Gaming Applied to the Promotion of Active Aging (GAMAPEA)

Active aging programs have been recommended by the World Health Organization to help deal with the progressive aging of the population. However, older adults have difficulties in accessing these programs. Online video game-based interventions would improve their accessibility, while complementing these interventions with a mobile application (App) would increase adherence and professional monitoring. The main objective of this study is to assess the efficacy of an interactive, online, video game-based cognitive behavioral intervention with an App companion for active aging compared to a control group receiving therapeutically inactive information. The secondary objectives are to: (a) analyze the moderators of the change in the outcome variables and (b) evaluate adherence to the intervention.

A randomized controlled trial will be performed including healthy adults older than 44. Recruitment of 180 participants is planned, with random allocation to one of the two conditions (90 participants per group): (a) an experimental group receiving an interactive, online, multimedia, video game-based cognitive behavioral intervention with an App companion (CCI-V) or (b) a control group receiving online therapeutically inactive information about active aging (CG).

The intervention will be administered in 8 weekly modules comprised of 45-minute sessions. A blind evaluation will be conducted through online self-administered tests at baseline, post-intervention, and 6- and 12-month follow-up. The primary outcome will be the health status. Secondary outcomes will be emotional well-being, symptoms of depression, reinforcement, negative thoughts, self-reported memory, cognitive tasks, sleep hygiene, physical activity, eating habits, body mass index (BMI), social support, dropouts, treatment adherence, and satisfaction with the intervention.

Study Overview

• Status: Completed
• Conditions: Aging; Aging Problems
• Intervention / Treatment: Other: Control group; Behavioral: Video game-based intervention

Detailed Description

European population aging has increased in the last several decades: 19.1% of Europeans are currently older than 65, and 39.2% are over 50. Depression and dementia are some of the most prevalent conditions in older adults, and both have high socioeconomic costs. In this context, the World Health Organization has pointed out the importance of active aging promotion programs to help older adults maintain their independence and health for longer. In addition, healthy life habits such as physical activity and eating a balanced diet also help prevent disease and preserve mental and physical functions.

However, the lack of health care services for older adults, especially in rural areas which tend to have more older people, may limit access to active aging programs targeting depression, cognitive decline, and healthy habits. One way to overcome these barriers is through online video games that are accessible at home at any time with a low cost. However, the efficacy of video games in promoting active aging from middle to late adulthood has received very little attention in the literature.

A meta-analysis of 21 randomized controlled trials about video game-based interventions administered to healthy adults over 44 found that video game-based interventions produced positive effects on negative affect, objectively measured physical and social health with small effect sizes. However, the reviewed studies used non-standardized measures, and follow-ups were scarce. There was only one video game designed to prevent depression in older people. Furthermore, none of the reviewed studies involved integral interventions for emotional wellbeing, cognitive stimulation, or healthy life habits, even though a review of modifiable risk factors for dementia estimated that 51% of population-attributable risk was associated with cognitive inactivity, depression, physical inactivity, and obesity; and these midlife risk factors could be tackled early to prevent or delay the onset of dementia.

This study will assess the efficacy of an interactive, online, video game-based cognitive behavioral intervention to promote active aging from an integral health perspective, targeting emotional well-being, cognition, healthy life habits (sleep hygiene, physical activity, and eating habits), and social support.

Randomization will occur after screening and baseline assessments. An independent researcher (allocation concealment) will make allocation cards using computer-generated random numbers. He will keep the original random allocation sequences in an inaccessible location and will work with a copy. The randomization sequence will be communicated to the researchers in sealed numbered envelopes, one for each participant, with instructions to use them in numerical order.

Sample size calculation: We estimate that a sample size of 78 participants per group will be required, based on a previous meta-analysis of video game-based interventions for active aging reported effect sizes for mood and objectively measured physical health of 0.26 and 0.34, respectively, and another meta-analysis of video games for training cognition in older adults reported an effect size of 0.37, and assuming 80% power at a 0.05 (two-tailed) significance level and a mean of 8% attrition. To safeguard against an estimated 12% to 15% loss to follow-up, a minimum of 180 participants (90 in each group) must be recruited.

Ethics: Ethics approval has been obtained from the Bioethics Committee of the University of Santiago de Compostela (Spain), and the project complies with the Declaration of Helsinki. The confidentiality of all participants will be guaranteed. Participants will have to give their informed consent, which has been approved by the Bioethics Committee of the University of Santiago de Compostela (Spain).

• Study Type: Interventional
• Enrollment (Actual): 180
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Spain
  • A Coruña
    • Santiago De Compostela, A Coruña, Spain, 15782
      • Research Group on Mental Health and Psychopatology

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 45 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• adult older than 44 years old living in the Region of Galicia (Spain)
• accessibility to a personal computer and a smartphone with internet connection
• informed consent to participate in the study
• commitment to conduct the program and complete subsequent evaluations

Exclusion Criteria:

• serious neurological or mental disorder (depressive disorder, schizophrenia, bipolar disorder, major neurocognitive disorder, dissociative disorders, substance abuse and/or dependence)
• physical or psychological problems that prevent study implementation (e.g., severe auditory and/or visual loss)
• recent psychological or psychiatric treatment (in the past 2 months)
• participation in another trial

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Video game-based intervention; The participants in the experimental group will receive a cognitive-behavioral intervention for active aging via an interactive online multimedia video game with a complementary App. The intervention will consist of 8 modules each approximately 45 minutes long that will be administered at a rate of 1 per week with between-session homework.	Behavioral: Video game-based intervention; The intervention will be administered via an online graphic-adventure video game. It includes 3 components: depression prevention, cognitive stimulation, and healthy habits promotion. The depression prevention component will be adapted from an indicated depression prevention program based on the model by Lewinsohn, Hoberman, Teri, & Hautzinger, which is effective in short and long terms. The cognitive stimulation component is based on cognitive reserve and cerebral neuroplasticity. The healthy habits promotion component is based on the social learning and social cognitive theories. The App will allow participants to expand information, check progression, and receive reminders about homework
Active Comparator: Control group; Individuals assigned to this group will receive online therapeutically inactive information about active aging.	Other: Control group; The active control group will have access to a platform of online therapeutically inactive information related to active aging.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from baseline Health Status to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Health status will be measured with the 36-Item Short-Form Health Survey [SF-36]. This is a self-administered measure that assesses perceived health status. It contains 36 items that form 8 dimensions: General health, Physical functioning, Physical role functioning, Bodily pain, Vitality, Social functioning, Emotional role functioning, and Mental health. The 8 dimensions are obtained by recalibrating scores for 10 items, computing raw scales, and transforming them to a 0-100 scale. Dimension scores range from 0 to 100, with higher scores indicating better health status. Their internal consistencies (Cronbach's alphas) range from .71 to .94. These dimensions can be combined in two factors (Physical health and Mental health) with an average of 50 and a standard deviation of 10, and internal consistencies of .94 and .89, respectively.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from baseline Emotional distress to post-treatment (9 weeks), and follow-ups at 6 and 12 months	This will be measured with the General Health Questionnaire [GHQ-12]. This self-administered questionnaire consists of 12 items and assesses emotional distress. The person evaluates each item based on their emotional distress using a Likert scale with four response options ranging from "better than usual" to "much worse than usual," which are scored using a bimodal response scale (0, 0, 1, 1). The total score ranges from 0 to 12, with higher scores indicating greater emotional distress. The internal consistency (Cronbach's alpha) is .86 for people under 65 and .90 for people 65 and older.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Depressive symptomatology to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Depressive symptoms as measured by the Center for Epidemiological Studies Depression Scale [CES-D]. This 20-item scale is self-administered and assesses depressive symptoms. The person evaluates each item based on how often they have experienced it in the last week using a Likert scale with four response options ranging from 0 (rarely or none of the time) to 3 (most of the time). The total score ranges from 0 to 60, where higher scores correspond to greater depressive symptomatology. Internal consistency (Cronbach's alpha) of the scale is .89.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Reinforcement to post-treatment (9 weeks), and follow-ups at 6 and 12 months	To evaluate the reinforcement, we will use the Environmental Reward Observation Scale [EROS]. It is a self-administered 10-item scale that assesses the degree of positive reinforcement contingent on the response received from the media. Each item is evaluated based on the degree to which the individual believes applies to them, according to a Likert scale with four response options ranging from 1 (strongly disagree) to 4 (strongly agree). The total score ranges from 10 to 40, with higher scores indicating more positive reinforcement. The internal consistency (Cronbach's alpha) of the Spanish version is .86.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Negative automatic thoughts to post-treatment (9 weeks), and follow-ups at 6 and 12 months	The occurrence of automatic negative thoughts will be assessed through the Automatic Thoughts Questionnaire [ATQ]. This is a 30-item self-report questionnaire that assesses negative thoughts. The subject must indicate the frequency for which a number of thoughts have suddenly arisen in their mind over the last week on a five-point scale from 1 (never) to 5 (always). Scores range between 30 and 150, with a higher score indicating more negative thoughts experienced by the subject. The ATQ's internal consistency (Cronbach's alpha) is .96.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Self-reported memory to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Self-reported memory will be measured with the Multifactorial Memory Questionnaire [MMQ]. This 57-item self-administered test assesses subjective memory. Items are rated on a 5-point Likert scale based on the test taker's experiences over the previous two weeks. It comprises three dimensions: Contentment, Ability, and Strategy. Contentment measures satisfaction, concern, and overall appraisal of one's own memory; the score ranges from 0 to 72, with higher scores indicating greater satisfaction. The internal consistency is .95. Ability measures self-perception of everyday memory ability; the score range is 0 to 80, with higher scores indicating better self-reported memory ability, with an internal consistency of .93. Strategy measures the use of practical memory strategies in day-to-day life; the score range is 0 to 76, with higher scores indicating greater use of memory strategies. The internal consistency is .83.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Cognitive tasks	The number of cognitive tasks completed during the video game will be counted and registered.	During the intervention sessions (8 weeks)
Change from baseline Sleep hygiene behaviors to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Participants' sleep hygiene behaviors will be assessed with the Sleep Hygiene Index [SHI]. It is a 13-item self-report measure designed to assess the practice of sleep hygiene behaviors. Each item is rated on a five-point scale ranging from 0 (never) to 4 (always). The total score ranges from 0 to 52, with a higher score representing poorer sleep hygiene. Its internal consistency (Cronbach's alpha) is .66.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Physical Activity to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Participants' physical activity will be assessed with the Brief Physical Activity Assessment Tool [BPAAT]. This two-item questionnaire measures the frequency and duration of moderate and vigorous physical activity in an individual's usual week. Combining the results of both questions, scores can range from 0 to 8, with a higher score indicating higher physical activity. In addition, the subject can be classified as sufficiently (≥4 score) or insufficiently active (0-3 score). The questionnaire has good test-retest reliability and content validity.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Eating habits to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Eating habits will be assessed with the Rapid Eating and Activity Assessment for Participants-Shortened Version [REAP-S]. This 16-item scale assesses the consumption of different food groups. The total score ranges from 13 to 39, with a higher score representing better eating habits. This instrument has shown good convergent validity with the Block Semi Quantitative Food Frequency Questionnaire and is based on the Dietary Guidelines of the U.S. Department of Health and Human Services (Office of Disease Prevention and Health Promotion) and the Healthy People 2010 objectives.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Body Mass Index to post-treatment (9 weeks), and follow-ups at 6 and 12 months	The Body Mass Index (BMI) is a measure of nutritional status in adults. It is defined as an individual's weight in kilograms divided by the square of the height in meters (kg/m2) and classifies nutritional status as underweight, normal weight, pre-obesity, and obesity (I, II, and III).	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Change from baseline Social support to post-treatment (9 weeks), and follow-ups at 6 and 12 months	Social support will be assessed with the Duke-UNC Functional Social Support Questionnaire [Duke-UNC-11]. This self-report 11-item test assesses perceived social support. Each item is rated on a 5-point scale ranging from 1 (never) to 5 (always). The total score ranges from 11 to 55, with a higher score representing more social support. Its internal consistency (Cronbach's alpha) is .90.	Pre- and post-intervention (9 weeks) with follow-ups at 6 and 12 months
Drop outs and treatment adherence	Dropouts and treatment adherence will be assessed through frequency, duration playing the videogame and between-session homework accomplishment. It will be automatically registered and monitored through the online platform and the App companion.	During the intervention sessions (8 weeks)
Satisfaction with the service received	Participant satisfaction with the service received will be evaluated upon intervention completion. We will use the Client Satisfaction Questionnaire [CSQ-8]. It is a 8-item scale with 4 possible answers and a final ranking score ranging from 8 to 32, where a higher score implies greater satisfaction with the service received. It has an internal consistency of .80.	Post-intervention (9 weeks)

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Socio-demographic characteristics	Sociodemographic characteristics will be collected through a questionnaire elaborated ad hoc for this study. Participant data will include sex, age, marital status, family monthly income per household, level of education, and main occupation.	Pre-intervention
Cognitive function	Cognitive function will be assessed with the Mini-mental State Examination [MMSE]. This 30-item instrument is used extensively in clinical and research settings to measure cognitive impairment. It has norms adjusted for age and education, good reliability values, and a sensitivity of 89.8% and specificity of 75.1%.	Screening
Diagnostic Interview	For the diagnostic interview, the Mini International Neuropsychiatric Interview [M.I.N.I.] will be used. This diagnostic interview explores the main mental disorders of Axis I of the Diagnostic and Statistical Manual (DSM-IV) or International Classification Diseases (ICD-10) and must be applied by a clinician. It has adequate validity and reliability.	Screening

Collaborators and Investigators

• Sponsor: University of Santiago de Compostela
• Collaborators: European Regional Development Fund; Center for Industrial Technological Development of Spain
• Investigators: Principal Investigator: Fernando L. Vázquez González, PhD, University of Santiago de Compostela

Publications and helpful links

General Publications

• Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plann. 1979;2(3):197-207. doi: 10.1016/0149-7189(79)90094-6. No abstract available.
• Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992 Jun;30(6):473-83.
• Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. doi: 10.1016/0022-3956(75)90026-6. No abstract available.
• Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 34-57.
• Vilagut G, Valderas JM, Ferrer M, Garin O, Lopez-Garcia E, Alonso J. [Interpretation of SF-36 and SF-12 questionnaires in Spain: physical and mental components]. Med Clin (Barc). 2008 May 24;130(19):726-35. doi: 10.1157/13121076. Spanish.
• Alonso J, Prieto L, Anto JM. [The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results]. Med Clin (Barc). 1995 May 27;104(20):771-6. Spanish.
• Vazquez FL, Blanco V, Lopez M. An adaptation of the Center for Epidemiologic Studies Depression Scale for use in non-psychiatric Spanish populations. Psychiatry Res. 2007 Jan 15;149(1-3):247-52. doi: 10.1016/j.psychres.2006.03.004. Epub 2006 Dec 1.
• Vazquez FL, Torres A, Blanco V, Otero P, Diaz O, Ferraces MJ. Long-term Follow-up of a Randomized Clinical Trial Assessing the Efficacy of a Brief Cognitive-Behavioral Depression Prevention Intervention for Caregivers with Elevated Depressive Symptoms. Am J Geriatr Psychiatry. 2016 Jun;24(6):421-32. doi: 10.1016/j.jagp.2016.02.050. Epub 2016 Feb 27.
• mhGAP Intervention Guide for Mental, Neurological and Substance Use Disorders in Non-Specialized Health Settings: Mental Health Gap Action Programme (mhGAP): Version 2.0. Geneva: World Health Organization; 2016. Available from http://www.ncbi.nlm.nih.gov/books/NBK390828/
• Bellon Saameno JA, Delgado Sanchez A, Luna del Castillo JD, Lardelli Claret P. [Validity and reliability of the Duke-UNC-11 questionnaire of functional social support]. Aten Primaria. 1996 Sep 15;18(4):153-6, 158-63. Spanish.
• Barnes DE, Yaffe K. The projected effect of risk factor reduction on Alzheimer's disease prevalence. Lancet Neurol. 2011 Sep;10(9):819-28. doi: 10.1016/S1474-4422(11)70072-2. Epub 2011 Jul 19.
• Troyer AK, Rich JB. Psychometric properties of a new metamemory questionnaire for older adults. J Gerontol B Psychol Sci Soc Sci. 2002 Jan;57(1):P19-27. doi: 10.1093/geronb/57.1.p19.
• Lobo A, Saz P, Marcos G, Dia JL, de la Camara C, Ventura T, Morales Asin F, Fernando Pascual L, Montanes JA, Aznar S. [Revalidation and standardization of the cognition mini-exam (first Spanish version of the Mini-Mental Status Examination) in the general geriatric population]. Med Clin (Barc). 1999 Jun 5;112(20):767-74. Erratum In: Med Clin (Barc) 1999 Jul 10;113(5):197. Spanish.
• Segal-Isaacson CJ, Wylie-Rosett J, Gans KM. Validation of a short dietary assessment questionnaire: the Rapid Eating and Activity Assessment for Participants short version (REAP-S). Diabetes Educ. 2004 Sep-Oct;30(5):774, 776, 778 passim. doi: 10.1177/014572170403000512. No abstract available.
• Armento ME, Hopko DR. The Environmental Reward Observation Scale (EROS): development, validity, and reliability. Behav Ther. 2007 Jun;38(2):107-19. doi: 10.1016/j.beth.2006.05.003. Epub 2006 Dec 12.
• Farre M, Haro JM, Kostov B, Alvira C, Risco E, Miguel S, Cabrera E, Zabalegui A. Direct and indirect costs and resource use in dementia care: A cross-sectional study in patients living at home. Int J Nurs Stud. 2016 Mar;55:39-49. doi: 10.1016/j.ijnurstu.2015.10.012. Epub 2015 Nov 19.
• Orrell M, Yates LA, Burns A, Russell I, Woods RT, Hoare Z, Moniz-Cook E, Henderson C, Knapp M, Spector A, Orgeta V. Individual Cognitive Stimulation Therapy for dementia (iCST): study protocol for a randomized controlled trial. Trials. 2012 Sep 22;13:172. doi: 10.1186/1745-6215-13-172.
• Ballesteros S, Prieto A, Mayas J, Toril P, Pita C, Ponce de Leon L, Reales JM, Waterworth J. Brain training with non-action video games enhances aspects of cognition in older adults: a randomized controlled trial. Front Aging Neurosci. 2014 Oct 14;6:277. doi: 10.3389/fnagi.2014.00277. eCollection 2014. Erratum In: Front Aging Neurosci. 2015;7:82.
• Bandura A. Social foundations of thought and action: A social cognitive theory: Englewood Cliffs, NJ, US: Prentice-Hall, Inc; 1986.
• Barraca J, Pérez-Álvarez M. Adaptación española del Environmental Reward Observation Scale (EROS) [Spanish adaptation of the Environmental Reward Observation Scale (EROS)]. Ansiedad Estrés 16:95-107, 2010.
• Bertolini P, Pisano E, Sivini S, Scaramuzzi S. Poverty and social exclusion in rural areas: European Commission. Directorate-General for Employment, Social Affairs and Equal Opportunities; 2008.
• Block G. Invited commentary: comparison of the Block and the Willett food frequency questionnaires. Am J Epidemiol. 1998 Dec 15;148(12):1160-1; discussion 1162-5. doi: 10.1093/oxfordjournals.aje.a009601. No abstract available.
• Broadhead WE, Gehlbach SH, de Gruy FV, Kaplan BH. The Duke-UNC Functional Social Support Questionnaire. Measurement of social support in family medicine patients. Med Care. 1988 Jul;26(7):709-23. doi: 10.1097/00005650-198807000-00006.
• Buitenweg JIV, van de Ven RM, Prinssen S, Murre JMJ, Ridderinkhof KR. Cognitive Flexibility Training: A Large-Scale Multimodal Adaptive Active-Control Intervention Study in Healthy Older Adults. Front Hum Neurosci. 2017 Nov 1;11:529. doi: 10.3389/fnhum.2017.00529. eCollection 2017.
• DeSmet A, Van Ryckeghem D, Compernolle S, Baranowski T, Thompson D, Crombez G, Poels K, Van Lippevelde W, Bastiaensens S, Van Cleemput K, Vandebosch H, De Bourdeaudhuij I. A meta-analysis of serious digital games for healthy lifestyle promotion. Prev Med. 2014 Dec;69:95-107. doi: 10.1016/j.ypmed.2014.08.026. Epub 2014 Aug 27.
• Eurostat. European Commission. Rural development statistics by urban-rural typology: Eurostat 2013. Report No.: 9282869342. Available from http://ec.europa.eu/eurostat/statistics-explained/index.php/Rural_development_statistics_by_urban-rural_typology [Accessed 5 August 2018]
• Eurostat. Population data 2017. 2017. Available from: http://ec.europa.eu/eurostat/data/database?node_code=proj. [Accessed on 3rd August 2017];
• Ferrando L, Bobes J, Gibert J, Soto M, Soto O. MINI. Entrevista Neuropsiquiátrica Internacional. Versión en Español 5.0. [MINI. International Neuropsychiatric Interview. Spanish version 5.0] Madrid: Instituto IAP; 2000.
• Goldberg D, Williams P. A user's guide to the General Health questionnaire. Windsor, UK: NFER-Nelson. 1988.
• Hollon SD, Kendall PC. Cognitive self-statements in depression: development of an Automatic Thoughts Questionnaire. Cognit Ther Res 4:383-95, 1980.
• Lewinsohn PM, Hoberman H, Teri L, Hautzinger M. An integrative theory of depression. In: Reiss S, Bootzin RR, editors. Theoretical issues in behaviour therapy New York: Academic Press; 1985. p. 331-59.
• Li J, Theng YL, Foo S. Exergames for Older Adults with Subthreshold Depression: Does Higher Playfulness Lead to Better Improvement in Depression? Games Health J. 2016 Jun;5(3):175-82. doi: 10.1089/g4h.2015.0100. Epub 2016 May 2.
• Marshall AL, Smith BJ, Bauman AE, Kaur S. Reliability and validity of a brief physical activity assessment for use by family doctors. Br J Sports Med. 2005 May;39(5):294-7; discussion 294-7. doi: 10.1136/bjsm.2004.013771.
• Mastin DF, Bryson J, Corwyn R. Assessment of sleep hygiene using the Sleep Hygiene Index. J Behav Med. 2006 Jun;29(3):223-7. doi: 10.1007/s10865-006-9047-6. Epub 2006 Mar 24.
• Office of Disease Prevention and Health Promotion. Dietary guidelines for Americans. Available from: http://www.health.gov/dietaryguidelines. [Accessed on 3rd August 2017]
• Otero P, Vázquez FL, Blanco V, Torres A. Propiedades psicométricas del Cuestionario de Pensamientos Automáticos (ATQ) en cuidadores familiares [Psychometric properties of the Automatic Thoughts Questionnaire (ATQ) in family caregivers]. Behav Psychol. 25, 387-403, 2017.
• Puig Ribera A, Pena Chimenis O, Romaguera Bosch M, Duran Bellido E, Heras Tebar A, Sola Gonfaus M, Sarmiento Cruz M, Cid Cantarero A. [How to identify physical inactivity in primary care: validation of the Catalan and Spanish versions of 2 short questionnaires]. Aten Primaria. 2012 Aug;44(8):485-93. doi: 10.1016/j.aprim.2012.01.005. Epub 2012 Mar 29. Spanish.
• Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Applied psychological measurement. 1977; 1:385-401
• Rocha KB, Pérez K, Rodríguez-Sanz M, Borrell C, Obiols JE. Propiedades psicométricas y valores normativos del General Health Questionnaire (GHQ-12) en población general española [Psychometric properties and normative values of the General Health Quationnnaire (GHQ-12) for Spanish population]. International Journal of Clinical and Health Psychology. 11(1), 125-139, 2011.
• Shapiro M. Plasticity, hippocampal place cells, and cognitive maps. Arch Neurol. 2001 Jun;58(6):874-81. doi: 10.1001/archneur.58.6.874.
• Sheehan DV, Lecrubier Y, Harnett-Sheehan K, Janavs J,Weiller E, Keskiner A, Schinka J, Knapp E, Sheehan MF, Dunbar GC. VThe validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. Eur Psychiatry 12 (5):232-241, 1997.
• Sobocki P, Jonsson B, Angst J, Rehnberg C. Cost of depression in Europe. J Ment Health Policy Econ. 2006 Jun;9(2):87-98.
• Toril P, Reales JM, Ballesteros S. Video game training enhances cognition of older adults: a meta-analytic study. Psychol Aging. 2014 Sep;29(3):706-16. doi: 10.1037/a0037507.
• Tucker AM, Stern Y. Cognitive reserve in aging. Curr Alzheimer Res. 2011 Jun;8(4):354-60. doi: 10.2174/156720511795745320.
• US Department of Health and Human Services: Healthy People 2010. http://www/health/gov/healthypeople/. 2000. [Accessed on 3rd August 2018]
• Vázquez FL, Hermida E, Torres A, Otero P, Blanco V, Diaz O. Efficacy of a brief cognitive-behavioral intervention in caregivers with high depressive symptoms. Behavioral Psychology 22(1): 79-96, 2014.
• Vazquez FL, Otero P, Garcia-Casal JA, Blanco V, Torres AJ, Arrojo M. Efficacy of video game-based interventions for active aging. A systematic literature review and meta-analysis. PLoS One. 2018 Dec 11;13(12):e0208192. doi: 10.1371/journal.pone.0208192. eCollection 2018.
• Vázquez FL, Torres Á, Otero P, Blanco V, Attkisson CC. Psychometric Properties of the Castilian Spanish Version of the Client Satisfaction Questionnaire (CSQ-8). Current Psychology 1(1): 1-7, 2017.
• Vazquez FL, Torres A, Otero P, Blanco V, Diaz O, Estevez LE. Analysis of the components of a cognitive-behavioral intervention administered via conference call for preventing depression among non-professional caregivers: a pilot study. Aging Ment Health. 2017 Sep;21(9):938-946. doi: 10.1080/13607863.2016.1181714. Epub 2016 May 17.
• World Health Organization. Mental health and older adults. 2017. Available from: http://www.who.int/mediacentre/factsheets/fs381/en/. [Accessed 20th June 2017]
• World Health Organization: Body Mass Index (BMI). 2018 Available from http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmi [Accessed 5 August 2018].
• Otero P, Cotardo T, Blanco V, Vazquez FL. Development of a Videogame for the Promotion of Active Aging Through Depression Prevention, Healthy Lifestyle Habits, and Cognitive Stimulation for Middle-to-Older Aged Adults. Games Health J. 2021 Aug;10(4):264-274. doi: 10.1089/g4h.2020.0165. Epub 2021 Jul 20.
• Vazquez FL, Torres AJ, Otero P, Blanco V, Lopez L, Garcia-Casal A, Arrojo M. Cognitive-behavioral intervention via interactive multimedia online video game for active aging: study protocol for a randomized controlled trial. Trials. 2019 Dec 9;20(1):692. doi: 10.1186/s13063-019-3859-5.

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2018
• Primary Completion (Actual): March 31, 2019
• Study Completion (Actual): December 31, 2019

Study Registration Dates

• First Submitted: August 5, 2018
• First Submitted That Met QC Criteria: August 20, 2018
• First Posted (Actual): August 22, 2018

Study Record Updates

• Last Update Posted (Actual): March 24, 2020
• Last Update Submitted That Met QC Criteria: March 23, 2020
• Last Verified: March 1, 2020

More Information

Terms related to this study

• Keywords: older adults; health promotion; video game; study protocol; active aging
• Other Study ID Numbers: EXP - 00091195 / ITC-20161137

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Researchers will report study results through publications. The data supporting these findings will be presented in the main publications, and the datasets used during the study can be obtained from the corresponding author on reasonable request.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No