The Efficacy of Playing Videogames Compared with Antidepressants in Reducing Treatment-Resistant Symptoms of Depression

Abstract

Objective:

The goal of this month-long controlled study was to compare the efficacy of a second antidepressant (sAD) medication with a prescribed regimen of Plants vs. Zombies™ (PvZ), a casual videogame, in reducing treatment-resistant depression symptoms (TRDS) and improving heart rate variability (HRV).

Materials and Methods:

Approximately ∼8 weeks after beginning antidepressant therapy, participants returned to psychiatrists for evaluation and complained of TRDS. The psychiatrist gave them a choice of self-selecting a sAD medication or playing a prescribed regimen of PvZ as part of a research study. Those who agreed were referred to researchers who then screened them for major depression, the criteria for inclusion. PvZ was prescribed four times per week for 30–45 minutes over 4 weeks. Self-reported data were collected at four different times utilizing the Patient Health Questionnaire-9. HRV, an indicator of autonomic nervous system (ANS) functioning, was also recorded each time.

Results:

The sAD group's TRDS significantly improved. Remarkably, the PvZ group's TRDS improved significantly beyond the control group at all measurement times except for time 1 or baseline. In addition, a single 30-minute session of playing PvZ was significantly more effective in acutely reducing TRDS when compared with the sAD group that surfed the NIHM website on depression. Changes in HRV parameters indicated increased parasympathetic engagement and ANS balance in the PvZ group compared with the sAD group.

Discussion:

The findings illustrate the potential of PvZ as an acute and chronic intervention for reducing TRDS. Health care practitioners such as physicians and recreational therapists can consider recommending a regimen of prescribed PvZ play as a method to ameliorate symptoms of depression for those clients who self-select this option. Finally, a psychophysiological method for measuring the efficacy of videogames in reducing TRDS and a means to quantify ANS changes during gameplay are presented.

The bow cannot always stand bent, nor can human frailty subsist without some lawful recreation.

Miguel de Cervantes

Spanish adventurer, author, & poet (1547–1616)

Introduction

According to the World Health Organization, the proportion of the global population with depression in 2015 was estimated to be 4.4%. Prevalence rates vary by age, peaking in older adulthood: above 7.5% among females aged 55–74 years and above 5.5% among males. The total number of people living with depression in the world is 322 million.¹ The National Institute of Mental Health approximates that 16.1 million adults or 6.7% of the U.S. population older than 18 years experienced a major depressive episode in 2015.² Depression carries the most onerous burden of mental illness affecting U.S. adjusted life years by 3.7% and years lived with a disability by 8.3%.³ Suicide is considered a risk of depression and affects 788, 000 or 1.5% of all deaths worldwide, bringing it into the top 20 leading causes of death in 2015.¹

The Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) defines major depression, also known as clinical depression, as a condition characterized by discrete episodes of at least 2 weeks of duration (although most episodes last considerably longer) involving five or more symptoms in the areas of: affect, diminished interest in activities or pleasure, cognition, concentration, fatigue, and other neurovegetative functions and inter-episode remissions.⁴ Typical treatments for depression vary and include monoamine oxidase inhibitor skin patches; tricyclics; selective serotonin reuptake inhibitors, fluoxetine (Prozac^®), sertraline (Zoloft^®), escitalopram (Lexapro^®), paroxetine (Paxil^®), and citalopram (Celexa^®); and serotonin–norepinephrine reuptake inhibitors, venlafaxine (Effexor^®) and duloxetine (Cymbalta^®). Sometimes depression symptoms are resistant to this first line of treatment and require a second medication such as lithium, an anticonvulsant, or an antipsychotic medication such as aripiprazole (Abilify^®) and quetiapine (Seroquel XR^®). These medications have different degrees of efficacy, and the side effects can be serious and range from anxiety and insomnia to sexual dysfunction and suicide.⁵

Research has provided evidence that various nonpharmacological interventions can ameliorate symptoms of depression with varying degrees of efficacy including some that compare with antidepressant medications. For example, cognitive behavior therapy has been shown to be efficacious with mild, moderate, and severe depression.⁶ In addition, popular recreational activities such as board and card games have been shown to decrease cortisol levels, improve mood, and reduce stress when compared with a matched control group of inpatient alcholics.⁷ In a 2006 online survey conducted by Information Solutions Group on behalf of PopCap Games, 2191 randomly selected respondents (1663 women or 88%) indicated that they experienced stress relief from playing casual videogames (CVGs) and 74% of all respondents cited mental exercise as a benefit, in addition to entertainment and distraction benefits.⁸ Results of a randomly assigned controlled study conducted in our laboratory tested this theory with “normal” participants and found that playing CVGs could significantly improve mood and decrease stress,⁹ with positive changes in electroencephalography and electrocardiography results supporting the psychological findings.¹⁰ In a follow-up randomized controlled clinical study, we found that playing a prescribed regimen of CVGs could significantly decrease depression symptoms when compared with a control group.¹¹ Subjective reports coupled with research citing CVG effectiveness in improving mood and reducing depression symptoms were the basis for further testing the efficacy of CVGs.

Purpose

The purpose of this controlled clinical study was to investigate if playing a prescribed regimen of Plants vs. Zombies™ (PvZ), a popular CVG, was as efficacious as a second antidepressant (sAD) in reducing treatment-resistant depression symptoms (TRDS).

Materials and Methods

Human subjects' approval was obtained before beginning the study, which was conducted between October 31, 2012, and August 13, 2014, in eastern North Carolina. All participants were actively taking a prescribed antidepressant and had expressed during follow-up evaluations that they were still experiencing troubling symptoms of depression. Psychiatrists informed them about the study and gave them a choice of a sAD or a prescribed regimen of PvZ.

CVG intervention

CVGs defy a standard definition because of their diverse nature. Instead, the Casual Games Association offers an operational definition that asserts that they must be “fun,” quick to access, easy to learn, and require no previous videogame skills, expertise, or regular time commitment to play.¹² Playing PvZ, a popular commercially available CVG, in a prescribed manner was the experimental treatment in this study.

PvZ is a “tower defense” type game with real-time strategy elements designed to be played on mobile phones, tablets, computers, smart TVs, and videogame consoles. The development goal was an accessible, approachable, welcoming, enticing, and fun game. PvZ is not immersive and hinges on a delicate balance between plants and zombies and the skills of the players. The game was built to increase the level of difficulty concurrently with the player's developing abilities. Each level takes an average of 5–15 minutes. Once the player masters one level, they move to the next level that increases in difficulty. For example, new zombies with different abilities as well as new plants with different abilities are introduced. The players feel that playing is enjoyable and new levels become harder than the previous level. The players feel that they can accomplish the task of protecting the home while continuing to develop skills. The game is enhanced by a range of engaging visuals, sounds, and animations throughout the game and at the end of each level. Positive feedback is given for achievement in terms of receiving badges, occasional praise, and unlocking additional game modes where access to a new plant is given. The challenge of warding off the zombies is given through virtual feedback on individual progress. The game facilitates a sense of control and accomplishment but does not intentionally seek health changes. When health changes are reported, however, they are noted and often reinforced by programmers.

Instruments

Quick Inventory of Depressive Symptomatology

The Quick Inventory of Depressive Symptomatology (QIDS) was the preferred screening instrument by referring psychiatrists due to its diagnostic sensitivity and representation of all depression criterion symptom domains. The QIDS total score ranges from 0 to 27 and consists of 16 items that rate the 9-criterion domain of depression: sleep disturbance, psychomotor disturbance, appetite/weight disturbance, mood, interest, energy, guilt, concentration, and suicidal ideation. Each question uses a Likert type scale of 0–3. The total score on the QIDS is representative of the individual's depression severity. For example, a score of 2 represents no symptoms, and a score of 22 signifies very severe symptoms of depression.¹³ Concurrent validity research has demonstrated high correlations between the QIDS and the 17-item (c = 0.81) and 21-item Hamilton Rating Scale for Depression (c = 0.82).¹⁴ Based on recommendations from referring psychiatrists, a QIDS score of >5 (mild depression) was used as the depression screening benchmark.

Patient Health Questionnaire-9

The study's main dependent variable was major depression with TRDS. To quantify changes in the severity of depression symptoms throughout the study, participants were asked to complete the Patient Health Questionnaire-9 (PHQ-9), a self-administered health questionnaire. The PHQ-9 was developed from the PRIME-MD diagnostic study that included 6000 patients from primary care clinics. Construct validity was established by comparing the PHQ-9 with other longer self-reports on depression, and self-reports of sick days and clinic visits.¹⁵ The PHQ-9 is a nine-item scale that has been widely used as a brief measure for depression severity in patient populations with different disorders.¹⁶ The PHQ-9 uses check marks in a Likert type scale and is interpreted as follows: 0–4: none; 5–9: mild depression; 10–14: moderate depression; 15–19: moderately severe depression; 20–27: severe depression. A PHQ-9 score of ≥10 had 91% sensitivity and 89% specificity for major depression and 78% sensitivity and 96% specificity for any depression diagnosis. Criterion validity was established by comparing results with over 500 mental health professional interviews.¹⁷ The PHQ-9 was chosen over the QIDS and other depression inventories for measuring changes in depression symptoms over time due to its validation as an outcome indicator when measuring changes in depression symptoms in patients taking antidepressants¹⁸ and studies indicating it overall generalizability.¹⁹

Heart rate variability

Heart rate variability (HRV) is measured by calculating the heart's inter-beat intervals providing mathematical data in terms of sympathetic and parasympathetic influence on the autonomic nervous system (ANS). In general, HRV is indicative of the power and balance between the sympathetic and parasympathetic branches of the ANS²⁰ and is considered a measurement of ANS functioning.²¹ Measurement algorithms based on the established standards by the North American Society of Pacing and Electrophysiology and European Society of Cardiology²⁰ allowed clinician researchers to correlate changes in HRV with physical and mental health conditions, including major depression. HRV activity in an individual with depression shows increased sympathetic nervous system (SNS) involvement and reduced parasympathetic nervous system (PNS) involvement. This results in an unbalanced system, which consequently leads to increased heart rate and multiple other negative physiological and psychological symptoms.^22,23 A depressed HRV is considered a trait marker in people with depression.²⁴

Increases in the standard deviation of the normal to normal heartbeat (SDNN), representative of the SNS influence on the heart, and root mean square of the successive differences (RMSSD), representative of the parasympathetic influence on the heart, were the primary HRV outcome variables used to determine the effects of PvZ and sADs on the ANS during the study. HRV was measured using photoplethysmography (PPG) or light measurement technology to calculate the heart rate. Biocom Technologies HRM-02 ear clip PPG sensor and “HRV Live” software and algorithms were used to collect and analyze the data.²⁵

Study participants

Participants were required to be at least 18 years of age and able to read and speak English. Nonqualifying participants were given a free CVG. Sixty-one participants consented to participate in the study and were then screened for depression using the QIDS. Twelve participants were excluded. A total of 61 participants were assessed for eligibility. Six (6) participants did not meet the inclusion criteria. Three (3) sAD participants and two (2) PvZ participants did not complete the study. One (1) sAD participant had an incomplete data set and was excluded from data analysis. A total of Forty-nine (49) participants (23 sAD and 26 PvZ) were included in the data analysis.²⁶ Forty-nine participants met the entrance criteria and completed all sessions and assessments representing a 10% attrition rate. Twenty-three participants self-selected the sAD group and 26 participants self-selected the PvZ group.²⁶ The sAD group participants reported playing videogames in the previous week as 12 (never played), 6 (1–4 hours of play), and 5 (>4 hours of play). The PvZ group participants reported playing videogames in the previous week as 11 (never played), 9 (1–4 hours of play), and 6 (>4 hours of play). Table 1 presents an overview of the participant characteristics.

Table 1.

Participant Demographics

Group	PvZ	sAD	Total
Age, mean ± SD, years	41 ± 13.3	45 ± 12.2
Gender
Male	5	4	9
Female	21	19	40
Ethnic origin
European American	25	15	40
African American	1	6	7
Other		2	2
Marital status
Married/widowed	13	7	22
Separated/divorced	3	8	11
Never married	6	10	16
Education level
Some college or less	13	7	20
College grad or more	10	19	29
Employment status
Part-time	5	5	10
Full-time	7	17	24
Other	11	4	15

sAD, second antidepressant; SD, standard deviation.

Procedures

Patients who self-selected the sAD group were prescribed an sAD at ∼8 weeks and, if interested, referred to the research study for screening and potential inclusion into the control group. The sAD participants were asked to refrain from playing CVGs for 1 month and continue their current prescribed two antidepressant medication regimens. Participants in the PvZ group were provided game instructions by a researcher who was present during the game sessions as well as during the sAD group's surfing of the NIMH website. The sAD group's comparison task did not involve a game, but the NIMH website provided valuable information on depression and ways to overcome symptoms. Visiting the site was also used to imitate physical functioning involved in computer use and was similar to gameplay. Participants completed self-reports and had HRV data collected while they sat in the same chair in the same room at the same computer. PVZ participants could play more than the minimum amount of prescribed gameplay and were asked to record the duration of each PvZ session. The PvZ group followed a game playing prescription that consisted of 30–45 minutes of gameplay four times per week with at least 24 hours between sessions for a total of 16 sessions over 1 month.

Data collection times

PHQ-9 and HRV data were collected at four different times. Data collection at time 1 or baseline was obtained before playing PvZ, and the sAD group began reading the NIMH website about depression. Data collected at time 3 collected 1 month after baseline were compared with time 1 or baseline to answer the study's main question as to whether PvZ was efficacious in reducing TRDS. The standard PHQ-9 guidelines were used at time 1 and time 3 and participants were asked to answer the question with the following in mind: “Over the last 2 weeks, how often have you been bothered by any of the following problems?” Data collected at time 2 were used to compare changes pre- and post-PvZ and NIMH website sessions to determine the impact of a single session. Administration guidelines of the PHQ-9 were changed at time 2 and time 4 asking the participant to answer the questions with the following in mind: “How do you feel ‘right now?”

Approximately 4 weeks later, the sAD and PvZ group participants returned to meet the researcher (time 3 and time 4). All participants were asked to complete PHQ-9 questionnaire using standard guidelines again (time 3) and had HRV data collected while playing PvZ or visiting the NIMH website for a second time (time 4). Participants were asked again to answer how they felt “right now.” Upon completing the study, participants received a free copy of PvZ and a $100 visa gift card for their participation.

Results

Participant log reports revealed that they played the prescribed PvZ game four times a week for a month with a minimum of 30.0 minutes and a maximum of 101 minutes. The average PvZ playing time was M = 41.3, standard deviation = 13.9 minutes per session over the 1-month period. Due to potential self-selection bias, a repeated-measures mixed linear model adjusted with QIDS as a covariate was used as a model for statistical analysis. Partial eta squared is a measure of effect size, small effects are reported at 0.02; medium effects at 0.13; and large effects at 0.26 was employed to determine the contribution of variables in the overall change. Table 2 presents the means for sAD and PvZ for the PHQ-9 at four different times.

Table 2.

sAD and PvZ means and Standard Error at 4 Different Times

Group	Time	Mean	SE	95% confidence interval
Group	Time	Mean	SE	Lower bound	Upper bound
sAD	1	12.791^a	0.759	11.263	14.319
	2	9.984^a	1.073	7.825	12.143
	3	9.960^a	1.095	7.756	12.165
	4	7.567^a	0.946	5.663	9.471
PvZ	1	11.339^a	0.707	9.917	12.761
	2	3.976^a	0.998	1.966	5.986
	3	6.112^a	1.020	4.060	8.164
	4	2.421^a	0.880	0.649	4.194

Covariates appearing in the model are evaluated at the following values: QIDS time 1 = 12.45.

SE, standard error; QIDS, Quick Inventory of Depressive Symptomatology.

Mauchly's test was not significant, W = .971₅, P = 0.935; therefore, sphericity was assumed. The overall group × time interaction was significant (F_3,44 = 2.9, P = 0.035, eta sq. = 0.060). Between-subject effects (F_1,46 = 15.7, P < 0.001, eta sq. = 0.254) were also significant. Because of these findings, further analyses were conducted to determine individual time comparisons between the groups. There were no significant interactions with age, gender, or race. Table 3 presents the univariate analysis between both groups at four different data collection times.

Table 3.

PvZ and Second Antidepressant Comparisons at Four Different Measurement Times

	sAD (n = 23)		PvZ (n = 26)
	M	SE	M	SE	MD	SS	F	P	eta
Time 1	12.8	0.8	11	0.7	1.5	18	1.7	0.202	0.04
Time 2	10	1	4	1	6	314	14.4	0.000^***	0.24
Time 3	10	1	6	1	3.8	129	5.7	0.022^*	0.11
Time 4	7.6	1	2	0.9	5.1	230	13.6	0.001^**	0.23

M, mean; MD, mean difference; SS, sum of the squares; F, test result; P, level of significance: ^*<0.05, ^** <0.01, and ^*** <0.001. Degrees of freedom for contrast = 1; error = 46. Covariates appearing in this model are evaluated at the following values: QIDS at time 1 = 12.45.

Time 3 data were recorded when participants returned after 1 month and were compared with the baseline measure or time 1 to answer the study's main question of whether playing a self-selected game of PvZ was comparable to sADs in reducing TRSD. Results at time 2 and time 4 were used to answer the question of whether PvZ play would produce a significant acute reduction in TRDS immediately after gameplay when compared with participants reading the NIMH website on depression. Results indicated that the sAD group experienced changes in TRDS between time 1 and time 2: mean difference (MD) = 2.8, standard error (SE) = 1.1, P = 0.012; time 1 and time 3: MD = 2.8, SE = 1.2, P = 0.021; time 1 and time 4: MD = 5.2, SE = 1.1, P < 0.001; time 2 and time 3: MD = −0.023, SE = 1.1, P = 0.98; time 2 and time 4: MD = 2.4, SE = 1.1, P = 0.036; and time 3 and time 4: MD = 2.4, SE = 1.1, P = 0.032. The PvZ group reported changes in TRDS between time 1 and time 2: MD = 7.4, SE = 1, P < 0.001; time 1 and time 3: MD = 5.2, SE = 1.1, P < 0.001; time 1 and time 4: MD = 8.9, SE = 1, P < 0.001; time 2 and time 3: MD = −2.1, SE = 1, P = 0.04; time 2 and time 4: MD = 1.6, SE = 1, P = 0.14; and time 3 and time 4: MD = 3.7, SE = 1, P = 0.001.

A generalized estimating equation (GEE) model was used to examine changes in PHQ-9 clinical categories (Table 4). The GEE found no significant interactions between group and time (Wald chi-square 3.6, degrees of freedom (DF) = 3, P = 0.312). There were, however, significant effects for time and group. The PvZ group's downward shift of symptoms was significantly greater than the sAD group (Wald chi-square = 32.5, DF = 1, P < 0.001). Results also indicated a significant downward shift over time in all categories (Wald chi-square 116.8, DF = 3, P < 0.001).

Table 4.

Shift in Patient Health Questionnaire-9 Clinical Categories Pre–post Study

		None	Mild	Moderate	Severe	Very severe
PvZ	Pre	0	13	10	3	0
PvZ	Post	16	8	1	1	0
sAD	Pre	0	4	6	9	4
sAD	Post	4	6	6	3	4

Heart rate variability

The last 5 minutes of HRV data were analyzed while participants were playing PvZ and the sAD group was surfing the NIMH website on depression. The analysis found that SDNN changes were not significant. The main effect of RMSSD was not significant. A between subjects' comparison of overall RMSSD scores approached statistical significance (F_1,46 = 3.8, P = 0.058, eta sq. = 0.079). RMSSD also approached statistical significance at time 2 (F_1,46 = 3.42, P = 0.071, eta sq. = 0.069) and time 4 (F_1,46 = 3.9, P = 0.054, eta sq. = 0.078). There was also a significant change in the LF/HF ratio at time 2 or after the first comparison between the sAD and PvZ groups, MD = −1.2, SE = 0.55, P = 0.032. There were no other significant HRV changes.

Discussion

The results of this controlled clinical trial suggests that PvZ is efficacious. Following standardized treatment for depression, the sAD group experienced significant drops in TRDS over the 1-month study period. Remarkably, the PvZ groups' TRDS significantly decreased beyond that of the sAD group indicating increased efficacy in the self-selection group. At the completion of the study, 16 PvZ participants did not qualify for clinical depression. Nine of the PvZ participants experiencing moderate TRDS and two with severe TRDS at baseline shifted to mild or no symptoms. In contrast, only four participants in the sAD group did not qualify for clinical depression, and seven were still reporting severe and very severe symptoms. Results also illustrated the significant short-term positive effects of PvZ on TRDS supporting its potential as an acute intervention. This is the second study where the same CVG prescription was used and found to be efficacious with symptoms of depression. Additional research is needed to replicate these findings further and refine the game prescription (frequency, duration, intensity) to produce the maximum sustained benefit in various populations that experience TRDS. It is unclear to whom the results may generalize other than patients with depression. However, these results will hopefully lead to more robust trials using CVGs like PvZ for this purpose. Future studies might also consider comparing the effects of different CVGs on TRDS as well as the effects of various other physical and mental health conditions.

Clinicians can use the parameters outlined in this study as a guideline for prescribing PvZ as a treatment intervention and to monitor client's symptoms at designated points determining whether changes in the prescription were needed to increase efficacy. For example, a clinician could increase the frequency of the intervention to 5, 6, or 7 days a week, adjusting the intensity by splitting up the treatment from 1 × 35–45 minutes per day to 2 × 15–20 minutes per day with one session in the morning and one in the evening, and/or increasing the duration to 2, 3, or 6 months to improve outcomes.

Nonadherence to medical treatments estimates are 50%, with 25% of this amount being intentional.²⁷ Adherence to in the PvZ intervention was outstanding with all PvZ players meeting or exceeding the prescribed duration of gameplay. This advantage over traditional treatments needs further research to determine the factors that contribute to this motivation to comply. There were no reports of negative or adverse effects in the PvZ group supporting the notion that the PvZ intervention was also safe. Interestingly, a few players went well beyond the prescribed time, but the reason is unknown. Is it possible that these individuals have a propensity for addiction or perhaps they just decided they needed more “treatment”? Self-selection and game prescription by a health care professional may have made significant contributions to the efficacy of PvZ and needs further exploration. Self-selection involves the participants taking some control of their treatment. What impact did this factor have on the results? Is it possible that when a clinician prescribes a CVG it adds credibility that, in turn, increases the efficacy of the intervention?

SDNN may not have significantly improved due to the activation of the SNS secondary to game-produced simulation and therefore may not have been a good measure of stress reduction during CVG play. Future studies may want to consider measuring biochemical changes such as cortisol or alpha amylase changes as an option. Positive changes in RMSSD pre- and post-PvZ single-session gameplay indicate an increase in the PNS activity during these periods. PNS withdrawal is viewed as a trait marker in people with depression,²⁸ and PNS engagement is associated with improvement of depression symptoms.^29,30 Increases in RMSSD, a measure of PNS, could serve as a marker to help explain reductions in symptoms and as an outcome measurement when studying the effects of videogame interventions on depression symptoms.

Conclusions

This study was the third phase of research investigating the potential therapeutic benefits of CVG gameplay. In phase 1, we found that CVGs could decrease stress and improve mood. In phase 2, we prescribed CVGs in a month-long randomized controlled study on depression symptoms and found a significant decrease in the CVG group compared with the control group. In this third phase of research, we compared a specific CVG, PvZ, with an sAD prescribed for TRDS. In all three studies, we found physiological and psychological changes consistent with improved clinical depression. While replication studies are needed to confirm the findings, we conclude that a self-selected prescribed regimen of PvZ is an efficacious intervention for TRDS.

Given 75% of people in the world who suffer from depression do not receive any treatments, it seems reasonable and prudent to consider prescribing PvZ as an alternate or complementary intervention. Prescribing PvZ as an individualized alternative treatment and possibly as a preventive measure should be considered. CVGs like PvZ are inexpensive and have no reported untoward effects. Although there is always the possibility a person could become addicted to PvZ, unlike first shooter and betting games that want the player to play to exhaustion or to when they are broke, PvZ is designed to make it easy to cease and resume play. PvZ and other CVGs are readily accessible in retail stores and downloadable on cell phones, computers, and other web-based devices, but the public is mostly unaware of their therapeutic benefits. Adding games like PvZ to websites on depression, including the NIMH website, will add credibility to this type of game playing and provide access to a therapeutic intervention for reducing TRDS for millions of people. Big data collected and analyzed by a team of gamers and health content experts has the potential to provide a new window into the study of the causes and effects of depression and possibly lead to other nonpharmacological treatments.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

This study was underwritten by PopCap Games. The sponsor had no input into the creation of the study, analysis of the data or preparation and submission of this manuscript.

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