 elderly people in day-service or day-care centers. A hypothetical model, based on previous research, proposed that achievement motive would be affected by personality traits, theory of intelligence, and other factors (such as drinking and smoking habits, going out for activities, marital status, and hobbies); that personality traits would have some effect on the theory of intelligence and other factors; and that the theory of intelligence would affect personal factors. The hypothetical model was analyzed using a structural equation modeling approach.
Results:
The model was modified by removing statistically insignificant paths to achievement motive. The modified model exhibited an excellent fit and showed that achievement motive was affected by personality traits, going out for activities, and marital status (although, surprisingly, single people had stronger achievement motive). The model had an adjusted R2 of 0.593 (P < 0.001) for achievement motive.
Conclusion:
The results indicated that three of the Big Five personality traits (extraversion, conscientiousness, and openness to experience) tend to enhance elderly people’s motivation to achieve their goals; moreover, going out more frequently and being single were also associated with achievement motive.
Keywords: achievement motive, community-dwelling elderly people, personality traits, rehabilitation
INTRODUCTION
Achievement motive is a significant factor to consider in the assessment of clients and in the planning of interventions with clients during rehabilitation.1,2,3,4) It is defined as “the intention to achieve one’s goals while maintaining a standard of excellence.”5) According to the World Health Organization, the rehabilitation of people with disabilities is “a process aimed at enabling them to reach and maintain their optimal physical, sensory, intellectual, psychological and social functional levels. Rehabilitation provides disabled people with the tools they need to attain independence and self-determination.”6) Therefore, rehabilitation always involves helping clients to achieve their personal goals, and achievement motive is necessary for clients to take the initiative in their recovery process.
To evaluate the intensity of an individual’s achievement motive, the Scale for Achievement Motive in Rehabilitation (SAMR) has been developed (Table 1).5,7) The SAMR is a self-report questionnaire that focuses on activities unique to rehabilitation; it has a two-factor structure: (1) self-mastery-derived achievement motive and (2) means/process-oriented achievement motive. Self-mastery-derived motive refers to making an effort to enhance one’s own abilities and intelligence; means/process-oriented motive emphasizes the willingness to follow a rehabilitation program to achieve one’s goals.5) In previous studies, achievement motive has been shown to affect various outcomes such as health-related quality of life, purpose in life, social participation, and self-efficacy.7,8,9) However, few studies have sought to identify factors that can influence achievement motive. Consequently, the possibilities for effective intervention in this regard remain to be elucidated.
Table 1. Scale for Achievement Motive in Rehabilitation (SAMR).
| Item of SAMR | |
| 1) | I think that I can overcome any difficulties to achieve my goal. |
| 2) | I like planning ingenious tactics. |
| 3) | I do not accept to cease making an effort until I am satisfied. |
| 4) | I think that I make more efforts than others. |
| 5) | I do not spare any effort to recover earlier than others. |
| 6) | I want to work on a goal accepted by people around me. |
| 7) | I want to choose the rehabilitation that satisfies me most. |
| 8) | I think that it is important to rehabilitate by myself. |
| 9) | I want to work on rehabilitation that experts recommend is most effective. |
| 10) | I want to give top priority to the rehabilitation that is most suitable for me. |
Reproduced from reference 7, supplemental information 2.
Traditionally, achievement motive has been addressed by psychological studies of personalities, and achievement motive is considered to be high in people who are enthusiastic about achieving their goals and being successful.10,11) Recent research on personality traits has identified the so-called Big Five personality trait dimensions—extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience—as a robust, clear, and internationally useful analytical model.12) Several studies conducted in different countries on the relationship between personality and achievement motive found that achievement motive was positively related to three of the Big Five traits: extraversion, conscientiousness, and openness to experience.12,13,14,15)
Additionally, it is likely that achievement motive is interrelated with one’s theory of intelligence, a theory that seeks to understand the nature of personal abilities and to predict whether individuals will be oriented toward developing or documenting the adequacy of their abilities.16,17) In particular, belief in the incremental theory (according to which intelligence is malleable and can be developed) tends to make individuals more mastery-oriented and more likely to seek to improve their ability. In these individuals, good performance revitalizes interest in achievement.18) Moreover, several studies have suggested that low achievement motive is related to socially maladjusted behaviors such as drug use among adolescents and to drinking and smoking among inpatients.19,20,21)
However, little research has been carried out on the motives of community-dwelling elderly people. Consequently, the present study was designed to demonstrate the effects of personality traits, one’s theory of intelligence, and other personal factors (such as drinking and smoking habits, going out for activities, marital status, and hobbies) on the achievement motive of community-dwelling elderly people.
We devised a hypothetical model (Fig. 1) based on previous reports.12,13,14,15,18,19,21) It contains the following features: (1) achievement motive is affected by personality traits, theory of intelligence, and personal factors; (2) personality traits influence theory of intelligence and personal factors; and (3) theory of intelligence has some effect on personal factors. Additionally, gender, age, and nursing care levels were examined as covariates to determine whether these factors had an effect on all other variables.
Fig. 1.
The hypothesized model. Ovals represent latent variables (achievement motive, personality, intelligence, and covariance) and rectangles represent observed variables (drinking, smoking, marriage, hobby, and going out). The individual items for the measurement scales are omitted for clarity.
METHODS
Ethics Statement
Data collection conformed to the Declaration of Helsinki and the policies of the Ethics Committee of Kibi International University (Nos. 13–34). In addition, we obtained approval from the facility directors of the institutions that cooperated in this study. Participants had the right to withdraw from the study at any time for any reason. Participants indicated their informed consent by completing questionnaires and placing them in a box or submitting them to the study staff.
Participants
Participants were elderly people attending 11 day-care centers or institutions offering day-service. We excluded those who had been diagnosed with mental disorders such as schizophrenia and dementia, those who demonstrated clinical decline in cognitive functioning, and those who could not read the questionnaire forms or write their responses. We distributed the questionnaires to 304 subjects and excluded the datasets of participants who refused to answer during the study or who did not answer all items of any scales. The final dataset contained responses from 281 subjects (valid response rate: 92.4%), of whom 127 (45.2%) were men and 154 (54.8%) were women. The characteristics of the participants are summarized in Table 2.
Table 2. Characteristics of the 281 participants.
| Category | Class | n | Percentage |
| Gender | Male | 127 | 45.2% |
| Female | 154 | 54.8% | |
| Age: mean ± SD (range) | 77.1 ± 8.7 | (48–95) | |
| Disease | Orthopedic | 111 | 39.5% |
| Neurological | 108 | 38.4% | |
| Heart | 5 | 1.8% | |
| Others | 29 | 10.3% | |
| Unknown | 28 | 10.0% | |
| Care Level | Care5 | 0 | 0.0% |
| Care4 | 8 | 2.8% | |
| Care3 | 23 | 8.2% | |
| Care2 | 74 | 26.3% | |
| Care1 | 65 | 23.1% | |
| Support2 | 59 | 21.0% | |
| Support1 | 48 | 17.1% | |
| Nothing | 0 | 0.0% | |
| Unknown | 4 | 1.4% | |
| Drinking | Nothing | 197 | 70.1% |
| Once a month | 20 | 7.1% | |
| Once a week | 20 | 7.1% | |
| Every day | 38 | 13.5% | |
| Unknown | 6 | 2.1% | |
| Smoking | Smoker | 15 | 5.3% |
| Nonsmoker/abstainer | 263 | 93.6% | |
| Unknown | 3 | 1.1% | |
| Marriage | Married | 262 | 93.2% |
| Unmarried/divorced | 12 | 4.3% | |
| Unknown | 7 | 2.5% | |
| Going out: mean ± SD (range) | 4.0 ± 3.0 | (0–30) | |
| Hobby: mean ± SD (range) | 1.4 ± 1.3 | (0–11) | |
| Intelligence | Entity | 174 | 61.9% |
| Incremental | 105 | 37.4% | |
| Unknown/missing | 2 | 0.7% | |
Questionnaires
Demographic Information
The questionnaire covered the following demographic information: gender, age, the name of the primary illness or disease, nursing care level (needing care: 1–5, needing support: 1,2, or nothing), frequency of drinking alcohol (every day = 4, once a week = 3, once a month = 2, never = 1), smoking habits (current smoker, past smoker, or nonsmoker), marital status (married, unmarried, or divorced), number of times the subject went out each week, and hobbies in which the subject participated. Nursing care is funded by a long-term care insurance system in Japan. Subjects are evaluated by the municipal certification committee and allocated an appropriate level of long-term care (needing care 1–5) or support (needing support) based on their needs.
Achievement Motive
Achievement motive was measured using the SAMR, in which respondents allocate a score on a 7-point Likert scale [ranging from 1 (strongly disagree) to 7 (strongly agree)] for 10 self-rated items.5,22) The SAMR is based on a two-factor structure. Items 1–6 in our SAMR covered self-mastery issues (e.g., “I think that I can overcome any difficulty to achieve my goal”); items 7–10 covered means/process-oriented issues (e.g., “I want to choose the rehabilitation program that satisfies me most”). Total scores could be converted to a standardized scale, and higher standardized scores represent stronger achievement motive.
Personality Traits
Personality traits were measured using the Japanese version of the Ten Item Personality Inventory (TIPI-J) in which respondents indicate self-ratings on 10 items.23) This instrument also used a 7-point Likert scale ranging from 1 (completely disagree) to 7 (strongly agree). The TIPI-J is based on the assumption that most individual differences in human personality can be classified along five dimensions (the Big Five): extraversion (items 1 and 6), agreeableness (Items 2 and 7), conscientiousness (items 3 and 8), neuroticism (items 4 and 9), and openness to experience (items 5 and 10). Items 2, 6, 8, 9, and 10 of the TIPI-J were reverse-scored so that higher ratings reflected a greater amount of the trait. Examples of the items are as follows: for agreeableness, “sympathetic” and “warm”; for conscientiousness, “dependable” and “self-disciplined.”
Theory of Intelligence
The theory of intelligence held by an individual was measured by a three-item questionnaire: (1) “You have a certain amount of intelligence and you really can’t do much to change it,” (2) “Your intelligence is something about you that you can’t change very much,” and (3) “You can learn new things, but you can’t really change your basic intelligence.”17,18) These items have a 6-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree), with respondents indicating self-ratings. Those participants who believe that intelligence is fixed (entity theorists) should have a total score of 11 or greater, whereas participants who believe that intelligence is malleable (incremental theorists) should score 10 or less. The assignment to one of the two theories was converted to a dummy variable such that entity theorists had a score of 1 and incremental theorists had a score of 0.
Statistical Methods
Descriptive statistics were obtained and normality testing was conducted using SPSS Statistics version 22 (www-01.ibm.com/software/jp/analytics/spss/products/statistics/). Tests of item responses, structural validity, and structural relationships were conducted using Mplus version 7.2 (www.statmodel.com).
Descriptive Statistics
To observe overall patterns, the number of answers and response frequencies (%) for each choice on each item were examined. In addition, for each item, for subscale scores, and for total SAMR and TIPI-J scores, descriptive statistics were calculated, including the mean, standard deviation (SD), skewness, and kurtosis. The Kolmogorov–Smirnov test was used as a test of normality.
Item Responses and Structural Validity
Item responses and structural validity were analyzed for the SAMR and TIPI-J results to verify that the items and the factor structure of the scales used in this study were appropriate for this group of participants.
First, we applied item response theory (IRT) with a two-parameter logistic model using maximum likelihood with robust standard errors (MLR) with missing data to examine item discrimination and difficulty in the degree for each SAMR and TIPI-J item. IRT refers to a set of mathematical models that describe, in probabilistic terms, the relationship between a person’s response to a survey question and his or her level of the “latent variable” being measured by the scale.24) The equation for the two-parameter logistic model is
| Pj(θ)=1/(1+e−L)=1/{1+e[−1.702*aj(θ−bj)]} |
where aj is the item discrimination and bj is the item difficulty.25,26) Item discrimination indicates how well items identify respondents at different levels of the latent trait and is capable of unlimited range, but the standard range is between 0.5 and 2.5.24,25,26) The item difficulty indicates how difficult it is to achieve a 0.5 probability of a correct response for a specific item given the respondent’s level of the latent variable and is capable of unlimited range; however, the standard range is between –4.0 and 4.0.24,25,26) A higher value for item difficulty means that the item is more difficult to respond to.24) With regard to item discrimination or item difficulty, if some items proved not to be appropriate (i.e., fell outside these standard ranges), the items would be candidates for removal from the analysis.24,25) After removing such items, we performed IRT analysis again.
Second, we analyzed the factor structure of the SAMR and TIPI-J results using confirmatory factor analysis (CFA) with a structural equation modeling (SEM) approach27) for the participants in this study. The factor structure of each scale was examined using the items that met the requirements of the IRT approach and was based on the same factor structure as that used in the previous studies.5,22,23) We used the MLR with missing data for SAMR and the modified weighted least squares method (WLSMV) with missing data for TIPI-J. We applied several goodness-of-fit indices: the comparative fit index (CFI), the Tucker–Lewis index (TLI), and the root mean square error of approximation (RMSEA) with 90% confidence interval (CI). CFI and TLI values greater than 0.9 indicate a good model fit. For RMSEA, values ≤ 0.05 indicate a close fit, those between 0.05 and 0.08 indicate a reasonable fit, and those ≥ 0.1 indicate a poor fit.28)
Structural Relationships
Our hypothetical model was analyzed using a multiple indicator multiple cause model and an SEM approach. We used the WLSMV with missing data and again applied several fit indices, i.e., CFI, TLI, and RMSEA with 90% CI. The standard of the best model fit was the same as that for the CFA analysis. The adjusted R2 value was calculated based on latent variables or observation variables in the perceived path and was used as the coefficient of determination, indicating which percentage of the variance in these variables is explained by the combination of the intercept and slope. The R2 values for these variables, ranging between 0 and 1, explain a certain amount of information in the target variable.
RESULTS
Descriptive Statistics
Descriptive statistics for the SAMR and TIPI-J results are given in Table 3. All items and scores were found to be non-normal according to the Kolmogorov–Smirnov test, but there were no extreme deviations.
Table 3. Descriptive statistics and IRT analysis results.
| Descriptive statistics | Item response theory | |||||||||
| Mean | SD | Skewness | Kurtosis | Normality | Discrimination | Difficulty | Discrimination | Difficulty | ||
| SAMR | ||||||||||
| Item1 | 5.13 | 1.39 | –0.86 | 0.87 | 0.00 | 1.04 | –2.68 to 1.31 | |||
| Item2 | 5.09 | 1.33 | –0.76 | 1.01 | 0.00 | 1.01 | –2.84 to 1.32 | |||
| Item3 | 5.14 | 1.42 | –0.66 | 0.31 | 0.00 | 1.26 | –2.70 to 1.04 | |||
| Item4 | 4.72 | 1.44 | –0.54 | 0.23 | 0.00 | 1.55 | –2.11 to 1.44 | |||
| Item5 | 5.30 | 1.37 | –0.70 | 0.45 | 0.00 | 1.75 | –2.80 to 0.79 | |||
| Item6 | 4.75 | 1.39 | –0.34 | 0.12 | 0.00 | 1.28 | –2.71 to 1.41 | |||
| Item7 | 5.79 | 1.28 | –1.24 | 1.90 | 0.00 | 1.26 | –2.57 to 0.35 | |||
| Item8 | 5.51 | 1.30 | –0.97 | 1.04 | 0.00 | 0.99 | –3.20 to 0.83 | |||
| Item9 | 5.76 | 1.34 | –1.16 | 1.22 | 0.00 | 1.04 | –2.89 to 0.33 | |||
| Item10 | 4.71 | 1.64 | –0.49 | –0.30 | 0.00 | 0.64 | –2.87 to 1.64 | |||
| Self-mastery | 30.04 | 6.66 | –0.78 | 1.47 | 0.00 | |||||
| Means/process | 21.75 | 4.32 | –1.01 | 1.82 | 0.00 | |||||
| Total score | 51.80 | 9.98 | –0.82 | 1.56 | 0.03 | |||||
| TIPI-J | TIPI–J (after item elimination) | |||||||||
| Item1 | 4.61 | 1.53 | –0.58 | –0.03 | 0.00 | 1.19 | –2.03 to 1.83 | 1.45 | –1.89 to 1.70 | |
| Item2 | 5.54 | 1.44 | –0.62 | –0.67 | 0.00 | 0.01 | –244.70 to 24.61 | |||
| Item3 | 4.18 | 1.35 | –0.12 | 0.07 | 0.00 | 1.01 | –2.50 to 2.41 | 0.88 | –2.71 to 2.58 | |
| Item4 | 4.10 | 1.63 | –0.27 | –0.67 | 0.00 | 0.00 | 338.14 to –382.57 | |||
| Item5 | 4.12 | 1.51 | –0.26 | –0.26 | 0.00 | 0.74 | –2.46 to 2.72 | 0.78 | –2.39 to 2.64 | |
| Item6 | 3.92 | 1.53 | 0.48 | –0.38 | 0.00 | 0.07 | –34.21 to 19.61 | |||
| Item7 | 5.06 | 1.11 | –0.78 | 1.57 | 0.00 | 0.58 | –4.70 to 3.01 | |||
| Item8 | 4.75 | 1.55 | –0.02 | –0.93 | 0.00 | 0.28 | –8.99 to 3.13 | |||
| Item9 | 3.42 | 1.31 | 0.60 | 0.41 | 0.00 | –0.56 | 3.72 to –3.98 | |||
| Item10 | 3.61 | 1.50 | 0.56 | –0.33 | 0.00 | 0.26 | –7.81 to 6.82 | |||
| Extraversion | 8.53 | 2.43 | 0.18 | 0.25 | 0.00 | |||||
| Agreeableness | 10.62 | 1.95 | –0.48 | 0.13 | 0.00 | |||||
| Conscientiousness | 8.91 | 2.17 | 0.13 | –0.15 | 0.00 | |||||
| Neuroticism | 7.51 | 2.25 | –0.10 | 0.12 | 0.00 | |||||
| Openness | 7.74 | 2.28 | 0.19 | 0.03 | 0.00 | |||||
Underlined values indicate to deviate from the standard range for item discrimination or item difficulty.
Item Responses and Structural Validity
Results of the IRT analysis of the SAMR and TIPI-J scores are shown in Table 3. All SAMR items had values within the standard range; however, for TIPI-J, items 2, 4, and 6–10 deviated from the standard range for item discrimination or item difficulty. A repeat analysis of the other three TIPI-J items (items 1, 3, and 5) yielded acceptable values (Table 3, section below the heading “After item elimination”). Therefore, CFA on the SAMR data was carried out without excluding any items, and CFA on the TIPI-J data was conducted excluding items 2, 4, and 6–10.
CFA on the SAMR data yielded the following values for the fit statistics (Table 4): CFI = 0.955, TLI = 0.941, RMSEA = 0.061, 90% CI [0.040, 0.081]. Moreover, CFA on the TIPI-J data with a one-factor structure from the three items indicated good fit statistics (Table 4): CFI = 1.000, TLI = 1.000, RMSEA = 0.000, 90% CI [0.000, 0.000]; this combined factor was named “extraversion, conscientiousness, openness.” The one-factor structure of the TIPI-J was applied to test structural relationships.
Table 4. CFA for SAMR and TIPI-J.
| Estimate | SE | Estimate/SE | P-Value | |||
| SAMR | ||||||
| Self-mastery | Item1 | 0.698 | 0.046 | 15.320 | 0.000 | |
| Item2 | 0.701 | 0.046 | 15.097 | 0.000 | ||
| Item3 | 0.770 | 0.036 | 21.172 | 0.000 | ||
| Item4 | 0.817 | 0.029 | 28.196 | 0.000 | ||
| Item5 | 0.807 | 0.033 | 24.192 | 0.000 | ||
| Item6 | 0.718 | 0.042 | 17.265 | 0.000 | ||
| Means/process | Item7 | 0.837 | 0.035 | 23.799 | 0.000 | |
| Item8 | 0.717 | 0.049 | 14.760 | 0.000 | ||
| Item9 | 0.740 | 0.057 | 13.048 | 0.000 | ||
| Item10 | 0.510 | 0.068 | 7.464 | 0.000 | ||
| Fit index: CFI = 0.955, TLI = 0.941, RMSEA = 0.061, 90% IC [0.040, 0.081] | ||||||
| Correlation coefficient | ||||||
| Factor correlation | Mastery, means | 0.768 | 0.055 | 14.004 | 0.000 | |
| TIPI-J | ||||||
| Extraversion | Item1 | 0.809 | 0.052 | 15.662 | 0.000 | |
| Conscientiousness | Item3 | 0.591 | 0.053 | 11.199 | 0.000 | |
| Openness | Item5 | 0.553 | 0.046 | 11.994 | 0.000 | |
| Fit index: CFI = 1.000, TLI = 1.000, RMSEA = 0.000,90% IC [0.000,0.000] | ||||||
Estimate data represent factor loadings (standardized path coefficients) for each item, and factor correlations among factors of each scale.
Structural Relationships
Table 5 gives all parameter estimates based on the hypothesized model. Although the fit indices of the hypothesized model exhibited an excellent fit (CFI = 0.976, TLI = 0.969, RMSEA = 0.048, 90% CI [0.038, 0.058]), the paths of personality traits and covariates had a large number of statistically insignificant standardized path coefficients. Therefore, the paths with no statistical relationship to achievement motive were eliminated sequentially, and the modified model was run again using the SEM approach. Consequently, the fit indices of the modified model exhibited an excellent fit: CFI = 0.976, TLI = 0.972, RMSEA = 0.045, 90% CI [0.035, 0.055] (Fig. 2).
Table 5. Structural relationships of the hypothesized model.
| Two-tailed | Estimate | SE | Estimate/SE | P-Value | |
| Achievement motive By | |||||
| Self-mastery | 0.964 | 0.036 | 27.095 | 0.000 | |
| Means/process | 0.811 | 0.033 | 24.562 | 0.000 | |
| Achievement motive On | |||||
| Gender (Male) | –0.013 | 0.112 | –0.118 | 0.906 | |
| Age | –0.027 | 0.066 | –0.404 | 0.686 | |
| Nursing care level | 0.019 | 0.067 | 0.288 | 0.773 | |
| Personality | 0.719 | 0.063 | 11.468 | 0.000 | |
| Intelligence (entity) | 0.012 | 0.073 | 0.165 | 0.869 | |
| Drinking | 0.016 | 0.082 | 0.196 | 0.845 | |
| Smoking | 0.070 | 0.109 | 0.645 | 0.519 | |
| Marriage | –0.035 | 0.083 | –0.428 | 0.669 | |
| Going out | 0.080 | 0.052 | 1.534 | 0.125 | |
| Hobby | 0.045 | 0.060 | 0.751 | 0.452 | |
| Personality On | |||||
| Gender (male) | –0.091 | 0.080 | –1.133 | 0.257 | |
| Age | 0.046 | 0.076 | 0.608 | 0.543 | |
| Nursing care level | –0.099 | 0.078 | –1.257 | 0.209 | |
| Intelligence (entity) On | |||||
| Gender (male) | 0.179 | 0.074 | 2.423 | 0.015 | |
| Age | 0.082 | 0.075 | 1.096 | 0.273 | |
| Nursing care level | 0.108 | 0.074 | 1.470 | 0.142 | |
| Personality | 0.334 | 0.079 | 4.236 | 0.000 | |
| Drinking On | |||||
| Gender (male) | 0.465 | 0.070 | 6.592 | 0.000 | |
| Age | –0.160 | 0.076 | –2.114 | 0.034 | |
| Nursing care level | 0.170 | 0.079 | 2.157 | 0.031 | |
| Personality | 0.114 | 0.076 | 1.500 | 0.134 | |
| Smoking On | |||||
| Gender (male) | 0.617 | 0.136 | 4.525 | 0.000 | |
| Age | 0.168 | 0.109 | 1.540 | 0.124 | |
| Nursing care level | 0.161 | 0.130 | 1.244 | 0.214 | |
| Personality | –0.058 | 0.111 | –0.520 | 0.603 | |
| Marriage On | |||||
| Gender (male) | 0.186 | 0.144 | 1.287 | 0.198 | |
| Age | 0.061 | 0.159 | 0.382 | 0.702 | |
| Nursing care level | –0.064 | 0.148 | –0.432 | 0.666 | |
| Personality | –0.173 | 0.111 | –1.564 | 0.118 | |
| Going out On | |||||
| Gender (male) | 0.101 | 0.074 | 1.359 | 0.174 | |
| Age | 0.011 | 0.096 | 0.113 | 0.910 | |
| Nursing care level | 0.044 | 0.088 | 0.501 | 0.617 | |
| Personality | 0.067 | 0.057 | 1.177 | 0.239 | |
| Hobby On | |||||
| Gender (male) | 0.085 | 0.069 | 1.231 | 0.218 | |
| Age | –0.081 | 0.076 | –1.070 | 0.285 | |
| Nursing care level | 0.196 | 0.068 | 2.893 | 0.004 | |
| Personality | 0.248 | 0.062 | 4.006 | 0.000 | |
| Fit index: CFI = 0.976, TLI = 0.969, RMSEA = 0.048, 90% IC [0.038, 0.058] | |||||
"By" defines latent variables and "On" defines regression relationships. Variables for the scale items are omitted from the table.
Fig. 2.
Modified model using SEM. The fit indices for the model indicate an excellent fit: CFI = 0.976, TLI = 0.972, RMSEA = 0.045, 90% CI [0.035, 0.055]. The standardized path coefficients of achievement motive for the two factors of SAMR were restricted to 1. The values on the arrow lines are standardized path coefficients estimated using the SEM approach. The adjusted R2 value was used as the coefficient of determination. R2 values and the error terms are not given for each scale item to aid clarity. The underlined path coefficients are statistically significant at the 5% level, and those given in parentheses are slightly significant at the 10% level.
The results of the modified model indicated that the effects on achievement motive of personality traits, going out for activities, and marital status were statistically and slightly significant: for personality traits, estimate = 0.714, standard error (SE) = 0.059, estimate/SE = 12.199, P = 0.000; for going out, estimate = 0.130, SE = 0.061, estimate/SE = 2.133, P = 0.033; for marital status, estimate = –0.179, SE = 0.104, estimate/SE = –1.726, P = 0.084. Additionally, personality traits had significant effects on subjects’ theories of intelligence (estimate = 0.359, SE = 0.075, estimate/SE = 4.800, P = 0.000) and on hobbies (estimate = 0.224, SE = 0.065, estimate/SE = 3.477, P = 0.001). Gender (male) as a covariate factor had significant effects on theory of intelligence (estimate = 0.153, SE = 0.076, estimate/SE = 2.019, P = 0.043), on drinking (estimate = 0.471, SE = 0.070, estimate/SE = 6.749, P = 0.000) and on smoking (estimate = 0.606, SE = 0.135, estimate/SE = 4.480, P = 0.000). The modified model yielded R2 = 0.593 for achievement motive, 0.933 for self-mastery-derived, 0.652 for means/process-oriented, 0.281 for theory of intelligence, 0.368 for smoking, 0.221 for drinking, 0.041 for marital status, and 0.101 for hobbies.
DISCUSSION
The purpose of this study was to demonstrate the effects of various factors on the achievement motive of community-dwelling elderly people. The findings indicate that personality traits, going out for activities, and marital status have an appreciable effect on achievement motive.
These findings partly support our hypothesis. Achievement motive was affected by personality traits, the frequency of going out, and marital status. Personality traits also had some effect on the theory of intelligence and hobbies. Moreover, gender (male) as a covariate affected the theory of intelligence, smoking, and drinking. Furthermore, the results indicated that about 60% of achievement motive was attributable to all the variables examined in this study. In particular, personality traits (one factor composed of extraversion, conscientiousness, and openness) had the largest effect on achievement motive. This finding is consistent with previous studies that found these three of the Big Five dimensions to be associated with achievement motive.12–15 We consider that going out frequently leads participants to have greater opportunities to enjoy various stimuli and pleasures, thereby enhancing their desire to achieve their personal goals. Although we expected that a married person would be more motivated because of the presence of a partner and family members in his or her life, this prediction was not supported; on the contrary, the reverse was true. We conjecture that single people may have higher achievement motive due to the greater need to accomplish tasks themselves, such as self-care and housework.
In conclusion, this study demonstrated that three personality dimensions (which capture the traits of being outgoing and sociable, responsible and deliberate, and imaginative and curious) enhance people’s intention to achieve their rehabilitation goals. Moreover, going out more frequently and being single (either unmarried or divorced) also had a tendency to enhance achievement motive.
In contrast, theories of intelligence, drinking patterns, smoking experience, and three covariates (gender, age, and care level) were found to have no statistically significant effect on achievement motive in this study; this finding is not consistent with previous reports.16,17,19,21,29) Perhaps, the elderly participants in this study had fully established views of intelligence and had stable habits of drinking or smoking, so these factors may not have had much psychological impact.
Both the SAMR and TIPI-J were administered in this study, and the characteristics of individual items and a factor structure were established through CFA and the IRT approach to understand the achievement motive and the role of personality traits more rigorously. The results for SAMR item responses and structural validity indicated that all items on this scale had sufficient values for item discrimination and difficulty. Consequently, the same structure as that used in previous studies could be applied to this study. For the TIPI-J, it was necessary to eliminate some items that had insufficient values for item discrimination or difficulty. The remaining three items from the TIPI-J represented the dimensions of extraversion, conscientiousness, and openness to experience, and these items were sufficiently identified as reflecting respondents’ attributes. It is appropriate that the structural validity analysis of the TIPI-J interpreted the three personality traits as a one-factor structure because previous studies have indicated a significant correlation among multiple personality factors.22)
Limitations and Future Research Directions
This study has several limitations. Achievement motive was examined in this study as an unique construct in rehabilitation, which is slightly different from how it has been treated in previous studies.1,2,3,4,12,13,14,15) Also, about 40% of achievement motive was not attributable to any of the variables examined in this study; this portion of achievement motive could presumably be identified only through assessment interviews with individual patients as to the specific content and importance of their goals. In addition, personality traits and theories of intelligence represent characteristics and philosophies that are deeply ingrained and difficult to alter in an intervention. However, it is important that we understand the trait of achievement motive. The findings of this study indicate that it could be beneficial, from an early stage, to identify and support elderly people who have a tendency not to strive to achieve their goals. Given these considerations, it would be useful for future studies to examine the effect of particular interventions, selected based on the findings of this study and previous studies, in raising individuals’ achievement motive.
ACKNOWLEDGEMENTS
We are grateful to the participants, the research assistants at the cooperating facilities, and our colleagues in the laboratory for their support of this study.
This publication was supported by JSPS KAKENHI Grant Number JP16HP1002.
Footnotes
CONFLICT OF INTEREST: The authors declare that there are no conflicts of interest.
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