Patient and carer perceptions and experiences of technology-facilitated appointment reminders in healthcare: a scoping review

Anastasia Rousaki; Debra Jones; Dawn Dowding; Norina Gasteiger

doi:10.1093/jamia/ocag112

. 2026 Jun 24;33(10):2029–2039. doi: 10.1093/jamia/ocag112

Patient and carer perceptions and experiences of technology-facilitated appointment reminders in healthcare: a scoping review

Anastasia Rousaki ^1,^2,^✉, Debra Jones ³, Dawn Dowding ^4,⁵, Norina Gasteiger ^6,⁷

PMCID: PMC13630306 PMID: 42341159

Abstract

Background and aim

Missed healthcare appointments, or “Did Not Attends” (DNAs), pose challenges for healthcare systems. Technology-facilitated reminder systems, such as SMS and phone calls are often implemented to improve attendance. This scoping review aimed to map the evidence on patient and carer perspectives and experiences of technology-enabled appointment reminders in healthcare and, secondly, examine how equity-relevant characteristics were reported.

Methods

A scoping review which searched EMBASE, MEDLINE, PsycINFO, Web of Science, Scopus, and EBSCO from September to October 2025 for studies published between 2010 and 2025. Studies examining patient or informal/unpaid carer perceptions and experiences of technology-based reminder systems were included. Equity-relevant dimensions were examined using the PROGRESS-Plus framework. Data were extracted and summarised using a structured form; with findings synthesised thematically.

Results

A total of 45 studies were included. Most focused on patient perspectives, with comparatively fewer centered specifically on carers. The majority were cross-sectional surveys, with fewer longitudinal and theory-informed designs. SMS reminders were the most studied modality, followed by phone calls and app-based notifications. Patients and carers reported high satisfaction. Recurring barriers included digital exclusion, language challenges, confidentiality concerns, and socio-economic inequalities. Equity reporting across studies was inconsistent, with many studies describing sociodemographic characteristics without examining how they influenced engagement with reminder systems.

Conclusions

Technology-enabled appointment reminders are widely perceived as useful. Digital exclusion, privacy, language, and trust-related barriers limit engagement and access. Greater user involvement is needed to ensure reminder systems support, rather than reproduce, healthcare inequalities. Future research and implementation efforts should prioritise equity-informed design and evaluation.

Keywords: did not attend, appointment reminders, healthcare, perceptions, scoping review

1 Introduction

Unattended healthcare appointments without prior notice, commonly referred to as Did Not Attends (DNAs), are a challenge for healthcare systems and have attracted growing academic interest.¹ In the United Kingdom (UK), DNAs are estimated to cost the UK’s National Health Service (NHS) approximately £216 million annually, leading to under-used clinical time, greater administrative workload and longer waiting lists.² Clinically, they risk delaying diagnoses and treatments, exacerbating chronic conditions and increasing mortality among high-need populations.²

To prevent DNAs, healthcare systems worldwide have implemented reminder strategies, such as telephone calls and SMS notifications. These interventions are generally associated with improved attendance and reduced nonattendance rates.¹^,^3–7 However, nonattendance is also influenced by structural, social, psychological, and material barriers, including scheduling difficulties, work constraints, low health literacy, financial hardship, transport difficulties, chronic illness, disability, and safety concerns.⁸ Migrant patients may additionally face language barriers, and systemic constraints. Social stigma, chronic illness, physical disability, and transportation difficulties, particularly in rural areas, further influence attendance. For some patients, particularly children and socially vulnerable groups, attendance may also depend on informal carers to facilitate or accompany appointments.⁹ More broadly, patterns of appointment attendance are closely shaped by wider social and health inequalities.

Health inequities refer to avoidable, unfair differences in health outcomes.¹⁰ In the context of technology-facilitated reminder systems, such inequities may be reproduced if access to, and engagement with, digital communication is unevenly distributed across populations.¹¹

A growing body of research has shown that digital health systems can widen existing inequalities, with those excluded from technology-based interventions often being older and medically more complex.¹² Racial and ethnic disparities in the uptake and use of digital health tools have also been documented, including lower engagement among Black and Hispanic patients¹³ and persistent under-representation of minoritised groups even where invitation bias is reduced.¹⁴ More broadly, inequities may also be intertwined with digital infrastructures themselves, including through design and data quality limitations, as well as organizational constraints that shape whose needs are recognized and supported.¹⁵ Reliance on structured electronic health record fields can under-identify racial and ethnic minority patients, with those missing from structured documentation differing systematically in sociodemographic and clinical characteristics.¹⁶ Notably, rural public health leaders have reported limited data availability, data quality challenges, and lack of analytic capacity as barriers to addressing health disparities.¹⁷

Previous reviews have focused on the effectiveness of reminder strategies and comparisons of reminder formats;⁷^,^18–20 prioritizing quantitative findings over patient experiences. Few reviews consider structural or equality-related barriers such as digital exclusion or accessibility challenges experienced by marginalized populations.¹⁸^,¹⁹ Across the literature, patients generally report high satisfaction with reminders, particularly SMS and phone calls, and often prefer personalized or human-initiated communication due to greater trust, while engagement may also be shaped by social norms and financial incentives⁷^,²⁰ and emotional responses such as guilt or anxiety.²¹ Digital exclusion, including low digital literacy, shared device use, and privacy concerns, also shapes engagement with reminders.¹⁸^,²² However, these insights remain fragmented, and few reviews examine patient and carer perspectives on acceptability, satisfaction, barriers, or reminder preferences in depth.¹⁹^,^23–25 More recent research has examined predictive model-based interventions that use electronic health record data to identify patients at high risk of nonattendance and target reminders accordingly.²⁶ While promising, these approaches offer limited evidence on acceptability or the perspectives of patients and carers, particularly among those with health issues, socio-economic vulnerabilities, mental health conditions, and caring responsibilities. Despite extensive research on reducing nonattendance, important gaps remain in understanding how reminder systems are perceived and experienced, particularly in the context of structural barriers that shape engagement.

Recent methodological work examining qualitative systematic reviews has demonstrated that equity, diversity, and inclusion are frequently referenced but inconsistently applied across review stages.²⁷ This review therefore aimed primarily to map and synthesize evidence on patient and carer perspectives regarding technology-enabled appointment reminder systems, while secondarily examining how equity-relevant characteristics were reported and considered across this literature.

2 Methods

This scoping review followed the methodological framework proposed by Arksey and O’Malley²⁸ and refined by Levac et al.²⁹ Reporting adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline³⁰ (see completed reporting checklist in Supplementary file 1). The protocol was registered with the Open Science Framework (https://osf.io/nm7rj/overview) in July 2025.

Prior analyses of equity-focused evidence synthesis have highlighted that equity is frequently referenced but unclearly conceptualized in reviews of public health interventions.³¹ The review was conducted with attention to equity-relevant dimensions (eg, age, socioeconomic status, ethnicity, digital access), informed by equity-oriented reporting guidance.³² Although the PRISMA-E 2012 reporting guideline was developed specifically for systematic reviews, its principles were used to broadly inform the consideration of equity reporting throughout this scoping review.³²

2.1 Formulation of research question

The review aim and research question were informed by previous research, especially Aldadi et al.,⁸ who emphasized the complexity of barriers to healthcare access and the potential for targeted interventions to improve patient engagement.

2.2 Inclusion and exclusion criteria

In line with emerging guidance on implementing equity across qualitative evidence synthesis processes,²⁷ this review centered patient and carer perspectives on access, digital exclusion, and vulnerability as core analytic dimensions rather than post hoc considerations. Eligibility criteria were defined using the Population, Concept, Context (PCC) framework as recommended by the Joanna Briggs Institute³³ (see Table 1). Studies were eligible if they examined patient or informal carer experiences and perspectives on appointment reminder systems within healthcare settings and contexts. The concept of interest entailed all technology-based reminders, as well as reminder modalities that were used alongside technology-based modalities, such as postal reminders. The context included any healthcare setting without geographical restriction. Studies were included if they explored perceptions, experiences, acceptability, satisfaction, trust, or barriers and facilitators to engagement with reminder systems. Only empirical studies were eligible. It is important to note that equity was examined as a secondary analytic lens across included studies, rather than as a primary inclusion criterion.

Table 1.

Eligibility criteria based on population (P), concept (C), and context (C) framework.

Population	Patients of any age and informal carers [defined as individuals providing unpaid caregiving outside a professional context³⁴]. Studies focusing solely on healthcare providers or administrative staff were excluded.
Concept	Technology-enabled appointment reminders, including SMS messages, telephone calls, emails, app notifications, AI-enabled reminders, and other digital reminder systems; as well as reminders that accompanied them, for example, postal reminders. Studies explored perceptions, experiences, acceptability, satisfaction, barriers, or facilitators related to these systems.
Context	All healthcare settings (eg, primary care, secondary care, outpatient services, hospitals, and community-based care). No geographical restrictions were applied, but the studies must have been published in English between 2010 and 2025.
Types of Evidence	Primary empirical studies employing qualitative, quantitative, or mixed-methods designs. Reviews (eg, systematic and narrative reviews gray literature were excluded) although their reference lists were screened for relevant primary studies. Opinion pieces and commentaries were not included.

Open in a new tab

Abbreviations: SMS, short message service; AI, Artificial Intelligence.

We excluded studies focusing on provider or administrative perspectives, interventions unrelated to appointment reminders, or studies reporting only effectiveness outcomes without user perspectives. Non-primary research (reviews, protocols, conference abstracts) was excluded but used for contextual insights or study identification. Only English-language studies published between 2010 and 2025 were considered. Evidence predating 2010 was excluded due to the use of outdated technologies.

2.3 Search strategy

Between June and September 2025, six electronic databases were searched: EMBASE, MEDLINE, PsycINFO, Web of Science, Scopus, and EBSCO. Search strategies were tailored for each database and combined controlled vocabulary and free-text keywords related to four main conceptual clusters: (1) patient and carer perspectives (2) appointments and attendance (3) reminder and digital health technologies and (4) healthcare settings.

Boolean operators (AND/OR) were used to combine search terms within and across clusters. Example terms included “patient satisfaction” “carer experiences” “appointment” “no show” “reminder system” “mHealth” “digital health” “SMS” and “hospital.” The search strategy was informed by the PCC framework, refined through discussion among the researchers and finalized with input from a nursing librarian (see Supplementary File 1 for an example from one database).

Additional sources beyond database indexing were consulted. Citation tracking and backward/forward reference searching were conducted on all included studies and relevant reviews to identify further eligible records. Google Scholar was searched using simplified keyword combinations to capture literature not indexed in the main databases. All searches, including Google Scholar, were limited to English-language records and followed the same date restrictions. Reference lists of included studies and relevant literature were hand-searched to identify additional eligible records (ie, snowballing).

As equity-related terms are inconsistently indexed in health databases,¹⁰ we did not rely on explicit inequity search terms. Instead, this review aimed to tackle studies that addressed disparities in access, literacy, or vulnerability within broader reminder-system research. Disadvantage was not used as a study inclusion or exclusion criterion. The review did not restrict eligibility to specific socially or economically marginalized populations. Rather, disadvantage was considered during data extraction and interpretation through examination of reported sociodemographic characteristics and contextual factors relevant to health equity.

2.4 Screening

Study selection followed a two-stage screening process: (1) title and abstract review and (2) full-text review, applying the predefined inclusion and exclusion criteria. Search results were imported into Rayyan³⁵ for screening and de-duplication. After duplicates were removed, two reviewers independently screened all records at both stages, resolving discrepancies through discussion. Reasons for exclusion were documented. Inter-rater reliability was calculated at each stage using raw agreement rates (percentages), with ≥80% deemed acceptable.

2.5 Data extraction, charting and synthesis

Data were extracted using a structured Microsoft Excel form. Extracted data included study characteristics (author, year, country, setting, design), participant details (sample size, demographics, patient/carer status), and findings related to patient and carer perspectives such as satisfaction, acceptability, preferences, trust, privacy concerns, barriers and facilitators to engagement, and implementation challenges. Recent guidance emphasizes that equity must be a consideration across all stages of evidence synthesis.³⁶ As a result, population characteristics were mapped onto the PROGRESS-Plus framework,³⁷ including variables such as place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, digital literacy, and age. In line with equity-focused synthesis guidance,³² we aimed to examine contextual and experiential factors shaping engagement with reminder systems. We additionally documented whether studies addressed health equity considerations more broadly, including not only reporting of sociodemographic characteristics but also examination of differential experiences or outcomes across population subgroups. The extracted data were synthesized using a thematic approach, following suggested scoping review methodology.²⁸^,²⁹ While PROGRESS-Plus offered a framework for identifying broadly relevant axes of social stratification, we applied it as a flexible organizing lens. We recognize that some domains may not map neatly onto all international contexts, particularly settings where disadvantage may be structured differently or described through context-specific indicators.

3 Results

3.1 Search and screening summary

A total of 1604 records were identified through database searches. Following the removal of 523 duplicates, 1081 unique records were screened by title and abstract, of which 1015 were excluded. Sixty-six full-text articles were assessed for eligibility, and 34 were excluded for reasons including wrong outcome (ie, attendance/service outcomes only; no patient/carer perspectives) (n = 16), wrong intervention (n = 8), inaccessible full text (n = 2), retracted articles (n = 2), review papers (n = 5), and one protocol (n = 1); resulting in 32 studies included in the synthesis. An additional 74 records were identified through Google Scholar, of which one met the inclusion criteria. Finally, through snowballing of included papers and relevant reviews, 12 additional (eligible) studies were included. The agreement rates were 98.1% at the first stage and 93.55% at the second stage. A total of 45 studies were included in the review (see Figure 1 and Supplementary File 1 for all included studies).

For image description, please refer to the figure legend and surrounding text. — PRISMA flow diagram of study selection showing the identification, screening, eligibility and inclusion of studies.

3.2 Characteristics of studies

Among the 45 studies, 36 primarily examined patient perspectives, 8 focused primarily on carers (most commonly parents/caregivers), and one included both patients and carers. 26 were cross-sectional,²²^,^38–63 with six studies a hypothetical reminder system.²²^,⁴⁷^,⁵⁴^,⁵⁸^,⁶¹^,⁶⁴ Eight studies were randomized controlled trials (RCTs);⁴^,^65–71 five studies were quasi-experimental designs;³^,^72–75 four were cohort designs;¹^,⁶^,⁷⁶^,⁷⁷ two were pilot studies.⁵³^,⁷⁸ Seven were survey-only cross-sectional designs^44–47^,⁴⁹^,⁵⁴^,⁶⁴ and one study used a discrete choice experiment survey.²²

Six studies used theory to inform or develop the tools used to gather data on perceptions.⁶^,⁴⁶^,⁴⁹^,⁵⁹^,⁶¹^,⁶⁴ Of these, two studies used the ‘Technology Acceptance Model’⁶ and the ‘framework for examining patients attitudes regarding applications of AI in healthcare’.⁶¹ The remaining four used the ‘Patient Preference Theory’,⁴⁶ ‘Consumer Behavior and Expertise Theory’,⁴⁹ ‘Nielsen’s Heuristic Evaluation’ (usability inspection method),⁶⁴ and acceptability/perception healthcare quality elements chosen from the ‘Alberta Quality Matrix for Health’.⁵⁹ Four studies considered language and used health literacy tools^38–40 reading level tools¹ or translation³⁸^,⁴⁹ to improve reach and understanding. See Supplementary File 1 for a list of the included studies and further information.

Across the 45 included studies, sample sizes varied substantially with a total sample of approximately 22 040 individuals; with the youngest being infants (via carers) at 71.6 days⁶⁶ and the oldest being 80+ years old.⁴⁶^,⁴⁹ Participant samples in the majority of studies consisted of patients¹^,³^,⁴^,⁶^,²²^,⁴²^,^44–55^,⁵⁸^,^60–64^,^67–76^,⁷⁸ with eight using carers/parents as their main demographic.^38–40^,⁴³^,⁵⁹^,⁶⁵^,⁶⁶^,⁷⁷ One study engaged with both patients and carers.⁵⁶ Women represented the majority of participants in multiple studies.⁶⁶ Mixed-gender adult samples were more prevalent, and common in HIV and chronic illness settings.⁵¹^,⁷² Men made up the majority of participants in a number of HIV-focused studies⁴⁷ and a few veteran studies.⁶⁰ Only one study included transgender individuals.⁴⁷

The 45 studies spanned diverse geographical regions. Twenty-five studies were conducted in the USA.¹^,³^,⁶^,^38–40^,⁴²^,⁴⁶^,⁴⁷^,⁴⁹^,⁵³^,⁵⁴^,^58–60^,^62–64^,⁶⁷^,⁶⁹^,⁷⁰^,^73–78 One study was conducted in the UK.⁶¹ Four studies were located in Oceania (Australia or New Zealand),²²^,⁴³^,⁵⁰^,⁵² two were located in Switzerland,⁴^,⁶⁸ Cameroon⁵⁵^,⁵⁶ and in South Africa,⁴⁵^,⁵¹ and one each was conducted in Iran,⁵⁷ Saudi Arabia,⁷¹ Nigeria,⁴⁸ Zimbabwe,⁶⁵ Argentina,⁴⁴ Guatemala⁶⁶ and Taiwan.⁷²

Hospital and specialist outpatient clinics were the most common settings (n = 21), HIV specific clinics⁴⁵^,⁴⁷^,⁵¹^,⁵⁶ and internal medicine and multispecialty clinics.⁶^,⁵²^,⁵⁷^,⁶⁰^,⁷¹^,⁷⁶ Seven studies occurred in primary care clinics including primary medicine and HIV Clinics,⁴^,⁶⁸ academic multispecialty practices⁶⁷ and integrated health systems.⁷⁰ Five studies were situated in public or community health facilities.⁴⁴^,⁵⁵^,⁵⁸^,⁶⁶ Five studies were conducted in paediatric-specific settings.³⁸^,⁴⁰^,⁴³^,⁵⁹^,⁷⁷ Two studies focused on homeless-oriented clinics.⁵³^,⁵⁴ Two studies used online panels rather than clinical settings.²²^,⁴⁶

SMS reminders were the most common reminder modality, used in 37 studies.¹^,³^,⁴^,⁶^,²²^,^38–40^,^42–49^,^51–55^,⁵⁷^,⁵⁸^,⁶⁰^,^62–66^,⁶⁸^,^70–72^,⁷⁴^,⁷⁶^,⁷⁷ Seventeen studies used telephone calls,⁴^,²²^,^44–46^,⁴⁹^,⁵¹^,⁵²^,⁵⁶^,⁵⁷^,⁵⁹^,⁶⁰^,⁶⁷^,⁶⁸^,⁷⁰^,⁷²^,⁷⁵ four discussed app-based notifications⁵⁶^,⁵⁷^,⁶⁹^,⁷⁸ and two utilized patient portals.⁶⁰^,⁷³ One study employed an app-based notification system and voice message reminders,⁴⁸ one explored automated and AI-enabled reminders⁶¹ and another used automated phone call reminders.⁶⁷ Traditional postal reminders were examined in four studies and were looked at in addition to tech.²²^,⁴⁶^,⁵²^,⁶⁸^,⁷² Finally, along with other measures, one study examined social media and e-calendar reminders.⁴⁶

3.3. Characteristics of participants and equity reporting

Across the 45 included studies, reporting of equity-relevant characteristics was variable and often limited (see Supplementary File 2). Most studies primarily examined patient perspectives and only secondarily reported PROGRESS-Plus characteristics, if at all. Broadly, studies fell into three groups: those with minimal equity reporting, those reporting equity-relevant variables descriptively without examining their relationship to engagement or outcomes, and a smaller subset that analytically examined differences in access, preferences, or use across social groups.

Some studies reported PROGRESS-Plus characteristics, such as race/ethnicity, socioeconomic indicators, education, employment, or insurance status.³⁸^,⁴⁵^,⁵⁸^,^62–64 Others provided minimal demographic information.¹^,³^,⁴^,⁶^,⁴²^,⁵⁰^,^59–61^,⁶⁷^,⁷⁰^,⁷¹^,⁷³^,^75–77 Many studies demonstrated partial/moderate equity reporting, whereby variables were not analyzed in depth.²²^,³⁹^,⁴⁰^,⁴³^,⁴⁴^,⁴⁶^,⁴⁸^,⁴⁹^,⁵¹^,⁵²^,^54–57^,⁶⁴^,⁶⁶^,⁶⁸^,⁶⁹^,⁷²^,⁷⁴^,⁷⁸ Few studies analytically examined inequalities,⁶² or associations between reminder use and demographic factors (e.g, gender, age, education, and literacy).⁴⁵

Reporting of equity-related demographic variables was inconsistent and rarely analyzed in relation to intervention outcomes. Although several studies reported participants’ gender,⁸^,²⁷^,³⁹^,⁴⁰^,⁴⁴^,⁴⁵ most did not explore whether reminder effectiveness differed by gender. Transgender representation was minimal⁴⁷^,⁶⁴ only one study reported on religion.⁵

Reporting of race and ethnicity was highly variable. Several studies provided no information.¹^,^42–44^,⁵⁰^,⁵¹^,^55–57^,^65–68^,⁷¹^,⁷²^,⁷⁵^,⁷⁶ Some studies conducted in specific geographic or linguistic populations included predominantly Chinese-speaking participants⁷³ or immigrant populations in urban primary care settings⁴ while others focused on African American men recruited through community or church settings.⁶³ Where race and ethnicity was reported, studies either described diverse samples⁴⁰^,⁴⁷^,⁵⁴^,⁶²^,⁶⁴^,⁶⁹^,⁷⁰^,⁷⁴^,⁷⁷ or focused on specific groups, such as Latino populations in the United States,³⁸ Hispanic or Spanish-speaking parents³⁹ and Black African populations in South African HIV clinic settings.⁴⁵ In some cases, race or ethnicity was analyzed descriptively or in regression analyses⁶²^,⁷⁶ but typically treated as neutral demographic variables.

Socioeconomic indicators [ie, employment, education and socio-economic status (SES)] were also inconsistently reported. Many studies provided no information on occupation or employment status,¹^,³^,⁴^,⁶^,²²^,⁴²^,⁴³^,⁴⁷^,⁴⁹^,⁵⁰^,⁵³^,⁵⁴^,^58–61^,⁶⁴^,⁶⁷^,⁶⁸^,^71–75^,⁷⁷ education¹^,³^,⁴^,⁶^,⁴²^,⁴³^,⁴⁹^,⁵⁰^,⁵⁵^,⁶⁰^,⁶¹^,^70–73^,⁷⁵^,⁷⁶ or socioeconomic status.¹^,³^,⁴^,⁶^,⁴²^,⁵⁰^,^55–57^,⁶⁰^,⁶¹^,^66–68^,^71–73^,⁷⁵^,⁷⁶ Instead, these characteristics were often implied such as in studies involving pregnant women,⁴² adolescents³ and insurance and socioeconomic proxies.⁷⁰^,⁷⁸ Where reported, studies described diverse employment profiles ranging from full-time employment, part-time employment, unemployment, retirement, or student status.⁴⁶^,⁵¹^,⁵²^,⁶²^,⁶⁹ Other studies reported mixed educational profiles.⁴⁸^,⁵¹^,⁶⁶^,⁶⁹ Several studies reported proxy indicators of SES, including insurance type, employment status, or area-level deprivation.⁴³^,⁶²^,⁷⁰^,⁷⁷ In several cases, SES was indirectly suggested through contextual indicators as some studies referenced populations experiencing housing instability or marginalization without reporting detailed SES measures.⁵⁸^,⁵⁹

Digital literacy was rarely measured directly. Some studies required participants to own a mobile phone²⁸^,⁵⁵ and be able to use SMS.⁴¹^,⁷¹^,⁷⁸ In some high-income settings, digital access appeared widespread [eg, 98% cellular phone use in African American men⁶³] high smartphone and internet use in homeless veterans yet structural instability (such as frequent number changes, or running out of credit) made consistent digital engagement challenging.⁵³^,⁶⁴ In low-and middle-income contexts, literacy and functional SMS capacity were more explicitly problematized: with shared phone use, low IT literacy, usability barriers, and lack of internet or smartphones as key constraints,⁵⁵^,⁵⁷ while high functional literacy and regular SMS use co-existed with significant phone instability.⁵¹ Variation in texting frequency and familiarity with technology predicted responsiveness to reminders, suggesting that digital capability shapes intervention effectiveness.⁴⁹ Even where literacy was discussed⁵¹ it was seldom analyzed as an equity variable.

3.4 Participant perspectives

Overall, patients felt that the number of reminders was appropriate,¹ and timely,⁷⁰^,⁷² enabling them to adjust their schedules.⁷⁵ Tailored, time-specific instructions were facilitators of attendance⁷⁶ although across studies there was variation in views on timing,³¹^,⁶⁷ reminders delivered 24-48 hours before an appointment³^,⁴^,⁶⁸^,⁷³ and sent in the morning or flexibility in timing.⁴⁴^,⁵⁰^,⁵²^,⁵⁶^,⁵⁷^,⁶⁶^,⁶⁹ Two studies that used reminders for participants with ongoing care (antenatal, HIV-positive patients) reported a preference for weekly SMS contact.⁴⁴^,⁵¹

Thirty-eight studies explored preferences for modality, timing, and content. SMS reminders were most preferred,¹^,³^,⁴^,⁶^,²²^,³⁸^,³⁹^,^42–52^,^54–60^,⁶²^,⁶³^,⁶⁵^,⁶⁶^,⁶⁹^,⁷⁰^,⁷²^,⁷⁴^,⁷⁵^,⁷⁷ followed by phone calls.⁵⁵^,⁵⁸^,⁷¹^,⁷²^,⁷⁵ One study reported that participants favored SMS reminders over untimely phone calls or voicemails.⁴⁰ Another study reported half of participants preferred SMS reminders to paper-based reminders.⁷⁴ Some studies highlighted the importance of language accessibility and multilingual support.⁴⁸^,⁵² Reminders were more trusted when sent directly from a known healthcare provider or clinic.⁴⁵^,⁶⁴^,⁷⁷ One study reported that participants appreciated having two-way communication.⁵⁵ Impersonal or automated tones stemmed in negative sentiments.⁷⁰

Across studies, participants generally viewed reminders positively. Eighteen studies found reminders acceptable and appropriate¹^,^38–40^,⁴⁴^,⁴⁵^,⁴⁷^,⁵⁰^,⁵³^,⁵⁵^,⁵⁶^,⁶²^,⁶⁵^,⁶⁹^,⁷¹^,⁷²^,⁷⁷^,⁷⁸ and eight studies reported high satisfaction with reminders.¹^,³^,⁴⁸^,⁵³^,⁶¹^,⁷⁰^,⁷⁵^,⁷⁶

Twenty-four studies reported that participants found reminders useful and convenient.³^,⁴^,⁶^,³⁸^,⁴²^,⁴³^,^50–52^,⁵⁴^,⁵⁷^,⁵⁸^,⁶¹^,⁶²^,⁶⁴^,^66–69^,⁷¹^,⁷²^,⁷⁵^,⁷⁷^,⁷⁸ However, two studies highlighted that participants found reminders were useful only if messages were consistent and accurate⁴³ and timely and detailed.⁵²

3.5 Barriers, challenges and negative perceptions

While many studies reported positive outcomes and perceptions regarding digital reminder systems, several challenges were also identified. Five studies described technical issues such as lost devices, poor reception, message delays, or low recall rates.³^,⁴⁰^,⁶³ System failures reduced trust and satisfaction.⁵⁷ Participants who regularly changed phones sometimes failed to receive reminders.⁶

Seven studies tackled barriers regarding digital exclusion and access.³^,⁴⁴^,⁴⁵^,⁴⁷^,⁴⁹^,⁵¹^,⁶⁶ These included reminders not being received due to issues with the device (damaged, lost, lacking credit), sharing of phones or numbers changing.³^,⁴⁵^,⁴⁷^,⁶⁶ Other barriers included lack of access to devices, the internet or email.⁴⁴^,⁴⁹^,⁵¹ Language was also an issue in seven studies, with concerns over the ability of recipients to read and understand messages if they were non-native speakers.¹^,⁴^,³⁸^,⁴⁰^,⁷⁶ A study by Ezelote et al.⁴⁸ reported that voice-notes were used to make reminders more accessible to those with low literacy levels.

Socio-economic circumstances, particularly related to cost issues were shown to shape access to/perceptions of reminder systems in nine studies.²²^,³⁸^,³⁹^,⁴⁴^,⁴⁹^,⁵²^,⁵³^,⁵⁸^,⁶⁴ Variations also occurred across populations, with Black and Hispanic participants being more likely to find SMS reminders helpful compared to White participants in one study,⁵⁸ an over reliance on postal letters disproportionately affecting Māori (indigenous), Pasifika and low-income groups in New Zealand;⁵² and access issues in homeless veterans and rural communities.²²^,⁶⁴

Concerns regarding privacy and confidentiality were evident in 14 studies.³^,⁴²^,⁴⁵^,⁴⁷^,⁴⁸^,⁵⁰^,^54–56^,⁵⁸^,⁶¹^,⁶⁴^,⁶⁶^,⁶⁹ These included risks of confidentiality breaches related to lost or shared phones³^,⁴²^,⁴⁵^,⁴⁸^,⁵⁴^,⁶⁶ and perceived risks to privacy and data security concerns,⁵⁸^,⁶¹^,⁶⁹ particularly in relation to HIV disclosure.⁵⁵^,⁵⁶ However, other studies found privacy issues to be less prominent in certain contexts;⁴⁷^,⁶⁴ confidentiality breaches were rare, but presented ethical concerns.⁵⁰ Four studies tackled trust,⁵⁰^,⁵²^,⁵⁷^,⁶² with poorly coordinated or delayed reminders damaging patient trust;⁵² participants felt “told off” after missed appointments. Poor planning, technical failures, and limited usability reduced confidence in the reliability of reminder systems⁵⁷ with patients raising concerns about unwanted messages and lack of trust/clarity in the source they originated from.⁶² Moreover, adolescents in mental health care occasionally found text reminders annoying and intrusive.⁵⁰

The studies discussed the negative impact of poorly timed or overly frequent reminders⁶¹ including calls during work hours or early in the day being intrusive,⁶⁸ and excessive reminders leading to “spam fatigue”⁵⁸ and annoyance.⁶⁰ Message delays, inaccurate timing, and limited-character SMS contributed to confusion.⁴⁰^,⁵² Patients wanted the ability to cancel or reschedule via SMS.⁴³

4 Discussion

Consistent with critiques of qualitative evidence syntheses that insufficiently address power and marginalization²⁷ this review aimed to consider how reminder systems are perceived, but also how they may intersect with structural determinants of digital exclusion and healthcare access. The results indicate that digital reminders were viewed as helpful, acceptable, and satisfactory by patients, though their experiences were shaped by contextual and socio-economic circumstances. Technology-based reminders were generally considered acceptable and engaging, with multiple reminders perceived as more effective than single ones. This aligns with previous findings reporting high satisfaction with SMS and phone reminders, particularly when personalized or human-initiated.⁷^,²⁰ Participants valued simplicity and SMS was the preferred modality. Timing remained important, with preferences for reminders sent one to two days in advance, which is consistent with earlier evidence recommending two-days⁷⁹ or less than 3 days²² prior to an appointment. Prior reviews similarly emphasize how shared device use and privacy concerns influence engagement.¹⁸^,²²

Yet, consistent with equity-oriented synthesis approaches that emphasize context and implementation processes¹⁰ our findings demonstrate that reminder effectiveness is inseparable from infrastructural and digital access conditions. More specifically, digital exclusion and socio-economic inequalities emerged as an ongoing challenge. Across the included studies, access to reminders were an issue with phone ownership/frequent number changes, shared devices, lack of credit and damaged phones. Such issues with digital reminders risk reproducing and intensifying existing health inequalities, particularly where access to devices, emails, or internet connection is limited. These perceptions echo past literature, with evidence of an association between deprivation or minority ethnic status and health/mental health issues with nonattendance at appointments.⁸⁰^,⁸¹

Appointment reminders delivered via SMS or phone call differ from more intensive digital interventions in that they are brief, low-intensity, and integrated with administrative workflows, often positioned as neutral communication mechanisms. Yet, this apparent simplicity can obscure the infrastructural assumptions they carry; even brief reminders rely on stable access to a functioning device, uninterrupted connectivity, literacy, language concordance, privacy, and the ability to respond within institutionally-defined timeframes. As a result, their design, particularly with respect to timing, clarity, framing, and delivery mode plays a critical role in shaping accessibility. Treating reminders as universally accessible risks overlooking how they may reproduce exclusion, underscoring the need for more targeted research on inclusive design in these “light touch” interventions.

Language and literacy barriers identified how monolingual or text-heavy reminders were inaccessible to users with low literacy or for whom the message language differed from their own. Past reviews similarly reported that a lack of literacy¹⁸ and language barriers can affect reminder understanding.⁸⁰^,⁸¹ Finally, trust in reminder systems is context-dependent, with unclear messages or reminders with an unknown source/origin, poor coordination or a tone perceived as intrusive negatively affecting trust.⁸²^,⁸³

Greater user involvement in the design of reminder systems may help ensure that these interventions better reflect the communication practices, preferences, and constraints of those expected to engage with them. While many studies highlighted positive perceptions of digital reminders, the findings also demonstrated that engagement was shaped by users’ socio-economic and material contexts, including access to functioning devices, stable phone numbers, digital literacy, language, privacy, and trust. Reminder systems developed without sufficient attention to these contexts may risk reproducing preexisting structural inequalities. Previous research where user involvement has been incorporated into the development or redesign of reminder interventions demonstrates the potential value of aligning system design with users’ practices and preferences. For example, Bogale et al.,⁸⁴employed co-design with end users via in depth interviews with women and providers; drafting SMS texts and reminders through understandability testing. Similarly, Teo et al.⁶⁰ conducted a qualitative study to improve appointment reminders by using repeated waves of patient interviews to generate redesign recommendations, employing a user-centered redesign process.

As highlighted in equity-focused evidence synthesis, interventions may have different effects in populations who face structural challenges or risks.¹⁰ Appointment reminders may not function equally across patient groups. Those facing structural barriers to care may experience different benefits or harms, yet most studies were conducted in digitally connected populations and reported equity-relevant factors inconsistently. As a result, it remains unclear whether reminder systems reduce or reproduce existing inequalities in healthcare access.

5 Implications

While digital appointment reminders are often framed as low-cost, universally accessible interventions, their implementation risks reproducing existing health inequalities if socio-economic conditions, digital exclusion, trust, inclusion and privacy concerns are not addressed. Reliance on mobile phones, stable connectivity, and individual device ownership assumes access to various material and digital resources; essentially disadvantaging low-income populations and marginalized groups. As past research suggests, there is an association between deprivation and nonattendance.¹⁹ Therefore, future approaches to reminder systems must account for intersecting vulnerabilities that may further reproduce patterns of exclusion, with reminders sent directly from a known healthcare provider or clinic to be perceived as trustworthy.

There is a need to move from a one-size-fits-all, technologically deterministic approach toward reminders, structures and infrastructures that are co-designed with users and address structural barriers to healthcare access. It is essential to maintain offline and face-to-face options, as highlighted by previous research.⁸⁵ Future research should use qualitative and longitudinal designs, as cross-sectional surveys cannot capture how perceptions change over time. Existing evidence suggests that trust and acceptability are not static⁵⁸^,⁶⁰^,⁶¹^,⁷⁰ and may shift toward irritation or disengagement when reminders accumulate, are poorly timed, or undermine privacy.

The applicability of these findings to populations experiencing disadvantage is constrained by both the characteristics of included studies and the consistency of equity reporting. While several studies included older adults and, in some cases, racially or ethnically diverse samples, socioeconomic status, digital literacy, rurality, disability, and language access were not always reported. As a result, judgments regarding equity impact are based primarily on descriptive reporting of barriers and contextual factors. Studies reporting those factors highlight that findings potentially indicate mechanisms through which reminder systems may differentially affect disadvantaged populations. This is an area that warrants further consideration, both in research and when implementing digital reminders.

Finally, technological interventions alone cannot resolve the systemic issue of missed appointments. Meaningful improvement requires combining digital innovation with social and material support. Policy and funding initiatives should prioritize digital infrastructure alongside measures such as community outreach, material support and flexible communication strategies. Co-production with patients and carers during design and evaluation stages will ensure reminder systems reflect real communication practices and constraints.⁸⁶

5.1 Limitations of studies included in the review

The included studies mostly employed cross-sectional designs (n = 26) and relied primarily on surveys (n = 28), limiting depth of insight into user experiences. Six cross-sectional studies examined hypothetical reminder systems rather than lived engagement, which, while useful for identifying anticipated barriers and preferences, cannot capture naturally occurring practices or longer-term use. Use of theory was also limited, with only two studies drawing on technology-related frameworks, indicating a lack of conceptual grounding in the study of user perceptions. Greater engagement with technology acceptance and behavior-change theories, such as the Unified Theory of Acceptance and Use of Technology,⁸⁷ could strengthen future research by examining perceived usefulness, ease of use, trust, and behavioral intentions; however, more critical and socio-political lenses are also needed to situate reminder systems within contemporary, broader societal and structural contexts. Consistent with prior critiques of inequity reporting in evidence synthesis³² equity-related characteristics were inconsistently reported across included studies.

6 Review limitations

Only English-language publications were included, potentially excluding evidence from non-English-speaking contexts. The included studies varied widely in design, populations, and setting; thus limiting comparability. Although this review highlights both the usefulness of appointment reminders and existing barriers, most studies focused on evaluating current systems rather than exploring psychosocial or socio-economic factors.

7 Conclusion

Technology-facilitated appointment reminders are generally well accepted and perceived as effective for improving attendance and communication. However, benefits are unevenly distributed. Barriers related to digital access, literacy, privacy, and trust demonstrate the need for more inclusive and flexible implementation strategies. Future work should prioritize user involvement in the design and evaluation of reminder systems to ensure they support, rather than hinder, equal access.

Supplementary Material

ocag112_Supplementary_Data

ocag112_supplementary_data.zip^{(208KB, zip)}

Acknowledgments

We would like to thank Chunhu Shi and Sonya Rafiq for their assistance and comments on earlier versions of this research project, as well as Timothy Calvert for his help in developing the search strategy.

Contributor Information

Anastasia Rousaki, Division of Nursing, Midwifery and Social Work, School of Health Sciences, The University of Manchester, Manchester, United Kingdom; NIHR Applied Research Collaboration Greater Manchester (ARC-GM), School of Health Sciences, The University of Manchester, Manchester, United Kingdom.

Debra Jones, Division of Nursing, Midwifery and Social Work, School of Health Sciences, The University of Manchester, Manchester, United Kingdom.

Dawn Dowding, Division of Nursing, Midwifery and Social Work, School of Health Sciences, The University of Manchester, Manchester, United Kingdom; NIHR Applied Research Collaboration Greater Manchester (ARC-GM), School of Health Sciences, The University of Manchester, Manchester, United Kingdom.

Norina Gasteiger, Division of Nursing, Midwifery and Social Work, School of Health Sciences, The University of Manchester, Manchester, United Kingdom; NIHR Applied Research Collaboration Greater Manchester (ARC-GM), School of Health Sciences, The University of Manchester, Manchester, United Kingdom.

Author contributions

Funding acquisition: DD; Supervision: NG, DD; Conceptualization: AR, DD, NG; Methodology: AR, NG, DJ; Search, screening & analysis: AR, DJ; Drafting manuscript: AR, DJ; Review of final manuscript: All.

Supplementary material

Supplementary material is available at Journal of the American Medical Informatics Association online.

Funding

This research work was funded by the National Institute for Health and Care Research Applied Research Collaboration Greater Manchester (Grant award: NIHR200174). The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care.

Conflicts of interest

The authors have no conflicts of interest to declare.

Data availability

No new data was collected during this review.

References

1. Balakrishnan AS, Nguyen HG, Shinohara K, Au Yeung R, Carroll PR, Odisho AY. A mobile health intervention for prostate biopsy patients reduces appointment cancellations: cohort study. J Med Internet Res. 2019;21:e14094. [DOI] [PMC free article] [PubMed] [Google Scholar]
2. Wilson R, Winnard Y. Causes, impacts and possible mitigation of non-attendance of appointments within the National Health Service: a literature review. J Health Organ Manag. 2022; ahead-of-print. [DOI] [PubMed] [Google Scholar]
3. Branson CE, Clemmey P, Mukherjee P. Text message reminders to improve outpatient therapy attendance among adolescents: a pilot study. Psychol Serv. 2013;10:298-303. [DOI] [PubMed] [Google Scholar]
4. Junod Perron N, Dao MD, Righini NC, et al. Text-messaging versus telephone reminders to reduce missed appointments in an academic primary care clinic: a randomized controlled trial. BMC Health Serv Res. 2013;13:125. [DOI] [PMC free article] [PubMed] [Google Scholar]
5. Mahmud N, Doshi SD, Coniglio MS, et al. An automated text message navigation program improves the show rate for outpatient colonoscopy. Health Educ Behav. 2019;46:942-946. [DOI] [PMC free article] [PubMed] [Google Scholar]
6. Tofighi B, Grazioli F, Bereket S, Grossman E, Aphinyanaphongs Y, Lee JD. Text message reminders for improving patient appointment adherence in an office-based buprenorphine program: a feasibility study. Am J Addict. 2017;26:581-586. [DOI] [PubMed] [Google Scholar]
7. Hasvold PE, Wootton R. Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review. J Telemed Telecare. 2011;17:358-364. [DOI] [PMC free article] [PubMed] [Google Scholar]
8. Aldadi A, Robb KA, Williamson A. Factors influencing multiple non-utilised healthcare appointments from patients’ and healthcare providers’ perspectives: a qualitative systematic review of the global literature. BJGP Open. 2024;8 (4); 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
9. Powell C, Appleton JV. Children and young people’s missed health care appointments: reconceptualising ‘did not attend’ to ‘was not brought’ – a review of the evidence for practice. Journal of Research in Nursing. 2012;17:181-192. [Google Scholar]
10. Welch VA, Petticrew M, O’Neill J, et al. Health equity: evidence synthesis and knowledge translation methods. Syst Rev. 2013;2:43. [DOI] [PMC free article] [PubMed] [Google Scholar]
11. Veinot TC, Ancker JS, Bakken S. Health informatics and health equity: improving our reach and impact. J Am Med Inform Assoc. 2019;26:689-695. [DOI] [PMC free article] [PubMed] [Google Scholar]
12. Toscos T, Drouin M, Pater J, Flanagan M, Pfafman R, Mirro MJ. Selection biases in technology-based intervention research: patients’ technology use relates to both demographic and health-related inequities. J Am Med Inform Assoc. 2019;26:835-839. [DOI] [PMC free article] [PubMed] [Google Scholar]
13. Javier SJ, Troszak LK, Shimada SL, et al. Racial and ethnic disparities in use of a personal health record by veterans living with HIV. J Am Med Inform Assoc. 2019;26:696-702. [DOI] [PMC free article] [PubMed] [Google Scholar]
14. Kannan V, Wilkinson KE, Varghese M, et al. Count me in: using a patient portal to minimize implicit bias in clinical research recruitment. J Am Med Inform Assoc. 2019;26:703-713. [DOI] [PMC free article] [PubMed] [Google Scholar]
15. Dexheimer JW, Greiner MV, Beal SJ, Johnson D, Kachelmeyer A, Vaughn LM. Sharing personal health record data elements in protective custody: youth and stakeholder perspectives. J Am Med Inform Assoc. 2019;26:714-721. [DOI] [PMC free article] [PubMed] [Google Scholar]
16. Sholle ET, Pinheiro LC, Adekkanattu P, et al. Underserved populations with missing race ethnicity data differ significantly from those with structured race/ethnicity documentation. J Am Med Inform Assoc. 2019;26:722-729. [DOI] [PMC free article] [PubMed] [Google Scholar]
17. Bekemeier B, Park S, Backonja U, Ornelas I, Turner AM. Data, capacity-building, and training needs to address rural health inequities in the Northwest United States: a qualitative study. J Am Med Inform Assoc. 2019;26:825-834. [DOI] [PMC free article] [PubMed] [Google Scholar]
18. Demsash AW, Tegegne MD, Walle AD, Wubante SM. Understanding barriers of receiving short message service appointment reminders across African regions: a systematic review. BMJ Health Care Inform. 2022;29. [DOI] [PMC free article] [PubMed] [Google Scholar]
19. Alturbag M. Factors and reasons associated with appointment non-attendance in hospitals: a narrative review. Cureus. 2024;16:e58594; 1-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
20. Werner K, Alsuhaibani SA, Alsukait RF, et al. Behavioural economic interventions to reduce health care appointment non-attendance: a systematic review and meta-analysis. BMC Health Serv Res. 2023;23:1136. [DOI] [PMC free article] [PubMed] [Google Scholar]
21. Crable EL, Biancarelli DL, Aurora M, Drainoni ML, Walkey AJ. Interventions to increase appointment attendance in safety net health centers: a systematic review and meta-analysis. J Eval Clin Pract. 2021;27:965-975. [DOI] [PubMed] [Google Scholar]
22. Mohammed Selim S, Senanayake S, McPhail SM, Carter HE, Naicker S, Kularatna S. Consumer preferences for a healthcare appointment reminder in Australia: a discrete choice experiment. Patient. 2024;17:537-550. [DOI] [PMC free article] [PubMed] [Google Scholar]
23. Boksmati N, Butler-Henderson K, Anderson K, Sahama T. The effectiveness of SMS reminders on appointment attendance: a meta-analysis. J Med Syst. 2016;40:90. [DOI] [PubMed] [Google Scholar]
24. Lin H, Wu X. Intervention strategies for improving patient adherence to follow-up in the era of mobile information technology: a systematic review and meta-analysis. PLoS One. 2014;9:e104266. [DOI] [PMC free article] [PubMed] [Google Scholar]
25. Robotham D, Satkunanathan S, Reynolds J, Stahl D, Wykes T. Using digital notifications to improve attendance in clinic: systematic review and meta-analysis. BMJ Open. 2016;6:e012116. [DOI] [PMC free article] [PubMed] [Google Scholar]
26. Oikonomidi T, Norman G, McGarrigle L, Stokes J, van der Veer SN, Dowding D. Predictive model-based interventions to reduce outpatient no-shows: a rapid systematic review. J Am Med Inform Assoc. 2023;30:559-569. [DOI] [PMC free article] [PubMed] [Google Scholar]
27. Evans C, Hassanein ZM, Bains M, et al. Addressing equity, diversity, and inclusion in JBI qualitative systematic reviews: a methodological scoping review. JBI Evid Synth. 2025;23:454-479. [DOI] [PMC free article] [PubMed] [Google Scholar]
28. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8:19-32. [Google Scholar]
29. Levac D, Colquhoun H, O’brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. [DOI] [PMC free article] [PubMed] [Google Scholar]
30. Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467-473. [DOI] [PubMed] [Google Scholar]
31. Hollands GJ, South E, Shemilt I, Oliver S, Thomas J, Sowden AJ. Methods used to conceptualize dimensions of health equity impacts of public health interventions in systematic reviews. J Clin Epidemiol. 2024;169:111312. [DOI] [PubMed] [Google Scholar]
32. Welch V, Petticrew M, Petkovic J, PRISMA-Equity Bellagio group, et al. Extending the PRISMA statement to equity-focused systematic reviews (PRISMA-E 2012): explanation and elaboration. J Clin Epidemiol. 2016;70:68-89. [DOI] [PubMed] [Google Scholar]
33. Peters MD, Godfrey CM, McInerney P, Soares CB, Khalil H, Parker D. The Joanna Briggs Institute reviewers’ manual 2015: methodology for JBI scoping reviews. 2015.
34. Molyneaux V, Butchard S, Simpson J, Murray C. Reconsidering the term ‘carer’: a critique of the universal adoption of the term ‘carer’. Ageing Soc. 2011;31:422-437. [Google Scholar]
35. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5:210. [DOI] [PMC free article] [PubMed] [Google Scholar]
36. Ontario PH. Overview of equity-informed approaches to evidence synthesis. King’s Printer for Ontario. 2024.
37. O’Neill J, Tabish H, Welch V, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014;67:56-64. [DOI] [PubMed] [Google Scholar]
38. Ahlers-Schmidt CR, Ablah E, Rogers N, et al. Low-income urban Latino parents’ perceptions of immunization text reminders. Ethn Dis. 2014;24:229-235. [PubMed] [Google Scholar]
39. Ahlers-Schmidt CR, Chesser A, Brannon J, et al. “Necesita una vacuna”: what Spanish-speakers want in text-message immunization reminders. J Health Care Poor Underserved. 2013;24:1031-1041. [DOI] [PubMed] [Google Scholar]
40. Ahlers-Schmidt CR, Chesser AK, Paschal AM, et al. Parent opinions about use of text messaging for immunization reminders. J Med Internet Res. 2012;14:e83. [DOI] [PMC free article] [PubMed] [Google Scholar]
41.<1471-2296-11-79 (1).pdf>.
42. Bhat A, Mao J, Unutzer J, Reed S, Unger J. Text messaging to support a perinatal collaborative care model for depression: a multi-methods inquiry. Gen Hosp Psychiatry. 2018;52:14-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
43. Christie-Johnston CA, O’Loughlin R, Hiscock H. ‘Getting to clinic study’: a mixed methods study of families who fail to attend hospital outpatient clinics. J Paediatr Child Health. 2020;56:506-511. [DOI] [PubMed] [Google Scholar]
44. Cormick G, Kim NA, Rodgers A, et al. Interest of pregnant women in the use of SMS (short message service) text messages for the improvement of perinatal and postnatal care. Reprod Health. 2012;9:9. [DOI] [PMC free article] [PubMed] [Google Scholar]
45. Crankshaw T, Corless IB, Giddy J, Nicholas PK, Eichbaum Q, Butler LM. Exploring the patterns of use and the feasibility of using cellular phones for clinic appointment reminders and adherence messages in an antiretroviral treatment clinic, Durban, South Africa. AIDS Patient Care STDS. 2010;24:729-734. [DOI] [PubMed] [Google Scholar]
46. Crutchfield TM, Kistler CE. Getting patients in the door: medical appointment reminder preferences. Patient Prefer Adherence. 2017;11:141-150. [DOI] [PMC free article] [PubMed] [Google Scholar]
47. Czarny HN, Broaddus MR. Patient acceptability of receiving short message services from an HIV patient-centered medical home. AIDS Care. 2019;31:471-474. [DOI] [PubMed] [Google Scholar]
48. Ezelote CJ, Nwoke EA, Ibe SN, et al. Experiences of people living with HIV/AIDS in selected hospitals in Imo state, Nigeria, regarding the usability and satisfaction of reminders using M-health features: a qualitative study. Sci Rep. 2025;15:8987. [DOI] [PMC free article] [PubMed] [Google Scholar]
49. Finkelstein SR, Liu N, Jani B, Rosenthal D, Poghosyan L. Appointment reminder systems and patient preferences: patient technology usage and familiarity with other service providers as predictive variables. Health Inform J. 2013;19:79-90. [DOI] [PubMed] [Google Scholar]
50. Furber GV, Crago AE, Meehan K, et al. How adolescents use SMS (short message service) to micro-coordinate contact with youth mental health outreach services. J Adolesc Health. 2011;48:113-115. [DOI] [PubMed] [Google Scholar]
51. Georgette N, Siedner MJ, Zanoni B, et al. The acceptability and perceived usefulness of a weekly clinical SMS program to promote HIV antiretroviral medication adherence in KwaZulu-Natal, South Africa. AIDS Behav. 2016;20:2629-2638. [DOI] [PMC free article] [PubMed] [Google Scholar]
52. Hamilton K, Short S, Cudby K, et al. Role of communication in successful outpatient attendance in a New Zealand hospital: a qualitative study. Intern Med J. 2023;53:1648-1653. [DOI] [PubMed] [Google Scholar]
53. McInnes DK, Sawh L, Petrakis BA, et al. The potential for health-related uses of mobile phones and internet with homeless veterans: results from a multisite survey. Telemed J E Health. 2014;20:801-809. [DOI] [PubMed] [Google Scholar]
54. Moczygemba LR, Cox LS, Marks SA, Robinson MA, Goode JR, Jafari N. Homeless patients’ perceptions about using cell phones to manage medications and attend appointments. Int J Pharm Pract. 2017;25:220-230. [DOI] [PMC free article] [PubMed] [Google Scholar]
55. Nhavoto JA, Gronlund A, Klein GO. Mobile health treatment support intervention for HIV and tuberculosis in Mozambique: perspectives of patients and healthcare workers. PLoS One. 2017;12:e0176051. [DOI] [PMC free article] [PubMed] [Google Scholar]
56. Njumkeng C, Nicholas T, Mvilongo PTN, et al. Feasibility and acceptability of a mobile health application among adolescents and young adults living with HIV in Fako Division, South West, Cameroon: Guidance for development. 2024.
57. Ostadmohammadi F, Nabovati E, Jeddi FR, Arani LS. Stakeholders’ experiences, perceptions and satisfaction with an electronic appointment system: a qualitative content analysis. BMC Health Serv Res. 2025;25:220. [DOI] [PMC free article] [PubMed] [Google Scholar]
58. Person AK, Blain ML, Jiang H, Rasmussen PW, Stout JE. Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare. Telemed J E Health. 2011;17:189-195. [DOI] [PMC free article] [PubMed] [Google Scholar]
59. Quintanilha M, Tink L, Perez A, et al. Pediatric ambulatory appointment scheduling: a qualitative study of stakeholders’ perceptions and experiences. Int J Qual Health Care. 2020;32:643-648. [DOI] [PubMed] [Google Scholar]
60. Teo AR, Metcalf EE, Strange W, et al. Enhancing usability of appointment reminders: qualitative interviews of patients receiving care in the Veterans Health Administration. J Gen Intern Med. 2021;36:121-128. [DOI] [PMC free article] [PubMed] [Google Scholar]
61. Wood KV, Frings D, Flood C, Thomas N. Artificial intelligence machine learning-driven outpatient appointment management: a qualitative study on acceptability. Digit Health. 2025;11:20552076251321016. [DOI] [PMC free article] [PubMed] [Google Scholar]
62. Zallman L, Bearse A, West C, Bor D, McCormick D. Patient preferences and access to text messaging for health care reminders in a safety-net setting. Inform Health Soc Care. 2017;42:32-42. [DOI] [PubMed] [Google Scholar]
63. Le D, Holt CL, Saunders DR, et al. Feasibility and acceptability of SMS text messaging in a prostate cancer educational intervention for African American men. Health Inform J. 2016;22:932-947. [DOI] [PubMed] [Google Scholar]
64. McInnes DK, Petrakis BA, Gifford AL, et al. Retaining homeless veterans in outpatient care: a pilot study of mobile phone text message appointment reminders. Am J Public Health. 2014;104:S588-94. [DOI] [PMC free article] [PubMed] [Google Scholar]
65. Bangure D, Chirundu D, Gombe N, et al. Effectiveness of short message services reminder on childhood immunization programme in Kadoma, Zimbabwe - a randomized controlled trial, 2013. BMC Public Health. 2015;15:137. [DOI] [PMC free article] [PubMed] [Google Scholar]
66. Domek GJ, Contreras-Roldan IL, Bull S, et al. Text message reminders to improve infant immunization in Guatemala: a randomized clinical trial. Vaccine. 2019;37:6192-6200. [DOI] [PMC free article] [PubMed] [Google Scholar]
67. Parikh A, Gupta K, Wilson AC, Fields K, Cosgrove NM, Kostis JB. The effectiveness of outpatient appointment reminder systems in reducing no-show rates. Am J Med. 2010;123:542-548. [DOI] [PubMed] [Google Scholar]
68. Perron NJ, Dao MD, Kossovsky MP, et al. Reduction of missed appointments at an urban primary care clinic: a randomised controlled study. BMC Fam Pract. 2010;11:79. [DOI] [PMC free article] [PubMed] [Google Scholar]
69. Teeng LP, Guan NC, Kadir MS, Ling TS. Reminder through mobile messaging application improves outpatient attendance and medication adherence among patients with depression: an open-label randomised controlled trial. Med J Malaysia. 2021;76:617-623. [PubMed] [Google Scholar]
70. Steiner JF, Shainline MR, Dahlgren JZ, Kroll A, Xu S. Optimizing number and timing of appointment reminders: a randomized trial. Am J Manag Care. 2018;24:377-384. [PubMed] [Google Scholar]
71. Youssef A. Use of short message service reminders to improve attendance at an internal medicine outpatient clinic in Saudi Arabia: a randomized controlled trial. East Mediterr Health J. 2014;20:317-323. [PubMed] [Google Scholar]
72. Cheng CC, Li CY, Hu YJ, Shen HC, Huang SM. Effects of tooth scaling reminders for dental outpatients. J Telemed Telecare. 2013;19:184-189. [DOI] [PubMed] [Google Scholar]
73. Horvath M, Levy J, L’Engle P, Carlson B, Ahmad A, Ferranti J. Impact of health portal enrollment with email reminders on adherence to clinic appointments: a pilot study. J Med Internet Res. 2011;13:e41. [DOI] [PMC free article] [PubMed] [Google Scholar]
74. Richter JM, Ha JB, Marx M, Campbell EJ, Pandolfi MC. A digital preprocedure instruction program for outpatient colonoscopy. Telemed J E Health. 2020;26:468-476. [DOI] [PubMed] [Google Scholar]
75. Santiago VA, Warwick K, Ratnakumarasuriyar S, Oyewumi A, Robinson S, Sockalingam S. Evaluation of a patient-care planning intervention to improve appointment attendance by adults after bariatric surgery. Can J Diabetes. 2019;43:59-66. [DOI] [PubMed] [Google Scholar]
76. Nayor J, Feng A, Qazi T, Hurwitz S, Saltzman JR. Impact of automated time-released reminders on patient preparedness for colonoscopy. J Clin Gastroenterol. 2019;53:e456-e62. [DOI] [PubMed] [Google Scholar]
77. Roberts JR, Morella K, Dawley EH, et al. Direct-to-adolescent text messaging for vaccine reminders: what will parents permit? Vaccine. 2018;36:2788-2793. [DOI] [PMC free article] [PubMed] [Google Scholar]
78. Sankaranarayanan J, Sallach RE. Rural patients’ access to mobile phones and willingness to receive mobile phone-based pharmacy and other health technology services: a pilot study. Telemed J E Health. 2014;20:182-185. [DOI] [PubMed] [Google Scholar]
79. Wang D, Crilly J, Jaeger LA, Palmer G, editors. Assessing patient preferences for delivery of reminders on scheduled visits in a psychiatry ambulatory service. AMIA Annual Symposium Proceedings. 2007. [PMC free article] [PubMed]
80. McLean SM, Booth A, Gee M, et al. Appointment reminder systems are effective but not optimal: results of a systematic review and evidence synthesis employing realist principles. Patient Prefer Adherence. 2016;10:479-499. [DOI] [PMC free article] [PubMed] [Google Scholar]
81. Sung B, O’Driscoll F, Gregory A, et al. Identifying barriers to outpatient appointment attendance in patient groups at risk of inequity: a mixed methods study in a London NHS trust. BMC Health Serv Res. 2024;24:554. [DOI] [PMC free article] [PubMed] [Google Scholar]
82. Sherman E, Clauson KA, Elrod S, Eckardt P, Alkhateeb F, Jacobs R. Patient perceptions of text messaging to improve antiretroviral therapy adherence: a qualitative study of patients in a Ryan White Clinic. J Int Assoc Provid AIDS Care. 2018;17:2325958218759209. [DOI] [PMC free article] [PubMed] [Google Scholar]
83. Leon N, Surender R, Bobrow K, Muller J, Farmer A. Improving treatment adherence for blood pressure lowering via mobile phone SMS-messages in South Africa: a qualitative evaluation of the SMS-text Adherence SuppoRt (StAR) trial. BMC Fam Pract. 2015;16:80. [DOI] [PMC free article] [PubMed] [Google Scholar]
84. Bogale B, Mørkrid K, O’Donnell B, et al. Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study. BMC Med Inform Decis Mak. 2020;20:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
85. Kaihlanen A-M, Virtanen L, Buchert U, et al. Towards digital health equity-a qualitative study of the challenges experienced by vulnerable groups in using digital health services in the COVID-19 era. BMC Health Serv Res. 2022;22:188. [DOI] [PMC free article] [PubMed] [Google Scholar]
86. Rousaki A, Zamani ED, Sbaffi L, Hamblin K, Black R. The digitalization of social care in England and implications for older, unpaid carers: constructionist thematic analysis. J Med Internet Res. 2024; 26: e60056. [DOI] [PMC free article] [PubMed] [Google Scholar]
87. Yang M, Al Mamun A, Gao J, Rahman MK, Salameh AA, Alam SS. Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology. Sci Rep. 2024;14:339. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

ocag112_Supplementary_Data

ocag112_supplementary_data.zip^{(208KB, zip)}

Data Availability Statement

No new data was collected during this review.

[ocag112-B1] 1. Balakrishnan AS, Nguyen HG, Shinohara K, Au Yeung R, Carroll PR, Odisho AY. A mobile health intervention for prostate biopsy patients reduces appointment cancellations: cohort study. J Med Internet Res. 2019;21:e14094. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B2] 2. Wilson R, Winnard Y. Causes, impacts and possible mitigation of non-attendance of appointments within the National Health Service: a literature review. J Health Organ Manag. 2022; ahead-of-print. [DOI] [PubMed] [Google Scholar]

[ocag112-B3] 3. Branson CE, Clemmey P, Mukherjee P. Text message reminders to improve outpatient therapy attendance among adolescents: a pilot study. Psychol Serv. 2013;10:298-303. [DOI] [PubMed] [Google Scholar]

[ocag112-B4] 4. Junod Perron N, Dao MD, Righini NC, et al. Text-messaging versus telephone reminders to reduce missed appointments in an academic primary care clinic: a randomized controlled trial. BMC Health Serv Res. 2013;13:125. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B5] 5. Mahmud N, Doshi SD, Coniglio MS, et al. An automated text message navigation program improves the show rate for outpatient colonoscopy. Health Educ Behav. 2019;46:942-946. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B6] 6. Tofighi B, Grazioli F, Bereket S, Grossman E, Aphinyanaphongs Y, Lee JD. Text message reminders for improving patient appointment adherence in an office-based buprenorphine program: a feasibility study. Am J Addict. 2017;26:581-586. [DOI] [PubMed] [Google Scholar]

[ocag112-B7] 7. Hasvold PE, Wootton R. Use of telephone and SMS reminders to improve attendance at hospital appointments: a systematic review. J Telemed Telecare. 2011;17:358-364. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B8] 8. Aldadi A, Robb KA, Williamson A. Factors influencing multiple non-utilised healthcare appointments from patients’ and healthcare providers’ perspectives: a qualitative systematic review of the global literature. BJGP Open. 2024;8 (4); 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B9] 9. Powell C, Appleton JV. Children and young people’s missed health care appointments: reconceptualising ‘did not attend’ to ‘was not brought’ – a review of the evidence for practice. Journal of Research in Nursing. 2012;17:181-192. [Google Scholar]

[ocag112-B10] 10. Welch VA, Petticrew M, O’Neill J, et al. Health equity: evidence synthesis and knowledge translation methods. Syst Rev. 2013;2:43. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B11] 11. Veinot TC, Ancker JS, Bakken S. Health informatics and health equity: improving our reach and impact. J Am Med Inform Assoc. 2019;26:689-695. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B12] 12. Toscos T, Drouin M, Pater J, Flanagan M, Pfafman R, Mirro MJ. Selection biases in technology-based intervention research: patients’ technology use relates to both demographic and health-related inequities. J Am Med Inform Assoc. 2019;26:835-839. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B13] 13. Javier SJ, Troszak LK, Shimada SL, et al. Racial and ethnic disparities in use of a personal health record by veterans living with HIV. J Am Med Inform Assoc. 2019;26:696-702. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B14] 14. Kannan V, Wilkinson KE, Varghese M, et al. Count me in: using a patient portal to minimize implicit bias in clinical research recruitment. J Am Med Inform Assoc. 2019;26:703-713. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B15] 15. Dexheimer JW, Greiner MV, Beal SJ, Johnson D, Kachelmeyer A, Vaughn LM. Sharing personal health record data elements in protective custody: youth and stakeholder perspectives. J Am Med Inform Assoc. 2019;26:714-721. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B16] 16. Sholle ET, Pinheiro LC, Adekkanattu P, et al. Underserved populations with missing race ethnicity data differ significantly from those with structured race/ethnicity documentation. J Am Med Inform Assoc. 2019;26:722-729. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B17] 17. Bekemeier B, Park S, Backonja U, Ornelas I, Turner AM. Data, capacity-building, and training needs to address rural health inequities in the Northwest United States: a qualitative study. J Am Med Inform Assoc. 2019;26:825-834. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B18] 18. Demsash AW, Tegegne MD, Walle AD, Wubante SM. Understanding barriers of receiving short message service appointment reminders across African regions: a systematic review. BMJ Health Care Inform. 2022;29. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B19] 19. Alturbag M. Factors and reasons associated with appointment non-attendance in hospitals: a narrative review. Cureus. 2024;16:e58594; 1-16. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B20] 20. Werner K, Alsuhaibani SA, Alsukait RF, et al. Behavioural economic interventions to reduce health care appointment non-attendance: a systematic review and meta-analysis. BMC Health Serv Res. 2023;23:1136. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B21] 21. Crable EL, Biancarelli DL, Aurora M, Drainoni ML, Walkey AJ. Interventions to increase appointment attendance in safety net health centers: a systematic review and meta-analysis. J Eval Clin Pract. 2021;27:965-975. [DOI] [PubMed] [Google Scholar]

[ocag112-B22] 22. Mohammed Selim S, Senanayake S, McPhail SM, Carter HE, Naicker S, Kularatna S. Consumer preferences for a healthcare appointment reminder in Australia: a discrete choice experiment. Patient. 2024;17:537-550. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B23] 23. Boksmati N, Butler-Henderson K, Anderson K, Sahama T. The effectiveness of SMS reminders on appointment attendance: a meta-analysis. J Med Syst. 2016;40:90. [DOI] [PubMed] [Google Scholar]

[ocag112-B24] 24. Lin H, Wu X. Intervention strategies for improving patient adherence to follow-up in the era of mobile information technology: a systematic review and meta-analysis. PLoS One. 2014;9:e104266. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B25] 25. Robotham D, Satkunanathan S, Reynolds J, Stahl D, Wykes T. Using digital notifications to improve attendance in clinic: systematic review and meta-analysis. BMJ Open. 2016;6:e012116. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B26] 26. Oikonomidi T, Norman G, McGarrigle L, Stokes J, van der Veer SN, Dowding D. Predictive model-based interventions to reduce outpatient no-shows: a rapid systematic review. J Am Med Inform Assoc. 2023;30:559-569. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B27] 27. Evans C, Hassanein ZM, Bains M, et al. Addressing equity, diversity, and inclusion in JBI qualitative systematic reviews: a methodological scoping review. JBI Evid Synth. 2025;23:454-479. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B28] 28. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8:19-32. [Google Scholar]

[ocag112-B29] 29. Levac D, Colquhoun H, O’brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B30] 30. Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467-473. [DOI] [PubMed] [Google Scholar]

[ocag112-B31] 31. Hollands GJ, South E, Shemilt I, Oliver S, Thomas J, Sowden AJ. Methods used to conceptualize dimensions of health equity impacts of public health interventions in systematic reviews. J Clin Epidemiol. 2024;169:111312. [DOI] [PubMed] [Google Scholar]

[ocag112-B32] 32. Welch V, Petticrew M, Petkovic J, PRISMA-Equity Bellagio group, et al. Extending the PRISMA statement to equity-focused systematic reviews (PRISMA-E 2012): explanation and elaboration. J Clin Epidemiol. 2016;70:68-89. [DOI] [PubMed] [Google Scholar]

[ocag112-B33] 33. Peters MD, Godfrey CM, McInerney P, Soares CB, Khalil H, Parker D. The Joanna Briggs Institute reviewers’ manual 2015: methodology for JBI scoping reviews. 2015.

[ocag112-B34] 34. Molyneaux V, Butchard S, Simpson J, Murray C. Reconsidering the term ‘carer’: a critique of the universal adoption of the term ‘carer’. Ageing Soc. 2011;31:422-437. [Google Scholar]

[ocag112-B35] 35. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5:210. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B36] 36. Ontario PH. Overview of equity-informed approaches to evidence synthesis. King’s Printer for Ontario. 2024.

[ocag112-B37] 37. O’Neill J, Tabish H, Welch V, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014;67:56-64. [DOI] [PubMed] [Google Scholar]

[ocag112-B38] 38. Ahlers-Schmidt CR, Ablah E, Rogers N, et al. Low-income urban Latino parents’ perceptions of immunization text reminders. Ethn Dis. 2014;24:229-235. [PubMed] [Google Scholar]

[ocag112-B39] 39. Ahlers-Schmidt CR, Chesser A, Brannon J, et al. “Necesita una vacuna”: what Spanish-speakers want in text-message immunization reminders. J Health Care Poor Underserved. 2013;24:1031-1041. [DOI] [PubMed] [Google Scholar]

[ocag112-B40] 40. Ahlers-Schmidt CR, Chesser AK, Paschal AM, et al. Parent opinions about use of text messaging for immunization reminders. J Med Internet Res. 2012;14:e83. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B41] 41.<1471-2296-11-79 (1).pdf>.

[ocag112-B42] 42. Bhat A, Mao J, Unutzer J, Reed S, Unger J. Text messaging to support a perinatal collaborative care model for depression: a multi-methods inquiry. Gen Hosp Psychiatry. 2018;52:14-20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B43] 43. Christie-Johnston CA, O’Loughlin R, Hiscock H. ‘Getting to clinic study’: a mixed methods study of families who fail to attend hospital outpatient clinics. J Paediatr Child Health. 2020;56:506-511. [DOI] [PubMed] [Google Scholar]

[ocag112-B44] 44. Cormick G, Kim NA, Rodgers A, et al. Interest of pregnant women in the use of SMS (short message service) text messages for the improvement of perinatal and postnatal care. Reprod Health. 2012;9:9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B45] 45. Crankshaw T, Corless IB, Giddy J, Nicholas PK, Eichbaum Q, Butler LM. Exploring the patterns of use and the feasibility of using cellular phones for clinic appointment reminders and adherence messages in an antiretroviral treatment clinic, Durban, South Africa. AIDS Patient Care STDS. 2010;24:729-734. [DOI] [PubMed] [Google Scholar]

[ocag112-B46] 46. Crutchfield TM, Kistler CE. Getting patients in the door: medical appointment reminder preferences. Patient Prefer Adherence. 2017;11:141-150. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B47] 47. Czarny HN, Broaddus MR. Patient acceptability of receiving short message services from an HIV patient-centered medical home. AIDS Care. 2019;31:471-474. [DOI] [PubMed] [Google Scholar]

[ocag112-B48] 48. Ezelote CJ, Nwoke EA, Ibe SN, et al. Experiences of people living with HIV/AIDS in selected hospitals in Imo state, Nigeria, regarding the usability and satisfaction of reminders using M-health features: a qualitative study. Sci Rep. 2025;15:8987. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B49] 49. Finkelstein SR, Liu N, Jani B, Rosenthal D, Poghosyan L. Appointment reminder systems and patient preferences: patient technology usage and familiarity with other service providers as predictive variables. Health Inform J. 2013;19:79-90. [DOI] [PubMed] [Google Scholar]

[ocag112-B50] 50. Furber GV, Crago AE, Meehan K, et al. How adolescents use SMS (short message service) to micro-coordinate contact with youth mental health outreach services. J Adolesc Health. 2011;48:113-115. [DOI] [PubMed] [Google Scholar]

[ocag112-B51] 51. Georgette N, Siedner MJ, Zanoni B, et al. The acceptability and perceived usefulness of a weekly clinical SMS program to promote HIV antiretroviral medication adherence in KwaZulu-Natal, South Africa. AIDS Behav. 2016;20:2629-2638. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B52] 52. Hamilton K, Short S, Cudby K, et al. Role of communication in successful outpatient attendance in a New Zealand hospital: a qualitative study. Intern Med J. 2023;53:1648-1653. [DOI] [PubMed] [Google Scholar]

[ocag112-B53] 53. McInnes DK, Sawh L, Petrakis BA, et al. The potential for health-related uses of mobile phones and internet with homeless veterans: results from a multisite survey. Telemed J E Health. 2014;20:801-809. [DOI] [PubMed] [Google Scholar]

[ocag112-B54] 54. Moczygemba LR, Cox LS, Marks SA, Robinson MA, Goode JR, Jafari N. Homeless patients’ perceptions about using cell phones to manage medications and attend appointments. Int J Pharm Pract. 2017;25:220-230. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B55] 55. Nhavoto JA, Gronlund A, Klein GO. Mobile health treatment support intervention for HIV and tuberculosis in Mozambique: perspectives of patients and healthcare workers. PLoS One. 2017;12:e0176051. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B56] 56. Njumkeng C, Nicholas T, Mvilongo PTN, et al. Feasibility and acceptability of a mobile health application among adolescents and young adults living with HIV in Fako Division, South West, Cameroon: Guidance for development. 2024.

[ocag112-B57] 57. Ostadmohammadi F, Nabovati E, Jeddi FR, Arani LS. Stakeholders’ experiences, perceptions and satisfaction with an electronic appointment system: a qualitative content analysis. BMC Health Serv Res. 2025;25:220. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B58] 58. Person AK, Blain ML, Jiang H, Rasmussen PW, Stout JE. Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare. Telemed J E Health. 2011;17:189-195. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B59] 59. Quintanilha M, Tink L, Perez A, et al. Pediatric ambulatory appointment scheduling: a qualitative study of stakeholders’ perceptions and experiences. Int J Qual Health Care. 2020;32:643-648. [DOI] [PubMed] [Google Scholar]

[ocag112-B60] 60. Teo AR, Metcalf EE, Strange W, et al. Enhancing usability of appointment reminders: qualitative interviews of patients receiving care in the Veterans Health Administration. J Gen Intern Med. 2021;36:121-128. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B61] 61. Wood KV, Frings D, Flood C, Thomas N. Artificial intelligence machine learning-driven outpatient appointment management: a qualitative study on acceptability. Digit Health. 2025;11:20552076251321016. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B62] 62. Zallman L, Bearse A, West C, Bor D, McCormick D. Patient preferences and access to text messaging for health care reminders in a safety-net setting. Inform Health Soc Care. 2017;42:32-42. [DOI] [PubMed] [Google Scholar]

[ocag112-B63] 63. Le D, Holt CL, Saunders DR, et al. Feasibility and acceptability of SMS text messaging in a prostate cancer educational intervention for African American men. Health Inform J. 2016;22:932-947. [DOI] [PubMed] [Google Scholar]

[ocag112-B64] 64. McInnes DK, Petrakis BA, Gifford AL, et al. Retaining homeless veterans in outpatient care: a pilot study of mobile phone text message appointment reminders. Am J Public Health. 2014;104:S588-94. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B65] 65. Bangure D, Chirundu D, Gombe N, et al. Effectiveness of short message services reminder on childhood immunization programme in Kadoma, Zimbabwe - a randomized controlled trial, 2013. BMC Public Health. 2015;15:137. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B66] 66. Domek GJ, Contreras-Roldan IL, Bull S, et al. Text message reminders to improve infant immunization in Guatemala: a randomized clinical trial. Vaccine. 2019;37:6192-6200. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B67] 67. Parikh A, Gupta K, Wilson AC, Fields K, Cosgrove NM, Kostis JB. The effectiveness of outpatient appointment reminder systems in reducing no-show rates. Am J Med. 2010;123:542-548. [DOI] [PubMed] [Google Scholar]

[ocag112-B68] 68. Perron NJ, Dao MD, Kossovsky MP, et al. Reduction of missed appointments at an urban primary care clinic: a randomised controlled study. BMC Fam Pract. 2010;11:79. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B69] 69. Teeng LP, Guan NC, Kadir MS, Ling TS. Reminder through mobile messaging application improves outpatient attendance and medication adherence among patients with depression: an open-label randomised controlled trial. Med J Malaysia. 2021;76:617-623. [PubMed] [Google Scholar]

[ocag112-B70] 70. Steiner JF, Shainline MR, Dahlgren JZ, Kroll A, Xu S. Optimizing number and timing of appointment reminders: a randomized trial. Am J Manag Care. 2018;24:377-384. [PubMed] [Google Scholar]

[ocag112-B71] 71. Youssef A. Use of short message service reminders to improve attendance at an internal medicine outpatient clinic in Saudi Arabia: a randomized controlled trial. East Mediterr Health J. 2014;20:317-323. [PubMed] [Google Scholar]

[ocag112-B72] 72. Cheng CC, Li CY, Hu YJ, Shen HC, Huang SM. Effects of tooth scaling reminders for dental outpatients. J Telemed Telecare. 2013;19:184-189. [DOI] [PubMed] [Google Scholar]

[ocag112-B73] 73. Horvath M, Levy J, L’Engle P, Carlson B, Ahmad A, Ferranti J. Impact of health portal enrollment with email reminders on adherence to clinic appointments: a pilot study. J Med Internet Res. 2011;13:e41. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B74] 74. Richter JM, Ha JB, Marx M, Campbell EJ, Pandolfi MC. A digital preprocedure instruction program for outpatient colonoscopy. Telemed J E Health. 2020;26:468-476. [DOI] [PubMed] [Google Scholar]

[ocag112-B75] 75. Santiago VA, Warwick K, Ratnakumarasuriyar S, Oyewumi A, Robinson S, Sockalingam S. Evaluation of a patient-care planning intervention to improve appointment attendance by adults after bariatric surgery. Can J Diabetes. 2019;43:59-66. [DOI] [PubMed] [Google Scholar]

[ocag112-B76] 76. Nayor J, Feng A, Qazi T, Hurwitz S, Saltzman JR. Impact of automated time-released reminders on patient preparedness for colonoscopy. J Clin Gastroenterol. 2019;53:e456-e62. [DOI] [PubMed] [Google Scholar]

[ocag112-B77] 77. Roberts JR, Morella K, Dawley EH, et al. Direct-to-adolescent text messaging for vaccine reminders: what will parents permit? Vaccine. 2018;36:2788-2793. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B78] 78. Sankaranarayanan J, Sallach RE. Rural patients’ access to mobile phones and willingness to receive mobile phone-based pharmacy and other health technology services: a pilot study. Telemed J E Health. 2014;20:182-185. [DOI] [PubMed] [Google Scholar]

[ocag112-B79] 79. Wang D, Crilly J, Jaeger LA, Palmer G, editors. Assessing patient preferences for delivery of reminders on scheduled visits in a psychiatry ambulatory service. AMIA Annual Symposium Proceedings. 2007. [PMC free article] [PubMed]

[ocag112-B80] 80. McLean SM, Booth A, Gee M, et al. Appointment reminder systems are effective but not optimal: results of a systematic review and evidence synthesis employing realist principles. Patient Prefer Adherence. 2016;10:479-499. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B81] 81. Sung B, O’Driscoll F, Gregory A, et al. Identifying barriers to outpatient appointment attendance in patient groups at risk of inequity: a mixed methods study in a London NHS trust. BMC Health Serv Res. 2024;24:554. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B82] 82. Sherman E, Clauson KA, Elrod S, Eckardt P, Alkhateeb F, Jacobs R. Patient perceptions of text messaging to improve antiretroviral therapy adherence: a qualitative study of patients in a Ryan White Clinic. J Int Assoc Provid AIDS Care. 2018;17:2325958218759209. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B83] 83. Leon N, Surender R, Bobrow K, Muller J, Farmer A. Improving treatment adherence for blood pressure lowering via mobile phone SMS-messages in South Africa: a qualitative evaluation of the SMS-text Adherence SuppoRt (StAR) trial. BMC Fam Pract. 2015;16:80. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B84] 84. Bogale B, Mørkrid K, O’Donnell B, et al. Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study. BMC Med Inform Decis Mak. 2020;20:1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B85] 85. Kaihlanen A-M, Virtanen L, Buchert U, et al. Towards digital health equity-a qualitative study of the challenges experienced by vulnerable groups in using digital health services in the COVID-19 era. BMC Health Serv Res. 2022;22:188. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B86] 86. Rousaki A, Zamani ED, Sbaffi L, Hamblin K, Black R. The digitalization of social care in England and implications for older, unpaid carers: constructionist thematic analysis. J Med Internet Res. 2024; 26: e60056. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocag112-B87] 87. Yang M, Al Mamun A, Gao J, Rahman MK, Salameh AA, Alam SS. Predicting m-health acceptance from the perspective of unified theory of acceptance and use of technology. Sci Rep. 2024;14:339. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Patient and carer perceptions and experiences of technology-facilitated appointment reminders in healthcare: a scoping review

Anastasia Rousaki, PhD

Debra Jones, PhD

Dawn Dowding, PhD

Norina Gasteiger, PhD

Abstract

Background and aim

Methods

Results

Conclusions

1 Introduction

2 Methods

2.1 Formulation of research question

2.2 Inclusion and exclusion criteria

Table 1.

2.3 Search strategy

2.4 Screening

2.5 Data extraction, charting and synthesis

3 Results

3.1 Search and screening summary

Figure 1.

3.2 Characteristics of studies

3.3. Characteristics of participants and equity reporting

3.4 Participant perspectives

3.5 Barriers, challenges and negative perceptions

4 Discussion

5 Implications

5.1 Limitations of studies included in the review

6 Review limitations

7 Conclusion

Supplementary Material

Acknowledgments

Contributor Information

Author contributions

Supplementary material

Funding

Conflicts of interest

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases