Table 3.
Summary of key study characteristics
| Author(s) (year, country) [reference] | Research topics | Type of study | Sample | Data collection Instrumentsa) | Data analysis method* | Selected findings & comments on determinants, mediators and/or outcomes of self-determined motivation |
|---|---|---|---|---|---|---|
| Bailey & Phillips (2016, Australia) [26] | Explore relationships between motivation, university adaptation, wellbeing, and academic performance | Cross-sectional correlational | 184 First-year psychology students, 73% females, mean age 19.3 | Self-report of academic performance, academic motivation scale, student adaptation to college guestionnaire, the anxiety and depression subscales of general health guestionnaire, meaning in life guestionnaire, satisfaction with life scale and positive and negative affect schedule | Correlations and hierarchical regression | Outcomes: intrinsic motivation was positively associated with wellbeing, meaning in life, positive emotions and academic performance, and negatively associated with negative emotions. Amotivation had the reverse pattern. Introjected Regulation showed a positive association with positive emotions and with anxiety. Motivational orientations predicted wellbeing, mental health, and academic performance. |
| Baker (2004, UK) [27] | Examine relations between motivation and adjustment to university, stress, well-being and academic performance | Cross-sectional correlational | 91 Second-year psychology students, 78% females, mean age 19.5 | Self-report of academic performance, academic motivation scale, college adaptation guestionnaire, general health guestionnaire, and perceived stress scale | Correlations and hierarchical regression | Outcomes: Controlling for gender and age, amotivation led to worse psychosocial adjustment to university, higher levels of perceived stress, and greater psychological. Intrinsic motivation (to know) was associated with lower levels of stress. Neither extrinsic nor intrinsic motivation, nor amotivation were related to academic achievement. |
| Kusurkaretal. (2011,The Netherlands) [20] | Validity of the Strength of motivation for medical school guestionnaire | Cross-sectional Psychometric | 1,494 Medical students from two universities, 72% females | Strength of motivation for medical school guestionnaire, academic motivation scale and exhaustion subscale of Maslach burnout inventory | Correlations, group differences and exploratory factor analysis | Determinants: overall strength of motivation and its subscales of willingness to sacrifice, readiness to start and persistence correlations were positively correlated with autonomous motivation, and it decreased and became negative as moving towards controlled motivation and amotivation. |
| Kusurkaretal. (2013,The Netherlands) [17] | Explore relationships between motivation, study strategy, effort and academic performance by gender and method ofadmission | Cross-sectional correlational | 383 Second-to-six year medical students, 72% females, mean age 23.3 | Method ofadmission and academic performance provided by university. Study effort, academic motivation scale and revised study process guestionnaire | Correlations, regression, group differences and structured eguation modelling | Outcomes: relative autonomous motivation was positively associated with good study strategy, which was positively associated with high study effort and better performance. Females and gualitative selection procedures showed a higher self-determined profile. |
| Kusurkaretal. (2013,The Netherlands) [14] | Implications of gender on motivation, performance, learning approaches, exhaustion, autonomy support and perceived competence | Cross-sectional correlational | 95 Fourth year medical students, 71.5% females | Academic performance provided by university. Academic motivation scale, revised study process guestionnaire, Maslach burnout inventory, learning climate guestionnaire and perceived competence guestionnaire | Group differences | Determinants: males reported higher controlled motivation and higher perceived competence even when reporting higher surface learning strategy, lower deep learning strategy and lower or egual performance. |
| Kusurkaretal. (2013,The Netherlands) [16] | Generate motivational profiles and test associations with different outcomes | Quantitative, Cross-sectional correlational | 844 Year one-to-six medical students, 71.5% females | Academic performance provided by university. Academic motivation scale, study hours per week, study process guestionnaire, and exhaustion subscale of Maslach burnout inventory | Correlations, K-cluster, analysis ofvariance and multivariate analysis of covariance | Outcomes: high intrinsic low controlled motivation was associated with good study hours, deep learning strategy, good academic performance and low exhaustion. High intrinsic high controlled motivation was associated with a good learning profile, except showing high surface strategy. Low intrinsic high controlled and low intrinsic low controlled motivation were associated with least desirable learning behaviours. |
| Orsini etal. (2016, Chile) [23] | Understand how clinical teachers encourage intrinsic motivation | Phenomenology | 9 Clinical dental teachers, 7 males, mean age of teaching experience 15 | Semi-structured interviews on how teachers supported students'needs for autonomy, competence, and relatedness | Thematic analysis | Determinants: teachers emphasise the influence that the learning climate has on students'intrinsic motivation, stressing the relevance of empowering, supporting and building a horizontal relationship.Themes included: transference of responsibility; personal interests; constructive feedback; vicarious learning experience; teamwork, and safe environment. |
| Orsini etal. (2015, Chile) [18] | Validity of the academic motivation scale in a dental students sample | Cross-sectional Psychometric | 989 Year one-to-six dental students, 62% females, mean age 22.5 | Academic performance provided by university. Academic motivation scale, deep and surface motives subscales of revised study process guestionnaire, academic subscale of abbreviated five-factor self-concept guestionnaire, and positive subscale of positive and negative affect schedule | Confirmatory factor analysis, correlations and group differences | Determinants: third and fourth years showed the highest amotivation scores. |
| Outcomes: intrinsic and identified regulation showed positive correlations with deep motives, academic self-concept and positive affect, and negative correlation with surface motives. Amotivation showed the reverse pattern. | ||||||
| Park etal, (2012, Republic of Korea) [19] | Examine relationships between stress, motivation, personality, academic performance, and depression | Cross-sectional correlational | 160 First year medical students, 72.5% males | Academic performance provided by university. Academic motivation scale, medical stress scale, personality inventory, Beck depression inventory, and Hamilton depression scale | Correlations, group difference, regression and path analyses | Determinants: psychopathological was negatively correlated with self-determined motivation. |
| Sobral (2004, Brazil) [15] | Describe medical students'motivation relationships with different learning outcomes | Cross-sectional correlational with a longitudinal panel design component | 297 Second year medical students, 57% males, mean age 20.4 | Academic performance provided by university. Academic motivation scale, reflection-in-learning scale, approaches to studying inventory, 4 semesters follow-up on peer tutoring activity, and intention to continue studies | Correlations, K-cluster and group differences | Outcomes: autonomous motivation was associated with higher levels of meaning orientation, reflection in learning, academic achievement, cross-year peer-tutoring, and intention to continue with studies, and had negative relationship with reproductive orientation to learning. Amotivation showed the reverse pattern and controlled motivation was positively related to reproductive orientation. |
| Outcomes: self-determined motivation was positively associated with performance and negatively associated with depression. Stress was positively correlated with amotivation and identified regulation and negatively correlated with intrinsic motivation and with external regulation. | ||||||
| Stoeberetal. (2011, UK) [28] | Investigate relationships between passion for studying, academic engagement, burnout and motivation | Cross-sectional correlational | 103 Second-year psychology students, 89% females, mean age 20 | Passion scale, Utrecht Work Engagement Scale-student, Maslach burnout inventory, and Sheldon's idio-graphic method for motivational analysis | Correlations, multiple analysis ofvariance, multiple regression | Outcomes: autonomous motivation showed positive association with harmonious passion and engagement for studying, and negative significant association with burnout. Controlled motivation showed the reverse pattern. |
| Tanaka etal. (2009, Japan) [13] | Examine relationships between personality traits and intrinsic motivation | Cross-sectional correlational | 119 Second year medical students, 70% males, mean age 20.5 | Temperament and character inventory and intrinsic motivation scale toward learning. | Regression analyses | Determinants: on simple regression, persistence, self-direct-edness, cooperativeness and self-transcendence were positively associated with intrinsic motivation. On multiple regressions, adjusted for age and gender, persistence, self-directedness, and self-transcendence were positively associated with intrinsic motivation. |
| Tanaka etal. (2011 Japan) [21] | Examine relationships between academic and family conditions and intrinsic motivation | Cross-sectional correlational | 120 Second year medical students, 69% females, mean age 20.5 | Self-report of lifestyle, family and academic conditions, and intrinsic motivation scale toward learning. | Regression analyses | Determinants: spending time with family, taking pleasure in school and learning, understanding lectures, and attending school regularly, were positively associated with intrinsic motivation. |
| Williams & Deci (1996, USA) [7] | Exploration of SDT in students'adoption of psychosocial values and an autonomy-supportive style in patient interviewing skills | Longitudinal-pan-el design | Study 1:91 second-year medical students | Data collection: two times over 24 weeks on study 1 and five times on study 2 (three within the course, after 6 months, and after 2 years) | Correlations and regression analyses | Determinants and outcomes: positive relations between autonomous motivation, psychosocial beliefs, and perceived competence at interviewing before starting the course; perceived autonomy supportiveness of instructors promoted autonomous motivation, perceived competence, psychosocial beliefs, and behaving more autonomy-supportive with simulated patients. Increased relative autonomy mediated relations between instructors'autonomy support and the enhancement of psychosocial values and perceived competence. |
| Study 2:56 second-year medical students and course instructors | Instruments: physician psychosocial belief scale, general causality orientations scale, learning climate guestionnaire, learning self-regulation guestionnaire, interviewing competence scale, instructors'psychosocial beliefs, and health-care climate guestionnaire | |||||
| Williams etal. (1994, USA) [25] | Compare effects of facilitating students'interest' versus'controlling students learning'during internal medicine clerkship | Cross-sectional correlational | 89 Fourth year medical students at two Universities | Modified learning climate guestionnaire, competence in internal medicine scale, interest in internal medicine scale, pressure, tension scale, internal medicine career choice, and prior likelihood for career choice | Correlations, and structured eguation modelling | Determinants and outcomes: an autonomy supportive learning climate predicted increased perceived competence and interest, which in turn predicted specialty choice. Conversely, a controlling learning climate did not predict perceived competence or interest. |
| Williams etal. (1997, USA) [24] | Examine relationships between a utonomy-support, perceived competence, interest, prior likelihood and choosing internal medicine or surgery as a career | Cross-sectional correlational | 210 Fourth year medical students at three Universities, 61% males, mean age 27.4 | Modified learning climate guestionnaire, competence in internal medicine and surgery scale, interest in internal medicine scale, internal medicine and surgery career choice, and prior likelihood for career choice | Correlations, multiple regression and structured eguation modelling | Determinants and outcomes: perceived autonomy support predicted students'choices of internal medicine or surgery, even after the effects of prior (and actual) likelihood had been removed. |
| Wouters etal. (2014, The Netherlands) [22] | Investigate type of motivation and differences between selected and non-selected applicants of medical school. | Phenomenology | 96 Applicants, 72% females, mean age 23 | Document review of motivation statements | Thematic and content analysis, and fre-guencyand group comparison | Determinants: selected and non-selected applicants did not differ in types of motivation, reporting mainly autonomous motivation for applying. Findings raise guestions on the validity and reliability of the statement on motivation as a tool for selection. |
a)
All studies collected self-reported demographics and conducted descriptive analyses.