## 5 Result Analysis
### Ranking of mHealth Applications Based on Usability Aspect Using CODAS  
The weighted normalized decision matrix, NIS, ED, and TD of the alternatives given in Table 3 were calculated using Steps 1 to 5 referred to in Section 4.4 and are depicted in Table 17. Steps 6 and 7 from Section 4.4 were used to determine the relative assessment matrix and the alternative assessment scores. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Criteria** & **Sub-Criteria** & **Criteria** & **Sub-Criteria** & **Global** \\  & **Weight** & **Weight** & **Weights** & **Weights** \\ \hline \multirow{3}{*}{**Learnability (A1)**} & Familiarity(A11) & & 0.5392 & 0.0170 \\  & Learning time(A12) & 0.0315 & 0.1632 & 0.0051 \\  & Minimal Action(A13) & & 0.2974 & 0.0094 \\ \hline \multirow{3}{*}{**Efficiency (A2)**} & No. of Taps(A21) & & 0.0962 & 0.0061 \\  & Task Completion & & 0.2168 & 0.0137 \\  & Rate(A22) & 0.0634 & 0.1807 & 0.0115 \\  & Response Time(A23) & & 0.4345 & 0.0276 \\  & Ease of Use(A24) & & 0.0716 & 0.0045 \\  & Connection(A25) & & 0.5736 & 0.0160 \\ \hline \multirow{3}{*}{**Memorability (A3)**} & Saving(A31) & & 0.5736 & 0.0160 \\  & Retain(A32) & 0.0280 & 0.2864 & 0.0080 \\  & Reminder(A33) & & 0.1399 & 0.0039 \\ \hline \multirow{3}{*}{**Aesthetic (A4)**} & Attractive(A41) & & 0.2721 & 0.0466 \\  & Appeal(A42) & 0.1712 & 0.1199 & 0.0205 \\  & Organized(A43) & & 0.6080 & 0.1041 \\ \hline \multirow{3}{*}{**Error (A5)**} & Presence of & \multirow{3}{*}{0.1849} & \multirow{3}{*}{1} & \multirow{3}{*}{0.1849} \\  & Error(A51) & & & \\ \hline \multirow{3}{*}{**Navigation (A6)**} & Search(A61) & & 0.3338 & 0.0409 \\  & Intuitive(A62) & 0.1225 & 0.5247 & 0.0643 \\  & Involvement(A63) & & 0.1416 & 0.0173 \\ \hline \multirow{3}{*}{**Readability (A7)**} & Legible(A71) & \multirow{3}{*}{0.1229} & \multirow{3}{*}{0.75} & \multirow{3}{*}{0.0922} \\  & Understandable(A72) & & 0.25 & 0.0307 \\ \hline \multirow{3}{*}{**Cognitive Load (A8)**} & Essentiality(A81) & & 0.25 & 0.0217 \\  & Presentation(A82) & 0.0869 & & 0.75 & 0.0652 \\ \hline \multirow{3}{*}{**Provision for**} & Weak Muscle & \multirow{3}{*}{0.0748} & \multirow{3}{*}{0.5571} & \multirow{3}{*}{0.0417} \\  & Control(A91) & & & \\ \cline{1-1} \cline{4-4}  & Low Vision(A92) & & & \\ \cline{1-1} \cline{4-4}  & Hearing & & & \\ \cline{1-1} \cline{4-4}  & Impairment(A93) & & & \\ \hline \multirow{3}{*}{**Satisfaction (A10)**} & Provision(A101) & & 0.0921 & 0.0105 \\ \cline{1-1}  & Finding Correct & \multirow{3}{*}{0.1138} & \multirow{3}{*}{0.2720} & \multirow{3}{*}{0.0310} \\ \cline{1-1}  & Information(A102) & & & \\ \cline{1-1} \cline{4-4}  & Improvement(A103) & & & \\ \cline{1-1} \cline{4-4}  & Recommendation(A104) & & 0.4911 & 0.0559 \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Weights of criteria, sub-criteria and global weights. Based on the assessment score obtained in Table 18, Alt 2 (mySugr) had the highest assessment score (\(AS_{i}\)) (mySugr),while Alt 4 (Blood Glucose Tracker) had the lowest assessment score, indicating that mySugr is the best mHealth application in respect of the usability parameter. The ranking of the mHealth applications obtained using the CODAS approach based on the \(AS_{i}\) value is shown in Figure 5.  
To assess the proposed framework's stability and validity, a sensitivity analysis was performed. Threshold values ranged from 0.01 to 0.05, with assessment score (\(AS_{i}\)) values recorded for each threshold value. Similar rankings were produced for each threshold value using the indicated \(AS_{i}\) values, showing that the ranking results are stable and valid. Figure 6 shows the sensitivity analysis-based ranking achieved at various \(\tau\) values.