Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis

Nishant Mehra; Abayneh Tunje; Inger Kristensson Hallström; Degu Jerene

doi:10.1371/journal.pone.0254890

. 2021 Jul 22;16(7):e0254890. doi: 10.1371/journal.pone.0254890

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis

Nishant Mehra ^1,^*, Abayneh Tunje ^1,², Inger Kristensson Hallström ¹, Degu Jerene ³

Editor: Giuseppe Vittorio De Socio⁴

PMCID: PMC8297901 PMID: 34293033

Abstract

Background

Poor adherence to antiretroviral therapy in adolescents living with HIV is a global challenge. One of the key strategies to improve adherence is believed to be the use of digital adherence tools. However, evidence is limited in this area. Our objective was to investigate the effectiveness of mobile phone text message reminders in improving ART adherence for adolescents.

Methods

The preferred reporting item for systematic review and meta-analysis guideline was followed. A literature search was done in five databases (PubMed, Web of Science, Embase, Global Health and Cochrane) in August 2020. Additional searches for studies and grey literature were performed manually. We included studies with quantitative design exploring the effectiveness of text message reminders, targeting adolescents aged 10–19 years. Studies were excluded if the intervention involved phone calls, phone-based applications, or other complex tech services. Mean differences between intervention and standard of care were computed using a random effects model. Subgroup analyses were performed to identify sources of heterogeneity between one-way and two-way text messages.

Results

Of 2517 study titles screened, seven eligible studies were included in the systematic review. The total number of participants in the included studies was 987, and the study sample varied from 14 to 332. Five studies showed a positive impact of text messaging in improving adherence, while no significant difference was found between the intervention and the control (standard of care) group in the remaining two studies. The pooled mean difference between the intervention and the control group was 0.05 (95% CI: –0.08 to 0.17). There was considerable heterogeneity among the studies (I² = 78%).

Conclusion and recommendation

The meta-analysis of text message reminder interventions did not show a statistically significant difference in the improvement of ART adherence among adolescents living with HIV. The included studies were heterogeneous in the reported clinical outcomes, where the effectiveness of the intervention was identified in small studies which had a short follow-up period. Studies with bigger sample size and a longer follow-up period are needed.

Introduction

Human Immunodeficiency Virus (HIV), which causes Acquired Immunodeficiency Syndrome (AIDS), is one of the world’s most serious health and development challenges. Since the beginning of the HIV pandemic, more than 76 million people have been infected with HIV [1], and about 38 million people are currently living with HIV [2]. More than half of the disease burden for HIV is in East and Southern Africa, with an estimated 730,000 new cases in 2019. The latest estimates suggest that approximately 1.7 million adolescents have HIV, accounting for about 5% of all people living with HIV (PLHIV) [3, 4]. The definition of an adolescent used in this study is a person aged 10–19 years [5]. The adolescent age group is further subcategorised into early adolescents (10–15 years), middle adolescents (14–17 years) and late adolescents (16–19 years) [6].

With an emphasis on viral suppression, the Joint United Nations Programme on HIV/AIDS launched a 90-90-90 initiative in 2014 [7]. A target was set for 2020 that 90% of people living with HIV know their status, 90% of those who know their status start treatment, and 90% of those on treatment achieve viral suppression [7]. At the end of 2019, 12.6 million people (33% of people living with HIV) did not have access to antiretroviral therapy (ART) [8]. An estimated 840,000 children did not have access to ART at the end of 2019, amounting to 47% of all children living with HIV [8]. Even though ART has achieved great success, the 2020 treatment targets seem unachievable for many countries. Because of significant improvements in access to ART over the last decade, the annual AIDS-related death rate has declined significantly since 2003, with over 70% decrease in the age range of 0–9 years, but the decline in adolescents is a mere six percentage points [9, 10]. In 2019, global AIDS-related deaths among those aged below 15 years numbered 95,000 [8]. Also, retention in care and adherence to ART regimens have been increasingly seen as a challenge in the global fight against this pandemic. Treatment adherence is defined as how patients’ medication-taking behaviour corresponds to their health care professionals’ recommendations, including taking medications daily at roughly the same time without missing doses [11]. It is the key to better health outcomes in chronic diseases like HIV, and it also helps to limit onward transmission, thus helping to reduce the burden of disease [10, 12]. For optimal viral suppression, an adherence rate of more than 95% is widely cited [13]. However, recent studies suggest that even moderate adherence to potent ART regimens can achieve viral suppression [14]. Parienti et al. point to sustained treatment interruptions leading to viral rebound rather than interspersed missed doses [15]. Studies suggest that globally about 60% of adolescents adhere to ART [16]. Poor ART adherence leads to accelerated progression of PLHIV to AIDS [17], resulting in increased morbidity and mortality [18].

Frequently reported barriers to adherence to ART among adolescents are forgetfulness [19–21], stigmatisation of status disclosure [19, 21, 22], adverse effects of medication [19], anxiety, depression and substance abuse [19–22], financial constraints [21] and accessibility issues [19]. For these reasons, the World Health Organization (WHO) asserts the need for a better support system for adolescents to improve their adherence to ART [23].

Since the beginning of the 21st century, access to the internet and mobile phones among adolescents has improved globally [24]. This has stimulated an interest in exploring the role of information, communication, and technology in health, also known as eHealth [25]. The WHO Global Observatory for eHealth defines eHealth as “the use of information and communication technologies (ICT) for health” [26]. This involves the delivery of health information by using mobile phones’ short message service (SMS), patient monitoring devices, and internet-based components (social media, computer software, websites, mobile apps, games, and chat rooms) [27]. Mobile health (mHealth) technology is a specific kind of eHealth service that is defined by the Healthcare Information and Management Systems Society (HIMSS) as the use of small, portable computers or telecommunication equipment to meet the needs of health care and improve the quality of clinical research and healthcare on a global scale.

In the past decade, several studies have explored the acceptability, feasibility, and utility of eHealth and mHealth interventions to improve adherence among patients living with chronic diseases [28–31]. The advantages of using mHealth interventions are their low cost, making them suitable for use in low- and middle-income countries (LMIC), along with their convenience and accessibility. Besides, mHealth can provide users with a private space to curb the discrimination and stigma associated with HIV [32–35]. However, the path to mHealth incorporation into clinical care is fraught with many challenges [36].

In this study, the effect of a text message reminder intervention on ART adherence in adolescents living with HIV is explored by performing a systematic review and a meta-analysis. A text message is a simple mHealth service where patients receive an SMS reminding them to take their medication on time. The SMS is sent at a predetermined time, usually before the scheduled medication intake time for the patient as recommended by their doctors. Commonly the service can be categorised as either a one-way text message (patient receiving an SMS from the care provider) or a two-way text message (patient having the opportunity to respond to the SMS). A text message can be received on a mobile phone with basic features. This intervention avoids stigma and can be rolled out in a resource-limited setting. Previous studies have shown the effectiveness of mHealth interventions in improving treatment adherence among adults living with HIV [37–40], and the evidence is emerging in the adolescent age group.

This study therefore aims to identify and investigate the current literature looking into the effectiveness of mobile phone text message reminders in improving ART adherence among adolescents.

Methods

The preferred reporting item for systematic review and meta-analysis (PRISMA) guidelines was followed [41]. The search was based on a PICO (Population/Problem, Intervention, Control and Outcome) question with explicit inclusion and exclusion criteria: Does targeted mobile text messaging improve adherence to antiretroviral treatment among adolescents living with HIV compared to a “standard of care”?

Criteria for study selection

The inclusion criteria were: all peer-reviewed articles, registered trials and conference abstracts and posters available in English where the search for the records was not restricted to a time limit; HIV as the primary focus of the study; mobile phone text messaging (SMS) reminder as an intervention to improve adherence; using either adherence to ART (measured in different ways) or viral load as the study outcome; quantitative study design investigating the impact of text message reminders (cohort studies and randomised control trials (RCT)).

Studies were excluded if: phone calls or sophisticated mHealth or eHealth interventions such as smartphone applications, social media, internet etc.; the majority of study participants (more than 50%) do not belong to the adolescent age group as ascertained by reported mean age and standard deviation; qualitative study design, systematic reviews and meta-analysis and quantitative study design that do not account for effectiveness (cross-sectional studies etc.).

Source of data and search strategy

Under the guidance of a librarian, a comprehensive search strategy was developed. The search was performed using a combination of keywords and truncated terms in two sets using Boolean search strategy (intervention and disease): “mobile phone*”, “cell phone*”, “text reminder*”, “text messages*”, “phone based*” and “HIV”, “AIDS”, “ART”, “Antiretroviral therap*”. The literature search was done on PubMed, Embase, Web of Science, Global Health (CABI) and Cochrane databases on 18 August 2020. In the Embase database search, citations unique to this database were only included using the “Source” function. Additional articles were identified by hand searching the reference list of the screened articles, www.clinicaltrials.gov, Grey Literature Report, International AIDS Society–conference abstracts, Conferences on Retroviruses and Opportunistic Infections [42]. Citations of all studies were downloaded to EndNote 8 citation manager software [43], where they were further sorted.

Study selection

After removing the duplicates from the search hits, first titles and then abstracts were screened by NM based on the inclusion criteria. Later, full texts were read by two authors (NM and AT) and assessed based on the exclusion criteria. Fig 1 shows the detailed process of the screening and selection process. Disagreement concerning the inclusion of a study was resolved by the third and fourth researcher (IKH and DJ).

Data extraction and quality assessment

For each study, data on demographics, interventions and outcomes were extracted independently by two authors (NM and AT). This process was guided by Cochrane’s data collection recommendations [44]. Later data were tabulated into two tables: (1) study characteristics and (2) interventions and adherence results. Cochrane’s risk assessment tool was used to assess the quality of the included randomised studies at the level of individual studies [45]. Studies with a non-randomised study design were assessed using the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I) tool [46].

Quantitative analysis

A meta-analysis was undertaken where pooled mean differences in adherence for the intervention versus standard of care was calculated. Most studies included in this systematic review reported adherence to ART as a continuous outcome (mean adherence). Therefore, mean adherence was chosen as the outcome measure for quantitative analysis. For the meta-analysis, adherence is defined as how a participants’ pill count or MEMS data corresponds to their doctor’s prescription regimen during the period of trial. Mean adherence is a continuous variable that can take a value from 0–1, where 0 represents nil adherence, and 1 represent perfect adherence. The data used in the analysis were mean adherence rates, standard deviation, and the number of participants in each intervention arm. Where standard deviation was not available, other effect measures such as confidence intervals were converted to fit the model. If it was not possible to transform the effect measures without access to raw data, studies were excluded from the meta-analysis. Due to the anticipated heterogeneity of the structure of intervention, a random effects model was used to estimate the pooled mean difference between the intervention arms with a 95% confidence interval. Studies with a similar intervention (one-way text message, two-way text message and short follow-up (<6 months)) were further analysed in sub-groups using a fixed effects model. All statistical analyses were performed using Review Manager (version 5.4; The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark).

Results

Study characteristics

A total of 2517 study titles were screened based on the study selection criteria. Seven studies were included in the review; five RCTs (two in the USA and one each in Uganda, Nigeria, and Cameroon) and two cohort studies (one each in USA and Argentina) analysing the effect of mobile text reminders for improving adherence to ART among adolescents living with HIV were included (Fig 1). The total number of participants in the included studies was 987, and the study sample varied from 14 to 332 (Table 1). Of the seven studies included, four were peer-reviewed articles [47–50], two studies were registered trials with available results [51, 52] and a conference poster with results [53].

Table 1. Characteristics of included studies.

Author	Study	Study	Gender		Age of	ART treatment	Adherence status/
Year	design	size (N)	Male	Female	participants	experience	viral load at the
Country					(years)		time of recruitment
Hailey [47]	Cohort	87	70	17	15–24	New and existing	Sub-optimal adherence
2013						patients
USA
Stankievich [50]	Cohort	22	7	15	6–25	Unspecified	Viral Load
2014					mean 17		>1000 copies/ml
Argentina
Jeffries [53]	RCT	136	NA	NA	15–24	>1 year– 60%	New patients or
2016						<6 months– 24%	sub-optimal adherence
USA
Linnemayr [48]	RCT	332	151	181	15–22	Treatment experienced	Not reported
2017					mean 18
Uganda					mean 18
Abiodun [52]	RCT	212	108	104	15–19	Unspecified	Sub-optimal adherence
2019					mean 16
Nigeria
Ketchaji [54]	RCT	184	NA	NA	15–19	>6 months	Sub-optimal adherence
2019
Cameroon
Mimiaga [49]	RCT	14	8	6	16–24	Unspecified	Sub-optimal adherence
2019					mean 19
USA

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RCT–Randomised Control Trial; NA–Not Available

The mean age of the participants in most studies was in the late adolescent age group (16–19 years). One study had over 80% male participants [47], another had 69% females [50]. The remaining studies were more gender-equal. Six studies reported sub-optimal baseline adherence levels among recruited participants. Three studies [47, 48, 51] mentioned recruiting patients with experience of treatment (patient started ART at least six months before recruitment to trial) (Table 1). One study mentioned speaking English as a criterion for inclusion [53]. Access to mobile phones was an inclusion criterion in all the included studies. The study participants in all studies received text messages. In the study by Stankievich et al., about 30% of the participants’ parents received the text message [50].

Quality assessment and risk of bias

Of the five RCTs that were analysed using the Cochrane risk assessment tool, three–Linnemayr (2017), Abiodun (2019), and Ketchaji (2019)–were deemed to have a low risk of bias (Fig 2). The main concern with these studies was that the participants in different intervention arms were not blinded due to the unique nature of the intervention. Mimiaga’s (2019) study was judged to be at high risk of bias due to incomplete and selective reporting of outcomes compared with their research protocol [49, 55]. Jeffries’ (2016) study was judged to have an unclear risk of bias as this was a poster study and raw data could not be accessed. The two cohort studies by Hailey (2013), and Stankievich (2014), were assessed based on the ROBINS-I tool and judged to be at serious risk of bias as they lacked a control group. Overall, studies with a bigger sample size were found to be at low risk of bias [48, 52].

Summary of included studies

Overall, four studies had only text messages as their intervention, while the others included counselling or peer support as a part of both intervention and standard of care (Table 2). The primary outcome was reported either as medication adherence or viral load. Three studies (Hailey 2013, Abiodun 2019, and Ketchaji 2019) used self-reported data for outcome assessment, while two studies (Linnemayr 2014 and Mimiaga 2019) documented using a medication event monitoring system (MEMS) in addition to self-reported data. Medication adherence was reported as a mean adherence rate, odds ratio, or using a visual analogue scale (VAS) score. A laboratory test was used to report viral load, and this was reported as number of copies/ml. The follow-up period ranged from 4 months to 24 months. Most studies had a drop-out rate of less than 5% [47, 49, 52], while two studies had a drop-out of up to 19% [48, 54].

Table 2. Reviewed studies.

Author	Intervention	Follow-up	Drop-out rate	Outcome measures	Adherence and/or viral load measurement¹
Year	(no. of participants)	period		Measurement tool
Country				Unit
Hailey	I: Phase one: 2-way SMS (86)	24 months	Drop-out 0%	ART adherence	Baseline = 40–50%
2013	Phase two: video DOT (1)
USA				Self-reported	24 months = 80%
	C: No control group
				Mean score
Stankievich	I: Mobile generic contact	32 weeks	Drop-out 9%	Viral load	Baseline 1020–500,000
2014	Twice a month text message				(mean 25,100)
Argentina	and Facebook (22)			Blood test
	C: No control group				32 weeks
				mean copies/ml	Undetectable in 65%
				proportion of copies/ml	<1000 in 70%
Jeffries	I: 12 tailored messages	6 months	Drop-out not	Viral load	Baseline
2016	per week (91)		reported		I: 2.08, C: 2.28 (0.64)
USA				Blood test
	C: SOC (45)				3 months
				unit (p-value)	I: 1.96, C: 3.5 (0.039)
					6 months
					I: 1.5, C: 3.94 (0.003)
Linnemayr 2017 Uganda	I1: one-way SMS (110) I2: two-way SMS (110) C: SOC (112)	48 weeks	Drop-out 18%	ART adherence Self-reported mean score at baseline MEMS at 48 weeks mean (95% CI) p-value	Baseline
					I1: 81%, I2: 81%, C:81%
					48 weeks
					I1: 0.64 (0.58, 0.70)
					I2: 0.61 (0.56, 0.67)
					Pooled I: 0.63 (0.59, 0.67)
					Control: 0.67 (0.62, 0.72)
					p-value 0.35
Abiodun	I: SMS with counselling/group	20 weeks	Drop-out 1%	ART adherence	Baseline
2019	chat (106)				I: 0, C: 0
Nigeria				Self-reported
	C: counselling/group				20 weeks
	chat (106)			VAS score > = 95%	I: 57(54.3%), C: 47(45.2%)

					Baseline NA
Ketchaji	I1: Peer support (46)	6 months	Drop-out 19%	ART adherence and viral load	6 months
2019	I2: Daily SMS (46)				Self-reported and pill count
Cameroon	C1: SOC (46)			Self-reported and pill count	I1: 4.1 (1.6–10.9)
	C2: SOC (46)			Blood test	I2: 5.8 (2.3–14.9)

				Odds ratio (95%CI)	Viral load suppression
					I1: 14.7 (4.8–44.6)
					I2: 15.6 (4.2–57.7)
Mimiaga	I: Step 1: daily 2-way message	4 months	Drop-out 0%	ART adherence	Baseline
2019	Step 2: five counselling				score 74% (SD = 35.3)
USA	sessions (7)			MEMS and self-reported
					4 months
	C: SOC (7)			Mean score (SD)	I: mean change score
					13% (SD = 29.5)
					C: mean change score
					–26% (SD = 26.0)

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I–Intervention; I1 –First intervention; I2 –Second intervention; C–Control; SOC–Standard of Care; MEMS = Medication Event Monitoring System; SMS = Short Message Service, NA–Not Applicable

1 –Adherence and viral load measured at baseline and at the end of the follow-up period.

Assessment of the effectiveness of text messaging

Of the total seven reviews, five reported a positive impact of text messaging in improving treatment adherence: 3 RCTs (Jeffries 2016, Ketchaji 2019, and Mimiaga 2019) and 2 cohort studies (Hailey 2013 and Stankievich 2014) (Table 2). RCTs by Linnemayr (2014) and Abiodun (2019) showed no significant difference between the comparison groups. The unit of analysis in the meta-analysis was mean adherence, and this was the reported effect measure in the 3 RCTs: Abiodun et al. (2019), Linnemayr et al. (2014), and Mimiaga et al. (2019).

The pooled mean adherence difference was found to be 0.05 (Fig 3). However, these studies showed statistical heterogeneity (I² = 78%). Sub-group analysis of studies found no difference in mean ART adherence (mean difference = 0.00) among adolescents who receive only text message (one way) (Fig 4). For a sub-group analysis of a two-way text message intervention, the pooled mean difference was –0.03 (Fig 5).

A third subgroup analysis focusing on studies with a short follow-up period suggests that the overall effect of the intervention is insignificant (p-value = 0.15) (Fig 6).

Discussion

This systematic review identified seven eligible studies, which consisted of five RCTs and two cohort studies. The cohort studies showed a positive effect of the intervention but were judged to be at serious risk of bias as they lacked a control group. Of the five RCTs, three [47, 49, 51] demonstrated the effectiveness of mobile text messaging in improving ART treatment adherence among adolescents. However, the remaining two RCTs [48, 52] did not significantly differ between the intervention and comparison groups. A meta-analysis of three studies [48, 49, 52] showed considerable heterogeneity among the included studies and no significant pooled mean difference between the intervention arms. The meta-analysis findings were further affirmed by sub-group analyses, where no significant effect of the intervention was found compared to the standard of care.

To our knowledge, this is the first adolescent-specific systematic review of the effectiveness of mobile text messaging in improving adherence to ART. Several previous reviews assessing the effectiveness of text message reminders and other mobile phone-based interventions in improving ART adherence found the intervention to be effective among adults [37, 38, 56]. A meta-analysis study performed in the USA among adults revealed that mobile text message reminders significantly improved antiretroviral therapy adherence and viral load and/or CD4+count [57]. This was not evident in the present meta-analysis, which may be attributed to the heterogeneity of the studies included. However, a sub-group analysis for a one-way text message with no statistical heterogeneity also lacked an effect in improving adherence.

Studies in the adult age group in LMIC countries showed improved adherence in small samples and short follow-up [58, 59]. In the present review, findings from LMIC are unclear as the study from Cameroon [54] found improved adherence among adolescents, but this was contrary to the findings from studies conducted in Nigeria [52] and Uganda [48]. Most studies with a positive impact of text messaging in the current review were from high-income countries and had a small sample size [47, 49, 50]. However, these were judged to be at high risk of bias. Additionally, a small study effect cannot be ruled out in this case. These findings highlight the differences between adults and adolescents in their response to mobile phone text messaging regarding adherence to ART and the quality of evidence currently available. Fewer studies focusing on the adolescent age group may be a reason behind the differing findings.

Most of the studies included in the present review enrolled participants in the late adolescent age group [47–49, 51–53]. This may be because, in most countries, the legal age of consent for medical intervention is in the late adolescent years. Thus, age may be a deterrent for conducting trials with the early adolescent age group because obtaining a guardian’s consent may affect privacy. Accessibility to mobile phones was an inclusion criterion in all the studies, and this may have discouraged researchers from enrolling early age adolescents as they are comparatively less likely to have access to a mobile phone. Although adolescents’ access to mobile phones has increased in the past couple of decades, it still varies between countries depending on individuals’ socioeconomic status and the cultural norms of the society [60]. A recent study showed the acceptability of a text message reminder intervention to patients in urban and rural settings [60]. However, a study by Rana et al. [61] asserts the need to maintain confidentiality, which can be challenging if participants do not own a mobile phone or share it with other people at home [61]. Therefore, the feasibility of implementing such interventions in adolescents needs to be explored further at a community level.

Though eHealth and mHealth interventions are increasingly being used for chronic health conditions, this review found that few studies have looked at the late adolescent age group (16–19 years). The current evidence base is particularly meagre in resource-limited settings where we expect patients to benefit more from low-cost mHealth interventions. Therefore, more trials with larger study populations in LMIC are called for, and more evidence for the early adolescent age group is required.

Based on the overall assessment, the effectiveness of text reminders in improving adherence to ART remains inconclusive due to small studies that enrolled non-adherent treatment initiators. This might be due to the lower power of the included studies and the fact that few interventional studies have been conducted in the adolescent age group. There is a need to explore the potential of text messaging interventions further, especially with multi-component elements such as two-way messaging in adolescents. Future trials should have a larger sample size and a more extended follow-up period to have more power in the findings. The potential of text messages beyond reminders needs to be further explored.

The present study has both strengths and limitations. This is a comprehensive review of text message reminder interventions to improve ART adherence in the adolescent age group. In the process, a thorough search strategy was implemented under the guidance of an expert librarian, strengthening the validity of our findings. Further attempts were made to reach out to the authors of the included studies to gain access to raw data. Another strength of this study was the use of a mean age of participants in the included studies as a criterion, which contributes to the credibility of our findings as we intended to investigate a specific population. Since adolescent-specific systematic reviews are lacking on this topic, it makes this study a pioneering contribution to the field.

We also acknowledge some limitations in our study. Of the seven studies included in the current review, three were not published in peer-reviewed journals. This raises concerns about the overall quality of the evidence produced by these studies, and therefore entails the limitation that the results are based on data with questionable credibility. Moreover, five studies used self-reported data, which is considered a less sensitive measure of adherence than MEMS and tends to overestimate adherence [62]. We think that the inclusion of self-reported data in our meta-analysis may affect the validity of our findings, and this is therefore a limitation of the present study. Finally, variation in reported outcome (continuous or binary) and units posed a challenge to include most studies in the meta-analysis. Odds ratio is a more common outcome measure for adherence in a meta-analysis that evaluates a binary outcome. In the current study, the included studies dichotomised adherence at different points that posed a challenge to have odds ratio as an outcome measure. Nevertheless, the findings of this meta-analysis can guide the research potential of text messaging in adolescents.

Conclusion

There is a limited number of studies assessing the effectiveness of mobile phone text reminders in improving adherence to ART among adolescents. Adolescents were the sole recipients of the text messages in most of the studies. The few available studies have critical methodological weaknesses, including a lack of control groups and small sample sizes. Our review of the available evidence nevertheless suggests a positive impact of mobile phone text reminders on adherence to ART among adolescents. The included studies were heterogeneous in the reported clinical outcome. The meta-analysis showed no significant improvement in adherence. Further studies with a more rigorous design are needed to assess the effectiveness of mobile phone text messaging in improving ART adherence in the adolescent age group.

Supporting information

S1 Appendix. Search strategy.

(DOCX)

Click here for additional data file.^{(14.7KB, docx)}

S2 Appendix. PRISMA checklist.

(DOCX)

Click here for additional data file.^{(21.1KB, docx)}

S3 Appendix. Data for meta-analysis.

(XLSX)

Click here for additional data file.^{(10.5KB, xlsx)}

Acknowledgments

The authors would like to thank Ms. Maria Bjorklund for her guidance in developing the literature search strategy.

Abbreviations

AIDS: Acquired Immuno-deficiency Syndrome
ART: Anti-retroviral therapy
HIV: Human Immunodeficiency Virus
LMIC: Low- and middle-income countries
MEMS: Medication Event Monitoring System
RCT: Randomised control trial
ROBINS-I: Risk of bias in non-randomised studies of interventions
SMS: Short message service
USA: United States of America
WHO: World Health Organization

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The study was supported by the Swedish Research Council for Health, Working Life and Welfare Life (FORTE) (https://forte.se/en/) program support 2018–01399 and Swedish Research Council (Vetenskapsrådet) (https://www.vr.se/english.html) program support VR 2016-05706. The funder had no role in the design of the study and collection, analysis, and interpretation of data or in writing the manuscript. The grant was awarded to IKH and DJ.

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PLoS One. doi: 10.1371/journal.pone.0254890.r001

Decision Letter 0

Giuseppe Vittorio De Socio

5 Mar 2021

PONE-D-21-02241

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: a systematic review and meta-analysis.

PLOS ONE

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Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: The authors stated that "the data are fully available without restriction" and "all relevant data are within the manuscript and its supporting files". I was not able to find any data files or analysis code. I'd be happy to complete a full review once the data and code are shared. I'm marking as "reject" at this point on the recommendation of the handling editor as a way to request access to these materials. This recommendation is not based on any assessment that the paper is unsuitable for publication.

Reviewer #2: To the authors:

This manuscript addresses an extremely important topic and I applaud the authors for undertaking this systematic review and meta-analysis to help us understand whether mobile phone SMS hold promise to support improved adherence in a known vulnerable population: adolescents with HIV. I enjoyed reading the manuscript. I found a few places that need clarification. With some careful editing, I believe it will be worthy of publication.

Specific Comments:

Abstract

1. In the Results section, 3rd sentence, the authors write, “… while no significant difference was found in the standard of care in the remaining two studies.” This is confusing. Do you mean that no difference was found between intervention and control (standard of care) groups? This should be clarified.

2. In the Conclusion and recommendation section, I think it would be good to highlight more prominently that this study could not confirm its motivating question: whether mobile phone text message interventions can improve adherence among HIV-positive adolescents. The meta-analysis failed to show a significant difference – it’s there in this section but it’s a bit buried between other points. This fundamental finding should be highlighted, I think.

Introduction

3. On page 3, second paragraph, there are some confusing numbers provided. In line 6 of the paragraph (lines 67-68) beginning with “With an emphasis on viral suppression…”, the sentence that says, “… of which 53% were aged 0-14 years and 68% aged 15 and older living with HIV” doesn’t make sense. Can you clarify these numbers?

4. In the same paragraph, some of the references seem a bit old. For instance, the UNAIDS Global AIDS update is cited from 2017 – but the 2020 report is out, so I would recommend using the most recent numbers throughout this important background paragrph.

5. On page 4, in the first paragraph, top line of the page (line 75), the authors write, “Adherence to treatment, defined as how medication-taking behavior corresponds to the recommendations….” is not very helpful as an operational definition. What you mean is more like – “defined as taking HIV medications as prescribed, which includes taking them every day at roughly the same time, without missing doses.”

6. For the last sentence in the same paragraph (line 81), why is the Finitsis article on text message interventions the reference for a general statement on the importance of adherence in preventing progression to AIDS, morbidity, and death among PLHIV? I think it would be good to have a reference to a study whose purpose was to investigate the relationship between adherence and morbidity/death (such as Paterson et al (2000) and Arnsten et al (2001)).

7. On the next page (5), in the last paragraph (line 109), the authors write about their study focusing on the effect of text message reminders to improve ART adherence – but don’t specify that they are also focusing on a specific population: adolescents. This is an important part of their study and should be included here.

Methods

8. In the section on Study inclusion criteria, the text on the adherence measure seems confusing and inaccurate. The text reads (in line 138) “Adherence to ART either as pill count or viral load as an outcome.” One problem with this as written is that, while both outcomes are important, and HIV viral load can be an indicator of past adherence, it is not a measure of adherence itself, strictly speaking. The second problem is that saying “…ART either as pill count or viral load” suggests that adherence will be measured as pill count only. Pill count has a specific meaning in measuring adherence, and it is distinct from such measures as self-report, MEMS, etc. and the latter are clearly included in the papers included in the review – so this is very confusing. I would recommend dropping the “pill count” altogether (as that is misleading) and then revising the line somewhat to read: “using either adherence to ART (measured in various ways) or HIV viral load as a study outcome”. In reading the manuscript, this captures what the authors actually did.

9. For study inclusion/exclusion generally, I would not use bullets. I would recommend writing out the specific criteria separated by “;” or I would put them in a simple table.

Results

10. On page 9, in the first paragraph in the Study characteristics section, I would add a sentence clarifying where the five RCTs were done – how many in the USA how many in the four outside of the USA (e.g., in more resource-constrained environments)?

11. On page 13, in the paragraph under the sub-heading “Summary of included studies,” the authors describe the adherence outcome and the fact that some studies used self-report and others used MEMS. This is a really important distinction because most ART adherence researchers accept that self-report is not a very accurate measure of adherence. So one recommendation is to specify clearly how many studies used self-report (Table 2 indicates that two did) here. Second, I think it will be important to acknowledge this limitation in the meta-analysis if studies that use self-reported adherence are included.

12. Table 2 – could you add the time frame for the adherence and viral load outcomes? It is important to know when those measures are taken. That is, for adherence, is it mean adherence over the intervention period, or in the last month? It’s hard to have a sense of the rigor of these studies without knowing when data were collected/analyzed for these outcomes.

13. In Table 2, for the last study, were both MEMS and self-reported adherence used? If so, it might be better to use “and” there to be clear.

14. On page 18, line 250, the authors write, “Sub-group analysis of studies found no difference in mean ART adherence among adolescents who receive only text message (one way)….”. Do you mean that analysis found no significant effect on adherence from one-way text messaging?

Discussion

15. I would add as a study limitation that adherence was measured in different ways, including the limitation related to self-reported adherence.

16. Finally – while the writing is generally clear, there are a number of minor grammar errors that need correcting throughout the manuscript.

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Reviewer #1: Yes: Eric Green

Reviewer #2: No

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PLoS One. 2021 Jul 22;16(7):e0254890. doi: 10.1371/journal.pone.0254890.r002

Author response to Decision Letter 0

21 Mar 2021

We sincerely thank the reviewers for thorough reading of this manuscript and the editor for the opportunity to improve the manuscript. The suggestions and comments have been closely followed and revisions have been made accordingly. We have hopefully addressed the concerns to your satisfaction. Point-by-point responses to the comments are listed below. The revisions have been color tracked in the manuscript.

Answer: We deeply regret the inconvenience to our reviewer. We have attached data files in the Appendix section: S3 Appendix – Data for meta-analysis. We are looking forward to receiving feedback from our reviewer.

Reviewer #2: To the authors:

Specific Comments:

Abstract

Answer: Thank you for pointing out this oversight. We understand that our statement was not clear at this point therefore, we have updated the sentence (Page number 2, line numbers 42 – 44) as follows: “Five studies showed a positive impact of text messaging in improving adherence, while no significant difference was found between the intervention and the control (standard of care) group in the remaining two studies.”

Answer: As suggested by the reviewer, the Conclusion and recommendation section has been revised and it read as follows. (Page 2, line numbers 48 -54) “The meta-analysis did not show a statistically significant difference in improvement of ART adherence due to text message reminder intervention among adolescents living with HIV. The included studies were heterogeneous in the reported clinical outcomes where effectiveness of the intervention was identified in small studies which had a short follow-up period. Studies with a bigger sample size and a longer follow-up period are needed.”

Introduction

Answer: Thank you for pointing out this oversight. The statement (Page number 4, line number 72-76) has been updated as follows: “At the end of 2019, 12.6 million (33% of people living with HIV) people did not have access to antiretroviral therapy (ART). An estimated 840 000 children did not have access to ART at the end of 2019, amounting to 47% of all children living with HIV.”

Answer: Thanks for this valuable input. Latest references have been updated on page 4, line numbers 74 and 75.

Answer: We have updated the definition of Adherence (page number 5, line numbers 82-85) as follows: “Adherence to treatment is defined as how patient’s medication-taking behaviour corresponds to their health care professional’s recommendations which include taking medications daily at about roughly the same time without missing doses.”

Answer: We agree with the reviewer on this point. We have changed our reference to Paterson et al (2000). (Page number 5, line number 90).

Answer: Thanks for pointing this out. We have updated the statement (Page number 6, line number 118-119) as “In this study the effect of a text message reminder intervention on ART adherence in adolescents living with HIV is explored by performing a systematic review and a meta-analysis.”

Methods

Answer: We agree with the reviewer’s suggestion and have updated the statement (Page number 8, line numbers 148-149) as “Using either adherence to ART (measured in different ways) or viral load as the study outcome.”

9. For study inclusion/exclusion generally, I would not use bullets. I would recommend writing out the specific criteria separated by “;” or I would put them in a simple table.

Answer: Based on reviewer’s suggestion we have edited the text. (Page numbers 7-8, line numbers 142-158)

Results

Answer: We have updated the text (Page number 10, line numbers 206-209) and it reads as follows: “Seven studies were included in the review; five RCTs (two in the USA and one each in Uganda, Nigeria, and Cameroon) and two cohort studies (one each in USA and Argentina) analysing the effect of mobile text reminders for improving adherence to ART among adolescents living with HIV were included”

Answer: Thanks for this valuable insight. We have revised the text (page numbers 14-15, line numbers 233-237) as “Three studies (Hailey 2013, Abiodun 2019 and Ketchaji 2019) used self-reported data for outcome assessment, while two studies (Linnemayr 2014 and Mimiaga 2019) documented using a medication event monitoring system (MEMS) in addition to self-reported data.”.

As suggested by the reviewer we have updated our limitations of meta-analysis (page number 23, line numbers 342-345) as follows: “Moreover, five studies used self-reported data, which is considered a less sensitive measure of adherence than MEMS and tends to overestimate the impact. We think that inclusion of self-reported data in our meta-analysis may affect the validity of our findings and therefore is a limitation of this study.”

Answer: We duly acknowledge reviewer’s views on the issue. We have changed the heading of the last column in Table 2 (page number 16) to “Adherence and/or viral load measurement1”. We have further added a note at the bottom of the table (page number 18) “Adherence and viral load measured at baseline and at the end of the follow-up period.” We hope that our modification can address the issue raised by the reviewer.

13. In Table 2, for the last study, were both MEMS and self-reported adherence used? If so, it might be better to use “and” there to be clear.

Answer: Thanks for the suggestion. We have updated Table 2 (page number 18) in this regard.

Answer: At this point we wanted to say that the mean difference between one-way text messaging and control is zero. We have revised are statement (page number 19, line numbers 250-252) as “Sub-group analysis of studies found no difference in mean ART adherence (mean difference = 0.00) among adolescents who receive only text message (one way).” to clarify our viewpoint.

Discussion

15. I would add as a study limitation that adherence was measured in different ways, including the limitation related to self-reported adherence.

Answer: Thank you for this valuable insight. We have updated our limitations of meta-analysis (page number 23, line numbers 342-345) as follows: “Moreover, five studies used self-reported data, which is considered a less sensitive measure of adherence than MEMS and tends to overestimate the impact. We think that inclusion of self-reported data in our meta-analysis may affect the validity of our findings and therefore is a limitation of this study.”

16. Finally – while the writing is generally clear, there are a number of minor grammar errors that need correcting throughout the manuscript.

Answer: We have tried to correct grammatical errors in the manuscript. Additionally, we had our manuscript proofread by a native English speaker who has experience in academic writing.

Attachment

Submitted filename: Respone to reviewers.docx

Click here for additional data file.^{(21.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0254890.r003

Decision Letter 1

Giuseppe Vittorio De Socio

14 Apr 2021

PONE-D-21-02241R1

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: a systematic review and meta-analysis.

PLOS ONE

Dear Dr. Mehra,

Please submit your revised manuscript by May 30. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Giuseppe Vittorio De Socio, MD, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: No

**********

6. Review Comments to the Author

Reviewer #1: The authors conducted a meta-analysis of SMS reminder interventions on ART adherence among HIV-positive adolescents. My main concern is that the outcome is not clearly defined, and this made it hard for me to interpret the findings.

The authors write:

- "Adherence to treatment is defined as how patient’s medication-taking behaviour corresponds to their health care professional’s recommendations which include taking medications daily at about roughly the same time without missing doses."

- "adherence to ART (measured in different ways)"

- "The data used in the analysis were mean adherence rates"

- "Medication adherence was reported as a mean adherence rate, odds ratio, or using a visual analogue scale (VAS) score."

Is adherence a binary outcome? If so, what made someone "adherent" in the primary studies?

Is adherence defined as somone's adherent days / all days during each trial? Is it a pill count?

I searched a bit and confirmed my hunch that many (most?) meta-analyses of medication adherence studies report the effect sizes as odds ratios. It's possible that I'm out of touch on this, but I would benefit from an explanation from the authors about why mean differences of rates makes the most sense for this meta-analysis.

My other comments are minor and should not stand in the way of publication if that is the editor's decision:

- Unclear why cohort studies were included

- Unclear why interventions were limited to SMS (the field has expanded so much since SMS was dominant, e.g., WhatsApp)

- The introduction does not mention anything about the evidence in favor of SMS reminders for adherence among adults living with HIV (does appear in the discussion)

- The overall reporting of the methods and results could be improved

- Why is the age range of adolescents limited to 19? The definition varies across settings. I think more studies could have been included with a broader definition.

Reviewer #2: In this resubmitted version of the manuscript, the authors addressed the points in my original review. Some areas of the revised text are still a bit confusing, however. With a few relatively minor edits, I believe the manuscript will be worthy of publication and make an important contribution to the field.

Specific Comments:

Abstract

1. The authors clarified the main study finding, that the meta-analysis failed to show a significant difference of mobile phone text message reminders, but the text is a bit confusing (Page 2, line numbers 48-49). I would reorganize the first sentence slightly for clarity as follows: “The meta-analysis of text message reminder interventions did not show a statistically significant difference in improvement of ART adherence among adolescents living with HIV.”

Introduction

2. With reference to the edits made to define adherence (page number 4, line numbers 78-81), the authors made helpful edits, but “about” should be removed in the following sentence to avoid redundancy: “Adherence to treatment is defined as how patient’s medication-taking behaviour corresponds to their health care professional’s recommendations which include taking medications daily at [about—remove] roughly the same time without missing doses.”

Discussion

3. Adding that use of self-report as an adherence measure by some of the included studies in the meta-analysis is a study limitation is helpful (page 22, lines 342-345). However, some of that text is not quite accurate, as use of self-report overstates adherence, not impact. Rather than writing “…tends to overestimate the impact” I suggest that the authors say “…tends to overestimate adherence.” Also, it would be good to introduce that paragraph on limitations with something like: “We also acknowledge a number of study limitations…..”

4. Finally – there are still a lot of minor grammar errors and typos that need correcting in the manuscript. I'm sorry I don't have time to point out all the places that need editing. However, here are two examples, both from the Methods section of the Abstract. First, the second sentence beginning with “Literature search was done…” should read, “A literature search was done…” Second, the next to last sentence which ends with, “…computed using a random effect model” should read “…computed using a random effects model." The manuscript needs careful editing by a native English speaker to remove all the errors and typos before it can be published.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Eric Green

Reviewer #2: No

PLoS One. 2021 Jul 22;16(7):e0254890. doi: 10.1371/journal.pone.0254890.r004

Author response to Decision Letter 1

22 May 2021

Response to reviewers

We sincerely thank the reviewers for the thorough reading of this manuscript and the editor for the opportunity to improve the manuscript. The suggestions and comments have been closely followed, and revisions have been made accordingly. We have hopefully addressed the concerns to your satisfaction. Point-by-point responses to the comments are listed below. In addition, the revisions have been colour tracked in the manuscript.

The authors write:

- "adherence to ART (measured in different ways)"

- "The data used in the analysis were mean adherence rates"

- "Medication adherence was reported as a mean adherence rate, odds ratio, or using a visual analogue scale (VAS) score."

Is adherence a binary outcome? If so, what made someone "adherent" in the primary studies?

Response: Thank you for raising this important question. There was considerable heterogeneity in how adherence was reported in primary studies. Four out of seven primary studies reported adherence as a continuous variable where intervention was compared with a control group (Linnemayr et. al., Abiodun et al and Mimiaga et. al.) or a pre-and post-intervention adherence level was reported (Hailey et al). In these studies, the participants receiving the intervention were reported to be more (or less) adherent as compared to a control group and/or a pre-intervention state.

The study by Abiodun et. al., additionally reported a dichotomised variable based on a VAS score of >= 95%. Study by Ketchaji et. al., also reported a binary variable for adherence where criteria for dichotomisation was not reported.

The heterogeneity of the outcomes (continuous or binary) reported in the primary studies affected our choice of outcome measure for meta-analysis. Primary studies dichotomised mean adherence at different points. Therefore, we have updated our limitations as follows (Page 22, lines 345-347): “Finally, variation in reported outcome (continuous or binary) and their units posed a challenge to include most studies in the meta-analysis.”

Is adherence defined as somone's adherent days / all days during each trial? Is it a pill count?

Response: Thanks for highlighting this oversight. In the present study, adherence as an outcome variable is measured either as a pill count or MEMS counts (prescription drug bottle opening counts). In this regard, we have added the following sentences to our methodology (Page 8, lines 182-187) “Most studies included in this systematic review reported adherence to ART as a continuous outcome (mean adherence). Therefore, mean adherence was chosen as the outcome measure for quantitative analysis. For the meta-analysis, adherence is defined as how a participants’ pill count or MEMS data corresponds to their doctor’s prescription regimen during the period of trial. Mean adherence is a continuous variable that can take a value from 0-1, where 0 represents nil adherence, and 1 represent perfect adherence.”.

Response: We thank the reviewer for asking this important question. We agree with the reviewer that most studies used the odds ratio. Mean adherence is an absolute measure of effect as opposed to odds ratio, which is a relative measure of effect. The outcome variable needs to be binary to investigate the odds ratio. If the outcome measure for the analysis is a continuous variable, then it needs to be dichotomised at a specific point. For ART adherence, mean adherence rate is dichotomised at the point where viral suppression is assumed to have achieved.

In the current study, we undertook a comprehensive review of peer-reviewed and grey literature. We decided that having an absolute measure of effect (mean difference) in our meta-analysis will be more suitable due to the following reasons:

1. Using mean adherence rates allowed us to include more studies in the meta-analysis.

2. We were interested in examining whether text message reminder can improve adherence. Mean difference is a commonly used measure of effect in meta-analysis.

3. Mean difference evaluates a continuous variable (mean adherence) and, therefore, is not based on the assumption that viral suppression is achieved at a specific level of adherence.

In this regard, we have updated our methods section as follows (Page 8, lines 182-184) "Most included studies in this systematic review reported adherence to ART as a continuous outcome (mean adherence). Therefore, mean adherence was chosen as the outcome measure for quantitative analysis.". We further updated our limitations as (Page 22, lines 347-350) "Odds ratio is a more common outcome measure for adherence in a meta-analysis that evaluates a binary outcome. However, in the current study, the included studies dichotomised adherence at different points that posed a challenge to have odds ratio as an outcome measure."

My other comments are minor and should not stand in the way of publication if that is the editor's decision:

- Unclear why cohort studies were included

Response: We thank the reviewer for raising this question. The current study aimed to gather evidence of the effectiveness of text message reminder intervention. In addition to randomised studies, a cohort (non-randomised) study design can demonstrate the effectiveness of interventions. Therefore, cohort studies were made a part of the inclusion criteria. The inclusion criteria were decided a priori, given the limited number of randomised trials anticipated in this area.

- Unclear why interventions were limited to SMS (the field has expanded so much since SMS was dominant, e.g., WhatsApp)

Response: We thank the reviewer for this comment. The accessibility of smartphones (having WhatsApp) has been increasing worldwide, especially in high and upper-middle income countries but is currently lower in low and low-middle income countries. So, we first wanted to determine if this primary digital function, SMS, which is available almost everywhere, could have any beneficial impact. In the "Introduction", we have the following statement (Page 5, lines 120-122) "A text message can be received on a mobile phone with basic features. This intervention curtails stigma and can be rolled out in a resource-limited setting.".

- The introduction does not mention anything about the evidence in favor of SMS reminders for adherence among adults living with HIV (does appear in the discussion)

Response: We thank the reviewer for this question. We would like to mention that in the “Introduction” section, we have the following statement to inform on the evidence in favour of SMS reminder for adherence among adults living with HIV (Page 5-6, lines 121-124) “Previous studies have shown the effectiveness of mHealth interventions in improving treatment adherence among adults living with HIV (35-38), and the evidence is emerging in the adolescent age group.”. Four peer-reviewed references support our statement. We acknowledge that we have a more detailed narration on these studies in our "Discussion" section, where we have compared our findings with previous studies in this area.

- The overall reporting of the methods and results could be improved

Response: We thank the reviewer for this helpful suggestion. Based on the reviewers' comments and suggestions, we have tried to improve our methods and results section and tracked changes are made in the manuscript in this regard.

- Why is the age range of adolescents limited to 19? The definition varies across settings. I think more studies could have been included with a broader definition.

Response: We agree more studies could have been included if the age criteria was expanded. However, we utilised the definition of adolescents age group as recommended by the World Health Organisation. We aimed to focus our evidence search on the adolescent age group (defined by WHO) for two reasons. Firstly, we found out some unique challenges related to ART adherence and retention care in this age group. Secondly, we wanted to focus on identifying adolescent-friendly interventions that can improve adherence and retention in care in this unique age group.

Specific Comments:

Abstract

Response: Thanks for the suggestion. We have rewritten the statement as advised (Page 2, line number 48-50).

Introduction

Response: Thanks for the suggestion, we have rewritten the statement as advised (Page 4, line number 78-81).

Discussion

3. Adding that use of self-report as an adherence measure by some of the included studies in the meta-analysis is a study limitation is helpful (page 22, lines 342-344). However, some of that text is not quite accurate, as use of self-report overstates adherence, not impact. Rather than writing “…tends to overestimate the impact” I suggest that the authors say “…tends to overestimate adherence.” Also, it would be good to introduce that paragraph on limitations with something like: “We also acknowledge a number of study limitations…..”

Response: Thanks for this valuable suggestion. We have added a sentence (Page 22, lines 339) “We also acknowledge some limitations in our study.”

We have rewritten another statement in the paragraph (Page 22, lines 342-344) “Moreover, five studies used self-reported data, which is considered a less sensitive measure of adherence than MEMS and tends to overestimate the adherence”.

Response: Thanks for pointing this out. A native English speaker has reviewed the manuscript. We have made tracked changes throughout the manuscript.

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(23.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0254890.r005

Decision Letter 2

Giuseppe Vittorio De Socio

17 Jun 2021

PONE-D-21-02241R2

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis.

PLOS ONE

Dear Dr. Mehra,

See comment by Reviewer #2.

Please submit your revised manuscript by July 15. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Giuseppe Vittorio De Socio, MD, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: (No Response)

Reviewer #2: No

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: Thank you for addressing the comments of reviewers of the previous submission. It is much improved since the previous version. I have two remaining issues that I hope the authors will address.

1. On page 4, line 83, the authors write that adherence >95% is necessary for optimal viral suppression, and cite an article from 2000. ART regimens have improved substantially since 2000 and the precise level of “necessary” adherence for viral suppression is unclear (and is somewhat of a controversial subject). Numerous articles since 2000 have highlighted this point. Please see, for example:

**Bangsberg DR. Less than 95% adherence to nonnucleoside reverse-transcriptase inhibitor therapy can lead to viral suppression. Clin Infect Dis. Oct 1 2006; 43(7): 939-41.

**Parienti JJ, Das-Douglas M, Massari V, Guzman D, Deeks SG, Verdon R, Bangsberg DR. Not all missed doses are the same: sustained NNRTI treatment interruptions predict HIV rebound at low-to-moderate adherence levels. PLoS One. 2008; 3(7): e2783.

**Haberer JE, Sabin L, Amico KR, Orrell C, Galarraga O, Tsai AC, et al. Improving antiretroviral therapy adherence in resource-limited settings at scale: a discussion of interventions and recommendations. J Int AIDS Soc. 2017; 20(1): 21371.

2. The authors state that a native English speaker has reviewed the manuscript, but it still has numerous typos and sentences with incorrect grammar. Two examples are from the first page of the main manuscript: 1) Line 60: the sentence now beginning with “Latest estimates suggest…” should start with “The” so that the sentence reads, “The latest estimates suggest….”; 2) Lines 69-70: the sentence that reads “At the end of 2019, 12.6 million (33% of people living with HIV) people did not have…” should be revised to read: “At the end of 2019, 12.6 million people (33% of people living with HIV) did not have….” I suggest that the authors can do further proofreading and editing so that the manuscript is error free.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Eric Green

Reviewer #2: No

PLoS One. 2021 Jul 22;16(7):e0254890. doi: 10.1371/journal.pone.0254890.r006

Author response to Decision Letter 2

4 Jul 2021

**Bangsberg DR. Less than 95% adherence to nonnucleoside reverse-transcriptase inhibitor therapy can lead to viral suppression. Clin Infect Dis. Oct 1 2006; 43(7): 939-41.

Response: We would like to thank our reviewer for this valuable insight. We have updated our text and included relevant references. The following statements have been included in the manuscript on page 4 Line 84-86 – “However, recent studies suggest that even moderate adherence to potent ART regimens can achieve viral suppression (Bangsberg, 2006). Parienti et al. point to sustained treatment interruptions leading to viral rebound rather than interspersed missed doses (Parienti, 2006).”.

Response: We appreciate our reviewer’s concern. To ensure that our manuscript is error free, it has been reviewed again by a native English speaker. The grammatical corrections are shown as tracked changes throughout the manuscript.

Changes to the reference List

We had one retracted refence in our list that was replaced with a new reference. Furthermore, we identified that four of references are available at a different web location and therefore, they were updated. Lastly, we included 2 new references as per our reviewer’s suggestion above.

Retracted reference – (6) United Nations Children's Fund. Early and late adolescence: UNICEF; 2011 [Available from: https://www.unicef.org/sowc2011/pdfs/Early-and-late-adolescence.pdf].

New reference – (6) World Health Organization. Stages of Adolescent Development 2010 [Available from: https://apps.who.int/adolescent/second-decade/section/section_2/level2_2.php].

Old reference – (10) World Health Organization. Adherence to long-term therapies: evidence for action: World Health Organization; 2003 [Available from: https://www.who.int/chp/knowledge/publications/adherence_report/en/].

Updated reference – (10) World Health Organization. Adherence to long-term therapies: evidence for action Switzerland2003 [Available from: https://apps.who.int/iris/bitstream/handle/10665/42682/9241545992.pdf].

Old reference – (19) World Health Organization. Chapter 9: Guidance on operations and service delivery: WHO; 2013 [Available from: https://www.who.int/hiv/pub/guidelines/arv2013/operational/adherence/en/].

Updated reference – (19) World Health Organization. Chapter 9: Guidance on operations and service delivery: WHO; 2013 [Available from: https://www.who.int/publications/i/item/9789241505727].

Old reference – (23) World Health Organization. HIV and adolescents: guidance for HIV testing and counselling and care for adolescents living with HIV: recommendations for a public health approach and considerations for policy-makers and managers 2013 [Available from: https://www.who.int/hiv/pub/guidelines/adolescents/en/].

Updated reference – (23) World Health Organization. HIV and adolescents: guidance for HIV testing and counselling and care for adolescents living with HIV: recommendations for a public health approach and considerations for policy-makers and managers 2013 [Available from: https://www.who.int/publications/i/item/9789241506168].

Old reference – (26) World Health Organization. Global diffusion of eHealth: Making universal health coverage achievable. Report of the third global survey on eHealth: WHO; 2016 [Available from: https://www.who.int/goe/publications/global_diffusion/en/].

Updated reference – (26) World Health Organization. Global diffusion of eHealth: Making universal health coverage achievable. Report of the third global survey on eHealth: WHO; 2016 [Available from: https://www.who.int/publications/i/item/9789241511780].

Added reference – (14) Bangsberg D. R. Less Than 95% Adherence to Nonnucleoside Reverse-Transcriptase Inhibitor Therapy Can Lead to Viral Suppression. Clinical Infectious Diseases. 2006;43(7):939-41. doi 10.1086/507526

Added reference – (15) Parienti J. J., Das-Douglas M., Massari V., Guzman D., Deeks S. G., Verdon R. et al. Not all missed doses are the same: sustained NNRTI treatment interruptions predict HIV rebound at low-to-moderate adherence levels. PLoS One. 2008;3(7):e2783. doi 10.1371/journal.pone.0002783

Attachment

Submitted filename: Response to reviewers.docx

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PLoS One. doi: 10.1371/journal.pone.0254890.r007

Decision Letter 3

Giuseppe Vittorio De Socio

7 Jul 2021

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis.

PONE-D-21-02241R3

Dear Dr. Mehra,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Giuseppe Vittorio De Socio, MD, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0254890.r008

Acceptance letter

Giuseppe Vittorio De Socio

12 Jul 2021

PONE-D-21-02241R3

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis.

Dear Dr. Mehra:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Giuseppe Vittorio De Socio

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. Search strategy.

(DOCX)

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S2 Appendix. PRISMA checklist.

(DOCX)

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S3 Appendix. Data for meta-analysis.

(XLSX)

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Attachment

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Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

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PERMALINK

Effectiveness of mobile phone text message reminder interventions to improve adherence to antiretroviral therapy among adolescents living with HIV: A systematic review and meta-analysis

Nishant Mehra

Abayneh Tunje

Inger Kristensson Hallström

Degu Jerene

Roles

Abstract

Background

Methods

Results

Conclusion and recommendation

Introduction

Methods

Criteria for study selection

Source of data and search strategy

Study selection

Fig 1. Flowchart describing studies selection process.

Data extraction and quality assessment

Quantitative analysis

Results

Study characteristics

Table 1. Characteristics of included studies.

Quality assessment and risk of bias

Fig 2. Quality assessment of included studies that were randomised.

Summary of included studies

Table 2. Reviewed studies.

Assessment of the effectiveness of text messaging

Fig 3. Forest plot of text message reminder versus standard of care for ART adherence.

Fig 4. Forest plot of a sub-group analysis of one-way text message versus standard of care for ART adherence.

Fig 5. Forest plot of a sub-group analysis of two-way text message versus standard of care for ART adherence.

Fig 6. Forest plot of a sub-group analysis of text message versus standard of care of studies with short follow-up period.

Discussion

Conclusion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Giuseppe Vittorio De Socio

Roles

Author response to Decision Letter 0

Decision Letter 1

Giuseppe Vittorio De Socio

Roles

Author response to Decision Letter 1

Decision Letter 2

Giuseppe Vittorio De Socio

Roles

Author response to Decision Letter 2

Decision Letter 3

Giuseppe Vittorio De Socio

Roles

Acceptance letter

Giuseppe Vittorio De Socio

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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