Intervention fidelity and factors affecting the process of a mobile phone text messaging intervention among adolescents living with HIV: A convergent mixed methods study in southern Ethiopia
Abstract
Objective: To assess the intervention fidelity and explore contextual factors affecting the process of a mobile phone text messaging intervention in improving adherence to and retention in care among adolescents living with HIV, their families, and their healthcare providers in southern Ethiopia.
Design: A convergent mixed-methods design guided by the process evaluation theoretical framework and the RE-AIM framework was used alongside a randomised controlled trial to examine the fidelity and explore the experiences of participants in the intervention.
Setting: Six hospitals and five health centres providing HIV treatment and care to adolescents in five zones in southern Ethiopia. Participants: adolescents (aged 10–19), their families and their healthcare providers.
Intervention: Mobile phone text messages daily for 6 months or standard care (control). Results: 306 participants were enrolled in the process evaluation. Among the intervention participants (N =153), 171 (55.9%) of whom were men, most resided in an urban area 225 (73.5%), and participants had a mean age of 15 (2.62). The overall experiences of implementing the text messages reminder intervention were described as helpful in terms of treatment support for adherence but had room for improvement. During the study, 30,700 text messages were sent, and fidelity was high, with 99.4% successfully receiving text messages during the intervention. Barriers such as failed text messages delivery, limitations in phone ownership, and technical limitations affected fidelity. Technical challenges can hinder maintenance, but a belief in the future of digital communication permeates the experiences of the text messages reminders.
Conclusions: Overall fidelity was high, and participants’ overall experiences of mobile phone text messages were expressed as helpful. Contextual factors, such as local telecommunications networks and local electric power, as well as technical and individual factors must be considered when planning future interventions.
https://doi.org/10.5061/dryad.n8pk0p31s
We have submitted our raw data (Interventionfidelity_data.csv)
Description of the data and file structure
ID= study identification
weight = weight of participants in kilograms (kg)
height = height of participants in centimeter (cm)
viral = viral load status of participants
study_arm= participants enrolled as intervention arm
antirethroviral_adherence= participants antiretroviral treatment adherence status
dose_missed_six_months = number of drug missed prescribed for six months
doze_per_month= number of drug missed in one month
age = age of participants
psycho_social_peer_support = participated in psycho social peer support group
cotermoxiazol_preventive_theraphy_adherence = participants cotermoxiazol preventive theraphy adherence status
functional_status = functional status of participants
current_regimen = current regimen of participants
Tuberculosis = tuberculosis treatment status of participants
patient_provider_satisfaction = patient provider satisfaction of participants about treatment and care
visit_frequency = visit frequency of participants
satsfied_vist_schedule = participants satsfied with vist schedule
ever_missed_apointment =participants appointment missing status
transportation_cost = transportation cost of participants to visit facilities
know_drug_name = participants know the name of the drugs taking
know_pill_dose = participants know pill dose of the day
drug_taking_morning_evening = participants taking treatment drug twice a day
knows_instructions = participants know instructions to take drugs
WHO_stage = participants WHO stage
indications_Antiretroviral_theraphy = indications of patients for Antiretroviral treatment
antiretro_viral_regimen_change = any change in Antiretroviral treatment regimen
switch_2ndline_follow = any switch to second line treatment regimen
antiretro_viral_dosage_adjustment_follow = dosage adjustment of the drugs
miss_medication = missed to take prescribed drugs in scheduled period
drug_morning_hour = participants receiving morning drugs
pillcount_adherence = pill count adherence of participants
Sharing/Access information
This is a section for linking to other ways to access the data and for linking to sources the data is derived from, if any.
Links to other publicly accessible locations of the data: no other sources
data was derived from the following sources:
- uploaded from personal computer
Code/Software
Stata/SPSS is required to run the data