Published on in Vol 24, No 9 (2022): September

Preprints (earlier versions) of this paper are available at, first published .
Effects of Serious Games on Depression in Older Adults: Systematic Review and Meta-analysis of Randomized Controlled Trials

Effects of Serious Games on Depression in Older Adults: Systematic Review and Meta-analysis of Randomized Controlled Trials

Effects of Serious Games on Depression in Older Adults: Systematic Review and Meta-analysis of Randomized Controlled Trials

Authors of this article:

Yesol Kim1 Author Orcid Image ;   Soomin Hong1 Author Orcid Image ;   Mona Choi2, 3 Author Orcid Image


1College of Nursing and Brain Korea 21 FOUR Project, Yonsei University, Seoul, Republic of Korea

2Mo-Im Kim Nursing Research Institute, College of Nursing, Yonsei University, Seoul, Republic of Korea

3Yonsei Evidence Based Nursing Centre of Korea, A JBI Affiliated Group, Seoul, Republic of Korea

Corresponding Author:

Mona Choi, PhD

Mo-Im Kim Nursing Research Institute

College of Nursing

Yonsei University

50-1 Yonsei-ro


Seoul, 03722

Republic of Korea

Phone: 82 2 2228 3341

Fax:82 2 2227 8303


Background: Depression is a severe psychological concern that negatively affects health in older adults. Serious games applied in various fields are considered appropriate interventions, especially in mental health care. However, there is a lack of evidence regarding the effects of serious games on depression in older adults.

Objective: This study aimed to investigate the characteristics and effectiveness of serious games for depression in older adults.

Methods: A systematic review and meta-analysis of randomized controlled trials were conducted. In total, 5 electronic databases (PubMed, CINAHL, Embase, PsycINFO, and Cochrane Library) were searched to identify relevant studies published until July 6, 2021. A total of 2 reviewers independently conducted study selection, data extraction, and quality appraisals. The risk of bias in the included studies was assessed using the JBI Critical Appraisal Checklist. For the meta-analysis, the effect size was calculated as the standardized mean difference (SMD) by using a random effects model.

Results: A total of 17 studies with 1280 older adults were included in the systematic review, and 15 studies were included in the meta-analysis. Serious game interventions were classified into 3 types: physical activity (PA), cognitive function, and both PA and cognitive function. The meta-analysis demonstrated that serious games reduced depression in older adults (SMD −0.54, 95% CI −0.79 to −0.29; P<.001). Serious games had a more significant effect size in community or home settings (SMD −0.61, 95% CI −0.95 to −0.26; P<.001) than in hospital settings (SMD −0.46, 95% CI −0.85 to −0.08; P=.02); however, the difference between groups was not significant. Among the types of games, games for PA (SMD −0.60, 95% CI −0.95 to −0.25; P<.001) and games for both (SMD −0.73, 95% CI −1.29 to −0.17; P=.01) had a significant effect on reducing depression in older adults. However, no significant correlations were observed between the duration or number of serious games and depression.

Conclusions: Serious games were beneficial in reducing depression in older adults. Regardless of the study setting, serious games appeared to reduce depression. Particularly, serious games including PA had a significant impact on reducing depression. Furthermore, high-quality randomized controlled trials are needed to establish substantial evidence for the effectiveness of serious games on depression in older adults.

Trial Registration: PROSPERO CRD42021242573;

J Med Internet Res 2022;24(9):e37753




The aging population is increasing worldwide. The average life span has increased, and health-related concerns in older adults require attention [1], highlighting their physical and mental health concerns [2]. Researchers have examined the psychosocial aspects of older adults, including anxiety, depression, sleep disorders, loneliness, and social functional impairment [3-5]. Specifically, depression is a severe and typical mental health concern characterized by sadness and hopelessness [6]. Older adults are more vulnerable to depression owing to their psychosocial concerns. During the COVID-19 pandemic, older adults had a high risk of depression owing to a decrease in social relations, regardless of their environment or context [7,8].

The clinical conditions of older adults also make them likely to develop depression. Physical and cognitive problems and functional loss are the primary causes of depression in older adults [2]. Older adults experience ambiguous symptom profiles of depression, and atypical symptoms make early detection challenging [9]. In addition, insufficient psychosocial relationships and decreased economic status after retirement lead to depression in older adults [10,11].

The prevention, early detection, and treatment of depression in older adults are crucial. However, older adults tend to avoid using mental health services because of poor physical function, psychological barriers, and reduced mobility [12]. To improve the mental health of older adults, specific methods are required that consider their characteristics and attributes. Moreover, detailed and personalized interventions are required to manage depression in older adults. For instance, physical function, cognitive function (CF), sensory function impairment, comorbidities, medication, and environmental factors should be considered [13-16].

Digital interventions for mental health care are considered promising [17,18] and have become indispensable since the COVID-19 pandemic. Digital interventions have been found to be effective in reducing the symptoms of depression [19], loneliness [5], and social isolation [20] in older adults. There has been a gradual increase in the use of digital interventions for older adults in clinics and research, although digital interventions may pose certain challenges to older adults [21,22]. A mixed methods study has identified that although older adults may wish to make use of digital interventions to alleviate depression, they might also initially face certain obstacles to participation [23]. Digital interventions that consider the daily lives of older adults, ease of use, and low cost may help reduce depression [23]. In light of their perspectives, circumstances, and contexts, it is necessary to develop and implement effective interventions for older adults.

Serious games, a type of digital intervention, refer to a series of activities performed by combining the aspects of video games for specific purposes, such as education or rehabilitation [24]. Initially, they were developed for military purposes in the 1970s and recently appeared in more advanced forms with the development of computers and mobile devices [25]. In addition, they are now widely used in education and health care [26], such as physical rehabilitation [27], cognitive training [28,29], and health promotion [30]. Interest in serious games which allow participants to voluntarily achieve their goals has increased.

Various interventions of serious games have been conducted not only for adolescents [31] and younger adults [32] but also for older adults [33-35]. They were applied to older adults in different ways, including video games, using devices such as Nintendo [36,37], and virtual reality serious games [38]. When developing serious game interventions to improve the health of older adults, there are a variety of goals, such as strengthening physical function or CF. In addition, the composition or content of serious games was altered to fit the purpose of the intervention. For instance, if a serious game is designed to improve physical function, older adults require to move their bodies during the game [39]. In a previous study, a serious game was used and evaluated to enhance spatial memory in older adults by implementing the appearance of a real-world city and systematically applying a virtual environment [40].

Serious games are considered appropriate interventions in mental health care, including for the general population and patients with or without psychiatric concerns [41-43]. Studies have reported that serious games influence depression [44,45]; however, a systematic review and meta-analysis focusing on the effect size of a serious game on depression in older adults is rare. In addition, the intervention effects differed in studies on serious games for older adults [33,46-48]. Therefore, further analysis of serious games for depression in older adults is required.


This systematic review and meta-analysis aimed to analyze the effects of various types of serious games on depression in older adults. The detailed research questions leading to this study are as follows: (1) What are the characteristics of serious games used to intervene in depression among older adults? (2) How effective are serious games to intervene in depression among older adults? (3) Which aspects of serious games affect depression in older adults?


This systematic review and meta-analysis of randomized controlled trials were reported following the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [49] and the JBI manual [50]. The study protocol was registered with PROSPERO (registration number CRD42021242573).

Search Strategy

We conducted a systematic search by using electronic databases (PubMed, CINAHL, Embase, PsycINFO, and the Cochrane Library) on July 6, 2021. To organize the search terms, free text and Medical Subject Headings terms were combined according to the participants, interventions, comparisons, and outcomes. Key search terms were as follows: (“aged” or “older” or “elder*” or “senior”) and (“game” or “gaming” or “exergame” or “serious game” or “serious gaming”) and (“depression” or “depressive disorder”). A summary of search strategies is presented in Multimedia Appendix 1.

Eligibility Criteria

Eligibility criteria were determined according to the participants, interventions, comparisons, outcomes, and study design. The inclusion criteria were as follows: (1) participants—studies that included older adults with a mean age of ≥65 years; (2) interventions—studies that applied serious games comprising exergames, virtual reality games, or digital games; (3) comparisons—studies that applied usual care or nonserious games for the control group; (4) outcomes—studies measuring depression; and (5) study design—randomized controlled trials only. The exclusion criteria were as follows: (1) studies that applied different doses or intensities of the serious game for the control group; (2) studies published in a language other than English; and (3) gray literature such as theses, dissertations, or conference abstracts.

Study Selection

After searching for studies in electronic databases, one researcher (YK) exported all the studies to the reference management software EndNote X9 (Clarivate Analytics), and the other researchers (SH and MC) rechecked the extracted studies. The titles and abstracts of the extracted studies were independently screened according to the inclusion criteria by 2 researchers (YK and SH). Subsequently, they reviewed the full texts separately to select the final studies to be included. If the screening results did not match, a consensus was reached through discussion. The other researcher (MC) supervised the screening process.

Data Extraction

Two researchers (YK and SH) independently extracted the data. The data extraction of the selected studies was performed using a structured form that included study, participant, intervention, and outcome characteristics. First, the study characteristics included authors, publication year, country, and setting. Second, the participant characteristics included health status, age (mean and SD), and sample size. Intervention characteristics consisted of type, the device used, content, duration, frequency, time, dose of serious games, type of control group, and the interventionist. Finally, outcome characteristics comprised the measurement of depression, the main result, mean, and SD for the experimental and control groups. If data required for analysis could not be found in the article, researchers requested data from the respective authors via email.

Risk-of-Bias Assessment

Two researchers (YK and SH) independently evaluated the methodological quality of the included studies according to the JBI Critical Appraisal Checklist for randomized controlled trials [50]. The checklist has 13 items to assess the risk of bias, including participants, assignments, measurement, and analysis domains, and 1 overall appraisal item. After each included study was assessed using a 13-item checklist as “yes,” “no,” and “unclear,” the final quality judgment was drawn according to the “yes” ratio. The risk of bias was evaluated as follows: (1) ≥75% was ranked as high quality, (2) the range between 50% and 74% was ranked as medium quality, and (3) <50% was considered poor quality [51].

Data Analysis

We calculated effect sizes as the standardized mean difference (SMD) with a 95% CI by using the mean and SD to synthesize the pooled effect of serious games on depression in older adults. When depression values were not presented as mean and SD in original studies, SMD was calculated through the conversion process by using SE, median, range, or IQR [52,53]. On the basis of the study by Cohen [54], the effect sizes were considered small (0.2≤SMD<0.5), medium (0.5≤SMD<0.8), and large (SMD≥0.8). To identify the effects of heterogeneity in the meta-analysis, I2 was used. Heterogeneity was classified as low (25%), moderate (50%), or high (75%) according to I2 values [55]. Because the characteristics of the participants and interventions included in the meta-analysis were heterogeneous, we conducted a meta-analysis by using a random effects model. According to the heterogeneity results, a subgroup analysis was conducted on the setting, participant characteristics, type of serious game, and the control group. In addition, we performed a meta-regression to explore the causes of heterogeneity regarding the duration and dose of serious games. Publication bias was assessed using funnel plots and Egger test. Statistical significance was set at P<.05. Statistical analysis was performed using the Comprehensive Meta-analysis software (version 3.0) and Review Manager software (version 5.4).

Study Selection

Figure 1 shows a PRISMA 2020 flow diagram for screening and selection. A total of 2301 studies were extracted from 5 databases. After removing duplicate records (n=620, 26.94%), 1681 (73.06%) studies were screened using the inclusion and exclusion criteria based on title, abstract, and full text. Finally, 0.74% (17/2301) of studies were included in this study.

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 flow diagram for study screening and selection.
View this figure

Risk of Bias of the Studies

The results for the risk of bias in this study are presented in Multimedia Appendix 2 [50-66]. As confirmed by the number that met the criteria “yes,” the distribution of satisfying the risk-of-bias evaluation items ranged from 4 (31%) to 10 (77%) out of 13 items. Only 1 study [56] was evaluated as high quality, which indicated a low risk of bias. In total, 5 studies were ranked as poor quality (<50%) [57-61]. The remaining 11 studies were categorized as medium quality, with a distribution of 54% to 69%.

Study Characteristics

The characteristics of the selected studies are summarized in Table 1. A total of 17 studies were published between 2012 and 2021 and conducted in 10 countries. The United States had the most research conducted [57,58,60,62], followed by Brazil [61,63,64], Korea [59,65], and Hungary [66,67]. More than half of the studies were conducted in community settings such as retirement villages, nursing homes, long-term care facilities, and assisted living facilities [56,60-63,68-71]. In total, 5 studies were conducted in hospitals [59,64-67] and 3 in homes [57,58,72].

A total of 1280 older adults were included in this review. Among the 17 studies, 7 (41%) mentioned health problems as the criteria for participant selection. The health status characteristics of the participants included neurocognitive problems, such as Parkinson disease and predementia [64-66,71], depression [57], limited mobility [67], and stroke [59]. For the 3-arm study, control groups were indicated by “control group a” and “control group b” [58,64,66,67]. The mean age of the participants ranged from 66.4 (SD 0.8) [63] to 85.0 (SD 6.1) [71], and the sample size varied between 16 [69] and 351 [62].

Various measurements of depression in older adults were described in the included studies. In 35% (6/17) of the studies, the Geriatric Depression Scale, including 5, 15, and 30 items, was used to measure depression [58,60,64,65,68,70]. In 29% (5/17) of the studies, depression was measured using the Beck Depression Inventory [59,61,66,67,69]. Other studies (6/17, 35%) used the Patient Health Questionnaire-9 [56,62], Profile of Mood States [63,72], Cornell Scale for Depression in Dementia [71], and Hamilton Depression Rating Scale [57].

Table 1. Characteristics of the included studies (N=17).
Authors, yearCountry, settingCharacteristics of participantsAge (years), mean (SD)Sample size, nMeasureEffect sizea (95% CI)
Rendon et al [60], 2012United States, communityCommunity-dwelling older adultsEb: 85.7 (4.3); Cc: 83.3 (6.2)E: 20; C: 20GDSd-30−0.72 (−1.41 to −0.03)
Schoene et al [56], 2015Australia, communityCommunity-dwelling older adults81.5 (7.0)E: 47; C: 43PHQ-9e−0.29 (−0.72 to 0.14)
Choi et al [59], 2016Korea, hospitalHospitalized patients with ischemic strokeE: 61.0 (15.2); C: 72.1 (9.9)E: 12; C: 12BDIf−0.11 (−0.91 to 0.69)
Levy et al [69], 2016France, communityCommunity-dwelling older adults with the fear of fallingE: 72.4 (12.3); C: 68.7 (19.1)E: 9; C: 7BDI−0.75 (−1.77 to 0.27)
Nouchi et al [72], 2016Japan, homeCommunity-dwelling older adults68.9 (3.7)E: 36; C: 36POMSg2NCh
Anguera et al [57], 2017United States, homeMajor depression68.0 (6.3)E: 12; C: 10HAM-Di−0.13 (−0.97 to 0.71)
Ferraz et al [64], 2018Brazil, hospitalParkinson disease69.0 (5.0)E: 22; C-aj: 25; C-bk: 25GDS-15a: −0.10 (−0.71 to 0.51); b: −0.11 (−0.74 to 0.52)
Belchior et al [58], 2019United States, homeCommunity-dwelling older adults73.2 (5.5)E: 26; C-a: 20; C-b: 25GDS-30NC
Smith et al [62], 2019United States, communityLived in supported senior living settings80.6 (9.1)E: 173; C: 178PHQ-9−0.10 (−0.34 to 0.14)
Stanmore et al [70], 2019United Kingdom, communityLived in assisted living facilitiesE: 77.9 (8.9); C: 77.8 (10.2)E: 56; C: 50GDS-5−0.17 (−0.58 to 0.24)
Tollár et al [66], 2019Hungary, hospitalParkinson diseaseE: 70.0 (4.7); C-a: 70.6 (4.1); C-b: 67.5 (4.3)E: 25; C-a: 25; C-b: 24BDIa: −0.17 (−0.72 to 0.38); b: −1.22 (−1.83 to −0.61)
Tollár et al [67], 2019Hungary, hospitalMobility-limited older adults69.6 (3.5)E: 28; C-a: 27; C-b: 28BDIa: −0.28 (−0.81 to 0.25); b: −1.46 (−2.05 to −0.87)
de Morais et al [63], 2020Brazil, communityOlder adults66.4 (0.8)E: 29; C: 29POMS−0.29 (−0.80 to 0.22)
Rica et al [61], 2020Brazil, communityInstitutionalized older women aged >60 yearsNot reportedE: 16; C: 34BDI−2.08 (−2.81 to −1.35)
Jahouh et al [68], 2021Spain, communityInstitutionalized in nursing home or attending day centerE: 85.1 (8.6); C: 83.3 (8.8)E: 40; C: 40GDS-15−0.65 (−1.10 to −0.20)
Kang et al [65], 2021Korea, hospitalPredementia state74.5 (5.8)E: 25; C: 20GDS-30−0.19 (−0.82 to 0.44)
Swinnen et al [71], 2021Belgium, communityOlder adults with neurocognitive disorder residing in long-term care facilitiesE: 84.7 (5.6); C: 85.3 (6.5)E: 28; C: 27CSDDl−1.38 (−2.03 to −0.73)

aEffect size was calculated as the standardized mean difference with a 95% CI.

bE: experimental group.

cC: control group.

dGDS: Geriatric Depression Scale.

ePHQ-9: Patient Health Questionnaire-9.

fBDI: Beck Depression Inventory.

gPOMS: Profile of Mood State.

hNC: not calculated because required data were not provided.

iHAM-D: Hamilton Depression Rating Scale.

jC-a: a control group of the 3-arm study.

kC-b: the other control group of the 3-arm study.

lCSDD: Cornell Scale for Depression in Dementia.

Characteristics of the Serious Game Intervention

The characteristics of the serious game intervention are presented in Tables 2 and 3. Serious game interventions were classified into 3 types: games for physical activity (PA; 9/17, 53%), games for CF (5/17, 29%), and games for both PA and CF (3/17, 18%).

Regarding games for PA, the devices used in the intervention were Microsoft Xbox 360 [61,63,64,66,67]; Nintendo [60]; Microsoft Kinect [70]; tablet computers and smartphones with a Bluetooth connection [59]; and V8 Head Mount Display, 3D electromagnetic sensor, and PlayStation 2 [69]. Studies using the Xbox 360 primarily provided various commercial games that involved the movement of the participant’s body. Studies using Nintendo had applied strength training, aerobics, and balance games of Wii Fit. A study applying Kinect provided 16 exergames targeting the lower or upper limbs by using the Medical Interactive Recovery Assistant digital platform [70]. Choi et al [59] reported that a game improved the mobility of the upper extremity through a mobile app and Bluetooth connection to smart devices. A study using the V8 Head Mount Display, part of a virtual reality game, provided video games that required movements of the participants’ bodies [69].

Regarding games for CF, devices included tablet computers [57,72], controllers [58], CDs or computers [62], and Oculus Lift CV1 and touch controllers [65]. Studies using tablet computers applied the developed cognitive training game to participants. Commercial games that can improve CF were provided based on controllers, CDs, or websites. As part of a virtual reality game, a study using the Oculus Lift CV1 and touch controllers applied games that consisted of multidomain cognitive tasks.

Regarding games for both PA and CF, the devices used were electronic step pads [56,71] and Nintendo [68]. Studies applying electronic step pads provided step training that promoted both PA and CF, wherein participants moved in various directions. Another study provided various games that involved PA and CF using Nintendo (Table 2).

Among the 17 studies, 1 (6%) study [63] did not report the duration of intervention, whereas 16 (94%) studies reported the duration of intervention to be between 2 weeks [59] and 12 months [62]. Among the studies, the most frequent durations of intervention were reported as 8 weeks [57,64,68,71] and 12 weeks [58,61,69,70]. The prescribed serious game intervention was conducted for 1 to 5 sessions per week and 15 to 60 minutes per session. The total dose provided to the participants ranged from 2 sessions [63] to 60 sessions [58].

Of the included studies, the control groups consisted of usual care [58,60,65-70], exercise [59,64,66,67], nonserious games [61,62,72], watching a film or music videos [63,71], or other programs such as providing a brochure [56], cognitive training [58], and problem-solving therapy [57].

Of the 17 studies, 9 (53%) reported interventionists. Physical or occupational therapists [59,60,64,66,67,70,71], a neuropsychologist [65], and an interprofessional team [57] provided interventions to the participants (Table 3).

Table 2. Summary of serious game interventions of the included studies (N=17).
Authors, yearType of serious game; deviceContents
Rendon et al [60], 2012PAa; Nintendo
  • Wii fit using the Wii Balance Board
  • Balance games (lunges, single leg extensions, and twists)
Schoene et al [56], 2015Both; electronic step pad
  • The interactive training system used stepping onto an electronic step pad to interact with a computer interface, and videogame technology was used to deliver the training tasks on standard home television screens
  • Videogames (Stepper, StepMania, Trail-Stepping, and Tetris)
Choi et al [59], 2016PA; tablet computer and smartphone with Bluetooth connection
  • The MoU-Rehab consisted of 4 mobile game apps
  • All game apps were designed to improve strength, endurance, range of motion, control, speed, and accuracy of movement in the upper extremity
Levy et al [69], 2016PA; V8 Head Mount Display, 3D electromagnetic sensor, and EyeToy interface for PlayStation 2
  • Participants played video games that required moving their bodies
  • Games (wash a window and kung fu)
Nouchi et al [72], 2016CFb; tablet computer
  • In total, 12 processing speed training games to function on the tablet computer
  • All games required participants to detect, identify, discriminate, and localize targets as quickly as possible
Anguera et al [57], 2017CF; tablet computer
  • Mobile iPad intervention called Project: EVO based on the video game called NeuroRacer
  • This game involves guiding a character through an immersive environment while responding to select targets, with the design format being ideally entertaining
Ferraz et al [64], 2018PA; Xbox 360
  • Exergames use full-body motion to allow the player to engage in a variety of mini games, all of which feature jump-in, jump-out multiplayer play
  • Physical components involved in those games included strength and muscular endurance, cardiorespiratory fitness, postural balance, and executive function
Belchior et al [58], 2019CF; videogame and controller
  • Crazy taxi is a driving game with key features that include rapid navigation through an urban environment, attending to speed, and roadway features
  • Characteristics of this game were speed; elevated perceptual, cognitive, and motor loads; and having items of interest often presented at the periphery of the visual field and under divided attention conditions
Smith et al [62], 2019CF; CDs or web using computer
  • Road Tour on CDs and Double Decision, a web-based version, were used
  • Road Tour and Double Decision performed the same way
  • Speed of processing training participants saw an object (either a car or truck) in the center of the monitor and a target (route 66 road sign) along with 7 rabbit distractor signs in a near-periphery orbit. Participants viewed the monitor image as quickly as they could while still correctly identifying the object and the target location
Stanmore et al [70], 2019PA; Microsoft Kinect
  • Kinect tracks the user’s performance and records parameters
  • Each participant was given a prescribed program of standardized exergames that suited the participant’s starting level of ability with tailored progression
  • Individual exercise programs can be tailored using a choice of games for lower or upper limb exercises using 16 of Medical Interactive Recovery Assistant’s exergames (strength, balance, coordination, and flexibility exercises)
Tollár et al [66], 2019PA; Xbox 360
  • Exergame was designed to improve postural control, gait mobility, gait stability, turning, and dynamic and static
  • Exergame used the 3 visual feedback modules of the Xbox 360 core system, Kinect Adventures video game (Reflex Ridge, Space Pop, and Just Dance)
Tollár et al [67], 2019PA; Xbox 360
  • Exergame was designed to improve postural control, gait mobility, gait stability, turning, and balance
  • Exergame used 3 Xbox 360 modules (Reflex Ridge, Space Pop, and Just Dance)
de Morais et al [63], 2020PA; Xbox 360
  • Xbox Kinect—“Your Shape Fitness evolved” (Zen-Develop it, Pump it, Wall Breacker, Kick it, Hurricane, and Stack in Up)
  • The games are classified as easy, medium, or hard levels, and only the easy level was used
Rica et al [61], 2020PA; Xbox 360
  • For Kinect-based exercise protocol, balance games were included
  • Kinect Sports Ultimate Collection, Your Shape Fitness Evolved, Dance Central, and Nike + Kinect Training
Jahouh et al [68], 2021Both; Nintendo
  • The intervention made up of different activities with the Nintendo Wii Fit video game console
  • An aerobic-type game was used as a warm-up exercise
  • The next game was played specifically to work on attention, concentration, and memory. In this game, a goalkeeper throws balls or bears from both the left and right sides. The participant was required to lean to either side to avoid all possible bears and head all possible balls; in other words, the participants had to swing on the same side of the ball or on the opposite side of the bear
  • To end the session, the participants had to choose a game that they wanted to try or play
Kang et al [65], 2021CF; Oculus Rift CV1 and Oculus touch controllers
  • Training was accompanied by game elements to increase the interest and motivation of the participants
  • Games involving multidomain cognitive tasks to assess
Swinnen et al [71], 2021Both; Dividat Senso
  • Dividat Senso consisted of a step training platform that was sensitive to pressure changes
  • The sensors detected steps in 4 directions: left, right, top, and bottom
  • The platform was connected via a USB cable to a computer and a frontal television screen on which the exergames were displayed
  • Participants interacted with the game interface by pushing foot on 1 of the 4 different arrows
  • The games trained cognitive abilities
  • The device provided real-time visual, auditory, and somatosensory (vibrating platform) cues and feedback to enrich the game experience

aPA: physical activity.

bCF: cognitive function.

Table 3. Characteristics of serious game interventions of the included studies (N=17).
Authors, yearType of serious gameDuration, frequency, time per session, doseControl groupInterventionist
Rendon et al [60], 2012PAa6 weeks, 3 sessions per week, 35-45 minutes, 18 sessionsUsual carePhysical therapist
Schoene et al [56], 2015Both16 weeks, 3 sessions per week, 20 minutes, 48 sessionsBrochureNRb
Choi et al [59], 2016PA2 weeks, 5 sessions per week, 60 minutes, 10 sessionsExercise (conventional occupational therapy)Occupational therapist
Levy et al [69], 2016PA12 weeks, 1 session per week, <40 minutes, 12 sessionsUsual careNR
Nouchi et al [72], 2016CFc4 weeks, 5 sessions per week, 15 minutes, 20 sessionsNonserious game (knowledge quiz)NR
Anguera et al [57], 2017CF8 weeks, 5 sessions per week (biweekly), <20 minutes, 20 sessionsProblem-solving therapyInterprofessional team (clinicians, care managers, and therapists)
Ferraz et al [64], 2018PA8 weeks, 3 sessions per week, 50 minutes, 24 sessionsExercise (functional training); exercise (bicycle)Physical therapist
Belchior et al [58], 2019CF12 weeks, 5 sessions per week, 60 minutes, 60 sessionsCognitive training; usual careNR
Smith et al [62], 2019CF12 months, NR, NR (600 minutes per 5-6 weeks), NRNonserious game (computerized crossword puzzles)NR
Stanmore et al [70], 2019PA12 weeks, 3 sessions per week, NR, 36 sessionsUsual carePhysical therapist
Tollár et al [66], 2019PA5 weeks, 5 sessions per week, 60 minutes, 25 sessionsExercise (stationary cycling); usual carePhysical therapist
Tollár et al [67], 2019PA5 weeks, 5 sessions per week, 60 minutes, 25 sessionsExercise (stationary cycling); usual carePhysical therapist
de Morais et al [63], 2020PANR, NR, 30 minutes, 2 sessionsWatching a filmNR
Rica et al [61], 2020PA12 weeks, 3 sessions per week, 60 minutes, 36 sessionsNonserious game (board games)NR
Jahouh et al [68], 2021Both8 weeks, 2-3 sessions per week, 40-45 minutes, 20 sessionsUsual careNR
Kang et al [65], 2021CF4 weeks, 2 sessions per week, 20-30 minutes, 8 sessionsUsual careNeuropsychologist
Swinnen et al [71], 2021Both8 weeks, 3 sessions per week, 15 minutes, 24 sessionsWatching music videosPhysical therapist

aPA: physical activity.

bNR: not reported.

cCF: cognitive function.

Effects of Serious Games on Depression

Among the 17 studies included in the review, a meta-analysis was conducted on 15 (88%) studies, excluding 2 (12%) studies that did not provide raw data [58,72]. As 3 studies had 2 control groups each [64,66,67], we included 18 results in this meta-analysis. The pooled SMD between groups was −0.54 (95% CI −0.79 to −0.29; P<.001) with a medium effect size. These results indicate that serious games reduce depression in older adults. The heterogeneity of the meta-analysis was moderate to high across the studies (I2=73%; P<.001; Figure 2).

Figure 2. Forest plot for the effect of a serious game on depression.
View this figure

Subgroup Analysis

The results of the subgroup analysis of serious games for depression are shown in Figures 3-6. Regarding the setting, serious games had a more significant effect size in communities or homes (SMD −0.61, 95% CI −0.95 to −0.26; P<.001) than in hospitals (SMD −0.46, 95% CI −0.85 to −0.08; P=.02). However, the difference in the effect size between the groups was not statistically significant (χ21=0.3; P=.59; Figure 3).

Figure 3. Forest plot for the effect of a serious game on depression according to setting.
View this figure

Regarding the characteristics of participants, the effect sizes of participants without health problems and with neurocognitive problems were −0.55 (95% CI −0.91 to −0.20; P=.002) and −0.52 (95% CI −0.99 to −0.05; P=.03), respectively, which significantly reduced depression (Figure 4).

A subgroup analysis of the type of serious game revealed that games for both had a significant effect on reducing depression in older adults (SMD −0.73, 95% CI −1.29 to −0.17; P=.01). In addition, games for PA significantly reduced depression (SMD −0.60, 95% CI −0.95 to −0.25; P<.001), whereas there was no significant effect of games on CF (Figure 5).

In the control group, serious games versus usual care had a significant effect on reducing depression (SMD −0.72, 95% CI −1.10 to −0.33; P<.001). However, subgroups of serious games versus other active comparators such as exercise, nonserious games, watching a film or music videos, and other programs presented no significant effect (Figure 6).

The results of the meta-regression indicated that no significant correlation existed between depression and the duration (P=.40) or dose of serious games (P=.43; Multimedia Appendix 3).

Figure 4. Forest plot for the effect of a serious game on depression according to the characteristics of participants.
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Figure 5. Forest plot for the effect of a serious game on depression according to the type of serious games. CF: cognitive function; PA: physical activity.
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Figure 6. Forest plot for the effect of a serious game on depression according to the type of control group.
View this figure

Publication Bias

In this study, the publication bias was considered low. The funnel plot revealed a fairly symmetrical pattern (Multimedia Appendix 4). In addition, Egger test demonstrated that no publication bias was present in this meta-analysis (P=.27).

Principal Findings

This study aimed to investigate the characteristics of serious games and their effects on depression in older adults. A total of 17 studies included in the systematic review have been conducted since 2012, and the number of studies has been steadily increasing. This study identified 3 types of serious games: games for PA, games for CF, and games for both PA and CF. Furthermore, it was demonstrated that the equipment and components of the game varied for each type of serious game. In addition, this study could provide substantial scientific evidence and produce high-quality findings as it included randomized controlled trials.

Older adults may face certain barriers to the use of digital interventions, such as physical changes because of aging and a lack of knowledge about technology [73]. In addition, studies included in this review reported that older adults who participated in serious games might experience difficulties with costs related to devices or programs [58], use of technology [70], and physical symptoms such as nausea, oculomotor dysfunction, and disorientation [65]. Despite these obstacles, the results of our meta-analysis indicate that serious games significantly reduce depression in older adults to a moderate effect size (SMD=−0.54). This aligns with the meta-analysis findings that showed reduced depression in young people [45]. In addition, the effect size of our findings was larger than that of studies targeting the general population [44,74]. Compared with the young or general population, serious games may effectively reduce depression in older adults, who face barriers in the application of digital interventions. As overcoming obstacles related to digital intervention may increase the interest and confidence of older adults [75], a serious game is considered effective and acceptable for them.

In this study, interventions of serious games were primarily conducted in places where older adults lived their daily lives, such as communities and homes, rather than in hospitals. Our findings showed that serious games played in communities or homes significantly reduced depression. Even without a supervised environment, such as a hospital, we found that the settings did not significantly affect older adults in applying serious games. This can be particularly convenient when applying the intervention to older adults with poor mobility or other accompanying diseases [47]. Therefore, a serious game can be applied regardless of the location once the appropriate environment or equipment is prepared.

In a subgroup analysis, serious games reduced depression in older adults without health problems or with neurocognitive problems. Appropriate physical abilities are required to perform serious games [76]; the intervention was effectively provided to older adults without health problems. Moreover, depression is considered an important health issue in older adults with neurocognitive problems such as Parkinson disease [77] and the predementia stage [78]. Accordingly, the findings of this study might be promising, as serious games may help reduce depression. However, the evidence may be relatively weak owing to the small number of studies. Further intervention studies are needed to confirm the relationship between the characteristics of older adults and the effectiveness of games.

Among the types of games, those that applied PA, including games for both accounted for approximately 70%. Our findings indicated that helping body movements directly by using various devices had a significant effect on reducing depression compared with games for CF. PA has been found to reduce depression through biological and psychosocial mechanisms [79]. In addition, a previous meta-analysis illustrated that exercise can significantly reduce depression in older adults [80]. Games promoting PA suggest the possibility of improving the quality of life and reducing depressive symptoms in older adults [61]. Therefore, PA should be considered as an essential component in the application of serious games to manage depression in older adults.

In the meta-analysis, we included studies that provided a control group with usual care as well as studies that provided other interventions considered active comparators. For studies comparing usual care groups, participation in serious games was found to have a significant impact on reducing depression. However, studies comparing active comparators, such as exercise, nonserious games, and watching videos, showed a reduction in depression, but this was not statistically significant. These findings are consistent with those of a meta-analysis that included active comparators [81]. The absolute and relative effects of the intervention can be interpreted according to the type of control group [82]. When the control group received usual care, the results indicated an absolute effect of the intervention. However, when the control group had active comparators, the results demonstrated a relative effect of the intervention. In this study, the absolute effect of participation in serious games was confirmed, but the relative effect was not. These findings indicate that participation in serious games has a unique and significant effect on older adults. Among the advantages of serious games, older adults can participate in such games regardless of the location [59], and it is generally easy to participate in such games [57]. In addition, participation in serious games motivates older adults and improves engagement [58,61], which has been found to increase adherence to interventions [57,63]. Participation in serious games for older adults may be viewed as an acceptable strategy to reduce depressive symptoms, as it has been confirmed that they have relatively high interest, satisfaction, and usability in serious games [59,65,70]. Therefore, we suggest that it is necessary to develop serious games that reflect helpful characteristics so that the relative effect as well as the absolute effect of interventions can be confirmed.


This study systematically reviewed the literature and analyzed the effectiveness of an overall serious game conducted to manage depression, without limiting the health characteristics of older adults. However, this study has a few limitations. First, some studies in which depression was not the primary outcome of the intervention were also selected because depression itself was of interest in this study. Generally, this selection may have a weak causal relationship between serious games and depression. In this review of 17 studies, 9 (53%) and 8 (47%) studies measured depression as a primary and secondary outcome, respectively. Depression had a significant reduction effect in 5 out of 9 (56%) studies measured as a primary outcome and 38% (3/8) of studies measured as a secondary outcome. The effects are greater when the intervention is performed for the main purpose of reducing depression. Therefore, further research is needed to clarify the relationship between depression as an outcome of intervention and its effectiveness. Second, methodological quality appraisals were performed using the JBI Critical Appraisal Checklist for the 17 studies included in this review. Only 6% (1/17) of high-quality studies had a low risk of bias, and approximately one-third (n=5, 29%) of the studies had a high risk of bias. Therefore, it can be considered that the evidence of the synthesized results is relatively low. Finally, this study included a variety of health characteristics, devices, and contents of serious games, which might lead to moderate to high heterogeneity (I2=73%). Thus, it is necessary to pay attention to the interpretation of the results.


Our findings may contribute to the understanding of the effects of serious games on reducing depression in older adults. The findings of this study also provide researchers and health care providers with several implications for managing depression in older adults. First, there is a need to apply serious games involving PA to manage depression in older adults. It may be beneficial to add various types of serious games to increase their effectiveness. Second, serious games should be developed and adapted to suit the various characteristics and needs of older adults. In addition, it is necessary to further explore devices, content, and duration that will be effective for older adults. Finally, a large-scale and more rigorously designed randomized controlled trial of serious games should be conducted to provide scientific evidence.


The findings of this review and meta-analysis demonstrate that serious games are beneficial for reducing depression in older adults. Among the types of serious games, those that include PA significantly reduce depression. Regarding the setting, interventions conducted in the community, including homes, can alleviate depression in older adults. We also found that studies provided by nurses or multidisciplinary teams were limited; therefore, nurse researchers should conduct serious game interventions further. In addition, more high-quality randomized controlled trials are needed to establish substantial evidence of the effectiveness of serious games on depression in older adults.


This research was supported by the Brain Korea 21 FOUR Project funded by the National Research Foundation of Korea, Yonsei University College of Nursing, and Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (2020R1A6A1A03041989). This research was also supported by a 2020 grant from Yonsei University College of Nursing.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Search strategies and results of this study.

DOCX File , 18 KB

Multimedia Appendix 2

Methodological appraisal of the included studies (N=17).

DOCX File , 21 KB

Multimedia Appendix 3

Results of the meta-regression for subgroups of a serious game on depression.

DOCX File , 267 KB

Multimedia Appendix 4

Funnel plot of this study.

DOCX File , 106 KB

  1. Griffin L, Patterson D, Mason TM, Vonnes C. Improving care coordination for patients 65 and older. Geriatr Nurs 2021;42(2):610-612. [CrossRef] [Medline]
  2. Mental health of older adults. World Health Organization. 2017 Dec 12.   URL: [accessed 2022-01-11]
  3. Kim HS, Kang JS. Effect of a group music intervention on cognitive function and mental health outcomes among nursing home residents: a randomized controlled pilot study. Geriatr Nurs 2021;42(3):650-656. [CrossRef] [Medline]
  4. Lee KC, Tang WK, Bressington D. The experience of mindful yoga for older adults with depression. J Psychiatr Ment Health Nurs 2019 Apr;26(3-4):87-100. [CrossRef] [Medline]
  5. Choi M, Kong S, Jung D. Computer and internet interventions for loneliness and depression in older adults: a meta-analysis. Healthc Inform Res 2012 Sep;18(3):191-198 [FREE Full text] [CrossRef] [Medline]
  6. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th edition. Washington, DC, USA: American Psychiatric Publishing; May 27, 2013.
  7. Egeljić-Mihailović N, Brkić-Jovanović N, Krstić T, Simin D, Milutinović D. Social participation and depressive symptoms among older adults during the Covid-19 pandemic in Serbia: a cross-sectional study. Geriatr Nurs 2022;44:8-14 [FREE Full text] [CrossRef] [Medline]
  8. Siegmund LA, Distelhorst KS, Bena JF, Morrison SL. Relationships between physical activity, social isolation, and depression among older adults during COVID-19: a path analysis. Geriatr Nurs 2021;42(5):1240-1244 [FREE Full text] [CrossRef] [Medline]
  9. Charlton RA, Lamar M, Ajilore O, Kumar A. Preliminary analysis of age of illness onset effects on symptom profiles in major depressive disorder. Int J Geriatr Psychiatry 2013 Nov;28(11):1166-1174 [FREE Full text] [CrossRef] [Medline]
  10. Czaja SJ, Moxley JH, Rogers WA. Social support, isolation, loneliness, and health among older adults in the PRISM randomized controlled trial. Front Psychol 2021 Oct 05;12:728658 [FREE Full text] [CrossRef] [Medline]
  11. Kim C, Chang EJ, Kim CY. Regional differences in the effects of social relations on depression among Korean elderly and the moderating effect of living alone. J Prev Med Public Health 2021 Nov;54(6):441-450 [FREE Full text] [CrossRef] [Medline]
  12. Liu Y, Gellatly J. Barriers and facilitators of engagement in psychological therapies among older adults with depression: a systematic review and thematic synthesis. J Psychiatr Ment Health Nurs 2021 Aug;28(4):509-520. [CrossRef] [Medline]
  13. Apóstolo J, Bobrowicz-Campos E, Rodrigues M, Castro I, Cardoso D. The effectiveness of non-pharmacological interventions in older adults with depressive disorders: a systematic review. Int J Nurs Stud 2016 Jun;58:59-70. [CrossRef] [Medline]
  14. Irwin MR, Carrillo C, Sadeghi N, Bjurstrom MF, Breen EC, Olmstead R. Prevention of incident and recurrent major depression in older adults with insomnia: a randomized clinical trial. JAMA Psychiatry 2022 Jan 01;79(1):33-41 [FREE Full text] [CrossRef] [Medline]
  15. Kassel MT, Rhodes E, Insel PS, Woodworth K, Garrison-Diehn C, Satre DD, et al. Cognitive outcomes are differentially associated with depression severity trajectories during psychotherapy treatment for late life major depressive disorder. Int J Geriatr Psychiatry 2022 Aug;37(8):e5779. [CrossRef] [Medline]
  16. Holland JC, Weiss Wiesel T, Nelson CJ, Roth AJ, Alici Y. Geriatric Psycho-Oncology: A Quick Reference on the Psychosocial Dimensions of Cancer Symptom Management. Oxford, UK: Oxford University Press; Mar 03, 2015.
  17. Seiler A, Klaas V, Tröster G, Fagundes CP. eHealth and mHealth interventions in the treatment of fatigued cancer survivors: a systematic review and meta-analysis. Psychooncology 2017 Sep;26(9):1239-1253. [CrossRef] [Medline]
  18. Zhao P, Yoo I, Lancey R, Varghese E. Mobile applications for pain management: an app analysis for clinical usage. BMC Med Inform Decis Mak 2019 May 30;19(1):106 [FREE Full text] [CrossRef] [Medline]
  19. Harerimana B, Forchuk C, O'Regan T. The use of technology for mental healthcare delivery among older adults with depressive symptoms: a systematic literature review. Int J Ment Health Nurs 2019 Jun;28(3):657-670. [CrossRef] [Medline]
  20. Chen YR, Schulz PJ. The effect of information communication technology interventions on reducing social isolation in the elderly: a systematic review. J Med Internet Res 2016 Jan 28;18(1):e18 [FREE Full text] [CrossRef] [Medline]
  21. Bostrom J, Sweeney G, Whiteson J, Dodson JA. Mobile health and cardiac rehabilitation in older adults. Clin Cardiol 2020 Feb;43(2):118-126 [FREE Full text] [CrossRef] [Medline]
  22. Zaman SB, Khan RK, Evans RG, Thrift AG, Maddison R, Islam SM. Exploring barriers to and enablers of the adoption of information and communication technology for the care of older adults with chronic diseases: scoping review. JMIR Aging 2022 Jan 07;5(1):e25251 [FREE Full text] [CrossRef] [Medline]
  23. Eichenberg C, Schott M, Sawyer A, Aumayr G, Plößnig M. Feasibility and conceptualization of an e-Mental health treatment for depression in older adults: mixed-methods study. JMIR Aging 2018 Oct 23;1(2):e10973 [FREE Full text] [CrossRef] [Medline]
  24. Giunti G, Baum A, Giunta D, Plazzotta F, Benitez S, Gómez A, et al. Serious games: a concise overview on what they are and their potential applications to healthcare. Stud Health Technol Inform 2015;216:386-390. [CrossRef] [Medline]
  25. Vieira C, Ferreira da Silva Pais-Vieira C, Novais J, Perrotta A. Serious game design and clinical improvement in physical rehabilitation: systematic review. JMIR Serious Games 2021 Sep 23;9(3):e20066 [FREE Full text] [CrossRef] [Medline]
  26. Gillois P, Di Marco L, Nicolàs JM, Moreau-Gaudry A, Ego A, David-Tchouda S, et al. Biostatistics disruptive acculturation through serious gaming: a new hope. Stud Health Technol Inform 2020 Jun 16;270:1215-1216. [CrossRef] [Medline]
  27. Vinolo Gil MJ, Gonzalez-Medina G, Lucena-Anton D, Perez-Cabezas V, Ruiz-Molinero MD, Martín-Valero R. Augmented reality in physical therapy: systematic review and meta-analysis. JMIR Serious Games 2021 Dec 15;9(4):e30985 [FREE Full text] [CrossRef] [Medline]
  28. Masurovsky A. Controlling for placebo effects in computerized cognitive training studies with healthy older adults from 2016-2018: systematic review. JMIR Serious Games 2020 Jun 26;8(2):e14030 [FREE Full text] [CrossRef] [Medline]
  29. Yan M, Yin H, Meng Q, Wang S, Ding Y, Li G, et al. A virtual supermarket program for the screening of mild cognitive impairment in older adults: diagnostic accuracy study. JMIR Serious Games 2021 Dec 03;9(4):e30919 [FREE Full text] [CrossRef] [Medline]
  30. Luo Y, Li M, Tang J, Ren J, Zheng Y, Yu X, et al. Design of a virtual reality interactive training system for public health emergency preparedness for major emerging infectious diseases: theory and framework. JMIR Serious Games 2021 Dec 14;9(4):e29956 [FREE Full text] [CrossRef] [Medline]
  31. Abraham O, Rosenberger C, Tierney K, Birstler J. Investigating the use of a serious game to improve opioid safety awareness among adolescents: quantitative study. JMIR Serious Games 2021 Dec 23;9(4):e33975 [FREE Full text] [CrossRef] [Medline]
  32. Schakel L, Veldhuijzen DS, van Middendorp H, Prins C, Drittij AM, Vrieling F, et al. An internet-based psychological intervention with a serious game to improve vitality, psychological and physical condition, and immune function in healthy male adults: randomized controlled trial. J Med Internet Res 2020 Jul 24;22(7):e14861 [FREE Full text] [CrossRef] [Medline]
  33. Corregidor-Sánchez AI, Segura-Fragoso A, Rodríguez-Hernández M, Criado-Alvarez JJ, González-Gonzalez J, Polonio-López B. Can exergames contribute to improving walking capacity in older adults? A systematic review and meta-analysis. Maturitas 2020 Feb;132:40-48. [CrossRef] [Medline]
  34. Paliokas I, Kalamaras E, Votis K, Doumpoulakis S, Lakka E, Kotsani M, et al. Using a virtual reality serious game to assess the performance of older adults with frailty. Adv Exp Med Biol 2020;1196:127-139. [CrossRef] [Medline]
  35. Yang C, Han X, Jin M, Xu J, Wang Y, Zhang Y, et al. The effect of video game-based interventions on performance and cognitive function in older adults: Bayesian network meta-analysis. JMIR Serious Games 2021 Dec 30;9(4):e27058 [FREE Full text] [CrossRef] [Medline]
  36. Alhasan H, Alshehri MA, Wheeler PC, Fong DT. Effects of interactive videogames on postural control and risk of fall outcomes in frail and pre-frail older adults: a systematic review and meta-analysis. Games Health J 2021 Apr;10(2):83-94. [CrossRef] [Medline]
  37. Williams T, Kennedy-Malone L, Thompson J, Monge EC. The effect of an exergame on physical activity among older adults residing in a long-term care facility: a pilot study. Geriatr Nurs 2022;44:48-53. [CrossRef] [Medline]
  38. Zhu K, Zhang Q, He B, Huang M, Lin R, Li H. Immersive virtual reality-based cognitive intervention for the improvement of cognitive function, depression, and perceived stress in older adults with mild cognitive impairment and mild dementia: pilot pre-post study. JMIR Serious Games 2022 Feb 21;10(1):e32117 [FREE Full text] [CrossRef] [Medline]
  39. Beltran-Alacreu H, Navarro-Fernández G, Godia-Lledó D, Graell-Pasarón L, Ramos-González Á, Raya R, et al. A serious game for performing task-oriented cervical exercises among older adult patients with chronic neck pain: development, suitability, and crossover pilot study. JMIR Serious Games 2022 Feb 01;10(1):e31404 [FREE Full text] [CrossRef] [Medline]
  40. Merriman NA, Roudaia E, Ondřej J, Romagnoli M, Orvieto I, O'Sullivan C, et al. "CityQuest," a custom-designed serious game, enhances spatial memory performance in older adults. Front Aging Neurosci 2022 Mar 08;14:806418 [FREE Full text] [CrossRef] [Medline]
  41. Martinez K, Menéndez-Menéndez MI, Bustillo A. Awareness, prevention, detection, and therapy applications for depression and anxiety in serious games for children and adolescents: systematic review. JMIR Serious Games 2021 Dec 16;9(4):e30482 [FREE Full text] [CrossRef] [Medline]
  42. Novo A, Fonsêca J, Barroso B, Guimarães M, Louro A, Fernandes H, et al. Virtual reality rehabilitation's impact on negative symptoms and psychosocial rehabilitation in schizophrenia spectrum disorder: a systematic review. Healthcare (Basel) 2021 Oct 23;9(11):1429 [FREE Full text] [CrossRef] [Medline]
  43. Siriaraya P, Visch V, Boffo M, Spijkerman R, Wiers R, Korrelboom K, et al. Game design in mental health care: case study-based framework for integrating game design into therapeutic content. JMIR Serious Games 2021 Dec 01;9(4):e27953 [FREE Full text] [CrossRef] [Medline]
  44. Li J, Theng YL, Foo S. Effect of exergames on depression: a systematic review and meta-analysis. Cyberpsychol Behav Soc Netw 2016 Jan;19(1):34-42. [CrossRef] [Medline]
  45. Townsend C, Humpston C, Rogers J, Goodyear V, Lavis A, Michail M. The effectiveness of gaming interventions for depression and anxiety in young people: systematic review and meta-analysis. BJPsych Open 2022 Jan 07;8(1):e25 [FREE Full text] [CrossRef] [Medline]
  46. Cacciata M, Stromberg A, Lee JA, Sorkin D, Lombardo D, Clancy S, et al. Effect of exergaming on health-related quality of life in older adults: a systematic review. Int J Nurs Stud 2019 May;93:30-40 [FREE Full text] [CrossRef] [Medline]
  47. Chao YY, Scherer YK, Montgomery CA. Effects of using Nintendo Wii™ exergames in older adults: a review of the literature. J Aging Health 2015 Apr;27(3):379-402. [CrossRef] [Medline]
  48. Kappen DL, Mirza-Babaei P, Nacke LE. Older adults’ physical activity and exergames: a systematic review. Int J Human Comput Interact 2019;35(2):140-167. [CrossRef]
  49. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021 Mar 29;372:n71 [FREE Full text] [CrossRef] [Medline]
  50. Aromataris E, Munn Z. JBI Manual for Evidence Synthesis. Joanna Briggs Institute. 2020.   URL: [accessed 2021-07-06]
  51. Tiruneh GT, Yakob B, Ayele WM, Yigzaw M, Roro MA, Medhanyi AA, et al. Effect of community-based distribution of misoprostol on facility delivery: a scoping review. BMC Pregnancy Childbirth 2019 Nov 06;19(1):404 [FREE Full text] [CrossRef] [Medline]
  52. Higgins JP, Li T, Deeks JJ. Chapter 6: Choosing effect measures and computing estimates of effect. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al, editors. Cochrane Handbook for Systematic Reviews of Interventions. Version 6.3. London, UK: The Cochrane Collaboration; 2022.
  53. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 2014 Dec 19;14:135 [FREE Full text] [CrossRef] [Medline]
  54. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd edition. Hillsdale, NJ, USA: Lawrence Erlbaum Associates; 1988.
  55. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003 Sep 06;327(7414):557-560 [FREE Full text] [CrossRef] [Medline]
  56. Schoene D, Valenzuela T, Toson B, Delbaere K, Severino C, Garcia J, et al. Interactive cognitive-motor step training improves cognitive risk factors of falling in older adults - a randomized controlled trial. PLoS One 2015 Dec 16;10(12):e0145161 [FREE Full text] [CrossRef] [Medline]
  57. Anguera JA, Gunning FM, Areán PA. Improving late life depression and cognitive control through the use of therapeutic video game technology: a proof-of-concept randomized trial. Depress Anxiety 2017 Jun;34(6):508-517 [FREE Full text] [CrossRef] [Medline]
  58. Belchior P, Yam A, Thomas KR, Bavelier D, Ball KK, Mann WC, et al. Computer and videogame interventions for older adults' cognitive and everyday functioning. Games Health J 2019 Apr;8(2):129-143 [FREE Full text] [CrossRef] [Medline]
  59. Choi YH, Ku J, Lim H, Kim YH, Paik NJ. Mobile game-based virtual reality rehabilitation program for upper limb dysfunction after ischemic stroke. Restor Neurol Neurosci 2016 May 02;34(3):455-463. [CrossRef] [Medline]
  60. Rendon AA, Lohman EB, Thorpe D, Johnson EG, Medina E, Bradley B. The effect of virtual reality gaming on dynamic balance in older adults. Age Ageing 2012 Jul;41(4):549-552. [CrossRef] [Medline]
  61. Rica RL, Shimojo GL, Gomes MC, Alonso AC, Pitta RM, Santa-Rosa FA, et al. Effects of a Kinect-based physical training program on body composition, functional fitness and depression in institutionalized older adults. Geriatr Gerontol Int 2020 Mar;20(3):195-200. [CrossRef] [Medline]
  62. Smith M, Jones MP, Dotson MM, Wolinsky FD. Speed of processing training and depression in assisted and independent living: a randomized controlled trial. PLoS One 2019 Oct 17;14(10):e0223841 [FREE Full text] [CrossRef] [Medline]
  63. de Morais MA, de Lima BE, Bandeira Santos LC. Acute effect of Xbox exercise on mood states in older adults. Act Adapt Aging 2020;44(2):146-156. [CrossRef]
  64. Ferraz DD, Trippo KV, Duarte GP, Neto MG, Bernardes Santos KO, Filho JO. The effects of functional training, bicycle exercise, and exergaming on walking capacity of elderly patients with Parkinson disease: a pilot randomized controlled single-blinded trial. Arch Phys Med Rehabil 2018 May;99(5):826-833. [CrossRef] [Medline]
  65. Kang JM, Kim N, Lee SY, Woo SK, Park G, Yeon BK, et al. Effect of cognitive training in fully immersive virtual reality on visuospatial function and frontal-occipital functional connectivity in predementia: randomized controlled trial. J Med Internet Res 2021 May 06;23(5):e24526 [FREE Full text] [CrossRef] [Medline]
  66. Tollár J, Nagy F, Hortobágyi T. Vastly different exercise programs similarly improve Parkinsonian symptoms: a randomized clinical trial. Gerontology 2019;65(2):120-127. [CrossRef] [Medline]
  67. Tollár J, Nagy F, Moizs M, Tóth BE, Sanders LM, Hortobágyi T. Diverse exercises similarly reduce older adults' mobility limitations. Med Sci Sports Exerc 2019 Sep;51(9):1809-1816. [CrossRef] [Medline]
  68. Jahouh M, González-Bernal JJ, González-Santos J, Fernández-Lázaro D, Soto-Cámara R, Mielgo-Ayuso J. Impact of an intervention with Wii video games on the autonomy of activities of daily living and psychological-cognitive components in the institutionalized elderly. Int J Environ Res Public Health 2021 Feb 07;18(4):1570 [FREE Full text] [CrossRef] [Medline]
  69. Levy F, Leboucher P, Rautureau G, Komano O, Millet B, Jouvent R. Fear of falling: efficacy of virtual reality associated with serious games in elderly people. Neuropsychiatr Dis Treat 2016 Apr 15;12:877-881 [FREE Full text] [CrossRef] [Medline]
  70. Stanmore EK, Mavroeidi A, de Jong LD, Skelton DA, Sutton CJ, Benedetto V, et al. The effectiveness and cost-effectiveness of strength and balance Exergames to reduce falls risk for people aged 55 years and older in UK assisted living facilities: a multi-centre, cluster randomised controlled trial. BMC Med 2019 Feb 28;17(1):49 [FREE Full text] [CrossRef] [Medline]
  71. Swinnen N, Vandenbulcke M, de Bruin ED, Akkerman R, Stubbs B, Firth J, et al. The efficacy of exergaming in people with major neurocognitive disorder residing in long-term care facilities: a pilot randomized controlled trial. Alzheimers Res Ther 2021 Mar 30;13(1):70 [FREE Full text] [CrossRef] [Medline]
  72. Nouchi R, Saito T, Nouchi H, Kawashima R. Small acute benefits of 4 weeks processing speed training games on processing speed and inhibition performance and depressive mood in the healthy elderly people: evidence from a randomized control trial. Front Aging Neurosci 2016 Dec 23;8:302 [FREE Full text] [CrossRef] [Medline]
  73. Gitlow L. Technology use by older adults and barriers to using technology. Phys Occup Ther Geriatr 2014 Aug 12;32(3):271-280. [CrossRef]
  74. Li J, Theng YL, Foo S. Game-based digital interventions for depression therapy: a systematic review and meta-analysis. Cyberpsychol Behav Soc Netw 2014 Aug;17(8):519-527 [FREE Full text] [CrossRef] [Medline]
  75. Hill R, Betts LR, Gardner SE. Older adults’ experiences and perceptions of digital technology: (dis)empowerment, wellbeing, and inclusion. Comput Human Behav 2015 Jul;48:415-423. [CrossRef]
  76. de Boissieu P, Denormandie P, Armaingaud D, Sanchez S, Jeandel C. Exergames and elderly: a non-systematic review of the literature. Eur Geriatr Med 2017 Apr;8(2):111-116. [CrossRef]
  77. Ray S, Agarwal P. Depression and anxiety in Parkinson disease. Clin Geriatr Med 2020 Feb;36(1):93-104. [CrossRef] [Medline]
  78. Ma L. Depression, anxiety, and apathy in mild cognitive impairment: current perspectives. Front Aging Neurosci 2020 Jan 30;12:9 [FREE Full text] [CrossRef] [Medline]
  79. Kandola A, Ashdown-Franks G, Hendrikse J, Sabiston CM, Stubbs B. Physical activity and depression: towards understanding the antidepressant mechanisms of physical activity. Neurosci Biobehav Rev 2019 Dec;107:525-539. [CrossRef] [Medline]
  80. Schuch FB, Vancampfort D, Rosenbaum S, Richards J, Ward PB, Veronese N, et al. Exercise for depression in older adults: a meta-analysis of randomized controlled trials adjusting for publication bias. Braz J Psychiatry 2016;38(3):247-254 [FREE Full text] [CrossRef] [Medline]
  81. Zhang Q, Fu Y, Lu Y, Zhang Y, Huang Q, Yang Y, et al. Impact of virtual reality-based therapies on cognition and mental health of stroke patients: systematic review and meta-analysis. J Med Internet Res 2021 Nov 17;23(11):e31007 [FREE Full text] [CrossRef] [Medline]
  82. Karlsson P, Bergmark A. Compared with what? An analysis of control-group types in Cochrane and Campbell reviews of psychosocial treatment efficacy with substance use disorders. Addiction 2015 Mar;110(3):420-428 [FREE Full text] [CrossRef] [Medline]

CF: cognitive function
PA: physical activity
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
SMD: standardized mean difference

Edited by R Kukafka; submitted 07.03.22; peer-reviewed by YY Chao, D Sorkin; comments to author 28.03.22; revised version received 11.05.22; accepted 29.07.22; published 06.09.22


©Yesol Kim, Soomin Hong, Mona Choi. Originally published in the Journal of Medical Internet Research (, 06.09.2022.

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