• Stigma Consciousness, Coping Strategies And Cd4 Counts Of Persons With Hiv/aids

  • CHAPTER TWO -- [Total Page(s) 5]

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    • CHAPTER TWO

      LITERATURE REVIEW


      Many literatures have discussed the psychological issues of HIV/AIDS indicating that stigma is attached to the illness, but few have considered the phenomenological experiences of people living with HIV/AIDS in relation to coping strategies they use that help them to improve their health. Perceived or felt stigma may lead to stigma consciousness. Stigma consciousness and coping strategies can influence immune system among PLWHA as indicated in their CD4 counts, and this is supported by immunocompetence model. This chapter opened with theoretical background on immunocompetence (the ability of immune system to protect the body at any time), and further concerned with the review of literature on the nature of HIV/AIDS; immune system, CD4 counts and HIV/AIDS; stigma; stigma consciousness; coping strategies, and finally empirical review.

       

      THEORETICAL BACKGROUND

       

      Immunocompetence model Psychoneuroimmunology literatures have implicated psychosocial variables in immune system functioning. Sarason and Sarason (2008) refer to psychoneuroimmunology as the study of three bodily systems-the nervous system, endocrine and immune system that can communicate through complex chemical signals. Psychosocial factors have connections with neural-immunologic systems that govern adaptive biological responses to stress (Jemmott, 1985), and other negative psychological conditions. According to Kiecolt-Glasser (2002), Sarason and Sarason (2008) it is possible that some people who exhibit severe emotional and behavioural abnormalities show psychoneuroimmunological abnormalities as well. It is also possible that high stigma consciousness in people living with HIV/AIDS that can bring about negative psychological conditions will affect immune system. However, the immune system has ability to protect the body from infections. This idea is the root to immunocompetence model. Immunocompetence is the ability of immune system to protect the body at any given time (Rice, 1998). Immunocompetence model was developed to concern with casual connections between psychosocial variables such as grief following loss of a loved one and biological variables such as immune efficiency (Jemmott & Locke, 1984). The model was based on the hypothesis that psychosocial stressors lower immune system efficiency, which leads to an increase in medical symptoms (either morbidity or mortality). The model further suggests that risk for disease, the course of illness, and remission of symptoms may all be related to the interaction of psychosocial factors with the potency of biological threat, for example CD4 cell. The implication is that immune system can be active and effective or suppressed and less effective depending on some psychosocial variables such as stigma consciousness and application of coping strategies. Stigma consciousness can spawn psychological devastations, which renders immune system less effective, and requires application of coping strategies.

       

      The possibility of stigma consciousness affecting immune system as indicated in CD4 counts may result from hormonal changes during the course of internalizing stigma. Scientists may wish to explore the relationship between stigma consciousness and hormonal changes.

       

      Several earlier studies are in line with the idea of immunocompetence model (e.g.Totman & Kiff, 1979; Kasl, Evans, Niederman, 1979). Even animal studies have been useful in this area of research (e.g.Sklar & Anisman, 1980; Ader, 1983; Bovbjerg, Cohen & Ader, 1987). Therefore, enough evidences have been established on the link between psychosocial variables and immune system.

       

      Thus, there is need to establish connection between stigma consciousness and coping strategies with immune system functioning using CD4 count as measure among seropositive individuals. This study tested the implications of psychosocial variables such as stigma consciousness, social support, information coping, and problem coping on CD4 counts, a measure of immune system among people living with HIV/AIDS.

       

      The nature of HIV/AIDS The acronym HIV/AIDS is derived from two concepts–Human Immunodeficiency Virus (HIV) and Acquired Immune Deficiency syndrome (AIDS). Acquired immune deficiency syndrome is diagnosed when infection with Human Immunodeficiency Virus (HIV) has caused a person’s immune system to go down to such extent that the individual begins to show marked conditions associated with various viruses, fungal infections, and parasites. These are organisms which people with healthy immune systems are able to repel successfully (Herek, 1990). Thus, HIV is the retrovirus that causes AIDS (Kalichman, 2003). Some researchers noted that HIV belongs to a class of retrovirus called lent viruses (lent means “slow” in Latin) for it develops slowly as it takes years before symptoms appear; and HIVvirus infects the immune system, that is, the very system that the body uses to repel infections (Doka, 1997; Duh, 1991; Kalichman, 2003). On infection, HIV targets a particular type of white blood cells named T-helper lymphocyte cells or T-helper cells (Doka, 1997), that is CD4 count cell. T-helper cells control several branches of the immune system. They act as the body’s army since they command other immune cells to fight and destroy possible causes of infections and diseases (Doka, 1997; Kalichman, 2003).

       

      As HIV infections last, it impairs the body’s ability to fight against many diseases by destroying T-helper cells. The immune system tries to control HIV by producing antibodies against the virus. Nevertheless, the efforts are only partly effective because HIV hides inside of T-helper cells, gradually infecting more and more cells until the entire immune system can no longer function (Doka, 1997; Kalichman, 2003). It has been observed that a person who is infected with HIV does not necessarily feel sick if he does not yet have AIDS and he can feel healthy for years (Berer, 1993; Squire, 1993).

       

      Thus, it can be palliatively managed just like many other diseases. AIDS is the later stage of HIV infection.

       

      The advancement from HIV stage to AIDS will depend on how fast the body’s immune system is affected (Duh, 1991), and the rate of destruction depends on the number of viruses versus the number and quality of T-cells (CD4 cell) in the body. This implies that a person is diagnosed with AIDS after immune system becomes disabled by HIV or when the person becomes seriously ill from diseases that take advantage of the broken-down immune system (Doka, 1997; Duh, 1991; Evian 1991; Kalichman, 2003). The transition from HIV to AIDS is fragile and difficult to determine, hence the two are considered together as HIV/AIDS. Thus, AIDS is the final phase of infection with HIV.

       

      There are three phases of the HIV/AIDS illness. The first phase has the HIV infection and often it is not noticed and remains silent. In the second phase of HIV/AIDS, the disease becomes more visible with a range of infectious diseases. The third phase is potentially the most damaging of all since it involves an illness of social, cultural and political dimensions, for example stigma, discrimination, and denial (Parker & Aggleton, 2002).

       

      Immune System, CD4 Counts and HIV/AIDS Immunity is the individual’s ability to resist or overcome the effects of diseases or harmful foreign agents. Immune system is vital to both psychological and biological functioning of the human body. Immune system is crucially important to living with HIV/AIDS. As a result of that, a regular part of HIV/AIDS health care involves having blood tests to monitor immune system’s response to ART (medication or diet) by PLWHA. One of the most common laboratory tests conducted is the CD4 cell count. The immune system of an individual living with HIV/AIDS is affected by the number of CD4 cell count present in the body. HIV/AIDS harms the body’s immune system by targeting and infecting the CD4 cells.

       

      CD4 cells are a type of white blood cell whose function in the body is to resist infection and protect the body from illness. The CD4 cells are a major part of the body’s natural first-line defense against illness (Mark, 2007). Once inside the CD4 cells, HIV/AIDS takes over the cells and turns them into what Mark referred to as virus factories within the body, making thousands of copies of itself in each cell. As the amount of virus grows, the original CD4 cell is damaged and eventually destroyed. HIV/AIDS at last kills so many of these cells that the immune system is weakened and the body is no longer able to defend itself against infections.

       

      To Mark (2007), a normal healthy person who is not infected with HIV/AIDS has a CD4 count of between 500 and 1600 cells. This number varies from day to day depending on the physical and emotional stressors on the body. HIV/AIDS infection causes both physical and emotional feelings; thereby reducing the CD4 cell counts of people concerned. For PLWHA, CD4 count declines gradually as HIV/AIDS kills more and more cells. The more CD4 cells a person has, the stronger the immune system is. A CD4 cell count above 500 indicates that the immune system is fairly intact and that the chances of becoming sick are minimal. As the CD4 cell count decreases, the chances of permanent immune system damage and of developing symptoms of HIV/AIDS diseases are increased.

       

  • CHAPTER TWO -- [Total Page(s) 5]

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    • ABSRACT - [ Total Page(s): 1 ]ABSTRACT The study examined the influence of stigma consciousness (a belief or feeling that one will be negatively stereotyped by others) and coping strategies (social support, information and problem) on the CD4 counts (measure of immune system) of People Living With HIV/AIDS (PLWHA) in Anambra state. 430 PLWHA (men=148 & women=282), age (M=35.73, SD=8.4) years served as participants. Three Anti Retroviral Therapy (ART) sites were randomly selected from the three senatorial zones of ... Continue reading---

         

      APPENDIX A - [ Total Page(s): 1 ]APPENDIX A QUESTIONNAIRES INSTRUCTIONS The statements below are intended to collect information on your relationships with other people including your doctor. Please read each statement and decide how you agree with the statement. The information is for research purpose only and shall not be used against you, so be honest in your response. For each statement, show your answer by indicating to the right of the item the number that describes your level of agreement. T ... Continue reading---

         

      APPENDIX C - [ Total Page(s): 1 ]APPENDIX CReliability test on social support scaleStatistics for Mean Variance Std Dev VariablesScale 45.3611 65.8373 8.1140 15Item Means Mean Minimum Maximum Range Max/Min Variance3.0241 1.7500 4.1111 2.3611 2.3492 .3727Item Variances Mean Minimum Maximum Range Max/Min Variance1.4874 .7071 2.3135 1.6063 3.2716 .1748Reliability Coefficients 15 itemsAlpha = .7084 Standardized item alpha = .6805Reliability****** Method 1 (space saver) will be used for this analysis ******R E L I A B I L I T Y A N ... Continue reading---

         

      APPENDIX B - [ Total Page(s): 1 ] APPENDIX BRELIABILITY TEST ON STIGMA CONSCIOUSNESS QUESTIONNAIRE N ofStatistics for Mean Variance Std Dev VariablesScale 34.1522 46.7541 6.8377 10Item Means Mean Minimum Maximum Range Max/Min Variance3.4152 2.9565 3.6087 .6522 1.2206 .0400Item Variances Mean Minimum Maximum Range Max/Min Variance1.4292 1.0957 1.6870 .5913 1.5397 .0482Reliability Coefficie ... Continue reading---

         

      APPENDIX D - [ Total Page(s): 1 ]APPENDIX DReliability test on information coping scaleN ofStatistics for Mean Variance Std Dev VariablesScale 18.1750 12.7635 3.5726 5Item Means Mean Minimum Maximum Range Max/Min Variance3.6350 3.2000 3.9750 .7750 1.2422 .0877Item Variances Mean Minimum Maximum Range Max/Min Variance1.2222 .8199 1.6513 .8314 2.0141 .1044Reliability Coefficients 5 itemsAlpha = .6515 Standardized item alpha = .6662Factor Analysis on information coping scale ... Continue reading---

         

      APPENDIX E - [ Total Page(s): 1 ]APPENDIX EReliability test on problem coping scaleN ofStatistics for Mean Variance Std Dev VariablesScale 30.4688 19.6119 4.4285 8Item Means Mean Minimum Maximum Range Max/Min Variance3.8086 3.2500 4.2813 1.0313 1.3173 .1430Item Variances Mean Minimum Maximum Range Max/Min Variance1.1274 .5313 1.8710 1.3397 3.5218 .1722Reliability Coefficients 8 itemsAlpha = .6173 Standardized item alpha = .6148Factor Analysis on problem coping scale ... Continue reading---

         

      TABLE OF CONTENTS - [ Total Page(s): 1 ]     TABLE OF CONTENTSTITLE PAGE                      CERTIFICATION PAGE                DEDICATION                             ACKNOWLEDGEMENT                TABLE OF CONTENTS                 LIST OF ILLUSTRATIONS           ABSTRACT                             CHAPTER 1Introduction                             Statement of the probl ... Continue reading---

         

      APPENDIX F - [ Total Page(s): 1 ]APPENDIX F4-Way Analysis of Variance of stigma consciousness, social support, information & problem copings on CD4 Counts. ... Continue reading---

         

      APPENDIX G - [ Total Page(s): 1 ]APPENDIX GANALYSIS OF COVARIATE (ANCOVA) RESULT OF STIGMA CONSCIOUSNESS, SOCIAL SUPPORT, INFORMATION COPING, PROBLEM COPING WITH TREATMENT AS COVAVRIATE. ... Continue reading---

         

      APPENDIX H - [ Total Page(s): 1 ]APPENDIX HRESULTS OF MULTIVARIATE ANALYSIS OF VARIANCE OF COGNITIVE THERAPY ON STIGMA CONSCIOUSNESS, SOCIAL SUPPORT, INFORMATION, & PROBLEM COPINGS. ... Continue reading---

         

      CHAPTER ONE - [ Total Page(s): 3 ]that can infest anybody and decide to seek information on treatment, intervention, and supports whereas others may perceive it as an end to life and become hopeless. According to Carver (1998, as cited in Chukwudozie, 2008) such differences in perception could be among the strongest determinants of how individuals fare in situations of stressful or life-threatening experience, for example living with HIV/AIDS. These may determine how PLWHA fare with regards to their health as measured by ... Continue reading---

         

      CHAPTER THREE - [ Total Page(s): 3 ]information coping, and problem coping at a stretch. Four-way analysis of variance is appropriate statistic for a complex design study that adopts 2 X 2 X 2 X 2 - factorial design.   In the second analysis, analysis of covariate (ANCOVA) was used and treatment was entered as a covariate. Hinkle, Wiersma and Jurs (1998) stated two assumptions and their alternative for using ANCOVA as statistical control. The conditions are that relationship between the dependent variable and indepe ... Continue reading---

         

      CHAPTER FOUR - [ Total Page(s): 3 ] x=results of non significant interaction effects not included (see appendix G).   The results of analysis of covariate revealed that treatment produce significant main effect on CD4 counts of PLWHA, F(1,413) = 5.79, P =.02. Similarly, stigma consciousness was significant in influencing CD4 counts of PLWHA, F(1,413) = 36.83, P = .001. Also, social support produced significant real effect on CD4 counts of PLWHA, F(1,413) = 28.35, P =.001. Information coping was also significant, ... Continue reading---

         

      CHAPTER FIVE - [ Total Page(s): 2 ]Furthermore, this study found that there was strong evidence to support that problem coping exerts influence on immunity of people living with HIV/AIDS. Those people living with HIV/AIDS that focus on problem tended towards having more immunity when their CD4 counts were compared with those who avoid problem. The implication is that focusing on problem is beneficial to people living with HIV/AIDS. People living with HIV/AIDS should focus on problem by following plans of actions as provide ... Continue reading---

         

      REFRENCES - [ Total Page(s): 3 ]Scott-Sheldon, L.A.J., Kalichman, S.C., Carey, M.P. & Fielder, R.L. (2008). Stress Management Interventions for HIV + Adults: A meta-Analysis of Randomized Controlled Trials, 1989 to 2006. Health Psychology, 27, 2, 129 – 139.   Seeman, T.E., & Syme, S.L. (1989). Social networks and coronary artery disease: A comparison of the structure and function of social relations as predictions of diseases. Psychosomatic medicine, 49, 381 – 400.   Siegel, K., Howard, L., ... Continue reading---