Advances in digital technology in recent decades have created new opportunities for the mental health sector with applications in diagnostics, prevention, and treatment of people with mental illness [1-3]. However, older people with mental illness face a unique set of challenges that may impact the effectiveness of digital interventions. Therefore, this scoping review aimed to investigate (1) which digitalized treatments are available for older adults with mental illness and (2) how effective they are in treating mental illness in this age group.

Digital mental health interventions involve a broad range of technologies, from specifically designed digital interventions such as internet-delivered cognitive behavioral therapy (iCBT) to the use of already available functions such as music apps or SMS text messaging within treatments [4,5]. Previous findings regarding the effectiveness of digital interventions such as smartphone apps, SMS text messaging interventions, and virtual reality (VR) to improve mental health among adults have been encouraging [3,6]. There is ample evidence that iCBT is effective in treating depression and anxiety disorders in the general population [7,8] and it rivals face-to-face therapy in terms of effect sizes [9]. Recent studies seem to indicate a good usability, feasibility, and acceptance of technologies even for patients with serious mental illness [1,10]. For instance, a systematic review on digital technologies in the treatment of psychosis found that most participants used online interventions efficiently and perceived them to be useful [11].

However, technology use is highly correlated with age, a phenomenon that has been described as the “digital gray divide” [12] and that also applies to mental health—older adults with mental illness are less likely to use or even have access to the internet or own a computer or mobile phone [10,13-16]. This inequity in the digital realm likely mirrors inequities in the real world [17-19], with older adults with mental illness facing a specific set of challenges. Barriers to technology use appear to be cognitive deficits and, more specifically, reduced self-efficacy and heightened anxiety with regard to digital technology in older adults [13]. It should be noted that, despite these obstacles, older adults are not necessarily less interested than younger patients in using technology in their treatment and recovery [10,20]. A more general challenge with detrimental effects for the mental health of older adults concerns loneliness—older adults are more likely to live alone, have experienced the loss of loved ones, and have limited mobility and, thus, tend to report higher levels of social isolation and loneliness [21,22]. Both isolation and loneliness can exacerbate existing or contribute to the development of new mental and physical health problems [23-27]. Moreover, lack of social resources may further limit access to mental health services, preventing older adults from receiving timely and appropriate care [28]. However, technology could provide means to overcome some of these social problems and reduce the risk of loneliness (eg, by expanding social networks to the digital world [23,29]). Finally, older adults with mental illness are less likely to seek professional help and are underrepresented in referrals and treatment [30,31]. Commonly identified factors that influence the uptake of psychological treatment among older adults include worries about cost and being prescribed medication, transportation difficulties, and beliefs that illnesses such as anxiety and depression are a normal part of aging [30].

We believe that digital technologies may provide feasible solutions to overcome the identified set of unique challenges of older adults with mental illness. Furthermore, we also need to understand how digital interventions should be designed or adapted to be effective in this age group. Concerning the potential usefulness of digital interventions for older adults, there has been some evidence of technology’s potential to reduce social isolation in the general population, which may, however, vary according to the type of technology and level of use [32]. Moreover, among older adults, use of digital technology appears to be positively associated with health behavior and outcomes [33], potentially including better cognitive functioning [34-38]. In addition, promising results of digital interventions have been found for older adults without mental illness, such as cognitive training using VR, video games, and other software [34,35]. Thus, digital technology presents an exciting opportunity for the treatment of older people with mental illness with their unique challenges, as well as being easily scalable, with the potential for a lower cost per head and reduced burden on in-person mental health services. Concerning older adults’ specific needs when designing digital interventions for this population group, it should be considered that they have a higher rate of multimorbidity and may benefit from a different design and functionality from those for younger users [39]. Significantly, the ability of older adults to manage technology is not dependent just on their own skills but also on factors such as design and clinical diagnosis [40].

Despite the identified need and potential benefit of digital interventions for older people with mental illness, they have previously been underrepresented in research in this field, for example, with only 3% of participants in iCBT studies for depression being aged >65 years [41]. Given the challenges facing older people and their underrepresentation in research on digital technology, this scoping review aimed to provide a comprehensive overview of digital interventions for the treatment of older people with mental illness. This scoping review was guided by the following research questions:

The ultimate goal of this scoping review was to chart the state of the art of digitalized treatment options for older people with mental illness, providing an overview of the existing technologies and summarizing findings on their feasibility and effectiveness for various mental illnesses. This review shall inform clinicians, researchers, and patients alike, enabling decision-making processes for personalized treatments as well as guiding future research in the field.

This scoping review was conducted in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for conducting systematic scoping reviews [42]. A preregistration for this review was created in the Open Science Framework [43] before the final screening of studies and data analysis. An overview of the development of the scoping review is detailed in Multimedia Appendix 1.

To be included, studies needed to examine (1) the application of digital technology to treat (2) a population aged ≥65 years (3) with a psychiatric diagnosis according to established diagnostic criteria (eg, the International Classification of Diseases, Tenth Revision, or the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition) and (4) be available in English or German. Importantly, studies were eligible as long as they included participants aged ≥65 years even if the overall sample also comprised younger individuals, meaning that the age range of the participants across the included studies may extend to participants aged <65 years. Qualitative studies, case studies, study protocols, conference proceedings, and studies including no specific information on the sample were excluded from the results. No restrictions were made to publication date.

A search of the PubMed database was first conducted on April 30, 2024, and updated on April 28, 2025, by JAS for studies investigating the application of digital technology in the treatment of older adults with mental illness. Only PubMed was chosen due to its comprehensive coverage of health-related literature, for which it is the most widely used and accessible source, and the option to use Medical Subject Heading (MeSH) terms, as well as to limit the scope and ensure the feasibility of this scoping review. The search strategy was built to represent this review’s inclusion criteria in a combination of keywords and MeSH terms:

Using MeSH terms enhances the sensitivity of literature searches by automatically including related concepts and synonyms indexed under the same term. For instance, the MeSH term “psychotherapy” covers a wide array of nonpharmacological interventions ranging from cognitive behavioral therapy (CBT) and psychoanalysis to dance and art therapy.

Moreover, JAS manually examined the bibliographies of the included studies for additional relevant research.

The results of the search query were uploaded to EndNote (version 20; Clarivate Analytics). JAS and SAJ independently screened the results. In case of disagreement, JAS and SAJ conferred to reach a consensus about study selection.

Before conducting the search, outcome variables were defined based on the research questions. In addition to general information on the studies (eg, authors, title, year, and country) and sample characteristics, the type of technology used and measure of effectiveness of technology-based interventions were selected for later data extraction. SAJ conducted the process of data extraction for all tables, whereas JAS extracted the study data for the text of the manuscript. Relevant data from the included studies on study characteristics, type of technology, and effectiveness of the technologies in the treatment of older adults with mental illness were summarized using descriptive statistics and descriptive narration.

After extraction, both authors independently examined the data to identify patterns and recurring use of certain types of technologies. Through an iterative process of discussion, these patterns were developed into preliminary categories, which were then refined into the final set presented in Table 1. The categories were derived inductively from the data, allowing the synthesis to reflect the diversity of the interventions and approaches identified in the literature. Discrepancies in categorization were resolved through consensus, and where needed, an external expert in the field was consulted to ensure the appropriateness and clarity of the final categorization.

The search yielded 207 results (n=165, 79.7% in the initial search and n=42, 20.3% in the updated search). After screening titles and abstracts, the full texts of 63 studies were retrieved for detailed review. Following application of the inclusion and exclusion criteria, of the 63 retrieved studies, 35 (56%) titles remained. The references of the included studies were screened based on the inclusion criteria, leading to the addition of 29 original studies. This brought the total number of studies included in the scoping review to 64. The process of study selection is detailed in a PRISMA flowchart (Figure 1 [64]). An overview of the characteristics of the included studies is provided in Multimedia Appendix 2 [44-53,55-62,65-103] Multimedia Appendix 3 [63,104-109]. Of the 64 studies, more than two-thirds had been published in the last 10 years (n=43, 67% since 2015), with 24 (38%) studies [53,63,65-69,92-107,109] published since 2020. Only 3% (2/64) of the studies had been published before 2000 [70,71] (Figure 2).

Original studies were conducted predominantly in the United States (18/57, 32%), followed by Italy (9/57, 16%) and Australia (8/57, 14%). The total number of participants across all the included original studies was 15,644, with sample sizes ranging between 2 and 12,576. Participants were aged 40 to 97 years, indicating that a lot of studies examining people aged ≥65 years also examined younger populations. Most original studies had small sample sizes, with 89% (51/57) of the studies not exceeding 80 participants. Although randomized controlled trials (RCTs) were common (18/57, 32%), most original studies (31/57, 54%) were conducted without a control condition. We identified nine categories of digitalized treatments in the search results (Table 1): (1) iCBT, (2) digital prompts for desired behaviors in patients, (3) digital music-based interventions, (4) digital media in reminiscence therapy, (5) digitally simulated family presence, (6) digital mental health skill training, (7) digital cognitive training, (8) social interaction and activation using robotics, and (9) miscellaneous technology. The most commonly researched diagnosis in the selected studies was dementia (37/64, 58%), which significantly outweighed the frequency of other investigated diagnoses. These included mild cognitive impairment (MCI; 5/64, 8%), anxiety (11/64, 17%), depression (10/64, 16%), and sleep disorders (4/64, 6%). This notable imbalance in the distribution of diagnoses highlights a clear focus on cognitive disorders, particularly dementia, within the literature. In the following section, the digital technologies available to treat mental illness among older adults are described in detail (first research question). In the subsequent section, the findings concerning the effectiveness of digital interventions are presented (second research question). Table 2 presents the summative results of the included studies by diagnosis.

The aims of this scoping review were to (1) identify which digitalized treatment options are available for older adults with mental illness, (2) chart the state of research on the feasibility and effectiveness of these treatments, and (3) derive potential directions for future research on the topic. On the basis of our search strategy and inclusion criteria, we found a total of 57 original studies and 7 reviews.

Regarding aim 1, we grouped the identified digitalized treatment options for older adults with mental illness into 9 different categories (Table 1). Web-based iCBT programs were the most common and designed to treat depression, anxiety, and sleep disorders in older adults. iCBT is attractive for the treatment of older adults as it can be conducted remotely, in their own homes, and at their pace. Moreover, online interventions can be adapted to the lived realities of older adults (eg, by integrating examples from their everyday life into the texts and assignments), making them more relatable. It should be noted that some older adults with mental illness may benefit more from in-person CBT sessions considering that loneliness and social isolation are a major burden in this age group [23,121]. One study found that, despite years of tailoring a digital intervention for older veterans, its effectiveness was limited by low motivation to engage in self-directed home practice, indicating that increased accessibility through technology did not necessarily address the underlying barriers to engagement [95]. Nevertheless, for individuals with limited mobility or no access to a human therapist, iCBT remains an appealing alternative. Acknowledging these differing needs, one study suggested that triaging could help identify those most likely to benefit from iCBT while directing others to offline interventions better suited to their circumstances [97].

Most of the other identified interventions for older adults with mental illness relied on basic technology such as audio, video, or digital photos to address the specific needs of people living with dementia, namely, inactivity, disorientation, emotional distress, and loneliness. Audio recordings were used to help patients successfully conduct domestic work in the home but also to simulate the calming presence of a family member in stressful situations. Existing treatment programs such as reminiscence therapy or other behavioral activation interventions for people with dementia were complemented with digital media, allowing for more engaging, personalized materials such as photos, videos, and music. An important finding of this review is that very few studies (7/64, 11%) dealt with more advanced technology such as AI, VR, or robotics. This is surprising as VR applications are increasingly being investigated in mental health [6] and appear to be feasible in the treatment of older adults with mental illness [122]. VR interventions are effective in treating posttraumatic stress disorder, anxiety disorders, and substance use disorders—all of which are prevalent in older adults [123]. However, all VR studies in our review (4/64, 6%) focused on dementia. In addition, despite the potential of AI technology in mental health, especially for serious mental illness [124,125], only 2% (1/64) of the included studies applied AI technology [79]. AI can be used for multiple aims in mental health, such as early detection and symptom monitoring, development of personalized treatment plans, analysis of medical health records, or social companionship. It should be leveraged to improve or create new treatment ideas tailored to the needs of older adults. Future studies exploring the usability of AI for older adults with mental illness could develop solutions for unsolved problems such as polypharmacy, loneliness, or loss of autonomy in this age group.

Concerning aim 2, the feasibility and effectiveness of the identified digitalized treatments, our review found some promising results as well as crucial gaps in the literature. The state of research on iCBT interventions for older adults reveals that these interventions are feasible, with satisfactory completion rates [76]. These interventions were systematically evaluated in controlled trials and shown to be moderately to highly effective in treating older adults with signs of depression, anxiety, and insomnia [44-46,67,69,72-76,88,106,109]. However, we identified several limitations of the state of research on iCBT for older adults with mental illness, namely, short follow-up periods in the evaluation trials, a lack of research with older patients (especially those aged >80 years), and a gap in the literature concerning comparisons of iCBT with and without guidance and its effectiveness compared to face-to-face treatment. Therefore, further research is needed to assess whether online interventions remain effective over time and are as effective in treating individuals of very old age and to what extent the level of guidance affects their outcome.

Another finding of our review was that the feasibility of integrating basic digital technology into dementia care is well established. Concerning the effectiveness of digitalized treatments, some studies (21/42, 50%) found that they alleviated symptoms of depression and agitation [56,71,81] and improved cognition [62,70,87] and completion of activities of daily living [47-52,77,78,89] as well as social interactions [57,63,66,80,84,104]. However, it should be noted that most of this research lacked systematic evaluation, with an abundance of original studies (25/37, 68%) having small samples or no control condition. As the feasibility of digitalized treatments in dementia care has been proven, future studies should take this research to the next level of systematic evaluation, investigating the effectiveness of these treatments with larger samples in controlled settings.

Furthermore, older adults with mental illness face specific barriers which limit the effectiveness of digital interventions. Limited digital skills and access to technology were reported as key challenges in samples from Brazil and India [92], and difficulties handling technical issues were reported as challenges in a study from Hong Kong [96]. These barriers are likely more broadly relevant given the negative correlation of digital competence with age and mental illness [14,111,126].

Finally (aim 3), we will summarize the identified gaps in the literature as well as directions for future research, which are also presented in Table 3. The summary of findings of the included studies reveals, first, a lack of research on how advanced technologies can be leveraged for the treatment of older adults with mental illness, especially VR and AI technologies. Future research should explore how these technologies can be used to address specific needs of older adults and what, if any, adaptations are needed to ensure the feasibility and usability of digitalized treatments among older adults. Second, the current state of the art neglects many mental disorders that are prevalent among older adults, prioritizing research on dementia care. While cognitive disorders are a relevant topic in older age, other mental disorders such as affective and anxiety disorders, substance abuse, psychosis, and other serious mental illnesses are highly prevalent in old age [123]. As digital interventions have been shown to be feasible and effective in treating serious mental illness in younger populations [1,6,11], older individuals with these conditions also deserve to benefit from the newest technological advances in treatments. Third, it was outlined that many of the included studies (32/57, 56%) were conducted with small sample sizes and without control groups. Moreover, the distribution of countries appeared imbalanced, with an overrepresentation of studies from North America and Italy and only 2% (1/64) of the studies being from Asia and none being from Africa. While one can only speculate about the reasons for this (eg, different distribution of age groups and resources between countries), the field would benefit from more diverse research samples as the findings of this review may not be generalizable. Thus, future research on the feasibility and effectiveness of all digitalized treatment options for older adults needs to be more systematic, with larger, more diverse samples and controlled study designs. Fourth, while our review found several examples of how technology can be tailored to meet the specific needs of older adults with mental illness, there is still a huge potential for personalized interventions in this field in dementia care and beyond. Future studies should explore how technology may solve the issue of many older adults with mental illness being isolated [21,22], experiencing more obstacles in finding professional mental health care [30,31], and having limited access to technology and digitalized treatments [10,13-16]. By developing strategies to bridge the digital divide, digital mental health care should be made accessible to all. Fifth, ethical considerations were insufficiently addressed in the included studies. As digital technologies become increasingly integrated into mental health care, it is essential to critically examine ethical concerns, particularly in vulnerable populations such as older adults with mental illness. Key issues include data privacy and security, transparency, algorithmic bias, informed consent, and appropriate use. Considering the biomedical ethical principles articulated by Beauchamp and Childress [127]—autonomy, beneficence, nonmaleficence, and justice—overreliance on technology or its improper use may cause more harm than benefit when they inadvertently undermine patient autonomy or exacerbate inequalities. If there is a significant gap in technology knowledge, this can also reinforce a power imbalance between younger clinical professionals and older patients. Importantly, technology should never infantilize older adults or replace meaningful human interaction, as outlined by one study on robotics [63]. Therefore, the ethical implications of digital interventions must be evaluated on a case-by-case basis. Technologies that may be unproblematic or even empowering for younger, technology-literate users could pose significant risks to older individuals unfamiliar with such tools. Future studies, especially on more advanced technologies such as AI, need to consider the ethical underpinnings of their research to ensure that older adults with mental illness can safely benefit from digitalized treatments. One promising approach is the inclusion of human-in-the-loop oversight, a key component of trustworthy AI [128]. Such oversight ensures that human judgment remains part of the decision-making process, reducing the risks associated with automated systems. The identified gaps in the literature show that the “digital gray divide” exists in mental health care and needs to be addressed to foster more equity between the age groups.

The results of this scoping review must be interpreted in light of some limitations and do not claim to be complete. Due to the exclusion of gray literature, conference proceedings, or other sources in this review, important findings may have been missed. The search strategy for this review was deliberately kept broad to provide an overview of as many different digitalized treatments as possible. Nevertheless, future reviews may use more specific search terms to include specific technologies such as AI. Another limitation of this review was that we only searched the PubMed database—including other specialized databases (eg, PsycINFO) may have yielded more articles and should be considered in future, more comprehensive reviews. Future reviews should also consider expanding the search strategy to include search terms that were not covered by MeSH terms. In addition, the references of the systematic reviews found in the initial search were not searched on the assumption that the most important findings would already have been summarized in the reviews themselves, which may have led to the exclusion of some relevant studies. Moreover, while excluding a formal risk-of-bias assessment is in alignment with the PRISMA guidelines for scoping reviews, it would have provided added value to the interpretation of the findings. Finally, the process of study selection could have been further improved by including a third author to resolve potential disagreements.

In conclusion, this scoping review has demonstrated that there is a wide range of applications of digital technology available to treat mental illness in older adults, generally proving it to be feasible and accepted by patients. Results on the effectiveness of digitalized treatments vary and often lack systematic conformation. In addition, the state of research focused on few specific topics in the field, such as iCBT and basic technology in dementia care, neglecting other highly relevant problems for older adults with mental illness. We identified several critical gaps in the research on digitalized treatments for older adults with mental illness, highlighting a selective focus in research that exacerbates the “digital gray divide.” More equitable research is needed to ensure that all older adults with mental illness can benefit from the potential of digital interventions—addressing accessibility first, followed by expanding the research topics and methods. By leveraging advanced technologies in an ethical fashion, crucial challenges in the lives of older adults could be addressed and solved, improving their quality of life.