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Abstract

Gifted and talented (GT) students are widely recognized for their academic strengths, yet less attention is given to their social-emotional experiences. Hope, a cognitive-motivational construct reflecting perceived ability to set meaningful goals, identify pathways to achieve them, and maintain the motivation to pursue those pathways (Snyder, 2002), has been linked to academic and psychosocial functioning but remains underexplored in GT students. In this study, we examined hope profiles in 194 Turkish adolescents attending a residential high school. Using latent profile analysis, two distinct groups emerged: a Hopeful profile characterized by slightly above-average hope scores and a Low Hope profile with substantially below-average scores. Students in the Hopeful profile reported higher positive affect, self-esteem, and well-being, as well as lower depressive symptoms and psychological distress, compared to peers in the Low Hope profile. Findings highlight hope as a meaningful psychosocial resource for GT adolescents and underscore the importance of fostering hope to support talent development.

Keywords

adolescents gifted and talented students hope psychosocial variables

Gifted and talented (GT) students are often celebrated for their academic performance, but their social-emotional challenges are not systematically recognized and addressed (Blaas, 2014; Dixson et al., 2020). Some studies have suggested that these students consistently thrive compared to peers, whereas other research has highlighted vulnerabilities in adjustment (Duplenne et al., 2024). Subotnik et al. (2011) argued that both perspectives oversimplified GT students’ experiences. Specifically, according to the talent development mega model (TDMM; Subotnik et al., 2011), understanding the psychosocial contributors to success among gifted youth is essential for translating high potential into realized ability, given that talent development is a longitudinal and dynamic process that is socially mediated and contextually bound.

Although the field of gifted education has acknowledged that creativity and high performance require more than ability, in practice, the emphasis has been more on cognitive skills (Olszewski-Kubilius et al., 2019; Worrell, 2009). In particular, identification practices, services, and program goals have been the primary areas of focus, whereas the crucial role of students’ psychosocial perceptions and emotional well-being in reaching their full potential has been neglected (Dixson et al., 2024; Zeidner, 2021). For example, GT students reported lower physical self-concept despite having higher academic self-concept (Infantes-Paniagua et al., 2022), and their life satisfaction tended to be more closely tied to academic achievement and school experiences compared to their peers (Ash & Huebner, 1998). Furthermore, contrary to evidence suggesting relative strengths in executive functioning (Leana-Taşçılar & Cinan, 2014), qualitative findings showed that gifted students do report challenges in planning and time management (Conejeros-Solar & Gómez-Arízaga, 2015; Worrell et al., 2025).

Limited research has addressed these unique dynamics (Duplenne et al., 2024), both in the global context and in Turkey. For example, Topçu and Leana-Taşcılar (2016) reported that academic motivation and self-esteem were associated with achievement in middle school students, Özyaprak and Deringöl (2013) found lower depressive symptoms in gifted elementary school students compared to their non-identified peers, and Başlantı and McCoach (2006) found that low levels of motivation were related to underachievement among undergraduate students. All of these studies focus on one or two psychosocial variables, but no researchers have taken a more holistic view. A more nuanced understanding of the experiences of GT students may guide effective support strategies (Worrell et al., 2025) and challenge inaccurate stereotypes, including that these students are self-sufficient (Bergold et al., 2021).

Hope is a promising psychosocial factor to study in the context of academic talent development, as more and less beneficial hope profiles have been found in GT students (Dixson et al., 2024). Moreover, levels of hope can be changed through brief school-based interventions (Feldman & Dreher, 2012; Weis & Speridakos, 2011), and higher hope is linked to favorable school-related and other psychosocial outcomes in general education (Gallagher et al., 2017; Marques et al., 2015) and GT students (Dixson, 2017; Dixson et al., 2024). However, the construct of hope remains underexplored among GT students, especially in relation to specific outcomes that can ultimately foster talent development (Dixson, 2017).

In this study, we examined profiles of hope in a sample of GT Turkish youth to explore its potential as a lens for rethinking how educational systems can better support these students. In the following sections, we review the literature on hope theory and its connection to key psychosocial outcomes. Next, we review the extant research on profiles of hope including literature on GT populations. We hypothesize that hope profiles will be associated with anticipated positive and maladaptive psychosocial outcomes.

Hope Theory

Snyder (1989, 2002) defined hope as a cognitive-motivational process that involves people’s self-appraised ability to envision paths to desirable future goals, regardless of current circumstances, combined with their belief and motivation to make those goals a reality. According to Snyder (2002), hope includes three main components centered on an individual’s perceived ability to (a) clearly set goals, (b) develop specific strategies to reach those goals (i.e., pathways thinking), and (c) initiate and sustain the motivation to use those strategies (i.e., agency thinking).

Agency, the motivational component of hope, represents an individual’s interest, ambition, and perseverance needed to pursue a goal (Dixson et al., 2024). Individuals higher in agency generally set more goals, overcome more obstacles, and persist longer in their pursuits than those with lower agency thinking (Snyder, 2002). Pathways is the cognitive component of hope, referring to an individual’s perceived ability to identify and strategize multiple routes to reach a goal (Snyder, 2002). High pathway thinkers can envision multiple routes, accounting for barriers and setbacks, to guide their actions toward achieving their goals (Dixson, 2017). Although agency and pathways thinking are different constructs, Snyder (2002) proposed a theoretical model in which pathways and agency thoughts mutually activate and refine one another throughout goal pursuit, with emotions cycling back to influence this iterative process. High-hope individuals, who tend to approach goals with a positive emotional set, benefit from a feedback loop that supports persistence in the face of stressors.

Hope’s Associations With Psychosocial Functioning

In child and adolescent populations, hope is typically measured using the Children’s Hope Scale (CHS; Snyder et al., 1997). Empirically, hope has been meaningfully associated with assets and positive outcomes and inversely associated with liabilities and negative outcomes, including among GT youth across diverse cultural contexts. Among Chinese GT adolescents, agency and pathways were positively associated with creativity, curiosity, and resilience, whereas agency was associated with subjective well-being (Chen, Cheung, et al., 2018; Chen, Fan, et al., 2018). Similarly, among Turkish middle school GT students, agency-mediated coping strategies were associated with subjective well-being and sustained academic engagement (Kaya & Islekeller-Bozca, 2022). Longitudinal findings from Australia linked lower hope to poorer academic performance among GT students and showed higher levels of sadness and social isolation among GT relative to their non-gifted peers (Vialle et al., 2007). Extending hope’s relevance to mental health, Chen et al. (2020) identified inverse associations between hope and suicidal cognitions among Chinese GT youth. Together, these cross-cultural findings position hope as a stable yet malleable psychosocial resource that supports both academic engagement and socioemotional well-being among gifted youth.

Further research involving Turkish youth has consistently demonstrated a meaningful association between hope and a host of psychosocial constructs. Hope has been found to correlate positively with self-esteem (Çelik et al., 2015), life satisfaction and positive affect (Telef, 2020), social support (Güngör, 2019; Sahranç et al., 2018; Çiçek, 2021), social connectedness (Sahranç et al., 2018; Çiçek, 2021), well-being (Cengiz et al., 2025), locus of control (Turan, 2021; Çelik et al., 2015), and school satisfaction and academic grit (Peker & Cengiz, 2023). Conversely, hope has been found to be negatively correlated with anger and depression (Taysi et al., 2015), social anxiety (Sahranç et al., 2018), negative affect (Telef, 2020), school burnout (Güngör, 2019), and the likelihood of participating in or experiencing bullying (Atik, 2009).

Multiple Turkish mediation analyses have offered insights into the role of hope in schooling. Specifically, hope and social competence fully mediated the association between well-being and school engagement (Demirci, 2020), hope and academic grit sequentially mediated the association between students’ school satisfaction and perceived teacher support (Peker & Cengiz, 2023), and hope mediated the association between secure attachment and academic, social, and emotional self-efficacy, accounting for 40% of the variance in overall self-efficacy (Demirtaş, 2019). In summary, studies have repeatedly demonstrated that hope (a) is associated with positive psychosocial outcomes, (b) may protect against adverse psychosocial outcomes, and (c) can be fostered and improved through intervention.

Hope Profiles

Per Snyder’s (2002) conceptualization of hope as a dynamic construct involving both agency and pathways thinking, examining these dimensions of hope in combination may more accurately capture its role in students’ functioning. Accordingly, an emerging body of research has sought to evaluate the utility of person-centered analyses of hope, in which the effects of patterns of agency and pathway thinking are considered rather than the effect of each component individually.

Dixson et al. (2017) examined hope profiles based on cluster analyses using pathways and agency scores, reporting four different clusters consistent with Snyder’s (2002) theorized hope groups: high hopers (high agency and high pathways), high-agency thinkers (high agency and average to low pathways), high-pathways thinkers (high pathways and average-to-low agency), and low hopers (low agency and low pathways). These groups had meaningfully different profiles of academic success, with the high hopers reporting the most success-oriented academic psychosocial profiles. Similar work with GT adolescents (Dixson et al., 2024) yielded three clusters of hope (i.e., high hope, average hope, and low hope) that meaningfully differed in psychosocial outcomes related to academic talent development. The high hope cluster was characterized by psychosocial outcomes most conducive to academic talent development, followed by those of the average hope and low hope clusters, respectively.

The Current Study

We have established the importance of promoting the adaptive development and holistic functioning of GT students and that hope is a powerful psychosocial tool for fostering such outcomes generally. Despite growing recognition of the importance of psychosocial functioning among GT students, relatively little research has directly examined hope and related psychosocial factors in this population. In this study, our goal was to better understand the associations between hope and psychosocial variables among Turkish GT adolescents in a residential school setting. As such, we investigated two primary research questions. First, we examined whether a latent profile analysis (LPA) of hope scores would yield interpretable profiles in our sample. Prior research has yielded different profile patterns (Dixson, 2019; Dixson et al., 2017, 2024). However, given the limited research on agency- and pathways-specific hope profiles among GT populations, we do not have an a priori hypothesis about the number or configuration of profiles that will emerge. Second, we examined whether students within the identified profiles differed in their scores reflecting psychosocial functioning. We hypothesized that the hope profiles would be meaningfully associated with the outcomes, such that students belonging to profiles characterized by higher levels of agency and pathways would also have higher scores on favorable outcomes (i.e., positive affect, self-esteem, subjective well-being) and lower scores on maladaptive outcomes (i.e., depressive symptoms, negative affect, perfectionism, psychological distress).

Method

Participants

Participants included 194 students (M_age = 15.44, SD_age = 1.08). The participants reported gender identities of male (51%) and female (49%), and one student identified as non-binary; there was no missingness in age and gender data. Admission to this school is based on a combination of multiple criteria including exceptional scores in national tests of aptitude (i.e., top 3%) and well above average IQ scores in standardized cognitive assessments (i.e., >130). The students, who come from various parts of the country, reside on campus full time during the academic year. On the 10-point MacArthur Scale of Subjective Social Status (Goodman et al., 2001), participants had a mean of 6.45 (SD = 1.44), indicating that their average perceived social standing was above the scale midpoint.

Measures

The participants completed an online survey that included various instruments assessing indicators of psychosocial functioning. A detailed description of the measures is provided in Table 1, including the thresholds for interpretation on the measures of depressive symptoms and psychological distress. Cronbach’s alpha estimates for scores on each measure in this study are also presented in Table 1.

Table 1.

Measures of Psychosocial Functioning

Variable	Author	Adaptation	Scale name	Subscale	Number of items	Likert range	Alpha
Affect	Watson et al., (1988)	Gençöz (2000)	Positive and Negative Affect Schedule		20	1–5
				Positive affect	10		.85
				Negative affect	10		.83
Depressive symptoms	Beck et al. (1996)	Dikmen (2020)	Beck Depression Inventory		20	1–4	.87
Hope	Snyder et al. (1997)	Atik and Kemer (2009)	Children’s Hope Scale		6	1–6	.82
				Agency	3		.67
				Pathways	3		.73
Perfectionism	Bento et al. (2020)	Yıldırım and Balcı Çelik (2022)	Child-Adolescent Perfectionism Scale-Short Form		9	1–5	.84
				Socially prescribed	5		.87
				Self-oriented	4		.89
Psychological distress	Kessler et al. (2002)	Altun et al. (2019)	Kessler Psychological Distress Scale		10	1–5	.92
Self-esteem	Rosenberg (1965)	Tukuş (2010)	Rosenberg Self-Esteem scale		10	1–4	.90
Well-being	Huebner (1994)	Çivitci (2007)	Multidimensional Students’ Life Satisfaction Scale		36	1–5
				Family	7		.89
				Friends	8		.84
				School	8		.82
				Living environment	7		.78
				Self	6		.73

Note. For depressive symptoms, the thresholds for interpretation are as follows (Beck et al., 1996; Dikmen, 2020): minimal (20–32), mild (33–38), moderate (39–47), and severe (48–80). For psychological distress, the thresholds for interpretation are as follows (Altun et al., 2019; Kessler et al., 2002): likely well (10–19), mild (20–24), moderate (25–29), and severe (30–50).

Procedure

Institutional Review Board approval was obtained from the authors’ academic institution prior to data collection (Protocol Number: 2024-02-17173). Participants were recruited from a residential high school for GT adolescents in Turkey during the 2024–2025 academic year and were eligible for study participation if enrolled in the school at the time of data collection. Study invitation, consent, and assent materials were shared with the school administration who then emailed these materials to all students. Interested students aged 18 or older provided consent electronically, whereas students under 18 provided assent. Teachers assigned as campus guardians approved participation for students who required adult consent. Confidentiality was ensured by using randomly generated ID numbers in the otherwise anonymous survey. The turnout rate was 72% of the student population with approximately equal distribution across cohorts.

Participants filled out an online questionnaire which included academic and demographic information as well as various survey items. As shown in Table 1, all instruments used in the study have been adapted and demonstrated sufficient psychometric properties in prior studies with Turkish samples. Each participant was compensated with electronic gift cards worth 100 Turkish Liras (approximately 3 USD), equivalent to the hourly minimum wage at the time of data collection.

Analytic Strategy

One hundred and ninety-four participants completed the surveys. Given that this was an exploratory study and that participants missed different items, we adopted a conservative approach and did not impute missing data, resulting in sample sizes ranging from 124 to 157 across constructs. Additionally, we examined the existence of hope groups using LPA, a probabilistic statistical procedure that groups individuals into hidden (i.e., latent) categories within a population based on specified variables (Muthén & Muthén, 2017). Standardized scores of the Agency and Pathway subscales were used to estimate 2- to 4-profile solutions with the robust maximum likelihood (MLR) estimator. Indicator variances were constrained to be equal across classes to reduce the risk of overfitting given the exploratory nature of this study.

Model selection was guided by lower values in Akaike information criterion (AIC) and Bayesian information criterion (BIC), which indicate model quality. Significant p-values for the Vuong-Mendell-Rubin (VLMR), Lo-Mendell-Rubin (LMR), and bootstrapped likelihood ratio test (BLRT) indicated whether increasing model complexity improved model fit to the data. Additionally, entropy and average latent class probabilities (ALCPs) were used to assess classification accuracy. We also considered the theoretical relevance and interpretability of the models. After selecting the optimal model, we used the three-step method recommended by Asparouhov and Muthén (2014) to examine differences in psychosocial outcomes across profiles while accounting for classification uncertainty. Pairwise Wald tests were used to assess the significance of mean differences between profiles, and effect sizes were manually calculated to guide interpretation of profile differences. Analyses were conducted using Mplus 8.1, SPSS, R (Version 4.2.2), and RStudio (Version 2023.06.0).

Results

Descriptive Statistics

As shown in Table 1, all measures used in the study had acceptable internal consistency. Specifically for the CHS, the internal reliability coefficient of the total score was .82, whereas the coefficients for the Agency and Pathways subscales were .67 and .73, respectively. This pattern of findings is consistent with findings from other translated versions of the CHS (Jovanovic, 2013; Ling et al., 2021), given that each subscale includes only three items. Means and standard deviations are reported in Table 2, and variable distributions were generally not skewed or kurtotic. Correlations are reported in Table 3, and correlations greater than .20, which all had confidence intervals that did not include zero, were considered practically significant or meaningful based on recommendations by Ferguson (2009) and Funder and Ozer (2019). Only 20 (16.7%) of the 120 correlations were not meaningful.

Table 2.

Descriptive Statistics for Psychosocial Variables

	N	M	SD	Min.	Max.	Skewness	Kurtosis
Affect
Positive affect	147	32.42	7.18	16	49	−0.15	−0.35
Negative affect	147	25.73	7.70	12	46	0.49	−0.45
Depressive symptoms	126	35.60	9.57	20	73	0.62	0.41
Hope
Global	157	4.32	0.91	1	5.83	−0.86	0.58
Agency	157	4.20	1.00	1	5.67	−0.77	0.19
Pathways	157	4.45	1.00	1	6	−0.75	0.56
Perfectionism
Self-oriented	131	15.69	3.96	4	20	−0.78	−0.06
Socially prescribed	131	16.53	4.70	5	25	−0.31	−0.52
Psychological distress	124	26.18	9.55	10	50	0.13	−0.96
Self-esteem	131	28.29	6.41	13	40	0.06	−0.81
Well-being
Global well-being	136	3.60	0.51	2.36	4.67	−0.24	−0.47
Family	137	3.65	0.94	1.29	5	−0.49	−0.54
Friends	137	3.99	0.56	2	5	−0.64	0.51
School	136	3.33	0.75	1.25	4.88	−0.39	−0.39
Living environment	137	3.32	0.79	1.29	4.86	−0.18	−0.57
Self	137	3.72	0.65	1.50	5	−0.65	0.70

Note. Scores on affect, depressive symptoms, perfectionism, psychological distress, and self-esteem were computed by the sum of responses, whereas scores on hope and well-being were computed by the mean of responses. All scores were computed in the same direction, such that higher scores on each measure indicated higher levels of the construct reflected in the scores.

Table 3.

Correlations Among Hope and Psychosocial Outcomes

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. Positive affect	—
2. Negative affect	−.29*	—
3. Depressive symptoms	−.49*	.61*	—
4. Perfectionism: Self-oriented	.34*	−.00	−.09	—
5. Perfectionism: Socially prescribed	.08	.13	.20	.31*	—
6. Psychological distress	−.41*	.74*	.78*	−.07	.29	—
7. Self-esteem	.53*	−.56*	−.71*	.23	−.08	−.66*	—
8. Overall well-being	.55*	−.37*	−.54*	.37	.04	−.44*	.56*	—
9. Well-being: Family	.45*	−.30*	−.42*	.32	−.07	−.36*	.42*	.78*	—
10. Well-being: Friends	.32*	−.18	−.35*	.21	.01	−.21	.30*	.76*	.46*	—
11. Well-being: School	.42*	−.41*	−.37*	.41*	.09	−.40*	.39*	.78*	.52*	.54*	—
12. Well-being: Living environment	.32*	−.25	−.36*	.05	−.08	−.29	.29*	.57*	.36*	.24	.28	—
13. Well-being: Self	.56*	−.27	−.49*	.42*	.19	−.34*	.70*	.74*	.53*	.46*	.53*	.25	—
14. Hope	.55*	−.39*	−.48*	.34	.09	−.48*	.60*	.43*	.32	.19	.37	.25	.58*	—
15. Hope: Agency	.54*	−.39*	−.58*	.27	.10	−.49*	.62*	.56*	.40*	.34	.46*	.23	.66*	.89*	—
16. Hope: Pathways	.47*	−.32	−.32	.38	.10	−.40*	.47*	.32	.24	.12	.29	.18	.48*	.91*	.64*	—

Note. *p < .001.

As hypothesized, hope scores were meaningfully associated with several theoretically related psychosocial constructs generally in the expected directions (see Table 3). Specifically, we found positive correlations of the global hope score with positive affect, self-esteem, overall well-being, and well-being in the domains of family, friends, living environment, school, and self. We also found negative associations of hope with depressive symptoms and psychological distress. Interestingly, total hope, agency, and pathways had meaningful correlations with self-oriented perfectionism but not socially prescribed perfectionism. Overall, the correlational patterns generally align with theoretical expectations. Higher hope scores in this sample were associated with stronger psychosocial assets and lower psychosocial liabilities.

LPA Results

Models with one through four profile solutions were evaluated. Fit indices are presented in Table 4, and ALCPs and class sizes are presented in Table 5. As can be seen, the 3-profile solution achieved the strongest fit: it yielded lower AIC and BIC values than the 2-profile solution, significant VLMR, LMR, and BLRT p-values, and the highest entropy (.911) among the models tested. However, the additional profile introduced by the 3-profile solution comprised only one individual (see Table 5), thereby limiting the theoretical and practical utility of this model. The 4-profile solution also produced extremely small classes, including a single-individual profile. Comparatively, the 2-profile solution demonstrated a significant BLRT p-value, strong classification quality (entropy = .829), and high average latent class probabilities (.918 and .963), indicating well-separated profiles.

Table 4.

Model Fit Statistics of the Two- Through Four-Profile Solutions

Profile solution	Log likelihood	df	AIC	BIC	Entropy	VLMR p	LMR p	BLRT p
2-Profile	−414.00	7	842.01	863.40	0.829	0.05	0.06	<0.001
3-Profile	−400.88	10	821.75	852.31	0.911	0.01	0.01	<0.001
4-Profile	−380.36	13	804.73	844.46	0.821	0.15	0.16	0.013

Note. AIC = Akaike Information Criterion. BIC = Bayesian Information Criterion. LMR = Lo, Mendell, and Rubin Likelihood Ratio Test. VLMR = Vuong-Lo-Mendell-Rubin Likelihood Ratio Test. BLRT = Bootstrapped Likelihood Ratio Test.

Table 5.

Average Latent Class Probabilities and Class Sizes of the Two- Through Four-Profile Solutions

	2-Profile		3-Profile			4-Profile
	Profile 1	Profile 2	Profile 1	Profile 2	Profile 3	Profile 1	Profile 2	Profile 3	Profile 4
Profile 1	.918	.037	.937	.063	.000	.919	.081	.000	.000
Profile 2	.037	.963	.032	.968	.000	.054	.825	.121	.000
Profile 3	—	—	.000	.000	1.000	.000	.072	.928	.000
Profile 4	—	—	—	—	—	.000	.000	.000	.000
Final class counts	33	124	30	126	1	14	49	93	1

Note. Values represent average latent class probabilities.

Taken together, these considerations supported retaining the 2-profile solution. The first profile, labeled the Low Hope group (n = 33 [21%]), consisted of individuals with substantially below average scores on both dimensions of the CHS, reflecting consistently low hope. The second profile, labeled the Hopeful group (n = 124 [79%]), included individuals with slightly above average Agency and Pathways scores relative to the whole sample. Given that the CHS is not a norm-referenced measure, the labels were selected relative to our sample’s findings. The profiles are presented in Figure 1. Local independence of the 2-profile model was evaluated using the bivariate residuals for covariances. The residual covariance between the Agency and Pathways subscales of the Hope Scale was 0.190, suggesting mild residual dependence between the indicators. However, this result is consistent with the theoretical and conceptual overlap inherent in Agency and Pathways (Snyder, 2002), and was therefore interpreted as theoretically reasonable rather than as a substantive violation of the local independence assumption.

Figure 1.

Differences in hope scores between profiles.

Differences Between Profiles

Mean differences between the Hopeful and Low Hope profiles are reported in Table 6. Effect sizes were calculated to determine the magnitude of profile differences. In the absence of an established baseline for comparisons of hope between groups, effect sizes greater than 0.40 with confidence intervals that did not contain zero were considered practically significant in accordance with Ferguson’s (2009) recommendations and used for interpretation. Except for age and socially prescribed perfectionism, meaningful differences were found between the Hopeful and Low Hope groups for all other variables. Specifically, Hopeful students reported higher positive affect and lower negative affect than their Low Hope peers. They also reported lower levels of depressive symptoms and psychological distress. Furthermore, Hopeful students had higher levels of self-esteem and self-oriented perfectionism compared to their Low Hope peers. Overall well-being was higher among Hopeful students, as well as well-being in the following subdimensions: friends, living environment, school, and self. However, the two groups did not differ on socially prescribed perfectionism.

Table 6.

Mean Differences Between Profiles on Outcomes

	Low Hope		Hopeful
	M (SD)	n	M (SD)	n	ΔM (SE)	Hedges’ g [95% CI]
Age	15.39 (1.24)	33	15.47 (1.02)	124	−0.08 (0.27)	0.07 [–0.31, 0.46]
Hope (CHS)
Agency	2.54 (0.24)	33	4.64 (0.59)	124	−2.10 (0.15)*	3.88 [3.30, 4.46]
Pathways	3.00 (0.80)	33	4.87 (0.53)	124	−1.87 (0.20)*	3.13 [2.61, 3.64]
Affect (PANAS)
Positive affect	24.85 (5.21)	27	34.10 (6.44)	120	−9.23 (1.50)*	1.47 [1.02, 1.93]
Negative affect	32.30 (7.25)	27	24.31 (6.82)	120	7.98 (1.83)*	−1.15 [–1.59, –0.71]
Depressive symptoms (BDI)	44.10 (6.89)	25	33.39 (8.89)	105	10.70 (2.04)*	−1.25 [–1.71, –0.78]
Perfectionism (CAPS-SF)
Self-oriented	13.92 (5.31)	25	16.14 (3.38)	106	−2.22 (1.25)	0.58 [0.14, 1.02]
Socially prescribed	15.93 (4.52)	25	16.69 (4.71)	106	−0.76 (1.16)	0.16 [–0.28, 0.60]
Psychological distress (K10)	34.31 (4.68)	25	24.13 (9.22)	91	10.78 (1.73)*	−1.19 [–1.66, –0.73]
Self-esteem (RSES)	22.60 (3.76)	25	29.69 (5.97)	105	−7.08 (1.30)*	1.25 [0.79, 1.72]
Well-being (MSLSS)
Global well-being	3.17 (0.39)	25	3.71 (0.47)	112	−0.54 (0.11)*	1.17 [0.71, 1.62]
Family	3.32 (0.81)	25	3.73 (0.95)	112	−0.41 (0.22)	0.44 [0.00, 0.88]
Friends	3.74 (0.50)	25	4.05 (0.55)	112	−0.31 (0.13)*	0.57 [0.13, 1.01]
School	2.79 (0.74)	25	3.46 (0.68)	112	−0.67 (0.19)*	0.95 [0.51, 1.40]
Living environment	2.93 (0.58)	25	3.41 (0.80)	112	−0.48 (0.17)*	0.63 [0.19, 1.07]
Self	3.02 (0.77)	25	3.89 (0.48)	112	−0.88 (0.19)*	1.61 [1.13, 2.08]

Note. *p < .05 (Wald test). Hedges’ g values ≥ |0.40| with confidence intervals that do not contain zero are bolded (Ferguson, 2009).

Discussion

In this study, we examined hope in a sample of GT students in Turkey. Our study contributes to the hope literature based on person-centered analyses. Specifically, our first goal was to consider whether an LPA of hope scores would yield meaningful profiles. Then, we investigated whether the students in the profiles we identified differed in their scores on various measures of psychosocial functioning. We found two distinct hope profiles that were associated with multiple variables, including affect, depressive symptoms, psychological distress, self-esteem, self-oriented perfectionism, and subjective well-being. Moreover, a far greater number of students were classified into the Hopeful profile (79%) compared to the Low Hope profile (21%), perhaps indicating that high achieving students are more likely to have higher levels of hope overall. In line with this hypothesis and the TDMM, which posits that psychosocial factors are critical to enhance the process of talent development (Olszewski-Kubilius et al., 2019; Subotnik et al., 2011), our findings indicate that the GT students with higher levels of hope reported more adaptive psychosocial functioning than their GT peers with lower levels of hope.

The fact that our analyses yielded only two profiles was also notable. Although previous findings indicated various numbers of hope profiles in adolescent samples (e.g., Dixson, 2019; Dixson et al., 2017, 2024), given the limited research among GT students, we did not have a specific hypothesis about the number of profiles. There may be several reasons for this finding. First, our sample had fewer students than half of the samples in the cited studies. Second, our sample comprised a homogeneous group of students from the same residential school and generally comparable levels of academic achievement, socioeconomic status, and sociocultural backgrounds. Nevertheless, the two hope profiles revealed meaningful differences across numerous indicators of functioning in our sample, supporting hope as an important construct shaping students’ experiences. Although students with the Hopeful profile had agency and pathways scores only slightly above the sample mean, their mean scores were substantially higher (≥1.5 SDs) than those of the students in the Low Hope profile. These findings establish a promising foundation for future work with larger samples in which a greater number of hope profiles may be identified.

Importantly, the LPA revealed a small, vulnerable subgroup of students with very low hope scores, who exhibited meaningfully worse outcomes across several psychosocial factors. Compared with the group with moderate levels of hope, the functioning of the Low Hope group was substantially worse across a broad range of adaptive functioning measures. This finding has several implications. First, only one-fifth of the sample were in the Low Hope group, which runs counter to the stereotype that all GT students are emotionally fragile and vulnerable. Nonetheless, students with the Low Hope profile reported moderate levels of depressive symptoms (i.e., ≥39/80; Beck et al., 1996; Dikmen, 2020) and severe levels of psychological distress (i.e., ≥30/50; Altun et al., 2019; Kessler et al., 2002). Second, the finding also contradicts the claims that GT students do not have emotional issues. What this finding makes clear is that there is a range of socioemotional functioning in GT groups, and that although classification as gifted may predict resilience in at-risk youth, this protection is not universal, and it is important to examine students as individuals and not through the lens of their GT classification status (Guénolé & Baleyte, 2017).

Relatedly, GT students with the Hopeful profile were not invulnerable. Our results showed that students with the Hopeful profile had scores that were above the cut scores according to the literature for mild depression (i.e., ≥33/80; Beck et al., 1996; Dikmen, 2020) and psychological distress (i.e., ≥20/50; Altun et al., 2019; Kessler et al., 2002) indicating potential areas of concern and intervention for this group as well. Although this pattern of results may be context-specific in how the entire student sample responded, it is also possible that their responses reflected shared experiences worth considering, or that another confounding variable we could not account for was present.

Another interesting finding was that the profiles differed in self-oriented perfectionism but not socially prescribed perfectionism, such that students with the Hopeful profile reported higher self-oriented perfectionism. Although we had expected hope to be inversely associated with all maladaptive outcomes, our findings are conceptually consistent. That is, given that self-oriented perfectionism involves internally derived standards associated with internal locus of control (Hewitt & Flett, 1991; Stoeber & Otto, 2006), it aligns with hope’s core components of agency and pathways thinking; self-oriented perfectionism is only problematic when students are unable to meet the standards that they set for themselves. Socially prescribed perfectionism, on the other hand, involves perceiving external demands associated with fear of failure and may not align with the autonomous goal pursuit that is central for hope (Stoeber & Rambow, 2007). Although the literature on GT students is limited, in the general population, Ashby et al. (2011) and Karababa (2020) also found similar results showing that early adolescents who reported higher adaptive perfectionism had higher levels of hope, whereas those with higher maladaptive perfectionism had lower hope compared to their peers.

More broadly, as per the TDMM, the robust literature on talent development suggests that it takes more than intellectual ability and school achievement for academic talent to be fully realized across the life course (Subotnik et al., 2011). Indeed, the psychosocial variables we explored in this sample may be necessary for adolescent intellectual potential to coalesce into outstanding achievement in adulthood. Taken together, our findings suggest that higher hope co-occurs with a constellation of adaptive developmental outcomes that may be relevant for the talent development of GT students.

Our findings underscore the importance of attending to students’ internal experiences as they navigate school and life, given that these experiences are often reflected in subjective psychosocial functioning rather than academic achievement alone. When these psychosocial dimensions go unexamined, educators may prioritize visible markers of success and inadvertently overlook students at risk for maladaptive outcomes, including depressive symptoms, negative affect, isolation, and psychological distress. Indeed, Vialle et al. (2007) found that teachers tended to use GT students’ academic success as the primary indicator of their well-being. This interpretation led to overly positive evaluations of students’ adjustment that conflicted with the GT students’ own reports of sadness and isolation. Against this backdrop, our findings replicate and extend Turkish research showing a positive association between hope and nearly identical psychosocial constructs (e.g., Atik, 2009; Cengiz et al., 2025; Çelik et al., 2015; Telef, 2020) and demonstrate that these patterns also hold for GT youth, highlighting the importance of monitoring and supporting psychosocial functioning beyond achievement. To our knowledge, this is the first study to examine hope and its correlates among GT high school students in Turkey and one of the few to explore hope profiles in the GT population.

Limitations and Future Directions

Our study had several limitations that are worth noting. First, because all participants attended the same residential high school, our sample was relatively homogeneous, limiting the generalizability of our findings to other contexts or groups of GT students. Second, the sample size was also relatively small for an LPA, which may have limited our ability to detect more hope profiles. Finally, given the reliance on self-report data collected at a single point in time, we cannot make causal claims. Future research should augment our findings by including larger and more diverse samples, using longitudinal designs, and incorporating multiple data collection methods such as qualitative studies with students and educators for in-depth inquiry, thereby building a more complete picture of how hope can potentially enhance psychosocial strengths and the process of talent development for GT students.

Implications for Theory, Research, Practice, and Policy

Our results extend previous research (e.g., Dixson et al., 2024) by applying person-centered analyses to examine correlates of hope. In doing so, we provide empirical evidence of distinct hope profiles in a non-Western gifted population and their association with indicators of well-being. In practice, our findings encourage educators to attend to potentially invisible distress and needs for support among GT students who may appear to be thriving by traditional achievement metrics. One way to address this concern is to build school environments that cultivate and monitor hope alongside academic achievement. Brief, targeted individual-level exercises can help students cultivate hope. For GT students, educators can support hope development by collaborating with learners to set stretch goals that are challenging yet attainable and responsive to individual strengths and needs (Dixson, 2020), consistent with Maree’s (2024) emphasis on uniquely tailored interventions for gifted youth.

At the small-group level, structured interventions that combine psychoeducation on hope theory with pathways-thinking goal mapping, obstacle planning, and agency-focused positive self-talk have been shown to increase students’ hope and well-being (Feldman & Dreher, 2012; Marques et al., 2011). In addition to these direct interventions, evidence from Turkish youth suggests that supportive environments characterized by caring, trusted adults are associated with higher levels of hope, underscoring the relevance of relational supports within broader school environments (Söngüt & Gözübüyük, 2025). Collectively, these findings point to key directions for designing school-based counseling and mental health support programs, advisory systems, and talent development models that intentionally foster hope among GT learners.

Footnotes

ORCID iDs

Ilke Bayazitli

Mark B. Pommer

Linsey B. Cohen

Carlos I. Recinos Bernabé

Raymond Q. Vo

Hetvi Desai

Golzar Ejadi

Frank C. Worrell

Ozge Hacifazlioglu

Funding

The research was supported by the Academic Talent Development Program at the University of California, Berkeley.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Biographies

Ilke Bayazitli is a doctoral student in School Psychology at the University of California, Berkeley. She holds a B.A. in Psychology from Boğaziçi University and an M.A. in Psychological Science from San Francisco State University. Her research focuses on promoting the well-being of youth, with particular attention to psychoeducational outcomes among underrepresented and gifted and talented students. Drawing on positive psychology, she examines risk and resilience factors that influence adolescent well-being to inform effective interventions. She also explores SEL and STEM integration in early childhood education and is interested in protective and preventive approaches to psychological practice.

Mark B. Pommer is a doctoral candidate in School Psychology at the University of California, Berkeley, where he holds an M.A.; he also earned an Ed.S. from Columbia University. His research centers on the psychology of hope across cultures and on sex-related differences in ADHD, with a particular focus on improving identification and care for underserved girls and women. These interests are rooted in a long career and ongoing practice as a school psychologist in Jackson, Wyoming.

Linsey B. Cohen is a doctoral student in School Psychology at the University of California, Berkeley. She holds a B.S. in Cognitive Studies and Child Development from Vanderbilt University. Her research asks what it means for a gifted child to thrive, exploring psychosocial dimensions of well-being in academically gifted youth that traditional achievement outcomes fail to capture. She holds particular interest in twice-exceptional students with ADHD whose neurocognitive profiles of gifts and needs often exist in tension within educational systems.

Carlos I. Recinos Bernabé is a doctoral student in School Psychology at the University of California, Berkeley. He received his B.A. from the University of Southern California in Psychology, with a minor in Education and Society. His research examines multilingual and immigrant youth, literacy and language development, and adolescent mental health and psychosocial functioning. His work pays particular attention to how academic experiences and socioemotional processes shape student well-being and trajectories of risk and resilience. Carlos is a proud immigrant from El Salvador.

Raymond Q. Vo is a doctoral student in the joint doctoral program in Special Education at the University of California, Berkeley and San Francisco State University. He holds a B.S. in Psychological and Brain Sciences from the University of California, Santa Barbara, and an M.A. in Education from the University of California, Berkeley. His research interests include dyslexia identification practices and approaches to early literacy instruction, with a particular focus on how these areas influence educational policy and student outcomes. He is currently pursuing this work with the goal of contributing to systemic educational reform through quantitative research.

Hetvi Desai is a doctoral student in School Psychology at the University of California, Berkeley. She earned her B.S. in Psychology from Purdue University and her M.A. in Applied Clinical Psychology from Penn State Behrend. Her research examines identity and culture among children and adolescents, with a focus on diverse ethno-cultural backgrounds.

Golzar Ejadi is a doctoral student in School Psychology at the University of California, Berkeley. She holds a B.S. with a double major in Biology and Psychology from the University of British Columbia and an M.S. in Clinical Psychology from San Francisco State University. Her research focuses on positive childhood development and factors influencing psychosocial outcomes, as well as supporting the well-being of parents, teachers, administrators, and school-based mental health professionals.

Frank C. Worrell, Ph.D., is a Distinguished Professor at the University of California, Berkeley. His areas of research include cultural identities, talent development, and time perspective. He is a Fellow of the American Educational Research Association, the American Psychological Association, and the Association for Psychological Science, and a member of the National Academy of Education and the Society for the Study of School Psychology. He was the 2022 President of the American Psychological Association.

Ozge Hacifazlioglu, Ph.D., is a Professor of Practice in the Leadership Programs at the University of California, Berkeley. She holds a doctorate in Educational Administration and completed her post-doctorate at Arizona State University. Prior to joining UC Berkeley, she held academic leadership roles for over 20 years, including vice rector at Hasan Kalyoncu University, interim dean at Istanbul Kultur University, and associate dean at Bahcesehir University. Her research spans higher education leadership, teacher education, communities of practice, and marginalized populations across Europe and the United States.

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A Little Hope Goes a Long Way: Identifying Profiles of Hope Among Gifted and Talented Turkish Adolescents

Abstract

Keywords

Hope Theory

Hope’s Associations With Psychosocial Functioning

Hope Profiles

The Current Study

Method

Participants

Measures

Procedure

Analytic Strategy

Results

Descriptive Statistics

LPA Results

Differences Between Profiles

Discussion

Limitations and Future Directions

Implications for Theory, Research, Practice, and Policy

Footnotes

ORCID iDs

Funding

Declaration of Conflicting Interests

Author Biographies

References