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- Ensayo clínico NCT03253406
Health Wearables and College Student Health
Use of Health Wearables to Improve Physical Activity and Eating Behaviors Among College Students: A 12-week Randomized Pilot Study
Descripción general del estudio
Estado
Intervención / Tratamiento
Descripción detallada
The prevalence of overweight and obesity among individuals 20-39 years of age is 60.9%. Unfortunately, physical inactivity and poor dietary practices among this age cohort appear to be two major contributory factors for the preceding statistic. Among the youngest individuals within this age cohort are college students. Research suggests college students possess risk factors for overweight and obesity as many of these individuals are now independent and, for some, making physical activity- and nutrition-related decisions autonomously for the first time. Studies on obesity- and weight-related behaviors in this population suggest approximately 25% to 30% of college students are overweight or obese. Desai et al. also suggested rates of complete physical inactivity among college students is between 37% and 46%. Unfortunately, dietary practices among college students are not ideal either.
Poor nutritional behaviors also contribute to risk factors among this population. In a study among college freshman and sophomores, Racette, Deusinger, Strube, Highstein, and Deusinger found that 70% of the 764 college students assessed consumed less than the U.S. Department of Agriculture (USDA) recommendations of two servings of fruit and three servings of vegetables daily. Strikingly, approximately half of the students surveyed also reported high-fat fast or fried food consumption ≥ 3 times in the past week. Notably, a subsample of these students was assessed again a year later with 70% of these students gaining, on average, four kilograms. Indeed, other studies have demonstrated the impact poor dietary practices (e.g., consumption of "junk foods", sugar-sweetened beverages, or fast foods high in fat and low in nutrient density) and obesogenic environments (e.g., continuously eating at buffet-style student dining halls) can have on weight gain from freshman year of college onward. As such, not only is it clear that theoretically-backed physical activity interventions are needed among college students, there is also a distinct need to include a dietary component within these interventions. Technology integration within these physical activity and nutritional interventions among college students might present a viable approach.
While few empirical data is available regarding health wearable use among young adults, it is likely that this technology-savvy age cohort represents a large proportion of the one in six consumers currently owning a health wearable. Further, with the number of health wearables sold in 2018 projected to be 110 million, it is likely that this age cohort will contribute substantially to this figure. Moreover, research indicates the popularity of social media among young adults. Indeed, among individuals 18-29 years of age, approximately 90% use at least one social media site. Currently, Facebook represents the most widely used social media site with 1.71 billion active users and individuals 18 to 34 years of age representing the majority of Facebook users.
Therefore, the combined use of health wearable technology, these devices' associated smartphone applications, and a theoretically-driven health intervention delivered via social media, may prove appealing and effective as a health promotion strategy among college students. Specifically, use of the Polar M400 may increase college students' ability to self-regulate physical activity behaviors as self-regulation is posited as an important factor in promoting behavior change. Further, the Polar M400's associated smartphone application-based and Internet-based portal allows individuals to not only track physical activity-related metrics, but view predicted energy expenditure as well, which may allow individuals to self-regulate food intake in relation to daily energy expenditure. In combination with the Polar M400's capabilities, a twice-weekly Facebook-delivered Social Cognitive Theory-based health intervention may be able to increase college students' self-efficacy, outcome expectancy, enjoyment, and social support while decreasing barriers for participation in greater physical activity and nutritious eating behaviors. Relatedly, it is vital to also examine the preceding intervention's ability to promote changes in college students' intrinsic motivation for these health behaviors-an investigation which can be completed via application of the Self-Determination Theory.
Tipo de estudio
Inscripción (Actual)
Fase
- No aplica
Contactos y Ubicaciones
Ubicaciones de estudio
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Minnesota
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Minneapolis, Minnesota, Estados Unidos, 55455
- Physical Activity Epidemiology Laboratory
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Criterios de participación
Criterio de elegibilidad
Edades elegibles para estudiar
Acepta Voluntarios Saludables
Géneros elegibles para el estudio
Descripción
Inclusion criteria:
- 18-29 years old
- Body mass index ≥ 18.5
- Is currently not engaging in physical activity levels above the Physical Activity Guidelines for Americans (PAGA; U.S. Department of Health and Human Services, 2008)-verified through a structured screening interview prior to participant recruitment and randomization
- Eats less than the recommended two serving of fruits and three serving of vegetables per day (USDA, 2015)-verified through screening using a 10-item fruit and vegetable food frequency questionnaire (F. Thompson et al., 2002)
- No self-reported diagnosed physical/mental disability
- Provides informed consent and completes the Physical Activity Readiness Questionnaire (PAR-Q)
- Willing to be randomized into an intervention or comparison group
Exclusion criteria:
- Self-reported diagnosed physical/mental disability
- Contraindication to physical activity participation as determined by PAR-Q results
Plan de estudios
¿Cómo está diseñado el estudio?
Detalles de diseño
- Propósito principal: Prevención
- Asignación: Aleatorizado
- Modelo Intervencionista: Asignación paralela
- Enmascaramiento: Único
Armas e Intervenciones
Grupo de participantes/brazo |
Intervención / Tratamiento |
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Experimental: Polar M400 + Facebook Group (PM400+FG)
Will be provided a Polar M400 to track physical activity and energy expenditure while also being included in a Facebook group wherein Social Cognitive Theory-based physical activity and nutritious eating tips will be provided twice weekly for 12 weeks.
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Throughout the intervention period experimental group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page.
Additionally, experimental group participants will be asked to track all physical activity with the Polar M400 smartwatch and use this information to set physical activity-related goals conducive to improved health.
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Comparador activo: Facebook Only Group (FG)
Included exclusively in a separate, but content-identical, Facebook group for 12 weeks.
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Throughout the intervention period comparison group participants will be asked to read and try to implement the twice-weekly physical activity- and nutrition-related health tips posted to the group's Facebook page.
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¿Qué mide el estudio?
Medidas de resultado primarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
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Physical Activity
Periodo de tiempo: "Change in Physical Activity from Baseline to 6 Weeks" and "Change in Physical Activity from Baseline to 12 Weeks"
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Will be assessed via Actigraph Link accelerometers with daily moderate-to-vigorous physical activity, light physical activity, sedentary behavior, steps per day, and energy expenditure the outcomes of interest.
The Actigraph accelerometer has been validated among adults (Kaminsky & Ozemek, 2012).
Participants will wear the accelerometer for seven days (ensuring the collection of physical activity data on at least two weekdays and one weekend day) as suggested for field-based accelerometer research (Trost, McIver, & Pate, 2005), with the accelerometer appended to the same wrist as the Polar M400.
Accelerometry measurements will take place at baseline, six weeks, and 12 weeks to examine changes over time in the aforementioned outcomes.
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"Change in Physical Activity from Baseline to 6 Weeks" and "Change in Physical Activity from Baseline to 12 Weeks"
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Medidas de resultado secundarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
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Cardiovascular Fitness
Periodo de tiempo: "Change in Cardiovascular Fitness from Baseline to 12 Weeks"
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Evaluated with YMCA 3-minute step test (Golding, Meyers, & Sinning, 1998).
Participants will step up and down for three minutes on a 12-inch riser to a metronome beep set at 96 beats per minute (each beep corresponding to one movement of the leg, with 4 beeps representing one "up-down" cycle).
Participants' heart rate will be assessed immediately for one minute following the conclusion of the test by the researcher via palpation of the carotid/radial artery.
The step test will be performed at baseline and 12 weeks to assess changes in cardiovascular fitness over time.
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"Change in Cardiovascular Fitness from Baseline to 12 Weeks"
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Body Composition
Periodo de tiempo: "Change in Body Composition from Baseline to 12 Weeks"
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Determined via bioelectrical impedance performed with the Tanita BC-558 IRONMAN® Segmental Body Composition Monitor (Tanita, Tokyo, Japan).
Bioelectrical impedance sends a small electrical pulsatile wave through the body.
Muscle is more conducive to electrical current transmission due to its higher water content versus fat meaning individuals with higher lean mass (i.e., lower body fat mass) will not impede the current to the degree of individuals with higher fat mass and therefore register lower body fat percentage values.
Bioelectrical impedance has proven a valid measure of body composition in young adults enrolling in the military (Aandstad, Holtberget, Hageberg, Holme, & Anderssen, 2014).
Notably, to decrease variability in these body composition measurements, individuals will be asked to come in for testing at approximately the same time of day and having eaten/drank similar foods/beverages the night before as they did prior to previous session(s).
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"Change in Body Composition from Baseline to 12 Weeks"
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Body Weight
Periodo de tiempo: "Change in Weight from Baseline to 12 Weeks"
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Body Weight will be assessed using a calibrated weight scale: the Tanita BC-558 IRONMAN® Segmental Body Composition Monitor (Tanita, Tokyo, Japan).
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"Change in Weight from Baseline to 12 Weeks"
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Self-Efficacy
Periodo de tiempo: "Change in Self-Efficacy from Baseline to 12 Weeks"
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Self-efficacy will be measured by a nine-question measure developed by Rodgers, Wilson, Hall, Fraser, and Murray (2008) wherein participants will rate how confident they feel in certain exercise situations (e.g., …"exercise when you feel discomfort" or "…exercise when you lack energy") on a percentage scale (0%: not confident at all to 100%: extremely confident in 10% increments).
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"Change in Self-Efficacy from Baseline to 12 Weeks"
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Social Support
Periodo de tiempo: "Change in Social Support from Baseline to 12 Weeks"
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Social support will be assessed using a five-question measure adapted from the Patient-Centered Assessment and Counseling for Exercise questionnaire, with participants rating on a five-point Likert-type scale (1: almost never to 5: almost always) how often significant others support/encourage them to be physically activity (Carlson et al., 2012).
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"Change in Social Support from Baseline to 12 Weeks"
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Enjoyment
Periodo de tiempo: "Change in Enjoyment from Baseline to 12 Weeks"
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A 5-question measure developed by Harter et al. (1978) quantified PA enjoyment as college students noted agreement with statements such as "Engaging in physical activity is the thing I like to do best" on a 5-point Likert-type scale (1: strongly disagree to 5: strongly agree).
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"Change in Enjoyment from Baseline to 12 Weeks"
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Barriers
Periodo de tiempo: "Change in Barriers from Baseline to 12 Weeks"
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A 14-question measure will evaluate participants' physical activity barriers, with participants asked to rate agreement between hypothetical barriers and their own barriers on a four-point Likert-type scale (1: strongly disagree to 4: strongly agree) (Sechrist, Walker, & Pender, 1987).
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"Change in Barriers from Baseline to 12 Weeks"
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Outcome Expectancy
Periodo de tiempo: "Change in Outcome Expectancy from Baseline to 12 Weeks"
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Outcome expectancy will be assessed with a nine-question measure developed by Trost et al. (1997) using a five-point Likert-type scale (1: strongly disagree to 5: strongly agree) to evaluate participants' agreement with responses originating from the stem "If I was to exercise on most days it would…".
Sample responses are "give me more energy" and "help to control my weight".
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"Change in Outcome Expectancy from Baseline to 12 Weeks"
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Intrinsic Motivation
Periodo de tiempo: "Change in Intrinsic Motivation from Baseline to 12 Weeks"
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Will be evaluated using the interest/enjoyment subscale of the Intrinsic Motivation Inventory (McAuley, Duncan, & Tammen, 1987).
This seven-question subscale requires participants to determent how true certain statements such as "I enjoyed this activity very much" and "I would describe this activity as interesting" are to them on a seven-point Likert-type scale (1: not at all true to 7: very true).
The Intrinsic Motivation Inventory has demonstrated good validity in the assessment of intrinsic motivation during exercise (Deci, Eghrari, Patrick, & Leone, 1994).
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"Change in Intrinsic Motivation from Baseline to 12 Weeks"
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Nutritious Eating Behaviors
Periodo de tiempo: "Change in Nutritious Eating Behaviors from Baseline to 12 Weeks"
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To assess participant eating behaviors, the National Cancer Institute's Automated Self-Administered (ASA) 24-hour Dietary Recall will be used requiring participants to recall all foods consumed within the past 24 hours.
The ASA 24-hour Dietary Recall has been validated in previous research (Kipnis et al., 2003; Moshfegh et al., 2008).
Participants will receive unique login information allowing them to access and complete the recall after which the researcher will be able to download and analyze the results.
The ASA 24-hour Dietary recall will be administered three times on random dates during the seven days following baseline and post-intervention testing at 12 weeks, with participants notified during these testing sessions that they will be asked to complete this questionnaire.
Concentration will be placed on examining changes in participants' fruit and vegetable consumption in addition to the participants' intake of fast food and sugar-sweetened beverages.
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"Change in Nutritious Eating Behaviors from Baseline to 12 Weeks"
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Facebook-Delivered Health Intervention Adherence
Periodo de tiempo: "Assessed Weekly throughout 12-Week Intervention Period"
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Regardless of group allocation, adherence to the social media-delivered health intervention previously outlined will be tracked.
Briefly, the researcher will determine whether the participants have checked the Facebook health tips twice weekly in two manners following the alert each participant will receive when a new post goes live on each groups' Facebook page.
First, Facebook now has a "Seen By" function that automatically indicates and lists everyone who has interacted with a new posting within a private Facebook group.
Second, the researcher will also ask participants to "Like" each of the postings they read.
In this way, the researcher will keep a running tally of whether each participant checked the posting by reviewing the "Seen By" function and whether the individual "Liked" the posting.
Only individuals listed both within the "Seen By" function and as having "Liked" the posting will be counted as having seen the health tips.
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"Assessed Weekly throughout 12-Week Intervention Period"
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Colaboradores e Investigadores
Patrocinador
Investigadores
- Investigador principal: Zan Gao, PhD, University of Minnesota
Publicaciones y enlaces útiles
Publicaciones Generales
- Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA. 2014 Feb 26;311(8):806-14. doi: 10.1001/jama.2014.732.
- McAuley E, Duncan T, Tammen VV. Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. Res Q Exerc Sport. 1989 Mar;60(1):48-58. doi: 10.1080/02701367.1989.10607413.
- Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, Paul DR, Sebastian RS, Kuczynski KJ, Ingwersen LA, Staples RC, Cleveland LE. The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008 Aug;88(2):324-32. doi: 10.1093/ajcn/88.2.324.
- Desai MN, Miller WC, Staples B, Bravender T. Risk factors associated with overweight and obesity in college students. J Am Coll Health. 2008 Jul-Aug;57(1):109-14. doi: 10.3200/JACH.57.1.109-114.
- Nelson TF, Gortmaker SL, Subramanian SV, Cheung L, Wechsler H. Disparities in overweight and obesity among US college students. Am J Health Behav. 2007 Jul-Aug;31(4):363-73. doi: 10.5555/ajhb.2007.31.4.363.
- Silva MN, Vieira PN, Coutinho SR, Minderico CS, Matos MG, Sardinha LB, Teixeira PJ. Using self-determination theory to promote physical activity and weight control: a randomized controlled trial in women. J Behav Med. 2010 Apr;33(2):110-22. doi: 10.1007/s10865-009-9239-y. Epub 2009 Dec 11.
- Racette SB, Deusinger SS, Strube MJ, Highstein GR, Deusinger RH. Weight changes, exercise, and dietary patterns during freshman and sophomore years of college. J Am Coll Health. 2005 May-Jun;53(6):245-51. doi: 10.3200/JACH.53.6.245-251.
- Millen BE, Abrams S, Adams-Campbell L, Anderson CA, Brenna JT, Campbell WW, Clinton S, Hu F, Nelson M, Neuhouser ML, Perez-Escamilla R, Siega-Riz AM, Story M, Lichtenstein AH. The 2015 Dietary Guidelines Advisory Committee Scientific Report: Development and Major Conclusions. Adv Nutr. 2016 May 16;7(3):438-44. doi: 10.3945/an.116.012120. Print 2016 May.
- Levitsky DA, Halbmaier CA, Mrdjenovic G. The freshman weight gain: a model for the study of the epidemic of obesity. Int J Obes Relat Metab Disord. 2004 Nov;28(11):1435-42. doi: 10.1038/sj.ijo.0802776.
- Piwek L, Ellis DA, Andrews S, Joinson A. The Rise of Consumer Health Wearables: Promises and Barriers. PLoS Med. 2016 Feb 2;13(2):e1001953. doi: 10.1371/journal.pmed.1001953. eCollection 2016 Feb.
- Perrin A. Social media usage: 2005-2015. Available from http://www.pewinternet.org/2015/10/08/2015/Social-Networking-Usage-2005-2015/. 2015
- Bandura A. Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes 50: 248-287, 1991.
- Kaminsky LA, Ozemek C. A comparison of the Actigraph GT1M and GT3X accelerometers under standardized and free-living conditions. Physiol Meas. 2012 Nov;33(11):1869-76. doi: 10.1088/0967-3334/33/11/1869. Epub 2012 Oct 31.
- Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S531-43. doi: 10.1249/01.mss.0000185657.86065.98.
- Golding L, Meyers C, Sinning W. Y's way to physical fitness: the complete guide to fitness testing and instruction (4th ed.). Champaign, IL: Human Kinetics. 1998
- Aandstad A, Holtberget K, Hageberg R, Holme I, Anderssen SA. Validity and reliability of bioelectrical impedance analysis and skinfold thickness in predicting body fat in military personnel. Mil Med. 2014 Feb;179(2):208-17. doi: 10.7205/MILMED-D-12-00545.
- Rodgers WM, Wilson PM, Hall CR, Fraser SN, Murray TC. Evidence for a multidimensional self-efficacy for exercise scale. Res Q Exerc Sport. 2008 Jun;79(2):222-34. doi: 10.1080/02701367.2008.10599485.
- Carlson JA, Sallis JF, Wagner N, Calfas KJ, Patrick K, Groesz LM, Norman GJ. Brief physical activity-related psychosocial measures: reliability and construct validity. J Phys Act Health. 2012 Nov;9(8):1178-86. doi: 10.1123/jpah.9.8.1178. Epub 2011 Dec 27.
- Sechrist KR, Walker SN, Pender NJ. Development and psychometric evaluation of the exercise benefits/barriers scale. Res Nurs Health. 1987 Dec;10(6):357-65. doi: 10.1002/nur.4770100603.
- Trost SG, Pate RR, Saunders R, Ward DS, Dowda M, Felton G. A prospective study of the determinants of physical activity in rural fifth-grade children. Prev Med. 1997 Mar-Apr;26(2):257-63. doi: 10.1006/pmed.1996.0137.
- Deci EL, Eghrari H, Patrick BC, Leone DR. Facilitating internalization: the self-determination theory perspective. J Pers. 1994 Mar;62(1):119-42. doi: 10.1111/j.1467-6494.1994.tb00797.x.
- Kipnis V, Subar AF, Midthune D, Freedman LS, Ballard-Barbash R, Troiano RP, Bingham S, Schoeller DA, Schatzkin A, Carroll RJ. Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol. 2003 Jul 1;158(1):14-21; discussion 22-6. doi: 10.1093/aje/kwg091.
- U.S. Department of Health and Human Services. 2008 physical activity guidelines for Americans. Available from https://health.gov/paguidelines/pdf/paguide.pdf. 2008.
- Thompson FE, Subar AF, Smith AF, Midthune D, Radimer KL, Kahle LL, Kipnis V. Fruit and vegetable assessment: performance of 2 new short instruments and a food frequency questionnaire. J Am Diet Assoc. 2002 Dec;102(12):1764-72. doi: 10.1016/s0002-8223(02)90379-2.
- Harter S. Effectance motivation reconsidered: toward a developmental model. Human Development. 1978, 21:34-64.
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Términos relacionados con este estudio
Otros números de identificación del estudio
- STUDY00000386
Plan de datos de participantes individuales (IPD)
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Información sobre medicamentos y dispositivos, documentos del estudio
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