five

Mobile phone intervention for improving ART adherence

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NIAID Data Ecosystem2026-03-10 收录
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A randomised control trial was done to determine the effect of mobile phone intervention on adherence in a two groups (Intervention and Control). Respondents (n = 362) age 18-60 years, HIV seropositive, with access to mobile phone were recruited and followed-up for six months. The Control group received standard care while the Intervention group received standard care, alarm prompting, weekly text messages and monthly voice calls. Primary (overall adherence: Self-report, visual analogue, pill identification, pill count) and secondary (CD4 count and Body Mass Index) outcomes were measured at baseline (B), month three (F1) and month six (F2). Series of data transformation and computations were done to derive final outcome. Data comprises nominal, ordinal and scale computations. -BMI= Weight in kilogram divided by height in meter square Scoring multimethod adherence tool 1.Self-reporting (Sr) There are four questions with Yes/No responses. Response Interpretation Code % Score No to all items Highly Adherent 3 95 or more Yes to 1 item Moderately adherent 2 75-94 Yes to 2 or more items Low adherence 1 75 or less 2.Visual Analogue Scale (VAS) Responses 0 1 2 3 4 5 6 7 8 9 10 Score (%) 0 10 20 30 40 50 60 70 80 90 100 3.Pill identification test (PIT) Response Interpretation % Score Ability to remember dose, time and instruction Highly Adherent 95 or more Ability to remember dose and time Moderately adherent 75-94 Ability to remember dose only Low adherence 75 or less 4. Pill Count (PC) % Adherence = Dispensed –Returned x 100 divided by Expected to be taken 5. Overall Adherence scores (OAS)More than 95 % (High) 75-95% (Moderate) Less than 75% (Low) Other Variables such as demographic profile, use of mobile phone and factors influencing adherence were also measure and categorised in data set. Mixed modeling requires data restructuring and use of the following syntax (replace variable to estimate other relationships. MIXED OAS BY Index1 id GROUP WITH age sex Ledu Mstatus employment Rel /CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001) HCONVERGE(0, ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE) /FIXED= time GROUP age sex Ledu Mstatus employment Rel time*GROUP /REPEATED = time | SUBJECT(id) COVTYPE(arh1) /emmeans = tables(GROUP*time) compare(GROUP) /emmeans = tables(GROUP*time) com MIXED BMIres BY id GROUP time /CRITERIA=CIN(95) MXITER(100) MXSTEP(10) SCORING(1) SINGULAR(0.000000000001) HCONVERGE(0, ABSOLUTE) LCONVERGE(0, ABSOLUTE) PCONVERGE(0.000001, ABSOLUTE) /FIXED= time GROUP time*GROUP /REPEATED = time | SUBJECT(id) COVTYPE(arh1) /emmeans = tables(GROUP*time) compare(GROUP) /emmeans = tables(GROUP*time) compare(time).
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2018-01-13
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