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\def\RunningAuthor{Divya Mol E C et al.}
\firstPage{2280}
\articleType{Original Article}
\receivedDate{01 Jun 2021}
\acceptedDate{22 Jul 2021}
\revisedDate{17 Jul 2021}
\journalVolume{2021, 12}
\journalIssue{3}
\journalDoi{ijrps.v12i3.4854}
\copyrightYear{2021}
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\title{\textbf{Assessment of Knowledge, Attitude and Practice (KAP) in Tuberculosis Patients}}
\author{Akash~S~Wallepure\textsuperscript{1},  
            Salin~Sebastian\textsuperscript{1},  
            Sradha~S~Thomas\textsuperscript{1},  
            Nishant~Khatiwada\textsuperscript{1},  
            Divya~Mol~E~C\textsuperscript{*}\textsuperscript{2}, 
            Vivekanand~Kumbar\textsuperscript{3}~\\[5pt]{\textsuperscript{1}Acharya and BM Reddy College of Pharmacy, Bengaluru -560107, Karnataka, India}~\\{\textsuperscript{2}Department of Pharmacy Practice, Acharya BM Reddy College of Pharmacy, Bengaluru-560090, Karnataka, India}~\\{\textsuperscript{3}Department of Pulmonary Medicine, ESIC Medical College and Post-Graduate Institute of Medical Science and Research Hospital, Bengaluru-560010, Karnataka, India}}

\begin{abstract}
Tuberculosis (TB) is a highly contagious airborne disease caused by \textit{Mycobacterium tuberculosis } that primarily affects the lungs. TB is a significant and major public health emergency globally. According to the WHO Global Tuberculosis Report 2020, 10 million people developed TB disease in the year 2019. The main objective of the study was to assess the level of knowledge, attitude and practice in TB patients. The study also reveals the association between KAP and the demographics of the subjects. An observational study was employed to collect data from a total of 71 subjects. Both quantitative and qualitative statistical analysis were adopted. From the findings, the mean age of the study population was 45.5 \ensuremath{\pm} 13.96 years. Over 15.50\% of subjects appeared to have adequate knowledge, 87.33\% of subjects had a fair attitude, and around 58\% of subjects were reported to have good practices towards TB. A weak positive correlation between knowledge and attitude (p = 0.051), weak positive correlation between knowledge and practice (p = 0.138) whereas, a significant and moderately positive correlation between attitude and practice (p = 0.002) was observed. The mean knowledge scores of graduates and post-graduates were higher in comparison with other study subjects. The study findings showed that the majority of subjects had several misconceptions about TB and hence prioritized interventions and more awareness programs at the root levels are needed to aid TB control and eradication. 
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}Tuberculosis,\newline Knowledge,\newline Attitude,\newline Practice
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Divya~Mol~E~C~\\ Phone:\ +91 9447408510~\\  Email:\ divyapieuse@gmail.com
        \par}\vspace*{-11pt}\hrulefill\par{\fontsize{12}{14}\selectfont ISSN: 0975-7538}\par% 
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\section{Introduction}
Tuberculosis (TB) is an infectious disease and a major global public health concern. In 2020 WHO Global Tuberculosis Report revealed that TB still remains a biggest threat due to the fact that, in 2019, around 10 million people developed TB disease and 1.4 million deaths from TB. India alone accounts for about 26\% of the world's annual incidence of TB, making it the highest contributor to the TB burden \unskip~\citep{1189853:22994652}. A KAP survey is a study of a specific population to gather information on what is known, believed and done in relation to a particular topic. In most KAP studies, data are collected verbally by an interviewer using a structured, standardized questionnaire. A KAP survey can be designed specifically to accumulate information about TB-related topics, but it may also include questions about general health practices and beliefs. KAP surveys can identify knowledge gaps, cultural beliefs, or behavioural patterns that may support understanding and action, as well as pose problems or create barriers for TB control efforts. KAP studies help organizations in making policies regarding chronic diseases like TB. 

They can also identify information that is commonly known and attitudes that are commonly held. To some extent, these studies can identify factors that can influence the behavior of people, reasons for their attitudes, and how and why people practice certain health behaviors \unskip~\citep{1189853:22994651}. Deficient TB knowledge and poor attitudes towards TB may lead to delays in the diagnosis and treatment of TB. TB knowledge and awareness about medical treatment are important for the success of TB prevention and control.  
    
\section{Materials and Methods}
\textbf{Study Ethics}

Ethical approval was obtained from the Institutional Ethics Committee (IEC) of ESIC Medical College \& PGIMSR, Rajajinagar, Bengaluru. \textbf{\space }

\textbf{Study design and study population}

This was an observational study. The subjects who were of age 18 years and above, those with a confirmed diagnosis of tuberculosis by sputum test or X-ray or CBNAAT with or without co-morbidities, subjects with active / inactive TB taking anti TB medications and subjects who were willing to participate in the study and signed the written informed consent were included. Subjects who were unable to answer, pregnant and lactating women, were excluded from the study.

\textbf{Data sources}

The data were collected from sources like patient case sheets, laboratory reports, face to face and telephonic interviews.

Data was collected using a self-designed data collection form, which contains details like subjects' demographics, chief complaints, history of present illness, past medication, medical history and laboratory reports. Data regarding KAP was collected using a self-designed questionnaire. This scale consists of 17 questions targeting knowledge, attitude and practices of TB. Morisky Green Levine Scale is a self-reported scale comprising of four questions with yes/no responses that assess the patient's medication-taking behaviour.

\textbf{Statistical analysis}

The results were analyzed and interpreted using Microsoft Excel and IBM-SPSS. Descriptive statistics such as mean \& standard deviation were computed for quantitative variables, and frequencies and percentages were calculated for categorical variables. Histogram was applied to find the nature of data distribution. All statistics were considered significant if the p-value was less than 0.05. The results were also presented in the form of frequency format and diagrammatic representations whenever necessary.
    
\section{Results and Discussion}
Out of 71 subjects, 54 (76.1\%) were males, and 17 (23.9\%) were females. The mean age was found to be 45.5 \ensuremath{\pm} 13.96 years. 37 subjects (52\%) belonged to the above 45 years age group, 21 subjects (29.6\%) belonged to 31-45 years age group, and 13 subjects (18.3\%) belonged to 18-30 years age group as shown in Figure~\ref{f-844e9772aa8a}.  


\bgroup
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\caption{\boldmath {Distribution of subjects between different age (in years) groups}}
\label{f-844e9772aa8a}
\end{figure*}
\egroup

\bgroup
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\caption{\boldmath {Educational qualifications of subjects}}
\label{f-4c644d1790f5}
\end{figure*}
\egroup
Smoking and alcohol consumption increase the risk of treatment failure and may lead to unfavourable clinical outcomes. Out of 71 subjects, 35.22\% of subjects were indulged in habits like smoking and/or alcoholism, whereas the remaining 64.78\% were not. The majority of subjects were educated; among them, 17 (23.9\%) subjects had primary education, 25 (35.21\%) subjects had secondary education, 9 (12.68\%) subjects were graduates, and 20 (28.17\%) subjects were illiterates, as shown in Figure~\ref{f-4c644d1790f5}. Among 71 subjects, 8 (11.26\%) subjects were relapsed cases, and the remaining 63 (88.73\%) subjects were new cases of a total number of subjects involved in the study, 59 (83.09\%) subjects were in an initial phase of anti-TB treatment, and 12 (16.90\%) subjects were in a continuous phase of treatment. 

\textbf{Assessment of knowledge towards TB}

Knowledge was assessed by questions focusing on aetiology, signs and symptoms, transmission and management. Each response was scored as 'yes' (1) or 'no' (0). The scoring range of the questionnaire was from 6 being the maximum score to 0 being the minimum score. A cut off level of {\textless}2 was considered as poor, and 3-4 was considered as moderate, whereas {\textgreater}5 was considered adequate knowledge about TB. Knowledge scorers for individuals were calculated and summed up to give the total knowledge score. Table~\ref{tw-8aa0b7d8f568} describes the responses of subjects to TB knowledge items.


\begin{table*}[!htbp]
\caption{\boldmath {Responses to TB knowledge items} }
\label{tw-8aa0b7d8f568}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.5146\linewidth-2\tabcolsep}p{\dimexpr.20759999999999998\linewidth-2\tabcolsep}p{\dimexpr.2778\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Knowledge items & \multicolumn{2}{p{\dimexpr(.4854\linewidth-2\tabcolsep)}}{\cAlignHack Correct answer}\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack N & \cAlignHack Percentage (\%)\\
\tblmidrule 
K1: Which organ is most effected in TB disease? &
  \cAlignHack 17 &
  \cAlignHack 24\\
K2: What are the signs and symptoms of TB? &
  \cAlignHack 61 &
  \cAlignHack 86\\
K3: What causes TB? &
  \cAlignHack 8 &
  \cAlignHack 11\\
K4: How can a person get TB? &
  \cAlignHack 40 &
  \cAlignHack 56\\
K5: In your opinion, who can be infected with TB? &
  \cAlignHack 66 &
  \cAlignHack 93\\
K6: Can TB be cured? &
  \cAlignHack 59 &
  \cAlignHack 83\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Responses to attitude items} }
\label{tw-233e3c04cb20}
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\begin{tabulary}{\linewidth}{p{\dimexpr.3893666666666666\linewidth-2\tabcolsep}p{\dimexpr.13906666666666672\linewidth-2\tabcolsep}p{\dimexpr.11956666666666667\linewidth-2\tabcolsep}p{\dimexpr.1209333333333334\linewidth-2\tabcolsep}p{\dimexpr.12113333333333337\linewidth-2\tabcolsep}p{\dimexpr.1099333333333334\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Attitude items & \cAlignHack Strongly agree & \cAlignHack Agree & \cAlignHack Don't know & \cAlignHack Disagree & \cAlignHack Strongly disagree\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack N (\%) & \cAlignHack N (\%)  & \cAlignHack N (\%)  & \cAlignHack N (\%)  & \cAlignHack N (\%) \\
\tblmidrule 
\cAlignHack A1: I~take my medications regularly &
  \cAlignHack 59 &
  \cAlignHack 6 &
  \cAlignHack 0 &
  \cAlignHack 4 &
  \cAlignHack 2\\
\cAlignHack  &
  \cAlignHack (83.09) &
  \cAlignHack (8.45)  &
  \cAlignHack (0)  &
  \cAlignHack (5.63)  &
  \cAlignHack (2.81) \\
\cAlignHack A2: Complete medication adherence  &
  \cAlignHack 49 &
  \cAlignHack 13 &
  \cAlignHack 6 &
  \cAlignHack 2 &
  \cAlignHack 1\\
\cAlignHack can cure TB &
  \cAlignHack (69.01) &
  \cAlignHack (1.83)  &
  \cAlignHack (8.45)  &
  \cAlignHack (2.81) &
  \cAlignHack (1.40) \\
\cAlignHack A3: BCG vaccination is the best  &
  \cAlignHack 2 &
  \cAlignHack 1 &
  \cAlignHack 66 &
  \cAlignHack 2 &
  \cAlignHack 0\\
\cAlignHack preventive method for P-TB &
  \cAlignHack (2.81) &
  \cAlignHack (1.40)  &
  \cAlignHack (93) &
  \cAlignHack (2.81) &
  \cAlignHack (0)\\
\cAlignHack A4: I~don't wear a mask every time  &
  \cAlignHack 14 &
  \cAlignHack 15 &
  \cAlignHack 4 &
  \cAlignHack 8 &
  \cAlignHack 30\\
\cAlignHack I~go out &
  \cAlignHack (19.71) &
  \cAlignHack (21.12)  &
  \cAlignHack (5.63) &
  \cAlignHack (11.26) &
  \cAlignHack (42.25)\\
\cAlignHack A5: I~stop taking medicines when my  &
  \cAlignHack 2 &
  \cAlignHack 4 &
  \cAlignHack 2 &
  \cAlignHack 13 &
  \cAlignHack 50\\
\cAlignHack symptoms improve &
  \cAlignHack (2.81) &
  \cAlignHack (5.63)  &
  \cAlignHack (2.81) &
  \cAlignHack (1.83) &
  \cAlignHack (70.42)\\
\cAlignHack A6: Society treats me differently &
  \cAlignHack 1 &
  \cAlignHack 3 &
  \cAlignHack 0 &
  \cAlignHack 17 &
  \cAlignHack 50\\
\cAlignHack  &
  \cAlignHack (1.40) &
  \cAlignHack (4.22) &
  \cAlignHack (0) &
  \cAlignHack (23.94) &
  \cAlignHack (70.42)\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Responses to practice items} }
\label{tw-e885f227ccfa}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.6433\linewidth-2\tabcolsep}p{\dimexpr.14939999999999998\linewidth-2\tabcolsep}p{\dimexpr.2073\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Practice items & \multicolumn{2}{p{\dimexpr(.3567\linewidth-2\tabcolsep)}}{\cAlignHack Yes}\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack N & \cAlignHack Percentage (\%)\\
\tblmidrule 
P1: Do you spend most of the time in crowded places?  &
  \cAlignHack 41  &
  \cAlignHack 58 \\
P2: Do you report it to your doctor when you have red/orange coloured urine?  &
  \cAlignHack 51  &
  \cAlignHack 72 \\
P3: Do you go for regular follow up?  &
  \cAlignHack 59  &
  \cAlignHack 83 \\
P4: Do you avoid using your hands while coughing and sneezing?  &
  \cAlignHack 28  &
  \cAlignHack 39 \\
P5: Do you take medications as prescribed by your physician?  &
  \cAlignHack 66  &
  \cAlignHack 93 \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Correlation between attitude and practice} }
\label{tw-1d19b1d529c5}
\centering 
\begin{threeparttable}

\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.194\linewidth-2\tabcolsep}p{\dimexpr.35580000000000005\linewidth-2\tabcolsep}p{\dimexpr.2314\linewidth-2\tabcolsep}p{\dimexpr.2188\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack  & \cAlignHack Attitude & \cAlignHack Practice\\
\tblmidrule 
\cAlignHack  &
  \cAlignHack Pearson Correlation &
  \cAlignHack 1 &
  \cAlignHack 0.358\ensuremath{^{**}}\\
\cAlignHack Attitude &
  \cAlignHack Sig. (2-tailed) &
  \cAlignHack  &
  \cAlignHack 0.002\\
\cAlignHack  &
  \cAlignHack N &
  \cAlignHack 71 &
  \cAlignHack 71\\
\cAlignHack  &
  \cAlignHack Pearson Correlation &
  \cAlignHack 0.358\ensuremath{^{**}} &
  \cAlignHack 1\\
\cAlignHack Practice &
  \cAlignHack Sig. (2-tailed) &
  \cAlignHack 0.002 &
  \cAlignHack \\
\cAlignHack  &
  \cAlignHack N &
  \cAlignHack 71 &
  \cAlignHack 71\\
\tblbottomrule 
\end{tabulary}\par 
\begin{tablenotes}\footnotesize 
    
\item{** Correlation is significant at the 0.01 level (2-tailed)}
\end{tablenotes}
\end{threeparttable}

\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Comparison of mean knowledge scores with a level of education} }
\label{tw-e925d1de8d2c}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.22823999999999998\linewidth-2\tabcolsep}p{\dimexpr.17176000000000005\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}p{\dimexpr.20\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Education level & \cAlignHack N & \multicolumn{2}{p{\dimexpr(.40\linewidth-2\tabcolsep)}}{\cAlignHack Knowledge } & \cAlignHack \\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack  & \cAlignHack Mean  & \cAlignHack SD  & \cAlignHack \textit{p-}Value\\
\tblmidrule 
Uneducated &
  \cAlignHack 20 &
  \cAlignHack 3.82 &
  \cAlignHack 0.83 &
  \\
Primary &
  \cAlignHack 17 &
  \cAlignHack 2.76 &
  \cAlignHack 1.39 &
  \\
Secondary &
  \cAlignHack 26 &
  \cAlignHack 3.58 &
  \cAlignHack 1.10 &
  \cAlignHack 0.031\\
Graduation &
  \cAlignHack 7 &
  \cAlignHack 4.43 &
  \cAlignHack 0.97 &
  \\
Post-graduation &
  \cAlignHack 1 &
  \cAlignHack 4 &
  \cAlignHack 0 &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
Out of 71 subjects, 10 (14.08\%) subjects were within poor knowledge range, 50 (70.42\%) subjects were in the moderate range, and 11 (15.50\%) subjects appeared to have adequate knowledge\textit{.} This was in contrary to a study conducted by \unskip~\cite{1189853:22994647} \textit{\textbf{\space }}in Vietnam, where 51\% of participants did not know signs and symptoms. Correct answers of about 86\%, 93\%, and 83\% were highest in response to questions K2, K5 and K6, respectively. Poor knowledge was apparent in response to question K1 and K3. The mean knowledge score was 3.54 \ensuremath{\pm} 1.18.

\textbf{Assessment of attitude towards TB} \textbf{\space }

The attitude was assessed by a questionnaire consisting of 3 items focusing on a positive attitude and 3 items focusing on a negative attitude. Each response was scored using the Likert scale. The subjects were then classified as those having low attitudes ({\textless}10), those with moderate attitudes (11-20) and those having high attitudes (21-30) towards TB. The responses towards attitude items are described in Table~\ref{tw-233e3c04cb20}.

Out of 71 subjects, 62 (87.33\%) subjects were within the high attitude range, 9 (12.67\%) subjects were within the moderate attitude range, and none of the respondents had a low attitude towards TB and its treatment. Overall, the subjects had a positive attitude towards TB with a mean score of 24.59 \ensuremath{\pm} 3.14. It was seen that 93\% of the subjects did not know about bacilli Calmette - Guerin (BCG) vaccination. Contrary to this is a study conducted by \unskip~\cite{1189853:22994648}\textit{\textbf{\space }}which reveals that 37\% of respondents reported BCG vaccination as a preventive measure for pulmonary TB. 

\textbf{Assessment of practices towards TB} \textbf{\space }

Practices towards TB were assessed by asking 5 questions to the subjects. Each response was scored as 'yes' or 'no'. A score of 1 was given to yes/good practice, while 0 was given to no/poor practice. The score range was from a maximum of 5 to a minimum of 0. Subjects were then classified into different levels based on cut off level. A cut off level of {\textless}1 was labelled as poor practice, 2-3 was considered as moderate, and {\textgreater}4 was considered as good practice. Table~\ref{tw-e885f227ccfa} \textit{\space }describes the responses given to practice items. 

Among 71 subjects, 41 (58\%) subjects were reported to have good practices, 27 (38\%) respondents were in moderate practice range, whereas 3 (4\%) respondents revealed poor practices towards TB. In general majority of the subjects reported to have good practices towards TB with a mean score of 3.45 \ensuremath{\pm} 1.07.

\textbf{Correlation between knowledge and attitude} \textbf{\space }

Statistical analysis reveals a weak positive correlation between knowledge and attitude with

r (69) = 0.233, p = 0.051 (p {\textgreater} 0.01) meaning that, correlation between knowledge and attitude is statistically insignificant.

\textbf{Correlation between knowledge and practice}

By using statistical analysis, a weak positive correlation was observed between knowledge and practice with r (69) = 0.178, p = 0.138, which means that the correlation between knowledge and practice is statistically insignificant.

\textbf{Correlation between attitude and practice}

Statistical analysis, as presented in Table~\ref{tw-1d19b1d529c5}, reveals a significant and moderately positive correlation between attitude and practice with r (69) = 0.358, p = 0.002.

\textbf{Association between mean KAP scores and Subject demographics} \textbf{\space }

Results of the KAP assessment were expressed in terms of three (Knowledge, Attitude and Practice) domains. Independent samples t-test (\ensuremath{\alpha } = 0.05) was performed to compare mean KAP scores and gender. The t-test reveals that there were no statistically significant differences between males and females in terms of KAP. 

The association between KAP scores and different age groups was analysed by the Kruskal-Wallis test at a significance level (\ensuremath{\alpha }) of 0.05. There were no statistically significant differences in knowledge, attitude and practice scores in relation to different age groups. In contrast, a study conducted by \unskip~\cite{1189853:22994650}\textit{\textbf{\space }}in Croatia showed that the mean knowledge score (8.85) was less among the youngest age group (18-29 years).

Kruskal-Wallis test was used to analyse the association between KAP scores and level of education. The testrevealed that there was a statistically significant difference in knowledge scores (\textit{p} \textless\ 0.05) as presented in Table~\ref{tw-e925d1de8d2c}, whereas no significant differences in attitude and practice scores in relation to the level of education. A similar study conducted by \unskip~\cite{1189853:22994649} (Esmael et al., 2013)\textbf{\space }showed 48\% of subjects with education levels of high school and above had good knowledge.
    
\section{Conclusion}
The study findings showed that the majority of subjects had several misconceptions about TB and hence prioritized interventions and more awareness programs at the root levels are needed to aid TB control and eradication. Assessment of medication adherence showed that most of the subjects were highly adherent to therapy. This shows that the health care workers are doing best in their part of counselling patients in about the importance of proper medication adherence.  
\section*{Acknowledgement}We are grateful to Dr. Gangaboraiah, professor of Statistics, for guiding us with the statistical analysis of our study. Assistance from Mrs. Sarala, health visitor at NTEP centre, Bengaluru, from our guide Dr. Divya and other health care workers from TB centre is greatly acknowledged. 

\textbf{Conflict of Interest}

The authors declare that they have no conflict of interest.

\textbf{Funding Support}

The authors declare that they have no funding support for this study.
    

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