SOLACE Spectrum: A Personality Assessment for Personal Growth in Therapy

Abstract

Personality assessment has long been recognized as a valuable tool for understanding individual differences with implications for self-understanding and growth-related processes. Building on the development of the Personality Spectrum Analysis (PSA), the present study evaluated the SOLACE Spectrum, a revised and expanded measure designed to provide a reliable and accessible framework for understanding personality in therapeutic and relational contexts. Data were collected from 1021 adults through online administration, and exploratory factor analysis revealed six components: Stability, Optimism, Leadership, Achievement, Compassion, and Extroversion. The instrument demonstrated strong internal consistency (α = 0.91) and robust test–retest reliability (0.851–0.922), indicating stability over time. Findings support the SOLACE Spectrum as a psychometrically sound measure that can inform understanding of personality traits, relationship processes, and personal growth processes. Its application may assist professionals in therapy, counseling, and educational or organizational settings by providing descriptive feedback on personality dimensions, highlighting areas of strength, and identifying potential areas for reflection and personal insight.

1. Introduction

Understanding personality is central to psychological research and practice, as it shapes identity development, personal growth, and well-being across the lifespan. While personality theories trace back to antiquity, validated and reliable assessments emerged primarily in the 19th century and have continued to evolve in response to advances in psychology and clinical practice. These instruments not only provide insight into individual differences but also serve as tools for fostering self-awareness, guiding therapeutic interventions, and supporting growth in relational, academic, and career domains. This article examines prominent personality assessments with attention to their efficacy and applicability, with a particular focus on the SOLACE Spectrum, a framework designed to enhance understanding of personality in the service of personal development and well-being.

Personality plays a fundamental role in psychology, shaping how individuals develop their sense of self, pursue personal growth, and psychological health (Bagby et al., 2016; Bucher et al., 2019). Personality psychology examines enduring patterns of thought, emotion, and behavior, with attention to both stability and variability across contexts (American Psychological Association, 2018). Scholars have long debated definitions, but most agree that personality reflects the consistent ways individuals interact with the world and adapt to their environment (Allport, 1961; Boag, 2011; Eysenck, 1970). Trait theories, in particular, propose that central dimensions of personality can predict behavior, though these must be understood alongside situational and biological influences (Boag, 2011; Friedman & Schustack, 2003; Widiger et al., 2019). Biological temperament—such as tendencies toward introversion or extroversion, emotional reactivity, or impulsivity—further shapes personality expression (Eysenck, 1970). Taken together, research supports the view that personality is best understood as enduring yet flexible patterns of behavior and interaction that provide meaningful insight into human motivation.

Efforts to translate theory into practice have led to numerous personality assessments, each with distinct strengths and limitations. Rosenblad (2014) developed the Personality Spectrum Analysis (PSA) as a practical, reliable, and accessible tool for identifying major personality dimensions. Based on data from 800 participants, the PSA was written at approximately a third-grade reading level to maximize accessibility and demonstrated strong psychometric properties, including evidence of content and construct validity. Internal consistency reliability for the overall instrument was 0.82, with individual component reliabilities ranging from 0.74 to 0.88, indicating acceptable to high reliability. Factor analysis identified six personality components—Achievement, Leadership, Compassion, Stability, Socializing, and Optimism—each characterized by distinct clusters of traits. To enhance clarity and clinical application, the framework was later refined into the SOLACE Spectrum, an acronym underscoring the role of personality awareness in providing “solace,” or comfort, through greater self-understanding and improved relationships.

1.1. Current Research Applications of Personality Assessment

Personality assessment has proven valuable in current research of counseling and supervision contexts. In clinical practice, assessment results support diagnosis, strengthen therapeutic alliance, guide treatment selection, and foster client insight (Bucher et al., 2019; Costa, 1991; Delgadillo et al., 2020; Holtzman & Raskin, 1989; Kamphuis & Finn, 2018). Clients who understand their personality patterns are better able to recognize strengths and address challenges, while counselors can tailor interventions to individual needs (Costa & McCrae, 2008; Delgadillo et al., 2020; Samuel et al., 2018). For example, individuals lower in openness may benefit from directive approaches, while those higher in openness may respond more effectively to experiential methods (Costa, 1991; Samuel et al., 2018). Personality assessment is also applied in couples and family counseling, where greater awareness of personality similarities and differences helps reduce conflict, improve communication, and enhance relational satisfaction (Lampis et al., 2018; Sperry & Carlson, 2000). Research further indicates that personality traits shape financial behaviors, conflict patterns, and relational adjustment (Jeanfreau et al., 2018; Myers et al., 2003). In supervision, both supervisors and trainees benefit from awareness of personality dynamics, which can improve communication, reduce conflict, and help trainees manage the stress of clinical training (Lewis et al., 2022; Rosenblad, 2014).

Beyond therapy, personality traits play a central role in shaping adolescents’ identity development (Hua & Zhou, 2023; Normandin et al., 2023). In addition, personality assessments have been widely used in career counseling, where matching individuals with roles that align with their traits is linked to higher job and life satisfaction (Granello & Young, 2019; Sowumni, 2022). In these contexts, personality serves as both a predictor of vocational success and a guide to well-being (Hua & Zhou, 2023).

1.2. Overview of Contemporary Personality Assessment Tools

1.2.1. Myers–Briggs Type Indicator (MBTI)

Several well-known assessments illustrate the field’s diversity. The Myers–Briggs Type Indicator (MBTI) was derived from Carl Jung’s (1921/1974) theory of psychological types, which posited that personality arises from the interaction between introversion and extraversion and four mental functions—sensing, intuition, thinking, and feeling—later expanded by Briggs and Myers to include judgment and perception (Pearman & Albritton, 1997). The Myers–Briggs Type Indicator (MBTI) categorizes individuals into 16 types, with results presented through four-letter codes that can be difficult for clients to recall and apply without professional interpretation. While the MBTI has a strong research base and is easy to administer, it is relatively costly, and its deeper interpretive materials are dispersed across multiple sources, making it less accessible for everyday use (Myers et al., 2003).

1.2.2. Big Five and NEO PI-R

The Big Five and NEO PI-R are grounded in trait theory and the lexical hypothesis, suggesting that enduring traits can be empirically identified through language and observed behavior (Costa & McCrae, 2008; Friedman & Schustack, 2003). These provide robust trait measures with high reliability, though their multidimensional scoring often requires the client to remember and interpret multiple domain and facet scores, which can limit their direct application to relationships or personal growth (Granello & Young, 2019). Furthermore, while early domains have shown strong reliability, the additional two domains of the NEO PI-R have required further validation (Piedmont, 2006).

1.2.3. 16pf

The Sixteen Personality Factor Questionnaire (16pf) emerged from Raymond Cattell’s factor-analytic model of personality, which identified clusters of correlated behaviors representing underlying dimensions of personality (H. E. Cattell & Mead, 2008; R. B. Cattell & Schuerger, 2003). Despite its comprehensive nature, the 16PF’s presentation of multiple global and primary factors may overwhelm clients who struggle to recall or apply so many dimensions in daily life. Reliability coefficients for the 16PF range from questionable to good (0.60–0.89; A. Field, 2009), and while test–retest stability is stronger, it remains a relatively expensive and complex assessment to interpret.

1.2.4. StrengthsFinder or CliftonStrengths

The StrengthsFinder (now CliftonStrengths) draws from positive psychology and talent theory, emphasizing innate patterns of thought, feeling, and behavior that can be developed into strengths. StrengthsFinder identifies individual talents and work styles but is framed more narrowly around occupational strengths making it less suitable for therapeutic exploration of interpersonal or emotional dynamics (Rath & Clifton, 2017).

1.2.5. Enneagram

The Enneagram integrates insights from ancient character typologies and modern psychodynamic theory, describing nine core types organized around motivational and defense patterns. Although it offers an intuitive typology widely recognized in popular culture, empirical support for its construct validity remains mixed (Newgent et al., 2017). In addition, the Enneagram’s system of labeling types by number can make it difficult for individuals to recall what each number represents—both for themselves and for others they are in relationship with—limiting its practical application in improving relational understanding and communication.

1.2.6. Personality Spectrum Analysis (PSA)

Finally, the Personality Spectrum Analysis (PSA) and subsequent SOLACE Spectrum are rooted in Adlerian theory, emphasizing social interest, relational functioning, and the individual’s unique style of life (Adler, 1956; Watts, 2012). The PSA operationalized these ideas into a practical typology to promote self-understanding and relational health, with the SOLACE Spectrum further refining the model for contemporary therapeutic and developmental use (Rosenblad, 2014).

While each assessment contributes valuable insight, limitations remain in cost, accessibility, and their usability in everyday contexts and relationships. Many popular instruments are either too expensive for routine use, too complex for clients to internalize, or too narrowly focused to address both intrapersonal and interpersonal functioning. The SOLACE Spectrum was developed to bridge these gaps—providing a theoretically grounded, psychometrically sound, and easily interpretable tool that fosters self-awareness, relational growth, and psychological well-being. The present study aims to clarify the personality dimensions originally identified in the PSA and to verify the factor structure, validity, and reliability of the SOLACE Spectrum as a tool aimed at providing insights into personal growth, relational health, and psychological well-being.

2. Materials and Methods

2.1. Transparency and Openness

All data are publicly available on the Open Science Framework (OSF) at www.osf.io/cmvkn. The study design and analyses were not preregistered. Data were analyzed using IBM SPSS Statistics (Version 29). The study was approved by the Hardin-Simmons University Institutional Review Board (IRB) in compliance with the DFFS Regulations for the Protection of Human Subjects (45 CFR-46).

2.2. Participants

2.2.1. Main Sample

A priori power considerations: Given the 90-item instrument and planned factorial analyses, we targeted a sample of approximately 450–600 participants. This target aligns with commonly cited recommendations of at least five participants per item for factor analysis (Comrey & Lee, 1992; MacCallum et al., 1999) and ensures adequate power and stability for confirmatory factor analysis of a six-factor model (Fabrigar & Wegener, 2012). Additionally, this sample size provides more than 80–90% power to detect medium-sized correlations (r ≈ 0.30; Cohen, 1988).

The final sample for the SOLACE Spectrum revised instrument comprised 1021 adults. Of these, 69.4% identified as female and 30.6% as male, compared to U.S. Census figures of 51% female and 49% male. In terms of race and ethnicity, 73.7% identified as White (U.S. average = 60.1%), 12.3% as Hispanic (U.S. = 18.5%), 5.1% as African American (U.S. = 13.4%), 3.4% as Asian American (U.S. = 5.9%), 0.7% as Native American (U.S. = 1.3%), 2.8% as Multiracial (U.S. = 2.8%), and 2% as Other (U.S. = 1.3%).

Table 1. Participant Demographic Information (N = 1021).

Participants	N	%
Age
18–19	313	30.7
20–29	348	34.1
30–39	119	11.7
40–49	94	9.2
50–59	86	8.4
60–69	50	4.9
70–79	7	0.7
80 and up	1	0.1
Missing	3	0.3
Gender
Female	709	69.4
Male	312	30.6
Race/Ethnicity
White	752	73.7
Hispanic or Latino	126	12.3
African American	52	5.1
Asian	35	3.4
Native American	7	0.7
Multi-racial	29	2.8
Other	20	2.0
Marital Status
Single	607	59.5
Married	352	34.5
Separated	5	0.5
Divorced	48	4.7
Widowed	8	0.5
Income
Less than $20,000	557	54.6
$20,001–50,000	240	23.5
$50,001–80,000	153	15.0
$80,001–110,000	46	4.5
Over $110,000	25	2.4
Level of Education
Not completed high school	73	7.1
Completed high school	178	17.4
Some college	259	25.4
Associate’s Degree	55	5.4
Bachelor’s Degree	238	23.3
Graduate Degree	218	21.4

provides full demographic information.

2.2.2. Test–Retest Subsample

A separate subsample of 138 participants from the main dataset completed the SOLACE Spectrum on two occasions to assess test–retest reliability. Test–retest reliability examines the stability of results across multiple administrations of the same instrument. Although a minimum of 50 participants is recommended (Fraenkel & Wallen, 2006), power analysis indicated that a sample of 22–28 would be sufficient to detect a correlation of 0.80 with α = 0.05 and a medium effect size (Stevens, 2009). Thus, the sample of 138 participants provided power exceeding 0.94.

Participants self-reported the number of prior completions and the time elapsed since the previous completion. Only matched-pairs were retained for analysis to ensure data integrity. Intervals between completions ranged from 1 week to 74 months (M = 6 months). Although the range was broad, prior research supports the relative stability of personality traits across extended time periods, allowing for long-term test–retest comparisons (Costa & McCrae, 2008). Data were reviewed prior to analysis to verify accurate matching and ensure that no missing values were present in the paired dataset.

The test–retest sample was primarily between ages 20–29 (41.0%), female (69.1%), White (70.5%), single (66.9%), low-income (<$20,000/year, 62.6%), and having completed some college (29.5%). Detailed demographics are presented in

Table 2. Test–Retest Participant Demographic Information (N = 138).

Participants	N	%
Race/Ethnicity
White	98	70.5
Hispanic or Latino	17	12.2
African American	12	8.6
Asian	5	3.6
Native American	0	0
Multi-racial	5	3.6
Other	2	1.4
Marital Status
Single	93	66.9
Married	39	28.1
Separated	5	3.6
Divorced	1	0.7
Widowed	1	0.7
Income
Less than $20,000	87	62.6
$20,001–50,000	29	20.9
$50,001–80,000	14	10.1
$80,001–110,000	5	3.6
Over $110,000	4	2.9

.

2.3. Measures/Instruments

2.3.1. Personality Spectrum Analysis Development

Rosenblad (2014) created the Personality Spectrum Analysis (PSA) as an accessible personality assessment. In its validation, the PSA was administered online to more than 1000 participants, of whom 800 were retained using stratified random sampling. The PSA demonstrated acceptable psychometric properties. Content and construct validity were established through literature, expert review, and factor analysis. Reliability was 0.82 overall, with component reliabilities ranging from 0.74 to 0.88, and a reading level of approximately 3.1 (Flesch-Kincaid). The PSA identified six personality components—Achievement, Leadership, Compassion, Stability, Socializing, and Optimism.

2.3.2. SOLACE Spectrum

The SOLACE Spectrum refines and expands the PSA, retaining the six dimensions—Stability, Optimism, Leadership, Achievement, Compassion, and Extroversion—with revised labels and test items for greater clarity and applicability. The ‘Socializing’ dimension was renamed ‘Extroversion’ so that each label would begin with a different letter, forming the word ‘SOLACE’—symbolizing the comfort gained from better understanding yourself. Development of the SOLACE Spectrum followed standard test construction practices (Sheperis et al., 2020). A table of specifications was created to align content areas with the PSA-derived components. PSA items with low correlation values were revised or replaced with new items supported by the literature. Subject matter experts rated each item on a 5-point scale (1 = very poor to 5 = very good) for how well it represented its designated personality type. At least 25 questions were created for each domain. The 15 highest-rated items per dimension, based on inter-rater agreement, were retained for the final instrument. The instrument includes 90 items on a 5-point Likert scale of (1) almost never, (2) rarely, (3) sometimes, (4) often, and (5) almost always (See Appendix A). The measure emphasizes Adlerian principles, including social interest, relational functioning, and individual style of life.

2.4. Procedure

The study employed a quantitative survey design to collect self-report data on personality traits. Participants were recruited through convenience sampling (e.g., university courses taught by the primary investigator, local career counseling services, conference presentations, social media, and email signature links). Snowball sampling also occurred as participants shared the instrument with peers and family, extending recruitment across states and internationally. Approximately half of the participants were recruited through convenience sampling, and half through snowball sampling. After consenting, participants completed the SOLACE questionnaire online. For test–retest reliability, responses from repeated completions were matched, anonymized, and stored securely. Outliers and invalid cases were later screened (e.g., via Mahalanobis distance).

2.5. Scoring

Two items were reverse scored: Item #49 (“I do not like to take risks”) was reversed so that higher values reflected greater risk-taking (“I like to take risks”), and Item #50 (“I do not get worried easily”) was reversed so that higher values indicated greater worry or emotional reactivity (“I get worried easily”).

Each of the six personality factor subscales was calculated by summing the corresponding items as follows:

• Stability: Items 1, 7, 13, 19, 25, 31, 37, 43, 49 (reversed), 55, 61, 67, 73, 79, 85;
• Optimism: Items 2, 8, 14, 20, 26, 32, 38, 44, 50 (reversed), 56, 62, 68, 74, 80, 86;
• Leadership: Items 3, 9, 15, 21, 27, 33, 39, 45, 51, 57, 63, 69, 75, 81, 87;
• Achievement: Items 4, 10, 16, 22, 28, 34, 40, 46, 52, 58, 64, 70, 76, 82, 88;
• Compassion: Items 5, 11, 17, 23, 29, 35, 41, 47, 53, 59, 65, 71, 77, 83, 89;
• Extroversion: Items 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78, 84, 90.

Raw subscale totals were transformed into z-scores to enable comparisons across dimensions within individual participants. For each individual, the z-scores across all six scales were centered at zero, with scores above zero reflecting traits more dominant in behavioral expression and scores below zero reflecting relatively less expressed tendencies. An online scoring calculator is available at www.SOLACESpectrum.com, which provides automated scoring and immediate feedback for users.

2.6. Data Analysis

Factorability checks: Mahalanobis distance was computed, and cases exceeding χ² = 137.21 were excluded. The Kaiser–Meyer–Olkin (KMO) = 0.92 and sample size (>500) indicated excellent adequacy (A. Field, 2009; Hutcheson & Sofroniou, 1999). Bartlett’s Test of Sphericity was significant (p < 0.001), supporting factorability. Reproduced correlations ranged from –0.003 to 0.655, and only 8% of residuals exceeded 0.05, well below the 50% threshold, confirming linearity assumptions.

Factor extraction: Exploratory factor analysis was conducted using Equamax rotation, an orthogonal method that balances the simplification of variable loadings (as in Varimax) with the simplification of factor structures (as in Quartimax). This approach was selected to retain uncorrelated factors while improving interpretability across the multidimensional personality structure of the SOLACE Spectrum. Equamax was preferred over other orthogonal methods (e.g., Varimax) for its ability to balance item and factor simplicity, and over oblique rotations (e.g., Promax) to maintain orthogonality for clearer factor interpretability and independent subscale scoring (Tabachnick & Fidell, 2019). Six components were extracted.

Reliability testing: Cronbach’s α for internal consistency. Intraclass correlation coefficients (ICCs) with 95% confidence intervals were computed using a mean rating (k = 2), absolute agreement, and a two-way mixed-effects model (Koo & Li, 2016). Bland–Altman analysis assessed agreement across administrations.

3. Results

3.1. Test–Retest Reliability

Test–retest reliability was examined using a subsample of 138 participants who completed the SOLACE Spectrum on two separate occasions. Temporal stability was assessed through intraclass correlation coefficients (ICCs) calculated between the initial and subsequent administrations. Analyses were conducted using a two-way mixed-effects model with absolute agreement to evaluate the consistency of scores across time points.

ICCs for all six SOLACE components ranged from good to excellent (see

Table 3. Intraclass Correlations between the test and retest assessment.

Component	ICC	95% Confidence Interval		Agreement
		Lower	Upper
Stability	0.881	0.832	0.915	Good to Excellent
Optimism	0.919	0.887	0.942	Good to Excellent
Leadership	0.883	0.837	0.917	Good to Excellent
Achievement	0.851	0.792	0.893	Good
Compassion	0.878	0.830	0.913	Good to Excellent
Extroversion	0.922	0.891	0.944	Good to Excellent

Note. ICC reliability determinants used were: values less than 0.5 were poor, values between 0.5 and 0.75 were considered fair, values between 0.75 and 0.9 were good, and values over 0.90 were considered excellent reliability (Koo & Li, 2016; Perinetti, 2018).

), demonstrating strong temporal stability. Specifically, ICCs ranged from 0.851 to 0.922 across dimensions, indicating good to excellent agreement according to established benchmarks (Koo & Li, 2016; Perinetti, 2018; Cicchetti, 1994).

To further evaluate agreement between test and retest administrations, Bland–Altman analyses were conducted. These analyses indicated minimal mean bias (<0.1) across all SOLACE components (Bland & Altman, 1986, 1999). Between 92.8 and 94.9% of score differences fell within confidence limits, demonstrating strong overall agreement. Although some proportional bias appeared in Extroversion, 93.5% of differences remained within the limits of agreement (see

Table 4. Bland–Altman limits of agreement analysis.

Component	Difference Mean (SD)	95% Confidence Interval		% Outside the LoA Interval	% Within the LoA Interval
		Lower	Upper
Stability	0.099 (0.53)	−0.932	1.130	5.1%	94.9%
Optimism	−0.056 (0.43)	−0.899	0.788	5.8%	94.2%
Leadership	−0.038 (0.50)	−1.015	0.939	5.8%	94.2%
Achievement	0.030 (0.51)	−0.979	1.039	7.2%	92.8%
Compassion	0.016 (0.48)	−0.926	0.958	7.2%	92.8%
Extroversion	−0.051 (0.51)	−1.060	0.957	6.5%	93.5%

).

Together, these findings provide strong evidence of the temporal stability and reliability of the SOLACE Spectrum across both short- and long-term intervals, supporting its use as a consistent measure of personality attributes over time.

3.2. Factor Analysis

After excluding multivariate outliers, KMO and Bartlett tests confirmed sampling adequacy and factorability. Six factors were extracted, explaining 40.95% of the variance. Though moderate, this variance is consistent with typical findings in personality and social–behavioral research, where complex constructs and item heterogeneity often limit explained variance (Costello & Osborne, 2005; Fabrigar et al., 1999).

3.3. Internal Consistency

The overall SOLACE Spectrum demonstrated strong reliability, with Cronbach’s α = 0.91. Subscale reliabilities ranged from 0.72 to 0.88, indicating acceptable to high internal consistency across dimensions (Sheperis et al., 2020; see

Table 5. Component Cronbach’s α Reliability Coefficients.

Component	Cronbach’s α	Reliability Determinant
1	0.88	High
2	0.83	High
3	0.85	High
4	0.88	High
5	0.81	High
6	0.72	Acceptable

).

3.4. Factor Descriptions

Each component is described below (with number of items, α, and variance explained):

• Achievement (α = 0.88; 19 items; 8.52% variance): Characterized by initiative, decisiveness, productivity, and high standards; individuals are efficient problem-solvers but may become over-responsible.
• Compassion (α = 0.83; 17 items; 7.37% variance): Defined by generosity, loyalty, and service orientation; individuals gain self-worth through helping others. One item (reverse-coded) indicated attraction to highly emotional individuals.
• Optimism (α = 0.85; 16 items; 7.20% variance): Marked by positivity, calmness, and resilience; individuals maintain a relaxed, hopeful outlook even during crises.
• Extroversion (α = 0.88; 13 items; 7.12% variance): Associated with sociability, expressiveness, and energy in group settings; individuals thrive in social contexts and are often perceived as charming and likable.
• Leadership (α = 0.81; 16 items; 5.86% variance): Defined by risk-taking, perseverance, and authority-seeking; individuals exhibit a strong work ethic, strive for recognition, and prefer control in group settings.
• Stability (α = 0.72; 9 items; 4.89% variance): Characterized by caution, tradition, and a preference for predictability; individuals seek security and avoid uncertain or embarrassing situations.

Full item loadings and reliabilities are presented in

Table 6. Primary Component Loadings from the Rotated Factor Matrix.

Item	Variable	Component
		1	2	3	4	5	6
9	Initiative	0.690
15	Take-charge	0.647
43	Productive in challenge	0.628
10	Productive	0.615
52	Efficient	0.609
28	Accept challenge	0.572
16	Problem-solve	0.551
40	Goal-oriented	0.510
34	Over-responsible	0.488
58	Detail problem-solve	0.473
3	Decisive	0.466
76	Skilled	0.458
64	Right way	0.453
55	Reliable	0.429
22	High standards	0.419
39	Strong	0.410
4	Charts	0.355
27	Influential	0.354
88	Not relaxed	0.327
23	Concern for others		0.757
11	Thoughtful		0.735
35	Help others		0.732
59	Sacrificial		0.695
41	Considerate		0.693
89	Generous		0.608
29	Listen		0.535
53	Serve		0.525
77	Worth from helping		0.513
5	Help by problem-solve		0.494
71	Polite		0.474
65	Emotional intelligence		0.423
83	Accept others		0.397
86	Don’t like emotions		−0.381
19	No conflict		0.375
17	Forgive		0.370
47	Loyal		0.367
44	Calm under pressure			0.700
62	Easy-going			0.678
68	Level-headed			0.608
32	Clear under pressure			0.591
14	Calm under pressure 2			0.581
38	Not upset			0.553
56	Relaxed			0.547
61	Self-control			0.515
31	Clear-headed			0.512
74	Carefree			0.509
26	Calm in crisis			0.475
20	Optimistic 3			0.452
8	Optimistic 2			0.362
75	Future vision			0.356
80	Not detailed			0.342
2	Optimistic			0.332
42	Social				0.783
24	Time with others				0.707
6	Make friends				0.702
18	Tell others				0.691
36	Extrovert				0.668
12	Expressive				0.629
66	Like groups				0.627
30	Lots friends				0.560
72	Center attention				0.527
60	Overshare				0.507
84	Charming				0.475
48	Depend on others				0.450
90	Work with others				0.435
82	Recognition for work					0.659
81	Outperform					0.620
21	Want recognition					0.595
45	Express strength					0.585
87	Authority					0.538
57	Want respect					0.538
63	Want challenge					0.462
51	Want it right way					0.419
33	Want excitement					0.419
69	Often right					0.390
70	Perfectionist					0.388
73	Self-sufficient					0.365
49	Take risks					0.346
78	Decide with heart					0.338
54	Want acceptance					0.332
67	No change					0.314
25	Know what to expect						0.674
13	Want safety						0.594
7	Careful plan						0.586
1	Want facts/prepare						0.532
79	Want expectations						0.511
37	Avoid embarrassment						0.506
46	Facts to problem-solve						0.485
85	Traditional						0.378
50	Worried						0.285

Factor loadings greater than 0.30 are displayed only for the factor where the loading was the highest. Factor loadings greater than 0.40 are in boldface.

. Factor loadings of 0.30 or higher are generally considered the minimum threshold for inclusion on a factor (A. P. Field, 2018; Tabachnick & Fidell, 2019). Loadings >0.40 are bolded. Although item 50 had a corrected item-total correlation just below the recommended 0.30, it was retained because it represented the highest loading for its factor, and its removal did not improve the reliability of the component. Therefore, it was retained to preserve theoretical coverage and scale consistency. Though the question is the opposite of worried, it is reverse-scored and labeled worried.

For complete factor loadings above 0.10 after Equamax rotation, see Appendix B. Because personality is conceptualized as a spectrum, some variables load substantially on two components; the highest loading was used to assign each trait to its primary personality type, though certain traits may be expressed across multiple types.

4. Discussion

The SOLACE Spectrum advances personality assessment by combining psychometric rigor with practical usability. Grounded in Adlerian principles of social interest, relational functioning, and individual style of life (Adler, 1956; Watts, 2012), the instrument operationalizes these principles into six dimensions—Stability, Optimism, Leadership, Achievement, Compassion, and Extroversion—translating theory into a usable framework for applied settings. The primary aim of SOLACE is to provide a theoretically grounded, empirically validated, and practically usable personality assessment that supports self-awareness, relational understanding, and personal growth.

This study extends prior work with the Personality Spectrum Analysis (PSA) by validating the SOLACE Spectrum in a substantially broader and more diverse participant base. While approximately 90% of participants were from Texas, respondents also represented multiple U.S. states and international locations, enhancing the generalizability of the findings. Psychometric evaluation confirmed a six-factor structure consistent with theoretical expectations, with each dimension demonstrating good to excellent internal consistency and strong test–retest reliability. These findings support the instrument’s construct validity and suggest that SOLACE reliably captures meaningful personality factors.

The accessible and descriptive nature of SOLACE allows users to identify personal strengths and areas for growth, apply insights in interpersonal interactions, and align behavior patterns with occupational preferences, potentially enhancing career satisfaction and engagement. Awareness of one’s own traits, as well as the traits of others, may foster empathy, tolerance, and understanding in relational contexts such as couples, families, and professional teams, which can contribute to improved communication and reduced relational tension. Although SOLACE provides descriptive feedback and supports reflection, its predictive validity regarding personal growth, self-awareness, relational satisfaction, or well-being has not yet been established. The instrument’s value lies in summarizing personality traits in an accessible format to inform counseling, supervision, and interpersonal understanding without overextending claims.

Several methodological limitations warrant consideration. The sample, though geographically diverse, was primarily composed of English-speaking participants from Texas, which may limit broader generalizability. Data were collected through self-report measures, introducing potential response bias. While exploratory factor analysis confirmed the six-factor structure, confirmatory analyses with independent samples are needed to evaluate stability and generalizability. Future research should examine predictive and discriminant validity across applied contexts, as well as potential cross-cultural validation and longitudinal outcomes.

Future studies may also explore the development of a shorter version of SOLACE that retains the core content of each dimension while improving ease of administration and accessibility for both researchers and practitioners. Although a shorter form may slightly reduce reliability, high correlations with the full instrument could ensure accurate measurement of the primary dimensions, supporting broader adoption in applied research, counseling, educational, and organizational settings.

5. Conclusions

The SOLACE Spectrum represents an accessible, evidence-based instrument that translates Adlerian theory into a practical framework for personality assessment. Results from this study confirm its reliability and validity across six dimensions, offering a robust tool for both research and applied contexts.

When used in counseling or organizational settings, the SOLACE Spectrum can support clients in identifying personal strengths, understanding relational dynamics, and making informed career choices. While the instrument shows promise for enhancing self-awareness, relational understanding, and vocational alignment, further research is needed to examine its predictive utility for personal growth, well-being, and applied outcomes. Overall, the SOLACE Spectrum contributes to the field by providing a theoretically informed, empirically validated approach to understanding personality in diverse contexts.