• Women's Health Nursing
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• v.2 no.2
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• pp.298-331
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• 1996

Recent improvements in living standard and development in medical care led to an increased interest in life expectancy and personal health, and also led to a more demand for higher quality of life. Thus, the problem of women's health draw a fresh interest nowadays. Since late-middle aged women experience various physical and socio-psychological changes and tend to have chronic illnesses, these women have to take initiatives for their health control by realizing their own responsibility. The basic elements for a healthy life of these women are understanding of their physical and psychological changes and acceptance of these changes. Health promoting behaviors of an individual or a group are actions toward increasing the level of well-being and self-actualization, and are affected by various variables. In Pender's health promoting model, variables are categorized into cognitive factors(individual perceptions), modifying factors, and variables affecting the likelihood for actions, and the model assumes the health promoting behaviors are affected by cognitive factors which are again affected by demographic factors. Since Pender's model was proposed based on a tool broad conceptual frame, many studies done afterwards have included only a limited number of variables of Pender's model. Furthermore, Pender's model did not precisely explain the possibilities of direct and indirect paths effects. The objectives of this study are to evaluate Pender's model and thus propose a model that explains health promoting behaviors among late-middle aged women in order to facilitate nursing intervention for this group of population. The hypothetical model was developed based on the Pender's health promoting model and the findings from past studies on women's health. Data were collected by self-reported questionnaires from 417 women living in Seoul, between July and November 1994. Questionnaires were developed based on instruments of Walker and others' health promotion lifestyle profile, Wallston and others' multidimensional health locus of control, Maoz's menopausal symptom check list and Speake and others' health self-rating scale. IN addition, items measuring self-efficacy were made by the present author based on past studies. In a pretest, the questionnaire items were reliable with Cronbach's alpha ranging from .786 to .934. The models for health promoting behaviors were tested by using structural equation modelling technique with LISREL 7.20. The results were summarized as follows : 1. The overall fit of the hypothetical model to the data was good (chi-square=4.42, df=5, p=.490, GFI=.995, AGFI=.962, RMSR=.024). 2. Paths of the model were modified by considering both its theoretical implication and statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data (chi-square =4.55, df=6, p=.602, GFI=.995, AGFI=.967, RMSR=.024). 3. The results of statistical testing were as follows : 1) Family function internal health locus of control, self-efficacy, and education level exerted significant effects on health promoting behaviors(${\gamma}_{43}$=.272, T=3.714; ${\beta}_[41}$=.211, T=2.797; ${\beta}_{42}$=.199, T=2.717; ${\gamma}_{41}$=.136, T=1.986). The effect of economic status, physical menopausal symptoms, and perceived health status on health promoting behavior were insignificant(${\gamma}_{42}$=.095, T=1.456; ${\gamma}_{44}$=.101, T=1.143; ${\gamma}_{43}$=.082, T=.967). 2) Family function had a significance direct effect on internal health locus of control (${\gamma}_{13}$=.307, T=3.784). The direct effect of education level on internal health locus of control was insignificant(${\gamma}_{11}$=-.006, T=-.081). 3) The directs effects of family functions & internal health locus of control on self-efficacy were significant(${\gamma}_{23}$=.208, T=2.607; ${\beta}_{21}$=.191, T=2.2693). But education level and economic status did not exert a significant effect on self-efficacy(${\gamma}_{21}$=.137, T=1.814; ${\beta}_{22}$=.137, T=1.814; ${\gamma}_{22}$=.112, T=1.499). 4) Education level had a direct and positive effect on perceived health status, but physical menopausal symptoms had a negative effect on perceived health status and these effects were all significant(${\gamma}_{31}$=.171, T=2.496; ${\gamma}_{34}$=.524, T=-7.120). Internal health locus and self-efficacy had an insignificant direct effect on perceived health status(${\beta}_{31}$=.028, T=.363; ${\beta}_{32}$=.041, T=.557). 5) All predictive variables of health promoting behaviors explained 51.8% of the total variance in the model. The above findings show that health promoting behaviors are explained by personal, environmental and perceptual factors : family function, internal health locus of control, self-efficacy, and education level had stronger effects on health promoting behaviors than predictors in the model. A significant effect of family function on health promoting behaviors reflects an important role of the Korean late-middle aged women in family relationships. Therefore, health professionals first need to have a proper evaluation of family function in order to reflect the family function style into nursing interventions and development of strategies. These interventions and strategies will enhance internal health locus of control and self-efficacy for promoting health behaviors. Possible strategies include management of health promoting programs, use of a health information booklets, and individual health counseling, which will enhance internal health locus of control and self-efficacy of the late-middle aged women by making them aware of health responsibilities and value for oneself. In this study, an insignificant effect of physical menopausal symptoms and perceived health status on health promoting behaviors implies that they are not motive factors for health promoting behaviors. Further analytic researches are required to clarify the influence of physical menopausal symptoms and perceived health status on health promoting behaviors with-middle aged women.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.