The core of the dissertation · 2023–2025 · Kyiv

How volunteer resilience is formed

Resilience is not a single trait: Hrishyn's instrument breaks it into eight components, each with its own set of factors. In a sample of 127 volunteers the study built nine regression models — one per component plus one for the integral score. Together they retained 23 predictors, and only one entered almost everywhere: social-support seeking, in eight models out of nine. This page brings the answer together as a single overview: conceptual architecture → empirical model → practical targets.

About the research

Object

the resilience of volunteers as a psychological phenomenon that forms and manifests in volunteer activity

Subject

the psychological factors, structure and conditions of resilience formation in volunteers

Sample

127 volunteers (49 women, 78 men) aged 18–60 · 3 tenure groups: newcomers — under 1 year (n=44), experienced — started with the full-scale invasion, up to 4 years (n=55), veterans — over 4 years, before the invasion (n=28)

When and where

2023–2025, under the conditions of the full-scale war in Ukraine. Carried out within the research topic of the P. R. Chamata Laboratory of Personality Psychology (state reg. no. 0122U000305)

Instruments

9 questionnaires: CD-RISC-10, Hrishyn's method, EPI, Spielberger–Khanin, Existenzskala, Längle's TEM, Shtepa's Personal Maturity Inventory, Lazarus–Folkman WCQ + the author's altruistic-orientation methodology (Barinov & Shandruk, 2025)

Analysis

descriptive statistics, Pearson linear correlation (r_xy), Kruskal-Wallis H, Mann-Whitney U, analysis of variance, factor and cluster analysis, and multiple regression analysis (9 models, R²=79.2–93.5%). Computed in Statistica 6.0

Contribution

a 4-level conceptual model of resilience formation + a validated altruistic-orientation diagnostic + a four-module formation programme, tested on 43 participants against a control group

Aim

to substantiate theoretically and investigate empirically the psychological factors and conditions of volunteer resilience formation, and to develop and experimentally test a psychological programme for forming it

127

volunteers
in the sample

regression
models

23 / 30

significant
predictors

levels of the
conceptual model

sessions
in the programme

198

sources in
the bibliography

Three levels of evidence: correlate, factor, predictor

The literature describes dozens of candidate factors of resilience — from temperament to existential meaning. Correlation on its own proves little: it is symmetric and cannot separate cause, effect and a shared third variable. The dissertation therefore puts every variable through three successive levels of testing, and reserves the word «predictor» for those that survive all three.

Correlate

Any variable statistically associated with resilience. Identified via correlation analysis. Symmetric relationship — does not indicate which causes which.

Broadest concept. Description: «moves together with resilience».

Factor

A correlate that additionally meets three conditions:

statistically significant correlation (r or ρ);
theoretical grounding of influence — a scientific framework explaining why the variable affects resilience (Maslow & Shtepa — personal maturity; Eysenck — temperament; Spielberger — anxiety; Längle — existence and FM; Lazarus-Folkman — coping; A. Beck, A. Ellis — cognitive-behavioural theory; Hobfoll — resources);
confirmed by group comparison — robust across sub-samples (Kruskal-Wallis H, Mann-Whitney U).

Mid-level. Description: «theoretically and empirically affects resilience».

Predictor

A factor that, in a regression model, retains a unique contribution to predicting resilience — after controlling for all other candidates. Has a significant β-coefficient (p < 0.05).

Narrowest, strictest. Description: «truly drives resilience, not merely co-occurs with it».

In the dissertation this path runs: dozens of correlates (Tables 2.10–2.18) → eight theoretically grounded factors (Chapter 2.3) → 23 predictors that retained a significant contribution in the regressions (Tables 2.22–2.30). The summary table below lists all 30 factors considered — those that made it through and those that dropped out.

Four principal results

The shortest summary of the nine regression models. Further down the page: what resilience consists of, how the four-level model of its formation works, which instruments measured it, and the full table of factors.

Social support — the universal engine

Seeking-social-support coping is a significant predictor in 8 of 9 regression models (β = 0.13–0.47). No other factor appears in so many models.

Conclusion: the volunteer's resilience is not an individual strength but a socially-rooted phenomenon. A lone resilient volunteer is the rare exception.

Neuroticism — the principal negative predictor

Neuroticism (emotional instability per Eysenck) lowers resilience in 4 of 9 components: orientation to challenges (β = −0.14), self-control (β = −0.31, the strongest negative effect in this model), social connectedness (β = −0.10), and optimal regulation (β = −0.23).

Conclusion: emotional lability is the key prevention target; working on it does not cure anxiety but forestalls a breakdown of resilience.

Meaning — the most compact core

The component "Self-determination and meaningfulness of life" has the highest explanatory parsimony: 3 predictors explain 90.4% of variance (seeking social support β = 0.24, accepting responsibility β = 0.11, distancing β = −0.08).

Conclusion: the sphere of meaning is the most integrated core of resilience; cultivating it yields maximum effect from minimal intervention.

The core of overall resilience

The integral indicator (CD-RISC-10) is explained by 5 key predictors at 87.5%: self-acceptance (β = 0.52), freedom (0.32), seeking social support (0.31), self-transcendence (0.25), synergy (0.15).

Conclusion: the four targets of the resilience-formation programme are not an arbitrary set but a statistically optimal target profile.

Structure of resilience: eight components and an integral score dependent variables (Y)

First — what we predict. Resilience is not a monolith: it decomposes into 8 functional components per E. Hrishyn's method + the integral CD-RISC-10 indicator for cross-validation. Each component has its own regression model (T2.22–2.30) with its own set of predictors and R². The boundary norms were determined empirically from the dissertation sample.

1
Orientation to challenges and goal achievement tendency to perceive difficulties as challenges T2.22 · R² = 82.5%
2
Self-control and ability to overcome difficulties self-regulation under pressure, persistence T2.23 · R² = 83.6%
3
Self-determination and meaningfulness of life inner authorship of life, presence of meaning T2.24 · R² = 90.4%
4
Stress resistance maintaining equilibrium under stress T2.25 · R² = 89.2%
5
Constructive coping command of adaptive coping strategies T2.26 · R² = 79.2%
6
Social connectedness community inclusion, maintaining connections T2.27 · R² = 93.5% — the highest
7
Optimal regulation flexible emotional-behavioural responding T2.28 · R² = 88.9%
8
Openness to life experience readiness to accept and learn from the new T2.29 · R² = 89.5%
∑
Overall resilience (integral indicator) summary score from CD-RISC-10 for cross-validation T2.30 · R² = 87.5%

Expand detailed cards for each component (predictors with β)

Orientation to challenges and goal achievement

Regression in T2.22 · R² = 82.5%

Tendency to perceive difficulties as challenges, to set goals and to pursue them. Expression of an active agentic stance under crisis conditions.

Sample-based norm: 16–32 points

Strongest predictors:

Seeking social support (β = 0.29)
Self-distancing (β = 0.49)
Self-transcendence (β = 0.35)
Neuroticism (β = −0.14, negative)

Self-control and ability to overcome difficulties

Regression in T2.23 · R² = 83.6%

Capacity for self-regulation under pressure, holding course despite emotional discomfort, persistent behaviour through difficulties.

Sample-based norm: 17–33 points

Strongest predictors:

Neuroticism (β = −0.31, strongest — negative)
Autonomy (β = 0.488)
Creativity (β = 0.38)
Freedom (β = 0.30)

Self-determination and meaningfulness of life

Regression in T2.24 · R² = 90.4%

A sense of inner authorship of one's life, presence of meaning, alignment of action with values. The most compact and strongest regression component (90% of variance explained by just 3 predictors).

Sample-based norm: 18–32 points

Strongest predictors:

Seeking social support (β = 0.24)
Accepting responsibility (β = 0.11)
Distancing (β = −0.08, negative)

Stress resistance

Regression in T2.25 · R² = 89.2%

Capacity to preserve functioning and psychological balance under stress. The most elaborate regression model (12 significant predictors) — effectively «assembled» from all the traits of personal maturity per Shtepa.

Sample-based norm: 14–28 points

Strongest predictors:

Self-acceptance (β = 1.08, record-high)
Synergy (β = 0.72)
Life philosophy (β = 0.71)
Contact (β = 0.60)
Decentration (β = 0.53)
+ 7 more predictors

Constructive coping

Regression in T2.26 · R² = 79.2%

Command of adaptive coping strategies — the ability to build an effective behavioural response to difficulties.

Sample-based norm: 6–17 points

Strongest predictors:

Seeking social support (β = 0.47)
FM-1 «Support, security, space» (β = 0.27)

Social connectedness

Regression in T2.27 · R² = 93.5%

Ability to establish and maintain social ties, to be embedded in a community. The highest R² across all components (93.5% of variance).

Sample-based norm: 6–12 points

Strongest predictors:

FM-2 «Relatedness, time, closeness» (β = 0.15)
Altruistic orientation (β = 0.12)
Responsibility (β = 0.17)
Confrontation (β = −0.11, negative)
Trait anxiety (β = −0.09, negative)
Neuroticism (β = −0.10, negative)

Optimal regulation

Regression in T2.28 · R² = 88.9%

Capacity to regulate one's emotional and behavioural dynamics effectively in response to the situation — a basis for flexible functioning amid chaos.

Sample-based norm: 12–26 points

Strongest predictors:

Seeking social support (β = 0.31)
Self-acceptance (β = 0.27)
Freedom (β = 0.26)
Neuroticism (β = −0.23, negative)
Trait anxiety (β = −0.19, negative)
+ FM-1, FM-2, FM-3

Openness to life experience

Regression in T2.29 · R² = 89.5%

Readiness to accept new experience, to learn from it, to integrate even painful events into one's narrative. The antithesis of frozen defences.

Sample-based norm: 6–17 points

Strongest predictors:

Seeking social support (β = 0.43)
Creativity (β = 0.40)
Altruistic orientation (β = 0.15)
Contact (β = 0.12)
FM-3 (β = 0.09)

∑

Overall resilience (integral indicator)

Regression in T2.30 · R² = 87.5% · CD-RISC-10

Summary score from the CD-RISC-10 by Campbell-Sills & Stein — a one-factor scale, an integrative measure of resilience as a personal disposition. Not the sum of the previous 8 components but a parallel instrument used for cross-validation.

Strongest predictors (the core of volunteer resilience):

Self-acceptance (β = 0.52)
Freedom (β = 0.32)
Seeking social support (β = 0.31)
Self-transcendence (β = 0.25)
Synergy (β = 0.15)
+ FM-2, FM-3, Responsibility, Accepting responsibility

How to use this: if you want to understand which «levers» drive a particular component of resilience — click on a regression model (T2.22–T2.30) and scroll the table below. If you want to target overall resilience — the main programme targets are self-acceptance, freedom of choice, social support seeking, and self-transcendence: four components from different categories that together explain 87.5% of variance.

How resilience is formed: four levels 8 categories of independent variables (X)

The eight categories of factors correspond to four levels of resilience formation, and the programme's four modules follow them, one per level. The order is substantive: from «who I am» through «why I do this» and «how I cope» to «what I do».

Personal (foundational) level

«Who I am»

Basic dispositions, traits, inner support. Without a solid foundation, subsequent levels cannot hold.

Factor categories

Personal maturity Shtepa's 10 scales
Emotional stability Eysenck EPI

Theoretical foundations

Humanistic psychology (A. Maslow, C. Rogers) — innate tendency toward self-actualisation; maturity and resilience are grounded in self-acceptance, authenticity, openness to experience
Biological theory of temperament (H. Eysenck) — neuroticism as inborn nervous-system reactivity; defines baseline emotional stability/instability as the foundation of stress response
Concept of personal maturity (O. S. Shtepa) — Ukrainian original 10-factor model of the mature personality; integrates the humanistic tradition into an empirical measurement tool

Program sessions (Module 1)

Session 1. Introduction, programme overview, baseline assessment
Session 2. Personal maturity and the volunteer's inner support
Session 3. Emotional stability and self-acceptance

Motivational-meaning level

«Why I do this»

Values, meanings, motives. The layer of «what drives» volunteer activity.

Factor categories

Existentiality Existenzskala
Fundamental motivations (FM) Längle's TEM
Altruistic orientation Barinov's own scale

Theoretical foundations

Self-Determination Theory (E. Deci, R. Ryan) — three basic psychological needs (autonomy + competence + relatedness) as conditions for intrinsic motivation and psychological well-being
Existential analysis (V. Frankl → A. Längle) — search for meaning as the principal motivational force; four fundamental motivations as conditions of existential fulfilment («I can be / I like to live / I have the right to be myself / I want to do something»)
Humanistic approach (C. Rogers) — innate growth tendency; congruence between real-self and ideal-self as a condition of healthy functioning
Theories of altruism (D. Batson — empathy-altruism hypothesis, demonstrates the selflessness of true helping; G. Allport — productive personality and prosocial values; E. Fromm — productive character, «to be rather than to have»)

Program sessions (Module 2)

Session 4. Motivation for volunteer activity
Session 5. Values and meaning of volunteer work
Session 6. Mature altruistic orientation

Regulatory level

«How I cope»

Coping strategies, emotion regulation, crisis response. The layer of «how to handle» stress and challenges.

Factor categories

Coping strategies WCQ Lazarus-Folkman
Anxiety Spielberger-Hanin

Theoretical foundations

Transactional theory of coping (R. Lazarus, S. Folkman) — stress arises not from the event itself but from its cognitive appraisal versus resources («am I able to handle this»); coping as a dynamic process of adaptive response
Cognitive-behavioural therapy (A. Beck — theory of dysfunctional beliefs and automatic thoughts; A. Ellis — rational emotive therapy, ABC model: activating event → irrational belief → emotional consequence; modifying beliefs changes the response)
Resource approach (S. Hobfoll) — Conservation of Resources theory: people have a fundamental motive to retain and accumulate resources (time, energy, status, relationships); stress arises under threat of resource loss or actual loss
Two-factor model of anxiety (C. D. Spielberger) — distinction between state (situational anxiety) and trait (stable disposition toward anxiety); each requires different interventions

Program sessions (Module 3)

Session 7. Stress and individual reactions of the volunteer
Session 8. Coping strategies for overcoming difficulties
Session 9. Emotion regulation and cognitive reappraisal

Behavioural level (integrative)

«What I do»

Integration of all previous levels into the volunteer's real behaviour. Consolidation at the behavioural level through transfer to daily practice.

Factor categories

Volunteer experience tenure structural indicator
+ integration of all categories from levels 1–3

Theoretical foundations

Systemic approach «personality–activity–environment» (O. Leontiev, S. Rubinstein, post-Soviet psychological school) — personality forms and manifests through activity; cannot change personality outside real action, cannot separate it from the environment in which it acts
Adaptation trajectories (G. Bonanno, 2004) — after a traumatic event people follow 4 typical paths: resilient (~60%, minimal symptoms), recovery, chronic distress, delayed reaction; resilience is the most common outcome, not exceptional
Existential-action integration — synthesis of the existential approach and activity theory: meaning is realised only through real actions with conscious choice, limits, and responsibility for consequences

Program sessions (Module 4)

Session 10. Conscious choice of forms of help
Session 11. Psychological boundaries and balance of involvement
Session 12. Integration of experience and final reflection

Model logic: each level rests on the previous one. Coping strategies (level 3) cannot be developed in a participant with critically low personal maturity (level 1) — it becomes a «facade» without foundation. Therefore the program proceeds sequentially: first strengthening the foundation, then building the motivational layer, then adding regulatory skills, and only at the end integrating everything into behavioural practice.

Methodological instruments quoted from the dissertation

«The empirical study used the following psychodiagnostic methods: 1) resilience diagnostic method in E. Hrishyn's adaptation; 2) the short version of the CD-RISC-10 Resilience Scale by Campbell-Sills & Stein in adaptation by Z. O. Kireieva, O. S. Odnostalko, B. V. Biron; 3) author's method for diagnosing the volunteer's altruistic orientation; 4) Existence Scale (Existenzskala) by A. Längle & C. Orgler in S. V. Kryvtsova's adaptation; 5) Test of Existential Motivations (TEM) by A. Längle in adaptation by V. B. Shumskyi, O. M. Ukolova, Ye. M. Osin, Ya. D. Lupandina; 6) Personal Maturity Questionnaire by O. S. Shtepa; 7) Eysenck Personality Inventory EPI; 8) Spielberger Anxiety Scale in Yu. L. Hanin's adaptation; 9) Ways of Coping Questionnaire by Lazarus & Folkman in L. Y. Vasserman's adaptation.»

Table view

Filter for the full table below — switch between all components, those that became significant predictors, and those that did not survive regression.

Factor category	Theory	Measurement method	Component	Predictor?	Resilience component affected
1. Personal maturity	Humanistic tradition (A. Maslow, C. Rogers, G. Allport, E. Fromm); personal maturity concept by O. S. Shtepa	Personal Maturity Questionnaire by O. S. Shtepa (10 scales)	Self-acceptance positive attitude toward self with all flaws	✓ yes	Stress resistance (β=1.08); Optimal regulation (β=0.27); Overall resilience (β=0.52)
			Creativity capacity for creative, non-standard thinking	✓ yes	Self-control (β=0.38); Stress resistance (β=0.51); Openness (β=0.40)
			Autonomy independence of choice, reliance on own decisions	✓ yes	Self-control (β=0.488); Stress resistance (β=0.49)
			Responsibility capacity to be accountable for one's actions and choices	✓ yes	Stress resistance (β=0.49); Social connectedness (β=0.17); Overall (β=0.09)
			Synergy ability to see wholeness in apparent contradictions	✓ yes	Stress resistance (β=0.72); Overall (β=0.15)
			Contactness openness and ease in interpersonal communication	✓ yes	Stress resistance (β=0.60); Openness (β=0.12)
			Life philosophy coherent, meaningful worldview	✓ yes	Stress resistance (β=0.71)
			Tolerance acceptance of people with different values and views	✓ yes	Stress resistance (β=0.51)
			Decentration ability to step out of one's own perspective	✓ yes	Stress resistance (β=0.53)
			Depth of experience capacity for intense, rich emotional experience	✓ yes	Stress resistance (β=0.52)
2. Emotional stability	Biological theory of temperament H. Eysenck	Eysenck Personality Inventory EPI — only the N scale used (in diss.: «emotional stability-instability scale»)	Neuroticism (N scale) emotional instability, anxiety, mood swings	✓ yes (minus)	Challenges orientation (β=−0.14); Self-control (β=−0.31); Social connectedness (β=−0.10); Optimal regulation (β=−0.23)
3. Anxiety	Two-factor model C. D. Spielberger (state–trait)	Anxiety scale by C. D. Spielberger in adaptation by Yu. L. Hanin	Trait anxiety stable disposition to perceive situations as threatening	✓ yes (minus)	Social connectedness (β=−0.09); Optimal regulation (β=−0.19)
3. Anxiety	Two-factor model C. D. Spielberger (state–trait)		State anxiety (situational) current anxiety level in a specific moment	✗ no	—
4. Existentiality	Existential analysis A. Längle (Viennese school, continuation of V. Frankl's logotherapy)	Existence Scale (Existenzskala) by A. Längle & C. Orgler in S. V. Kryvtsova's adaptation	Self-distancing (SD) capacity to detach from own affects	✓ yes	Challenges orientation (β=0.49)
			Self-transcendence (ST) openness to values beyond oneself	✓ yes	Challenges orientation (β=0.35); Overall (β=0.25)
			Freedom (F) capacity to choose with awareness of options	✓ yes	Self-control (β=0.30); Optimal regulation (β=0.26); Overall (β=0.32)
			Responsibility (V) acceptance of consequences	✗ no	— (not isolated in regression separately)
5. Fundamental motivations (FM)	Theory of 4 fundamental existential motivations A. Längle	Test of Existential Motivations (TEM) by A. Längle in adaptation by V. B. Shumskyi et al.	FM-1: support, security, space basic feeling: «I can be here»	✓ yes	Constructive coping (β=0.27); Optimal regulation (β=0.11)
			FM-2: relatedness, time, closeness valuing life: «I like to live»	✓ yes	Stress resistance (β=0.11); Social connectedness (β=0.15); Optimal regulation (β=0.13); Overall (β=0.11)
			FM-3: attention, fairness, value recognition self-identity: «I have the right to be myself»	✓ yes	Optimal regulation (β=0.12); Openness (β=0.09); Overall (β=0.11)
			FM-4: opportunity for action, inclusion, future value motivation of meaning: «I want to do something»	✗ no	—
6. Altruistic orientation	Concepts of altruistic orientation D. Batson, G. Allport, E. Fromm + author's concept by S. A. Barinov	Author's method of diagnosing volunteer's altruistic orientation (Barinov, Shandruk, 2025), 23 items, α=0.673, test-retest r=0.78	Altruistic orientation (overall score) selfless motivation to help others without external reward	✓ yes	Social connectedness (β=0.12); Openness (β=0.15)
7. Coping strategies	Transactional theory of stress and coping R. Lazarus & S. Folkman	Ways of Coping Questionnaire Lazarus-Folkman in L. Y. Vasserman's adaptation (8 scales)	Social support seeking turning to others for emotional and practical help	✓ yes (most universal)	8 of 9 models: Challenges orientation (β=0.29); Self-determination (β=0.24); Stress resistance (β=0.36); Constructive coping (β=0.47); Social connectedness (β=0.13); Optimal regulation (β=0.31); Openness (β=0.43); Overall (β=0.31)
			Accepting responsibility acknowledging own role in the problematic situation	✓ yes	Self-determination (β=0.11); Overall (β=0.09)
			Distancing emotional detachment without cognitive processing	✓ yes (minus)	Self-determination (β=−0.08)
			Confrontative coping aggressive venting of emotions without problem-solving	✓ yes (minus)	Social connectedness (β=−0.11)
			Planful problem-solving systematic situation analysis and step-by-step resolution	⚠ positioned as	Named in the integral conclusion of Chapter 2.4 as one of the most influential predictors; separate β not shown in reviewed regression tables T2.22–2.30 (strong correlation in T2.18: r=0.48–0.56)
			Self-control (behavioural) restraining emotional reactions during stress	✗ no	— (weak correlation r=0.24–0.39 only)
			Escape-avoidance physical or cognitive avoidance of the problem	✗ no	— (not significant in correlation either)
			Positive reappraisal reframing as opportunity for growth	✗ no	— (moderate correlation r=0.25–0.37 only)
8. Volunteer experience tenure	Adaptation trajectories research by G. Bonanno (dynamics of psychological adaptation after trauma) — directly cited in diss.	Study questionnaire, 3 groups: «beginners» (up to 1 yr, n=44), «experienced» (up to 4 yrs, n=55), «veterans» (4+ yrs, n=28)	Beginners / Experienced / Veterans volunteer tenure: up to 1 / 1–4 / 4+ years	— structural	Does not enter regression; serves as grouping variable for non-parametric comparison (Kruskal-Wallis, Mann-Whitney U)

Summary statistics

10/10

Components of Personal Maturity became predictors

100% — category with highest «predictor density»

8/9

Regression models include Social Support Seeking

Most universal coping predictor

Significant predictors in the Stress Resistance model

Richest programme target (R²=89.2%)

23 / 30

Components became significant predictors

≈77%; tenure — the eighth category — did not enter the regressions, it structures the sample

Limits of these conclusions

What the models show

Regression shows a statistical contribution, not an established causal link: the data are cross-sectional, collected at a single point in time
The high R² values (79–94%) were obtained on the same sample the models were fitted to — without validation on an independent sample they describe that sample rather than predict new cases
The sample is small (127) and unbalanced by sex (49 women, 78 men), so the sex differences should be read with caution

What the study did not test

The sample was not random: it consists of volunteers who agreed to take part — the most exhausted may never have reached the survey
The programme effect was measured immediately after completion; the durability of the change over time was not tracked
Any link between resilience and leaving volunteer work was not studied — the dissertation draws no conclusion on it

Who can use these results

What can be taken into practice from this — and what these data cannot support.

For psychologists

A validated diagnostic instrument for a volunteer's altruistic orientation (Cronbach's α 0.673; test–retest r = 0.78, p < 0.0001 on 67 people after two months) and a resilience-formation programme whose four modules match the levels of the model.

The author describes α = 0.673 as an acceptable initial level — the instrument suits group diagnostics, but individual conclusions should be supported by other data.

For volunteer coordinators

Social-support seeking entered eight models out of nine, and the most experienced volunteers significantly outperform newcomers on all eight components of resilience. That is an argument for making a supportive environment and mentoring of newcomers part of how the work is organised.

What the data do not say: the study examined neither volunteer turnover nor particular team formats, so prescriptions such as an optimal group size cannot be derived from it.

For volunteers

The model of general resilience rests mainly on self-acceptance (β = 0.52), inner freedom (0.32), a readiness to ask for support (0.31) and the capacity to relate oneself to something larger (0.25).

These are measures taken at one point in time, not a prescription. But they do point somewhere: resilience here looks more like a matter of relationships and one's stance towards oneself than of enduring alone.

For researchers

The four-level model of resilience formation (personal → motivational-meaning → regulatory → behavioural) and the full set of nine regression models with their β-coefficients, suitable for replication in other helping professions.

The obvious next steps are validation on an independent sample and a longitudinal design that would allow claims about causation rather than association.

Where to go next

This page is a map of the research. The individual parts are unpacked in other sections of the site:

Full dissertation text

All three chapters, 37 tables, 83 figures, 197 sources.

Read →

Dissertation FAQ

Questions and answers across 6 sections: from conceptual boundaries to practical application.

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122

Glossary

Terms, concepts, statistical methods. Cross-references and thematic clusters.

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Published articles

Peer-reviewed publications on the dissertation topic — from concept to validation.

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How to cite

Barinov, S. A. (2026). Psychological features of resilience formation in volunteers [PhD dissertation, G. S. Kostiuk Institute of Psychology, NAES of Ukraine]. Chapter 2, section 2.4: Regression models of resilience predictors, tables 2.22–2.30.