Journal of Education and Health Promotion

: 2019  |  Volume : 8  |  Issue : 1  |  Page : 192-

Antiretroviral therapy adherence based on information, motivation, and behavioral skills model and its association with depression among HIV-positive patients: Health promotion strategy towards the 909090 target

Mohammad Ali Morowatisharifabad1, Ehsan Movahed2, Jamileh Farokhzadian3, Rohollah Nikooie4, Mohsen Askarishahi5, Reza Bidaki6, Mahdieh Hosseinzadeh7,  
1 Elderly Health Research Center, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
2 Health Education and Health Promotion, School of Health, Jiroft University of Medical Sciences, Jiroft, Iran
3 Nursing Research Center, Kerman University of Medical Sciences, Kerman, Iran
4 Department of Exercise Physiology, Faculty of Sports Sciences, Shahid Bahonar University, Kerman, Iran
5 Department of Biostatistics and Epidemiology, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
6 Research Center of Addiction and Behavioral Sciences and Diabetes Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
7 Nutrition and Food Security Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Correspondence Address:
Dr. Ehsan Movahed
Health Education and Health Promotion, School of Health, Jiroft University of Medical Sciences, Jiroft


BACKGROUND: HIV-infected patients with poor antiretroviral therapy (ART) adherence are prone to depression, and depression can exacerbate the disease condition. This study was conducted to determine ART Adherence based on Information, Motivation, and Behavioral Skills (IMB) Model and its association with depression among HIV-positive patients. MATERIALS AND METHODS: This descriptive–correlational study was carried out on people over the age of 18 years with HIV/AIDS, who referred to the Behavioral Diseases Counseling Center in Kerman City, Iran, in 2017. In this regard, 119 patients were selected using the table of random numbers. To collect the data, we used the Beck's depressioninventory-II and the IMB researcher made questionnaire to evaluate the ART adherence. RESULTS: The results of the study reveal that a significant association was observed between the total adherence and all constructs of the IMB model (P < 0.001). Risk perception and self-efficacy had the highest mean scores regarding the ART adherence. The prevalence of depression was 71.5% among patients. Information, personal motivation, and total adherence had a significant association with depression. CONCLUSIONS: IMB model was an appropriate and practical strategy with regard to the ART adherence among people living with HIV who are prone to depression and drug consumption is crucial for them to achieve the 90-90-90 target. This article created a questionnaire to assist policy-makers and health professionals designing interventions to improve adherence and health outcomes of ART.

How to cite this article:
Morowatisharifabad MA, Movahed E, Farokhzadian J, Nikooie R, Askarishahi M, Bidaki R, Hosseinzadeh M. Antiretroviral therapy adherence based on information, motivation, and behavioral skills model and its association with depression among HIV-positive patients: Health promotion strategy towards the 909090 target.J Edu Health Promot 2019;8:192-192

How to cite this URL:
Morowatisharifabad MA, Movahed E, Farokhzadian J, Nikooie R, Askarishahi M, Bidaki R, Hosseinzadeh M. Antiretroviral therapy adherence based on information, motivation, and behavioral skills model and its association with depression among HIV-positive patients: Health promotion strategy towards the 909090 target. J Edu Health Promot [serial online] 2019 [cited 2019 Dec 14 ];8:192-192
Available from:

Full Text


HIV/AIDS is a major public health problem worldwide. The number of affected people was estimated as 36.7 million in 2014.[1] In a recent study, it was shown that the estimated number of HIV-infected people were 89,000 in 2009 with a projected increase to 106,000 in 2014.[2] One of the factors that help to control, treat, and suppress the HIV virus is consumption of and antiretroviral therapy (ART) adherence.[3] The rate of nonadherence to the ART in rural areas of Zambia was 40%[4] and North America was 45%.[5] The ART should be ≥95% in order to prevent drug resistance, transmit of HIV virus to noninfected sexual partners, progress of the disease to the AIDS stage, and achieve the 90-90-90 target.[6] The 90-90-90 target indicates that 90% of the patients should be diagnosed, 90% treated, and 90% should achieve the viral suppression, but in Iran, the ART adherence is 75.4%.[7]

Certainly, the antiretroviral (ARV) drugs should be used perpetually until the end of life; in the case that the medications discontinue, the number of HIV viruses in the patient's body increases rapidly.[8] The long-term use of medications and their complications lead to drug intolerance and depression among patients. On the other hand, poor adherence to the ART was associated with depression.[8] Studies conducted in countries with high and low income showed a strong association between AIDS and depression, so that depression was significantly associated with harmful effects of AIDS, low quality of life, low immune system, higher viral load, unemployment, and low labor productivity.[9] It is predicted that depression will be one of the three main causes of disease throughout the world along with AIDS and ischemic heart diseases by 2030.[10] Depression treatment can promote the patients' motivation and self-efficacy.[11] The prevalence of depression among HIV-positive patients was 50% in San Francisco.[12] The prevalence of moderate-to-severe depression among people living with HIV (PLHIV) was 68% in Iran.[13]

The Information, Motivation, and Behavioral Skills (IMB) model is one of the models widely considered in the area of ART adherence in health psychology.[14] In this model, information is considered as the prerequisite of personal and social motivation, while risk perception is a motivational prerequisite for learning skills.[15] The results of a study by Alexander et al. showed that behavioral skills were significantly affected by the mediating effects of information and motivation in treatment adherence.[14] Despite the studies conducted over the ART and use of IMB model in other countries,[16] no information is available on the ART adherence of the Iranian HIV-positive patients using the IMB model. Therefore, this study was conducted to answer two main research questions:

Is ART adherence based on the IMB model an appropriate strategy to achieve the 909,090 target?Does ART adherence lead to depression?

 Materials and Methods

Study design and setting

This descriptive–correlational study was conducted on PLHIV, who were 18 years and older and referred to the Behavioral Disease Counseling Center in Kerman city in 2017.

Participants and sampling

To collect the participants, the researchers referred to the Behavioral Disease Counseling Center and selected 119 patients randomly using the table of random numbers. The number of people receiving free ART was 188 at the time of data collection. The sample size was calculated as 119 people using the proportions formula with a significance level of 95%, d = 0. 09, and the adherence level of 0.50. The inclusion criteria consisted of having 18 years of age and older, taking drugs for 6 months, and having the willingness to participate in the study.


In this research, three questionnaires were applied to collect the data.

The first questionnaire was the demographic and clinical data of the patients including: age, sex, marital status, educational level, occupation, income level, number of children, housing, disease transmission forms, CD4 count, stage of disease, viral load, risk factors, history of disease, and body mass index.

Questionnaire of antiretroviral therapy adherence based on Information, Motivation, and Behavioral skills model

The questionnaire of ART adherence based on IMB model was developed by the researcher after conducting a qualitative research and investigating the manuscripts and scientific papers on the ART adherence. This questionnaire dealt with six constructs of the IMB model using a five-point Likert scale as information, personal motivation, social motivation, risk perception, self-efficacy, and behavioral questions. That the options ranging from “totally agree” (five scores) to “totally disagree” (zero). In the part of self-efficacy and behavior, the options included always (5 scores) and never (1 score). Some items in the sections of information (questions 5 and 6), personal motivation (questions 6–9), social motivation (questions 3–7), and behavior (question 6) were scored reversely. The validity of the questionnaire was confirmed by ten experts which was calculated as 70%. The Cronbach's alpha test was also used to determine the scientific reliability of the data collection tool. The reliability of the questionnaire with regard to the construct of information was 82%, personal motivation 83%, social motivation 83%, risk perception 88%, self-efficacy 83%, and behavior was 83% [Appendix 1].[INLINE:1]

Beck depression inventory II test

The Beck depression inventory-II (BDI-II) is widely used to diagnose depression and measure its severity. Kanmogne et al. investigate the validity and reliability of the French version of this questionnaire in Cameroon.[17] The BDI-II consists of 21 items to evaluate the emotional factors of depression, such as hopelessness, irritability, guilty feelings, pessimism, worthlessness, self-efficacy, and suicidal thoughts, as well as the physical factors such as loss of appetite, fatigue, as well as sleep and concentration problems. The options were scored from zero to three and the total score was calculated to determine the severity of depression: normal (0–13), mild (14–19), moderate (20–28), and severe (29–63).[17]

Ethical consideration

The Ethics Committee of Yazd University of Medical Sciences confirmed this study (IR.SSU.SPH.REC 1396.83). Subsequently, the participants were provided with comprehensive explanations about aim of the study, they were asked to sign the consent forms to participate in the research, and they were ensured about the confidentiality of information. In case that some people quit, we used the table of random numbers and selected participates to reach the determined sample size. To ensure the accuracy of participants in completing the questionnaires, the US $3 was paid to each participant after completing the questionnaire.

Statistical analysis

In this research, descriptive statistics was used to analyze the demographic characteristics, ART adherence, and depression of the study population. In addition, we used the Spearman's correlation test to analyze the association of the IMB model constructs with the total adherence, depression, and other demographic variables. The data were analyzed using SPSS 24. International Business Machines Corporation, New York, USA. The significance level was set at 0.05.


A total number of 119 PLHIV with an average age of 41.59 ± 9.57 years participated in the study. The results showed that 54.6% of the participants were male [Table 1].{Table 1}

The rate of CD4 was higher than 350 in 58% of cases. In addition, 93.3% of the samples were infected with HIV. The viral load was <100 in 63.9% of cases and 42% of participants did not mention any risk factors such as using drugs [Table 2].{Table 2}

A significant association was observed between the total adherence and all constructs of the IMB model (P < 0.001). Of the constructs of the model, the risk perception and self-efficacy had the highest mean scores in ART adherence [Table 3].{Table 3}

The prevalence of depression was 71.5% among patients; 29.4% of these participants had severe depression and the others had moderate-to-low depression. Furthermore, 28.6% of participants had no depression [Table 4].{Table 4}

According to Spearman's correlation coefficient, except for the constructs of information (P = 0.000), personal motivation (P = 0.04), and total adherence (P = 0.006), no significant relationship was observed between depression and ART adherence in other constructs. The results showed that gender had a significant correlation with information (P = 0.001) and total adherence (P = 0.008). In addition, marital status had a significant association with information (P = 0.01), personal motivation (P = 0.03), and total adherence (P = 0.02). Spearman's correlation showed a significant association between income and behavior (P = 0.03) [Table 5].{Table 5}


Considering the strong association of the IMB model constructs with total adherence and the significant effect of ART adherence on the reduction of depression, application of IMB model was appropriate for ART adherence. Risk perception and self-efficacy had the highest mean scores with regard to ART adherence among the constructs of the model. In confirmation of the second hypothesis, it should be noted that depression decreased with ART adherence, so that information and personal motivation were the predictors of depression reduction among PLHIV. The married and female patients had better medication adherence in comparison with other groups.

The results of the current study showed that risk perception was a strong predictor of ART adherence among PLHIV. In the same line with our research, the results of the study by Zhang showed that risk perception was one of the most important elements of the target behavior.[18] However, in other studies, the risk perception was low with regard to the medications.[8] However, the patients of the present study had a high-risk perception, which was due to the follow-ups and care services rendered by nurses and physicians as well as the beneficial effects of medications.

The results of our study indicated that the patients' self-efficacy was high in ART adherence, which was in the same line with other study.[8] However, the results of the study carried out by Barclay and Alexander et al. showed that self-efficacy was low among HIV-positive adults. Furthermore, they observed no significant association between self-efficacy and treatment adherence among the participants.[14],[19] This discrepancy in the findings can be attributed to the variety in participants' age and geographic region, so that the elderlies did not have enough trust in ART adherence.

In our study, all constructs of the IMB model were associated with the total ART adherence. Similar results were observed in other study.[20] However, the results of the study carried out by Chang were different with the results of the current study.[21] In the previous studies, the participants were selected from wide varieties of geographic region, and the sample size was large, which caused the difference in the results. Information and personal motivation, among other constructs of model, had the highest mean scores in ART adherence. In confirmation of our results, Norton et al. showed that high motivation affected the ART adherence.[22] Meanwhile, the results of the study by Starks et al. contradicted our results regarding three groups of PLHIV, which was due to the difference in mental health.[16] However, in the current study, the support from nurses and physicians of the Behavioral Disease Counseling Center increased the ART adherence among patients.

Furthermore, in the current study, information and personal motivation were considered as two important predictors of depression reduction, which was similar to a previous study.[23] However, Egede reported that only “social motivation” was the most important construct in reducing depression.[24] This discrepancy can be related to the difference in the applied data collection tools and the studied group, who were the people with diabetes in Egede research. Similar to the findings of Coleman, we found that the prevalence of moderate-to-severe depression was more than the average.[25] However, the results of other studies were not in the same line with our results.[17],[26] In our study as well as the study by Georgette,[16] participants included both genders and the BDI-II was applied as the research tool. Hence, the difference in the findings can be related to the large sample size in Georgette study, which was two times more than the sample size in our study. In the current study, females had a greater ART adherence than males, which was similar to other study.[27] However, Kim et al. (2018). did not confirm this finding.[28] This difference can be because many female participants were widowed and lived with their parents or other family members, so they were supported to a higher degree.[29] The results of this study showed that ART adherence was higher among the married individuals who were in the same line with the study by Oskouie et al.[30] However, this finding was different from the results reported by Mukui et al.[31] The study by Oskouie et al. showed that married females with HIV who were supported by their spouses had higher ART adherence.[30]

The strength of the study was to extract the questionnaire from the qualitative design that was done by face-to-face interviews. However, this study is limited by being conducted at one site, and the data were collected in a self-reporting mode.

Recommendations for practice and research

We suggest other researchers and health-care providers to use the IMB model in their interventional studies. Policy-makers are also recommended to consider the patients' mental health, social support, and financial support along with their ART adherence. However, given the high prevalence of depression in HIV patients, it is better to choose a smaller sample size.


The results of this study showed that IMB model was an appropriate, practical, and economic strategy with regard to the ART adherence among PLHIV, who are prone to depression and drug consumption. Furthermore, depression decreased by continuous ART adherence. So with the IMB model, we can reach the 90-90-90 target earlier.


We would like to acknowledge authorities of the Jiroft University of Medical Sciences in the Southern Iran.

Financial support and sponsorship

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflicts of interest

There are no conflicts of interest.


1World Health Organization. Data and Statistics 2017. Available from: [Last accessed on 2017 Aug 20].
2Nasirian M, Haghdoost AA, Doroudi F, Gooya MM, Sedaghat A, Rabbori ED. Modelling HIV modes of transmission in Iran. Retrovirology. 2012;9(Suppl 1):121
3Garbelli A, Riva V, Crespan E, Maga G. How to win the HIV-1 drug resistance hurdle race: Running faster or jumping higher? Biochem J 2017;474:1559-77.
4Sasaki Y, Kakimoto K, Dube C, Sikazwe I, Moyo C, Syakantu G, et al. Adherence to antiretroviral therapy (ART) during the early months of treatment in rural Zambia: Influence of demographic characteristics and social surroundings of patients. Ann Clin Microbiol Antimicrob 2012;11:34.
5Mills EJ, Nachega JB, Buchan I, Orbinski J, Attaran A, Singh S, et al. Adherence to antiretroviral therapy in sub-Saharan Africa and North America: A meta-analysis. JAMA 2006;296:679-90.
6Gordon LL, Gharibian D, Chong K, Chun H. Comparison of HIV virologic failure rates between patients with variable adherence to three antiretroviral regimen types. AIDS Patient Care STDS 2015;29:384-8.
7Morowatisharifabad MA, Movahed E, Farokhzadian J, Nikooie R, Hosseinzadeh M, Askarishahi M, et al. Antiretroviral therapy adherence and its determinant factors among people living with HIV/AIDS: A case study in Iran. BMC Res Notes 2019;12:162.
8Agustin DA, Prasetyo AA, Murti B. A path analysis on adherence to antiretroviral therapy among HIV/AIDS patients at Dr. Moewardi hospital, Surakarta using health belief model. J Health Promot Behav 2018;3:48-55.
9Pence BW, Miller WC, Gaynes BN, Eron JJ Jr. Psychiatric illness and virologic response in patients initiating highly active antiretroviral therapy. J Acquir Immune Defic Syndr 2007;44:159-66.
10Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ. Burden of depressive disorders by country, sex, age, and year: Findings from the global burden of disease study 2010. PLoS Med 2013;10:e1001547.
11Lund C, De Silva M, Plagerson S, Cooper S, Chisholm D, Das J, et al. Poverty and mental disorders: Breaking the cycle in low-income and middle-income countries. Lancet 2011;378:1502-14.
12Weiser SD, Riley ED, Ragland K, Hammer G, Clark R, Bangsberg DR, et al. Brief report: Factors associated with depression among homeless and marginally housed HIV-infected men in San Francisco. J Gen Intern Med 2006;21:61-4.
13Amini Lari M, Parsa N, Marzban M, Shams M, Faramarzi H. Depression, testosterone concentration, sexual dysfunction and methadone use among men with hypogonadism and HIV infection. AIDS Behav 2012;16:2236-43.
14Alexander DS, Hogan SL, Jordan JM, DeVellis RF, Carpenter DM. Examining whether the information-motivation-behavioral skills model predicts medication adherence for patients with a rare disease. Patient Prefer Adherence 2017;11:75-83.
15Fisher JD, Fisher WA, Shuper PA. The information-motivation-behavioral skills model of HIV preventive behavior. Emerging Theories in Health Promotion Practice and Research. San Francisco, CA: Jossey-Bass; 2009. p. 21-63.
16Starks TJ, Millar BM, Lassiter JM, Parsons JT. Preintervention profiles of information, motivational, and behavioral self-efficacy for methamphetamine use and HIV medication adherence among gay and bisexual men. AIDS Patient Care STDS 2017;31:78-86.
17Kanmogne GD, Qiu F, Ntone FE, Fonsah JY, Njamnshi DM, Kuate CT, et al. Depressive symptoms in HIV-infected and seronegative control subjects in Cameroon: Effect of age, education and gender. PLoS One 2017;12:e0171956.
18Zhang H, Liao M, Nie X, Pan R, Wang C, Ruan S, et al. Predictors of consistent condom use based on the information-motivation-behavioral skills (IMB) model among female sex workers in Jinan, China. BMC Public Health 2011;11:113.
19Barclay TR, Hinkin CH, Castellon SA, Mason KI, Reinhard MJ, Marion SD, et al. Age-associated predictors of medication adherence in HIV-positive adults: Health beliefs, self-efficacy, and neurocognitive status. Health Psychol 2007;26:40-9.
20Lee G, Yang SJ, Chee YK. Assessment of healthy behaviors for metabolic syndrome among Korean adults: A modified information-motivation-behavioral skills with psychological distress. BMC Public Health 2016;16:518.
21Chang SJ, Choi S, Kim SA, Song M. Intervention strategies based on information-motivation-behavioral skills model for health behavior change: A systematic review. Asian Nurs Res (Korean Soc Nurs Sci) 2014;8:172-81.
22Norton WE, Amico KR, Fisher WA, Shuper PA, Ferrer RA, Cornman DH, et al. Information-motivation-behavioral skills barriers associated with intentional versus unintentional ARV non-adherence behavior among HIV+patients in clinical care. AIDS Care 2010;22:979-87.
23Rongkavilit C, Naar-King S, Kaljee LM, Panthong A, Koken JA, Bunupuradah T, et al. Applying the information-motivation-behavioral skills model in medication adherence among Thai youth living with HIV: A qualitative study. AIDS Patient Care STDS 2010;24:787-94.
24Egede LE, Osborn CY. Role of motivation in the relationship between depression, self-care, and glycemic control in adults with type 2 diabetes. Diabetes Educ 2010;36:276-83.
25Coleman CL. Health related quality of life and depressive symptoms among seropositive African Americans. Appl Nurs Res 2017;33:138-41.
26Prasithsirikul W, Chongthawonsatid S, Ohata PJ, Keadpudsa S, Klinbuayaem V, Rerksirikul P, et al. Depression and anxiety were low amongst virally suppressed, long-term treated HIV-infected individuals enrolled in a public sector antiretroviral program in Thailand. AIDS Care 2017;29:299-305.
27Fonsah JY, Njamnshi AK, Kouanfack C, Qiu F, Njamnshi DM, Tagny CT, et al. Adherence to antiretroviral therapy (ART) in Yaoundé-Cameroon: Association with opportunistic infections, depression, ART regimen and side effects. PLoS One 2017;12:e0170893.
28Kim J, Lee E, Park BJ, Bang JH, Lee JY. Adherence to antiretroviral therapy and factors affecting low medication adherence among incident HIV-infected individuals during 2009-2016: A nationwide study. Sci Rep 2018;8:3133.
29Banagi YA, Unnikrishnan B, Ramapuram JT, Kumar N, Mithra P, Kulkarni V, et al. Factors influencing adherence to antiretroviral therapy among people living with HIV in Coastal South India. J Int Assoc Provid AIDS Care 2016;15:529-33.
30Oskouie F, Kashefi F, Rafii F, Gouya MM, Vahid-Dastjerdi M. Facilitating factors of self-care among HIV-positive young women in Iran: A qualitative study. Int J Adolesc Med Health 2018. pii:/j/ijamh.ahead-of-print/ijamh-2017-0172/ijamh-2017-0172.xml.
31Mukui IN, Ng'ang'a L, Williamson J, Wamicwe JN, Vakil S, Katana A, et al. Rates and predictors of non-adherence to antiretroviral therapy among HIV-positive individuals in Kenya: Results from the second Kenya AIDS indicator survey, 2012. PLoS One 2016;11:e0167465.