Identifying Patient Strengths Instruments and Examining Their Relevance for Chronic Disease Management: A Systematic Review

Deshira D. Wallace, PhD¹; Ruchir N. Karmali, PhD^1,2; Christine Kim, PhD¹; Ann Marie White, EdD^3,4; Kurt C. Stange, MD, PhD⁵; Kristen Hassmiller Lich, PhD¹ (View author affiliations)

Suggested citation for this article: Wallace DD, Karmali RN, Kim C, White AM, Stange KC, Lich KH. Identifying Patient Strengths Instruments and Examining Their Relevance for Chronic Disease Management: A Systematic Review. Prev Chronic Dis 2021;18;200323. DOI: https://doi.org/10.5888/pcd18.200323external icon.

PEER REVIEWED

Abstract

Introduction

Most health care focuses on patients’ deficits to encourage behavior change. A strengths-based approach, which relies on identifying patient strengths, has great potential to facilitate behavior change for chronic disease management. Little is known about instruments used to assess patient strengths. We conducted a systematic review to identify validated instruments that assess personal strengths by using a theory elaboration approach.

Methods

We searched 8 databases including Web of Science, Cumulative Index of Nursing and Allied Health (CINAHL), and PsycINFO (through July 2019) to identify peer reviewed, English-language studies that described strength-based instruments. Thereafter, we evaluated the validity and reliability of the instruments according to 18 Scientific Advisory Committee of the Medical Outcome Trust (SACMOT) criteria, and used an inductive, iterative editing process to identify constructs measured by the instruments.

Results

We identified 26 instruments that met our inclusion criteria. The instruments were validated in various clinical and nonclinical populations. Only 4 instruments met most of the SACMOT criteria for validation. We extracted 91 unique constructs that fell into 3 domains: inner strengths (49), external strengths (13), and personality constructs (29).

Conclusion

A limited number of reliable and valid instruments are available to assess strengths for the adult population, particularly for clinical populations. Internal strengths can be leveraged to improve patient health; however, the development and validation of additional instruments to capture personal strengths is necessary to examine the multilevel influence of external strengths on individual behaviors and well-being.

Top

Introduction

Approximately half of all US adults have 1 or more diagnosed chronic conditions, such as diabetes, heart disease, and arthritis (1). In 2016, the direct health care cost associated with chronic health conditions was $1.1 trillion dollars (2). Chronic conditions can be managed successfully by changing unhealthy behaviors (3–7). Patients, with their care team, can identify strategies and leverage skills to regulate behaviors (4). A strengths-based approach to chronic disease management can support self-management and behavior change.

The strengths-based approach emerged from the social work field and counteracts the deficit-based approach from the health science professions. A deficit-based approach focuses on what is wrong with patients rather than recognizing their strengths and resources (8). The strengths-based approach assumes that individuals have the capacity to grow, do the best they can, and know what is best for them (8). Strengths include personal attributes such as faith, use of humor, flexibility; interpersonal assets such as friends or family who can be called on for help; and external resources such as ability to access community resources for health. Whereas deficit-based approaches to chronic disease management focus on patients’ problems and behavioral shortcomings (eg, focusing on patient challenges in engaging with recommended behaviors), Rotegård et al (9) defined patient strengths, or health assets, as “the repertoire of potentials — internal and external strength qualities in the individual’s possession, both innate and acquired — that mobilize positive health behaviors and optimal health/wellness outcomes.” In practice, the care team works with a patient to identify their inherent strengths and the patient uses these strengths to promote recovery and well-being (10). The strengths-based approaches in counseling and case management are associated with an improvement in depressive symptoms, substance use behaviors, and postsurgery recovery by improving key determinants such as perceived patient empowerment (3,5,9,11–13).

Implementing a strengths-based approach relies on identifying a patient’s strengths (14–17). However, eliciting a patient’s strengths informally is challenging during time-constrained clinical visits (18). A formal strengths elicitation approach is needed to provide the structure during clinic visits to support patients in suggesting strengths to leverage (16). A concept analysis developed a theoretical framework for patient strengths (9); however, this framework was based on health assets in nursing care of cancer patients. Little is known about how patient strengths are operationalized as a construct in existing validated assessments — either broadly or among noninstitutionalized or community-based populations that frequent health care to manage a chronic condition (ie, clinical populations). Moreover, the construct of personal strengths has not been clearly defined in the literature, which could result in difficulties in distinguishing constructs from each other and instruments that may not adequately capture or sufficiently reflect the phenomenon.

The objective of our study was to identify and systematically summarize constructs that measure dimensions of personal strengths. Specifically, we were interested in understanding what we know about personal strengths and the extent to which instruments that measure personal strengths are validated for application in chronic care management. We reviewed instruments for measuring personal strengths by using the process of theory elaboration, to make a theoretical contribution in the field through specification of the aspects of the broad construct of personal strengths. The process of theory elaboration uses an existing model or conceptual idea as the basis for developing new theoretical insights, through contrasting, specifying, or structuring theoretical constructs to improve our understanding of the measurement of personal strengths (19). Although only a limited number of scales are specifically related to chronic disease management, examining currently validated scales that have been used in adults more broadly can provide information on what constructs and scales can be applied in populations that are managing chronic conditions. The results can inform the use of strengths-based scales in clinic settings for populations managing chronic conditions.

Top

Methods

Personal strengths is a broad construct; therefore, identifying dimensions of personal strengths can elucidate the multidimensionality of the construct. We used a theory elaboration approach for the analysis, specifically to improve construct validation and provide clarity of the scope of each dimension of personal strength as evidenced by previously conducted empirical studies (19).

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (20). First, we conducted a search of peer-reviewed literature to identify validated instruments that operationalized strength constructs. Second, we extracted information from the instrument about constructs, reliability, and validity. Finally, we grouped constructs into categories defined by the health assets framework to understand at what level personal strengths (eg, inner, personality, external) are measured by the instruments (9). Personal strengths can be innate or acquired. Health assets are influenced by antecedents (eg, values, beliefs), an individual’s potential to pull from internal assets such as motivation, or external assets such as interpersonal support, to mobilize themselves to engage in positive health behaviors and improve their health (9).

Data sources

We conducted the literature search to include any articles published from the earliest articles in each database through July 1, 2019. We worked with a university librarian to implement a search of peer-reviewed articles that combined phrases to describe strengths and data collection instrument in PubMed, Web of Science, Cumulative Index of Nursing and Allied Health (CINAHL), PsycINFO, PsycTESTS, Social Work Abstracts, the Health and Psychosocial Instruments, and Embase. After limiting results to humans and English-language articles and removing duplicates, the broad search was still explosive — returning more than 20,000 references. Therefore, we identified the strengths-related search terms with the worst specificity (ie, the largest absolute number of false positives based on a review of sampled abstracts for each term). The most problematic terms identified included “strength*”, “health resource*”, “protective factor*”, and “resilience”. Thereafter, we reviewed a randomly selected sample of 100 references and in working with the librarian, we replaced “strength*” in the main search with more specific terms capable of identifying appropriate references to balance a broad search with efficiency (ie, inner strength). Lastly, we reviewed any review papers (literature, scoping, systematic, meta-analysis) to further identify potentially relevant primary sources. Once we finalized our search strategy, we downloaded relevant citations to EndNoteX8 (Thomson ISI ResearchSoft), a reference management software. The search yielded 3,976 records.

Criteria for study selection

We were interested in instruments that assessed strengths; therefore, we identified studies that met the following criteria: 1) measured strengths at the individual, interpersonal, or environmental level; 2) applied the instrument to an adult population; 3) presented reliability or validity information; 4) used a structured, self-reported questionnaire to assess strengths; 5) had instruments that comprised 3 or more strength-related dimensions (ie, constructs); and 6) were peer-reviewed and published in English before July 2019. We also included instruments developed in languages other than English with findings written in English. We did not include studies focused on child and adolescent samples because strengths may manifest differently across the developmental period. We also excluded studies if they either measured strengths as a subscale of a larger instrument or used qualitative instruments (eg, semi-structured interviews).

For screening we had 2 pairs of reviewers independently screen titles and abstracts. The full team met to resolve disagreements, reach consensus, and revisit the inclusion and exclusion criteria. If we could not reach consensus, the abstract was included for full-text review. Full-text review comprised 3 teams of 2 who closely assessed studies against the inclusion and exclusion criteria, with a focus on reported reliability and validity information for strengths constructs.

Data extraction

We extracted descriptive characteristics, definitions of each construct, and reliability and validity information. For descriptive characteristics, we documented the purpose of the measure, the target population(s) in which the instrument was meant to be used (eg, gender-defined or clinically defined populations), and the settings in which the instrument was applied.

To assess reliability and validity information for each instrument we developed a structured extraction form by using the Scientific Advisory Committee of the Medical Outcome Trust (SACMOT) criteria (21). The 23 criteria are in 8 domains: conceptual models, reliability, validity, responsiveness, interpretability, burden, modes of administration, and cultural and language adaptations or translations (Table 1). Key validity criteria were face, content, criterion-related and construct validity, and reliability measures. Validity studies for each instrument were reviewed, and 2 reviewers (D.D.W. and R.N.K.) independently extracted validity data for each instrument by using the SACMOT criteria. Results were compared and any inconsistencies were resolved through team discussion. The first author reviewed all extraction for quality assurance.

We created a table that included a row for every construct and the original definition from the source instrument to ensure fidelity throughout the extraction and synthesis process. Overlapping constructs were grouped together based on the similarity of their definitions. To organize the final table, we adapted the health assets framework developed by Rotegård and colleagues (9). Two authors (D.D.W. and R.N.K.) independently categorized each construct into the framework domains. Although the health assets framework distinguishes between assets (ie, strengths) and self-awareness, we considered self-awareness as a potential asset and coded constructs into this domain when appropriate. We developed emergent domains for constructs that did not fit into the existing framework. Finally, subdomains were created to reflect groups of constructs within domains. Unique constructs that were extracted from nonvalidated instruments were kept for the purposes of showcasing the diversity of strengths-related constructs and the gaps in validation.

Top

Results

Beginning with 3,976 articles and after removing 1,807 duplicates, 2,169 articles remained (Figure). We excluded 2,057 articles during title and abstract review for not specifying a focus on strengths-related predictors or outcomes, not being published in English, or using a child or adolescent sample only. During the full-text review, we excluded an additional 86 non-English, non–peer reviewed, or not strength-relevant studies. This review yielded 20 studies that met our inclusion criteria and underwent data extraction. Some studies had multiple strengths instruments, thereby producing 26 instruments for review. We extracted information about the populations in which these instruments were validated and sorted them (Table 2).

Figure.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram to obtain studies of strengths instruments to be analyzed for their relevance for chronic disease management. [A text description of this figure is also available.]

Among the instruments assessed, 19 of 26 were developed in the United States, with the remaining 7 developed in Australia, Canada, Norway, Spain, Israel, the Netherlands, and the United Kingdom. Instruments were developed between 1957 and 2013. Although our method ensured all instruments were evaluated in at least 1 validity study, the number of validity studies ranged from 1 (eg, the Balanced Measure of Psychological Needs instrument [22]) to 55 (the California Psychological Inventory [23]), which is also the oldest instrument. Each instrument was validated for 1 or more populations (Table 2).

Use in clinical populations

Among the 26 instruments that matched our inclusion criteria, 5 focused on clinical settings. For example, the Cancer Empowerment Questionnaire measures strengths that cancer patients and survivors derive from themselves and their social network (24,25). The Chronic Illness Resources Survey assesses support and resources at the individual, interpersonal, and community level (26). The Inner Strength Questionnaire was constructed and validated among women with chronic illnesses in the United States (27). The Resilience Scale for Adults was constructed for outpatient adults in Norway (28). Although 5 instruments were developed specifically for clinic populations, an additional 7 instruments were developed in nonclinic settings but later validated in various clinic populations, including the Big Five Personality (29), Brief COPE (30,31), Connor-Davidson Resilience Scale (32), Five-Factor Personality Inventory (33), Interpersonal Support Evaluation List (34), Life Attitude Profile (35,36), and Post-traumatic Growth Inventory (37,38). The Caregiver Well-being Scale assesses family caregivers’ strengths and domains where additional support is desirable for the caregiver (39).

Scale construction, validity, and reliability assessment

We used 18 SACMOT criteria (21) to examine scale construction, reliability, and validity. These 18 criteria were reliability, reliability data collection, reliability estimates, reliability coefficient calculations, methods for reproducibility, test-retest or inter-rater reliability, validity rationale, content-related validity, construct-related validity, data on target population, hypothesis testing, criterion-related rationale, responsiveness, interpretability, respondent burden, administrative burden, administration modes, and cultural and language adaptations (Table 1). We found that the instruments with the most evidence of validity and reliability were the Big Five Personality (14 of 18 criteria), the California Psychological Inventory (13 of 18 criteria), the Resilience Scale for Adults (14 of 18 criteria), and the Sense of Coherence Scale (13 of 18 criteria) (40).

We found that definitions were clear for each construct, fulfilling the first SACMOT criterion (Table 1). All instruments had information on the dimensionality and distinctiveness of measured constructs. Most instruments (25 of 26) reported reliability estimates, such as a Cronbach α value (41).

Of the 26 instruments, 23 had at least 1 article detailing evidence on content validity, or the extent to which the items reflect the construct (42). Relatedly, construct validity measures comprised evidence for convergent and discriminant validity. We found 22 of 26 instruments assessed construct validity (eg, convergent and discriminant validity). Most instruments had measures of internal consistency to ensure reliability of the instrument and had reproducibility measures. Of the 26 instruments, 15 had information on less than 50% of the SACMOT criteria. The criterion with the least evidence was an evaluation of the administrative burden (2 of 26) and alternative modes of administering the instrument (3 of 26).

Construct categorization

We found 91 distinct constructs (Table 3). Most instruments contained unique constructs, indicating that constructs did not conceptually overlap with each other across instruments. Common constructs across instruments included flexibility, spiritual strength, and autonomy.

We organized the constructs into 3 domains based on the health assets framework developed by Rotegård et al (9): inner strengths, external strengths, and personality constructs. Approximately half of the constructs were coded as inner strengths (n = 49). On the basis of the framework, inner strengths comprised constructs that measure how people relate to others and their environment (relational, n = 17), what drives people when they encounter challenging situations (motivational, n = 10), characteristics that buffer individuals from undesired health outcomes (protective, n = 6), self-determination to accomplish goals (volitional, n = 9), and self-reflective characteristics (self-awareness, n = 7).

Of 91 constructs, 13 were coded as external strengths, split into 2 domains: social resources and institutional support. Whereas social resources focus more on interpersonal resources, such as forms of tangible social support and aid (n = 7), institutional support contains constructs measuring community or institutional-level characteristics that could support positive behaviors, such as the presence of community organizations (n = 6).

We classified 29 constructs as personality, which related to innate individual traits. Most of these personality constructs came from well-established personality-based instruments such as the Big Five Personality or Five-Factor Personality Inventory (33). Through coding, personality constructs were further split into 2 subdomains. One was resourcefulness (n = 10), defined as the ability to perform tasks independently or seek help from others when necessary. Constructs coded to resourcefulness included those pertaining to self-management skills and knowledge of and ability to use resources. The second subdomain was general personality traits (n = 19) related to intelligence, justice, approach to interaction with others, positivity, and approaches to learning.

Top

Discussion

Personal strengths is a broad phenomenon comprising many constructs including internal strengths such as self-efficacy and personality or interpersonal strengths such as social support. Strengths can also come from community and social levels; however, we did not identify any validated scales focused on these higher-level strengths. The objective of this review was to identify and systematically summarize constructs that measure dimensions of personal strengths. This review shows evidence of a limited number of reliable and valid instruments available to assess strengths for the adult population. We identified 26 instruments, most of which were developed in the United States and had reliability estimates. Content validity and construct validity were the most documented forms of validity, and information on administrative burden was the least documented. The instruments with the most reliability and validity evidence were personality assessments (Big Five Personality) and perceptions of interpersonal reactions (California Psychological Inventory) and resiliency (Sense of Coherence Scale).

Furthermore, 91 constructs are represented across the 26 instruments. Over 85 percent of constructs focused on inner strengths or personality factors rather than external resources (ie, community assets). Most of the constructs were focused on internal resources, reflecting the overarching health care rhetoric and practice of self-management, which is focused on changing the individual without fully acknowledging the potential external assets that can be used to promote self-management behaviors (43,44). These results are consistent with a review conducted by Golden and Earp (45), which found that 95% of behavioral interventions are conducted at the individual level and 67% are conducted at the interpersonal level. Despite evidence showing that community-level and policy-level factors are more effective than individual-level factors to change health behaviors, very few interventions are done at these levels (46). Overall, the rich set of constructs identified as inner strengths or personality factors can be leveraged to improve patients’ health in primary care settings. Additional instruments focused on external assets can be developed to capture personal strengths and improve patient care more holistically.

The variability in validation studies may result from the high number of constructs used as proxies for personal strength; therefore, proper validity testing is necessary to advance the measurement of this broad construct. One specific type of validation that can help advance measurement is discriminant validity, which requires that measures of distinctly different constructs not be correlated with each other (42). Advancements in discriminating between the types of personal strengths can be made by further applying theory elaboration and construct proliferation techniques in future studies (19,47).

In considering the use of personal strengths to inform the treatment and management of chronic conditions for individuals, studies have found evidence of cultivating personal strengths to improve self-management behaviors and improve patient health outcomes (48–50). However, we found that the number of instruments developed specifically for clinical populations or validated in clinical populations is limited. This may reflect how providers may focus on treating problems and identifying risk factors rather than evaluating patients on their personal strengths that can be integrated as part of the treatment plan. Therefore, additional studies are needed to develop instruments to measure personal strengths in clinical populations. Relatedly, interventions are needed in health care settings to integrate validated instruments and relevant items from those instruments in clinical care to identify personal strengths and to start conversations about strengths-based approaches to improving chronic disease management. These interventions could target clinician awareness of instruments and knowledge of how to apply and interpret the results as a means of improving care.

Limitations

Our systematic review found that few instruments assess strengths at the community and societal levels to emphasize an ecological approach to strengths identification. Most instruments were not developed specifically for clinical populations, therefore additional testing is needed in these populations. We limited our inclusion criteria to adults but recognize that validity assessments are needed for children and adolescents if they are to be implemented in clinical settings, particularly in primary care settings. Although we examined instruments validated in adult populations, the studies described participants homogenously rather than examining adults by different stages of the life course (eg, older adults). Parsing out adults by these key developmental periods could be explored given that health care is sorted by age-specific specialties, such as geriatrics. In addition, quality of life instruments were not included in this search as these assess multiple domains of an individual’s well-being. For this review, we wanted to limit the search to instruments that focus primarily on assessing personal strengths that an individual would have agency around, rather than instruments, such as health-related quality of life, that are broader constructs with a subdomain assessing strength. Our search may have been biased toward Western epistemologies, thereby excluding important strengths such as cultural group membership and connection, as research in Black psychology emphasizes (51).

Future research

Resilience, an important characteristic all on its own, was not included in our literature search because of how large the search results became. In addition, many of the instruments were validated in the general adult population or college students. Primary care settings need strengths-based instruments that account for developmental differences across adulthood (eg, younger or older adults) and that reflect how strengths are manifested in different cultural, racial, or ethnic groups (eg, Black, Indigenous, Asian, White). To ensure the validity of these measures in different populations, additional psychometric testing is needed to determine if each construct has the same meaning for each group. Implementation research is needed on how to use these instruments in health care settings in a way that supports the workflow of clinicians and leverages patient-generated information as part of the treatment process. Future research could use the constructs identified here to develop a comprehensive instrument of patient strengths in the clinical setting to improve chronic disease management. These instruments must be validated across multiple clinical populations, including those managing multiple chronic conditions such as cancer, hypertension, and type 2 diabetes.

We have reviewed 26 reliable and valid instruments that measure personal strengths in clinical and nonclinical adult populations. Constructs in these instruments can be used in both research and clinic settings to improve self-management behaviors among people with chronic conditions. Although these instruments tap into different forms of strengths, few instruments assess external strengths (eg, interpersonal, community). The development and validation of additional instruments to capture personal strengths is necessary to examine the multilevel influence of external strengths on individual behaviors and well-being.

Top

Acknowledgments

We thank the Patient-Centered Outcomes Research Institute (PCORI) for their support of this review. We thank Emily Gillen, PhD, for her help with reviewing articles, and thank University of North Carolina at Chapel Hill librarian Sarah Wright, MLIS, for her invaluable assistance in constructing the literature search.

The views presented in this manuscript are solely the responsibility of the authors and do not necessarily represent the views of PCORI, its Board of Governors, or Methodology Committee. PCORI is an independent, nonprofit organization authorized by the US Congress in 2010. Its mission is to fund research that will provide patients, their caregivers, and clinicians with the evidence-based information needed to make better-informed health care decisions. PCORI is committed to continually seeking input from a broad range of stakeholders to guide its work. Research reported in this manuscript was funded through a PCORI award (no. HSRP20142263).

D.D.W., R.N.K., and C.K. conducted the literature review and reviewed each article for inclusion with K.H.L. D.D.W., R.N.K., C.K., and K.H.L. collaboratively wrote the drafts of the manuscript. K.C.S. and A.M.W. provided extensive feedback and edits. All authors reviewed and edited the manuscript and approved the final version of the manuscript. The results have not been published or presented elsewhere. The authors have no conflicts of interest to declare. No financial disclosures were reported by the authors.

Top

Author Information

Corresponding Author: Deshira D. Wallace, PhD, Department of Health Behavior, University of North Carolina at Chapel Hill, 302 Rosenau Hall, 135 Dauer Dr, CB7440, Chapel Hill, NC 27599. Telephone: 984-464-0298. Email: ddwallac@live.unc.edu.

Author Affiliations: ¹Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. ²Northern California Kaiser Permanente Division of Research, Oakland, California. ³University of Rochester Medical Center, Rochester, New York. ⁴Children’s Institute, Rochester, New York. ⁵Center for Community Health Integration, Case Western Reserve University, Cleveland, Ohio.

Top

References

1. Ward BW, Schiller JS, Goodman RA. Multiple chronic conditions among US adults: a 2012 update. Prev Chronic Dis 2014;11:E62. CrossRefexternal icon PubMedexternal icon
2. Waters H, Graf M. The costs of chronic disease in the U.S. Santa Monica (CA): Milken Institute; 2018. 25 p. https://milkeninstitute.org/reports/costs-chronic-disease-us. Accessed March 26, 2021.
3. Battersby M, Von Korff M, Schaefer J, Davis C, Ludman E, Greene SM, et al. Twelve evidence-based principles for implementing self-management support in primary care. Jt Comm J Qual Patient Saf 2010;36(12):561–70. CrossRefexternal icon PubMedexternal icon
4. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA 2002;288(14):1775–9. CrossRefexternal icon PubMedexternal icon
5. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA 2002;288(19):2469–75. CrossRefexternal icon PubMedexternal icon
6. Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Aff (Millwood) 2001;20(6):64–78. CrossRefexternal icon PubMedexternal icon
7. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness: the chronic care model, part 2. JAMA 2002;288(15):1909–14. CrossRefexternal icon PubMedexternal icon
8. Staudt M, Howard MO, Drake B. The operationalization, implementation, and effectiveness of the strengths perspective. J Soc Serv Res 2001;27(3):1–21. CrossRefexternal icon
9. Roteg&aringrd AK, Moore SM, Fagermoen MS, Ruland CM. Health assets: a concept analysis. Int J Nurs Stud 2010;47(4):513–25. CrossRefexternal icon PubMedexternal icon
10. Simmons CA, Lehmann P. Strengths and psychotherapy. Tools for strength based assessment and evaluation. New York (NY): Springer Publishing Company; 2013. p. 1–17.
11. Flückiger C, Caspar F, Holtforth MG, Willutzki U. Working with patients’ strengths: a microprocess approach. Psychother Res 2009;19(2):213–23. CrossRefexternal icon PubMedexternal icon
12. Kress VE, Hoffman RM. Empowering adolescent survivors of sexual abuse: application of a solution‐focused Ericksonian Counseling Group. J Humanist Educ Dev 2008;47(2):172–86.
13. Skolasky RL, Mackenzie EJ, Wegener ST, Riley LH 3d. Patient activation and functional recovery in persons undergoing spine surgery. J Bone Joint Surg Am 2011;93(18):1665–71. CrossRefexternal icon PubMedexternal icon
14. Bird VJ, Le Boutillier C, Leamy M, Larsen J, Oades LG, Williams J, et al. Assessing the strengths of mental health consumers: a systematic review. Psychol Assess 2012;24(4):1024–33. CrossRefexternal icon PubMedexternal icon
15. Graybeal C. Strengths-based social work assessment: transforming the dominant paradigm. Fam Soc 2001;82(3):233–42. CrossRefexternal icon
16. Rashid T, Ostermann RF. Strength-based assessment in clinical practice. J Clin Psychol 2009;65(5):488–98. CrossRefexternal icon PubMedexternal icon
17. Tedeschi RG, Kilmer RP. Assessing strengths, resilience, and growth to guide clinical interventions. Prof Psychol Res Pr 2005;36(3):230–7. CrossRefexternal icon
18. Kristjansdottir OB, Stenberg U, Mirkovic J, Krogseth T, Ljos&aring TM, Stange KC, et al. Personal strengths reported by people with chronic illness: a qualitative study. Health Expect 2018;21(4):787–95. CrossRefexternal icon PubMedexternal icon
19. Fisher G, Aguinis H. Using theory elaboration to make theoretical advancements. Organ Res Methods 2017;20(3):438–64. CrossRefexternal icon
20. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009;151(4):264–9, W64. CrossRefexternal icon PubMedexternal icon
21. Aaronson N, Alonso J, Burnam A, Lohr KN, Patrick DL, Perrin E, et al. Assessing health status and quality-of-life instruments: attributes and review criteria. Qual Life Res 2002;11(3):193–205. CrossRefexternal icon PubMedexternal icon
22. Sheldon KM, Hilpert JC. The balanced measure of psychological needs (BMPN) scale: an alternative domain general measure of need satisfaction. Motiv Emot 2012;36(4):439–51. CrossRefexternal icon
23. Dicken CF. Convergent and discriminant validity of the California Psychological Inventory. Educ Psychol Meas 1963;23(3):449–59. CrossRefexternal icon
24. van den Berg SW, van Amstel FK, Ottevanger PB, Gielissen MF, Prins JB. The Cancer Empowerment Questionnaire: psychological empowerment in breast cancer survivors. J Psychosoc Oncol 2013;31(5):565–83. CrossRefexternal icon PubMedexternal icon
25. Custers JA, van den Berg SW, van Laarhoven HW, Bleiker EM, Gielissen MF, Prins JB. The Cancer Worry Scale: detecting fear of recurrence in breast cancer survivors. Cancer Nurs 2014;37(1):E44–50. CrossRefexternal icon PubMedexternal icon
26. Glasgow RE, Strycker LA, Toobert DJ, Eakin E. A social-ecologic approach to assessing support for disease self-management: the Chronic Illness Resources Survey. J Behav Med 2000;23(6):559–83. CrossRefexternal icon PubMedexternal icon
27. Roux G, Lewis K, Younger J, Dingley C. Development and testing of the inner strength questionnaire. J Cult Divers 2003;10(1):4–5. PubMedexternal icon
28. Friborg O, Hjemdal O, Rosenvinge JH, Martinussen M. A new rating scale for adult resilience: what are the central protective resources behind healthy adjustment? Int J Methods Psychiatr Res 2003;12(2):65–76. CrossRefexternal icon PubMedexternal icon
29. Fan J, Zhu X-z, Tang L-l, Wang Y-p, Li L, Yang Y, et al. Reliability and validity of Chinese Big Five Personality inventory brief version in breast cancer women. Chinese Journal of Clinical Psychology 2013;21(5):783–5.
30. Snell DL, Siegert RJ, Hay-Smith EJ, Surgenor LJ. Factor structure of the Brief COPE in people with mild traumatic brain injury. J Head Trauma Rehabil 2011;26(6):468–77. CrossRefexternal icon PubMedexternal icon
31. Mejorada RE, Tufiño MA, Sierra AV, Guerrero OT, Rosas AR, Sánchez Sosa JJ. Afrontamiento en pacientes con cáncer de mama en radioterapia: Análisis de la Escala COPE Breve. Psicología y Salud 2013;23(1):55–62. Spanish.
32. Connor KM, Davidson JR. Development of a new resilience scale: the Connor-Davidson Resilience Scale (CD-RISC). Depress Anxiety 2003;18(2):76–82. CrossRefexternal icon PubMedexternal icon
33. Hofstee W. Big-Five-profielen van persoonlijkheidsstoornissen. Psychodiagnostisch gereedschap. = The Big Five profile of personality disorders: psychodiagnostic tools. Psychooncology 1999;34(9):381–4.
34. Bastardo YM, Kimberlin CL. Relationship between quality of life, social support and disease-related factors in HIV-infected persons in Venezuela. AIDS Care 2000;12(5):673–84. CrossRefexternal icon PubMedexternal icon
35. Ahern NR, Kiehl EM, Sole ML, Byers J. A review of instruments measuring resilience. Issues Compr Pediatr Nurs 2006;29(2):103–25. CrossRefexternal icon PubMedexternal icon
36. Anagnostopoulos F, Slater J, Fitzsimmons D, Kolokotroni P. Exploring global meaning in Greek breast cancer patients: validation of the Life Attitude Profile — Revised (LAP-R). Psychooncology 2011;20(4):419–27. CrossRefexternal icon PubMedexternal icon
37. Mack J, Herrberg M, Hetzel A, Wallesch CW, Bengel J, Schulz M, et al. The factorial and discriminant validity of the German version of the Post-traumatic Growth Inventory in stroke patients. Neuropsychol Rehabil 2015;25(2):216–32. CrossRefexternal icon PubMedexternal icon
38. Mystakidou K, Tsilika E, Parpa E, Galanos A, Vlahos L. Post-traumatic growth in advanced cancer patients receiving palliative care. Br J Health Psychol 2008;13(Pt 4):633–46. CrossRefexternal icon PubMedexternal icon
39. Tebb S. An aid to empowerment: a caregiver well-being scale. Health Soc Work 1995;20(2):87–92. CrossRefexternal icon PubMedexternal icon
40. Frenz AW, Carey MP, Jorgensen RS. Psychometric evaluation of Antonovsky’s Sense of Coherence Scale. Psychol Assess 1993;5(2):145–53. CrossRefexternal icon
41. Alwin DF. Measurement errors in cross-cultural surveys. Extracted from Margins of error — a study of reliability in survey measurement. New York (NY): John Wiley and Sons; 2007.
42. DeVellis RF. Scale development: theory and applications. Thousand Oaks (CA): Sage Publications; 2016.
43. Madden MH, Tomsik P, Terchek J, Navracruz L, Reichsman A, Clark TC, et al. Keys to successful diabetes self-management for uninsured patients: social support, observational learning, and turning points: a safety net providers’ strategic alliance study. J Natl Med Assoc 2011;103(3):257–64. CrossRefexternal icon PubMedexternal icon
44. Reichsman A, Werner J, Cella P, Bobiak S, Stange KC; SNPSA Diabetes Study Working Group. Opportunities for improved diabetes care among patients of safety net practices: a safety net providers’ strategic alliance study. J Natl Med Assoc 2009;101(1):4–11. CrossRefexternal icon PubMedexternal icon
45. Golden SD, Earp JAL. Social ecological approaches to individuals and their contexts: twenty years of Health Education & Behavior health promotion interventions. Health Educ Behav 2012;39(3):364–72. CrossRefexternal icon PubMedexternal icon
46. Hirsch G, Homer J, Trogdon J, Wile K, Orenstein D. Using simulation to compare 4 categories of intervention for reducing cardiovascular disease risks. Am J Public Health 2014;104(7):1187–95. CrossRefexternal icon PubMedexternal icon
47. Shaffer JA, DeGeest D, Li A. Tackling the problem of construct proliferation: a guide to assessing the discriminant validity of conceptually related constructs. Organ Res Methods 2016;19(1):80–110. CrossRefexternal icon
48. Tai-Seale M, Downing NL, Jones VG, Milani RV, Zhao B, Clay B, et al. Technology-enabled consumer engagement: promising practices at four health care delivery organizations. Health Aff (Millwood) 2019;38(3):383–90. CrossRefexternal icon PubMedexternal icon
49. Greene J, Hibbard JH, Sacks R, Overton V, Parrotta CD. When patient activation levels change, health outcomes and costs change, too. Health Aff (Millwood) 2015;34(3):431–7. CrossRefexternal icon PubMedexternal icon
50. Alegría M, Sribney W, Perez D, Laderman M, Keefe K. The role of patient activation on patient–provider communication and quality of care for US and foreign born Latino patients. J Gen Intern Med 2009;24(Suppl 3):534–41. CrossRefexternal icon PubMedexternal icon
51. Jamison D. The SAGE encyclopedia of African cultural heritage in North America. Thousand Oaks (CA): Sage Publications; 2015.

Top

Tables

^a Shortened version of key criteria based on Aaronson et al (21).

^a A list of the publications cited in this table is in the Appendix.

^a These constructs are part of instruments that did not pass the validity assessment stage but had unique constructs not found in validated instruments.

Top

Appendix

Following is a listing of studies cited in Table 2 of the article.

Balanced Measure of Psychological Needs

Sheldon KM, Hilpert JC. The balanced measure of psychological needs (BMPN) scale: an alternative domain general measure of need satisfaction. Motiv Emot 2012;36(4):439–51. CrossRefexternal icon

Baruth Protective Factors Inventory

Baruth KE, Carroll JJ. A formal assessment of resilience: the Baruth Protective Factors Inventory. J Individ Psychol (1998) 2002;58(3):235–44.

Big Five Personality

Barrick MR, Mount MK. The Big Five personality dimensions and job performance: a meta‐analysis. Pers Psychol 1991;44(1):1–26. CrossRefexternal icon

Benet-Martínez V, John OP. Los Cinco Grandes across cultures and ethnic groups: multitrait-multimethod analyses of the Big Five in Spanish and English. J Pers Soc Psychol 1998;75(3):729–50. CrossRefexternal icon PubMedexternal icon

Fossati A, Borroni S, Marchione D, Maffei C. The big five inventory (BFI). Eur J Psychol Assess 2011;27(1):50–8. CrossRefexternal icon

Smits IA, Dolan CV, Vorst HC, Wicherts JM, Timmerman ME. Cohort differences in Big Five personality factors over a period of 25 years. J Pers Soc Psychol 2011;100(6):1124–38. CrossRefexternal icon PubMedexternal icon

Van Heck GL, Perugini M, Caprara G-V, Fröger J. The Big Five as tendencies in situations. Pers Individ Dif 1994;16(5):715–31. CrossRefexternal icon

Pulver A, Allik J, Pulkkinen L, Hämäläinen M. A Big Five personality inventory in two non–Indo‐European languages. Eur J Pers 1995;9(2):109–24. CrossRefexternal icon

Strelau J, Zawadzki B. The formal characteristics of behaviour — Temperament inventory (FCB — TI): validity studies. Eur J Pers 1995;9(3):207–29. CrossRefexternal icon

Wada S. Construction of the Big Five Scales of personality trait terms and concurrent validity with NPI. Shinrigaku Kenkyu 1996;67(1):61–7. CrossRefexternal icon

El-Ansarey B. The psychometric properties of NEO five-factor inventory (NEO-FFI-S) based on the Kuwaiti society. Derasat Nafseyah 1997;7:277–310.

Nunes CHSS, Hutz CS. Development and validation of an Agreeableness scale in the Big Five personality model. Psicol Reflex Crit 2007;20(1):20–5. CrossRefexternal icon

Hauck Filho N, de Lara Machado W, Teixeira MAP, Bandeira DR. Evidencias de validade de marcadores reduzidos para a avaliacao da personalidade no modelo dos Cinco Grandes Fatores. Psicologia: Teoria e Pesquisa 2012;28(4):417–23. Portuguese. CrossRefexternal icon

Rammstedt B. The 10-item Big Five Inventory: norm values and investigation of sociodemographic effects based on a German population representative sample. Eur J Psychol Assess 2007;23(3):193–201. CrossRefexternal icon

Mlacić B. National taxonomies, adjective markers and inventories: Three directions of application of the lexical approach to personality. Roczniki Psychologiczne 2008;11(1):152–60.

Hrebíčková M. Questionnaire in the Czech context. Stud Psychol (Bratisl) 2010;52:(3):165–77.

Karaman NG, Dogan T, Coban AE. A study to adapt the big five inventory to Turkish. Procedia Soc Behav Sci 2010;2(2):2357–9. CrossRefexternal icon

Gençöz T, Öcül Ö. Examination of personality characteristics in a Turkish sample: development of Basic Personality Traits Inventory. J Gen Psychol 2012;139(3):194–216. CrossRefexternal icon PubMedexternal icon

Morsünbül Ü. The association of internet addiction with attachment styles, personality traits, loneliness and life satisfaction. Journal of Human Sciences 2014;11(1):357–72.

Huang Y, Wang L. Sex differences in framing effects across task domain. Pers Individ Dif 2010;48(5):649–53. CrossRefexternal icon

Wang W, editor. How personality affects continuance intention: an empirical investigation of instant messaging. Proceedings of the Pacific Asia Conference on Information Systems (PACIS); 2010. No. 113.

Shi M, Liu L, Wang ZY, Wang L. The mediating role of resilience in the relationship between big five personality and anxiety among Chinese medical students: a cross-sectional study. PLoS One 2015;10(3):e0119916. CrossRefexternal icon PubMedexternal icon

Ledesma RD, Sánchez R, Díaz-Lázaro CM. Adjective checklist to assess the big five personality factors in the Argentine population. J Pers Assess 2011;93(1):46–55. CrossRefexternal icon PubMedexternal icon

Fan J, Zhu X-z, Tang L-l, Wang Y-p, Li L, Yang Y, et al. Reliability and validity of Chinese Big Five Personality inventory brief version in breast cancer women. Chinese Journal of Clinical Psychology 2013;21(5):783–5.

Brief COPE

Carver CS. You want to measure coping but your protocol’s too long: consider the brief COPE. Int J Behav Med 1997;4(1):92–100. CrossRefexternal icon PubMedexternal icon

Müller W.Lebe jetzt-einfach sein. Mainz (DE): Matthias-Grünewald-Verlag; 2003.

Doron J, Trouillet R, Gana K, Boiché J, Neveu D, Ninot G. Examination of the hierarchical structure of the Brief COPE in a French sample: empirical and theoretical convergences. J Pers Assess 2014;96(5):567–75. CrossRefexternal icon PubMedexternal icon

Muhonen T, Torkelson E. Kortversioner av fr&aringgeformulär inom arbets-och hälsopsykologi — om att mäta coping och optimism. Nord Psykol 2005;57(3):288–97. CrossRefexternal icon

Yusoff N, Low WY, Yip CH. Reliability and validity of the Brief COPE Scale (English version) among women with breast cancer undergoing treatment of adjuvant chemotherapy: a Malaysian study. Med J Malaysia 2010;65(1):41–4. PubMedexternal icon

Kimemia M, Asner-Self KK, Daire AP. An exploratory factor analysis of the Brief COPE with a sample of Kenyan caregivers. Int J Adv Couns 2011;33(3):149–60. CrossRefexternal icon

Snell DL, Siegert RJ, Hay-Smith EJC, Surgenor LJ. Factor structure of the Brief COPE in people with mild traumatic brain injury. J Head Trauma Rehabil 2011;26(6):468–77. CrossRefexternal icon PubMedexternal icon

Mejorada REO, Tufiño MAT, Sierra AV, Guerrero OT, Rosas AR, Sosa JJS. Afrontamiento en pacientes con cáncer de mama en radioterapia: análisis de la Escala COPE Breve. Psicología y Salud 2013;23(1):55–62.

Mohanraj R, Jeyaseelan V, Kumar S, Mani T, Rao D, Murray KR, et al. Cultural adaptation of the Brief COPE for persons living with HIV/AIDS in southern India. AIDS Behav 2015;19(2):341–51. CrossRefexternal icon PubMedexternal icon

Su XY, Lau JT, Mak WW, Choi KC, Feng TJ, Chen X, et al. A preliminary validation of the Brief COPE instrument for assessing coping strategies among people living with HIV in China. Infect Dis Poverty 2015;4(1):41. CrossRefexternal icon PubMedexternal icon

California Psychological Inventory

Gough HG. The construction of a personality scale to predict scholastic achievement. J Appl Psychol 1953;37(5):361–6. CrossRefexternal icon

Dicken CF. Convergent and discriminant validity of the California Psychological Inventory. Educ Psychol Meas 1963;23(3):449–59. CrossRefexternal icon

Darbes A, Mottesheard N, editors. A validity check of selected cluster scores of the California Psychological Inventory tests of 239 college students. Proceedings of the West Virginia Academy of Science 1964;36:191–4.

Goodstein LD, Schrader WJ. An empirically-derived managerial key for the California Psychological Inventory. J Appl Psychol 1963;47(1):42–5. CrossRefexternal icon

Gough HG. A managerial potential scale for the California Psychological Inventory. J Appl Psychol 1984;69(2):233–40. CrossRefexternal icon

Knapp RR. Personality correlates of delinquency rate in a Navy sample. J Appl Psychol 1963;47(1):68–71. CrossRefexternal icon

Gough HG. Academic achievement in high school as predicted from the California Psychological Inventory. J Educ Psychol 1964;55(3):174–80. CrossRefexternal icon

Gough HG. Graduation from high school as predicted from the California Psychological Inventory. Psychol Sch 1966;3(3):208–16. CrossRefexternal icon

Chapuis C, Quintard G, Wourms J. A new personality inventory: the CPI (California Psychological Inventory). Bull Psychol 1970;24(16-18):997–1004.

Nishiyama T. Cross-cultural invariance of California Psychological Inventory. Psychologia 1973;16(2):75–84.

Nishiyama T. Validation of the CPI femininity scale in Japan. J Cross Cult Psychol 1975;6(4):482–9. CrossRefexternal icon

Rosen A-S, Schalling D. On the validity of the California Psychological Inventory Socialization scale: a multivariate approach. J Consult Clin Psychol 1974;42(6):757–65. CrossRefexternal icon

Gough HG. Estimation of locus-of-control scores from the California Psychological Inventory. Psychol Rep 1974;35(1 Pt 2):343–8. CrossRefexternal icon PubMedexternal icon

Cohen A, Farley FH. The common-item problem in measurement: effects on cross-cultural invariance of personality inventory structure. Educ Psychol Meas 1977;37(3):757–60. CrossRefexternal icon

Pitariu H, Helmine H. Investigarea personalităţii cu ajutorul Inventarului Psihologic California (CPI). Rev Psihol 1980;26(4):461–73.

Pitariu H. Validation of the CPI femininity scale in Romania. J Cross Cult Psychol 1981;12(1):111–7. CrossRefexternal icon

Ahmed I. Initial psychometric evaluation of URDU version of California Psychological Inventory (CPI). Pak J Psychol Res 1986;(June 22):3–16.

Torki MA. The CPI femininity scale in Kuwait and Egypt. J Pers Assess 1988;52(2):247–53. CrossRefexternal icon

Ying Y-W. Validation of the California Psychological Inventory Femininity Scale in Taiwan college graduates. J Multicult Couns Devel 1991;19(4):166–72. CrossRefexternal icon

Blake RJ, Potter EH 3d, Slimak RE. Validation of the structural scales of the CPI for predicting the performance of junior officers in the U.S. Coast Guard. J Bus Psychol 1993;7(4):431–48. CrossRefexternal icon

Collins JM, Schmidt FL. Personality, integrity, and white collar crime: a construct validity study. Person Psychol 1993;46(2):295–311. CrossRefexternal icon

Kadden RM, Litt MD, Donovan D, Cooney NL. Psychometric properties of the California Psychological Inventory Socialization scale in treatment-seeking alcoholics. Psychol Addict Behav 1996;10(3):131–46. CrossRefexternal icon

Sandal GM, Endresen IM. The sensitivity of the CPI Good Impression Scale for detecting ‘faking good’ among Norwegian students and job applicants. Int J Sel Assess 2002;10(4):304–11. CrossRefexternal icon

Cancer Empowerment Questionnaire

Shin SH, Park H. [Development and validation of the empowerment scale for women with breast cancer]. J Korean Acad Nurs 2015;45(4):613–24. Korean. CrossRefexternal icon PubMedexternal icon

van den Berg SW, van Amstel FKP, Ottevanger PB, Gielissen MFM, Prins JB. The cancer empowerment questionnaire: psychological empowerment in breast cancer survivors. J Psychosoc Oncol 2013;31(5):565–83. CrossRefexternal icon PubMedexternal icon

Custers JAE, van den Berg SW, van Laarhoven HWM, Bleiker EMA, Gielissen MFM, Prins JB. The Cancer Worry Scale: detecting fear of recurrence in breast cancer survivors. Cancer Nurs 2014;37(1):E44–50. CrossRefexternal icon PubMedexternal icon

Caregiver Well-Being Scale

Tebb S. An aid to empowerment: a caregiver well-being scale. Health Soc Work 1995;20(2):87–92. CrossRefexternal icon PubMedexternal icon

Rubio DM, Berg-Weger M, Tebb SS. Assessing the validity and reliability of well-being and stress in family caregivers. Soc Work Res 1999;23(1):54–64. CrossRefexternal icon

Berg-Weger M, Rubio DM, Tebb SS. The Caregiver Well-Being Scale revisited. Health Soc Work 2000;25(4):255–63. CrossRefexternal icon PubMedexternal icon

Rubio DM, Berg-Weger M, Tebb SS, Lee ES, Rauch S. Objectifying content validity: conducting a content validity study in social work research. Soc Work Res 2003;27(2):94–104. CrossRefexternal icon

Tebb SS, Berg-Weger M, Rubio DM. The Caregiver Well-Being Scale: developing a short-form rapid assessment instrument. Health Soc Work 2013;38(4):222–30. CrossRefexternal icon PubMedexternal icon

Demirtepe D, Bozo Õ. Bakici ıyilik ölçeği’nin uyarlama, güvenirlik ve geçerlik çalişması. Turk Psikol Yaz 2009;12(23)28–37.

Chronic Illness Resources Survey

Glasgow RE, Strycker LA, Toobert DJ, Eakin E. A social-ecologic approach to assessing support for disease self-management: the Chronic Illness Resources Survey. J Behav Med 2000;23(6):559–83. CrossRefexternal icon PubMedexternal icon

Eakin EG, Reeves MM, Bull SS, Riley KM, Floyd S, Glasgow RE. Validation of the Spanish-language version of the Chronic Illness Resources Survey. Int J Behav Med 2007;14(2):76–85. CrossRefexternal icon PubMedexternal icon

College Student Hardiness Measure

Atri A, Sharma M, Cottrell R. Role of social support, hardiness, and acculturation as predictors of mental health among international students of Asian Indian origin. Int Q Community Health Educ 2006-2007;27(1):59–73. CrossRefexternal icon PubMedexternal icon

Connor-Davidson Resilience Scale

Connor KM, Davidson JR. Development of a new resilience scale: the Connor-Davidson Resilience Scale (CD-RISC). Depress Anxiety 2003;18(2):76–82. CrossRefexternal icon PubMedexternal icon

Baek H-S, Lee K-U, Joo E-J, Lee M-Y, Choi K-S. Reliability and validity of the Korean version of the Connor-Davidson Resilience Scale. Psychiatry Investig 2010;7(2):109–15. CrossRefexternal icon PubMedexternal icon

Notario-Pacheco B, Martínez-Vizcaíno V, Trillo-Calvo E, Pérez-Yus MC, Serrano-Parra D, García-Campayo J. Validity and reliability of the Spanish version of the 10-item CD-RISC in patients with fibromyalgia. Health Qual Life Outcomes 2014;12(1):14. CrossRefexternal icon PubMedexternal icon

Jeong HS, Kang I, Namgung E, Im JJ, Jeon Y, Son J, et al. Validation of the Korean version of the Connor-Davidson Resilience Scale-2 in firefighters and rescue workers. Compr Psychiatry 2015;59:123–8. CrossRefexternal icon PubMedexternal icon

Sarubin N, Gutt D, Giegling I, Bühner M, Hilbert S, Krähenmann O, et al. Erste Analyse der psychometrischen Eigenschaften und Struktur der deutschsprachigen 10- und 25-Item Version der Connor-Davidson Resilience Scale (CD-RISC). Z Gesundh psychol 2015;23(3):112–22. CrossRefexternal icon

Ni MY, Li TK, Yu NX, Pang H, Chan BH, Leung GM, et al. Normative data and psychometric properties of the Connor-Davidson Resilience Scale (CD-RISC) and the abbreviated version (CD-RISC2) among the general population in Hong Kong. Qual Life Res 2016;25(1):111–6. CrossRefexternal icon PubMedexternal icon

Xie Y, Peng L, Zuo X, Li M. The psychometric evaluation of the Connor-Davidson resilience scale using a Chinese military sample. PLoS One 2016;11(2):e0148843. CrossRefexternal icon PubMedexternal icon

Dispositional Resilience Scale

Hystad SW, Eid J, Johnsen BH, Laberg JC, Thomas Bartone P. Psychometric properties of the revised Norwegian dispositional resilience (hardiness) scale. Scand J Psychol 2010;51(3):237–45. CrossRefexternal icon PubMedexternal icon

Picardi A, Bartone PT, Querci R, Bitetti D, Tarsitani L, Roselli V, et al. Development and validation of the Italian version of the 15-item dispositional resilience scale. Riv Psichiatr 2012;47(3):231–7. PubMedexternal icon

Bartone PT. Predictors of stress-related illness in city bus drivers. J Occup Med 1989;31(8):657–63. CrossRefexternal icon PubMedexternal icon

Five-Factor Personality Inventory

Hendriks AJ, Hofstee WK, De Raad B. The Five-Factor Personality Inventory (FFPI). Pers Individ Dif 1999;27(2):307–25. CrossRefexternal icon

Buchanan T, Johnson JA, Goldberg LR. Implementing a five-factor personality inventory for use on the internet. Eur J Psychol Assess 2005;21(2):115–27. CrossRefexternal icon

Perugini M, Ercolani AP. Validity of the five factor personality inventory (FFPI): an investigation in Italy. Eur J Psychol Assess 1998;14(3):234–48. CrossRefexternal icon

Marshall GN, Wortman CB, Vickers RR Jr, Kusulas JW, Hervig LK. The five-factor model of personality as a framework for personality-health research. J Pers Soc Psychol 1994;67(2):278–86. CrossRefexternal icon PubMedexternal icon

Salgado JF. The Five Factor Model of personality and job performance in the European Community. J Appl Psychol 1997;82(1):30–43. CrossRefexternal icon PubMedexternal icon

Rodríguez-Fornells A, Lorenzo-Seva U, Andrés-Pueyo A. Psychometric properties of the Spanish adaptation of the Five Factor Personality Inventory. Eur J Psychol Assess 2001;17(2):145–53. CrossRefexternal icon

Hendriks AJ, Hofstee WK, Raad BD. The five-factor personality inventory (FFPI). Pers Individ Dif 1999;27(2):307–25. CrossRefexternal icon

Somer O, Korkmaz M, Tatar A. Bes Faktör Kisilik Envanteri’nin Gelistirilmesi-I: Ôlçek ve Alt Ôlçeklerin Olugturulmasi. Turk Psikol Derg 2002;17(49):21–33.

Araz A, Erkus A. Duygu Disavurum Tarzlarinin Kavramsallastirilmasi ve Ölçümü: Bir Envanter Gelistirme Çalismasi. Turk Psikol Derg 2014;29(74):50–61.

Fruyt FD, McCrae RR, Szirmák Z, Nagy J. The five-factor personality inventory as a measure of the five-factor model: Belgian, American, and Hungarian comparisons with the NEO-PI-R. Assessment 2004;11(3):207–15. CrossRefexternal icon PubMedexternal icon

Sharma S, Deller J, Biswal R, Mandal MK. Emotional intelligence: factorial structure and construct validity across cultures. Int J Cross Cult Manag 2009;9(2):217–36. CrossRefexternal icon

Inner Strength Questionnaire

Roux G, Lewis K, Younger J, Dingley C. Development and testing of the inner strength questionnaire. J Cult Divers 2003;10(1):4–5. PubMedexternal icon

Lewis KL, Roux G. Psychometric testing of the Inner Strength Questionnaire: women living with chronic health conditions. Appl Nurs Res 2011;24(3):153–60. CrossRefexternal icon PubMedexternal icon

Interpersonal Support Evaluation List

Brookings JB, Bolton B. Confirmatory factor analysis of the Interpersonal Support Evaluation List. Am J Community Psychol 1988;16(1):137–47. CrossRefexternal icon PubMedexternal icon

Schonfeld IS, Ruan D. Occupational stress and preemployment measures of depressive symptoms: The case of teachers. J Soc Behav Pers 1991;6(7):95.

Bates DS. Cross-sectional and longitudinal analyses of two measures of social support among the homeless [dissertation]. Buffalo (NY): State University of New York at Buffalo; 1995.

Bates DS, Toro PA. Developing measures to assess social support among homeless and poor people. J Community Psychol 1999;27(2):137–56. CrossRefexternal icon

McColl MA, Skinner H. Assessing inter- and intrapersonal resources: social support and coping among adults with a disability. Disabil Rehabil 1995;17(1):24–34. CrossRefexternal icon PubMedexternal icon

Rintala DH. Predictive validity of social support relative to psychological well-being in men with spinal cord injury. Rehabil Psychol 2013;58(4):422–8. CrossRefexternal icon PubMedexternal icon

Bastardo YM, Kimberlin CL. Relationship between quality of life, social support and disease-related factors in HIV-infected persons in Venezuela. AIDS Care 2000;12(5):673–84. CrossRefexternal icon PubMedexternal icon

Delistamati E, Samakouri MA, Davis EA, Vorvolakos T, Xenitidis K, Livaditis M. Interpersonal Support Evaluation List (ISEL) — college version: validation and application in a Greek sample. Int J Soc Psychiatry 2006;52(6):552–60. CrossRefexternal icon PubMedexternal icon

Szlachta E. The adaptation and preliminary validation of the Polish version of the Interpersonal Support Evaluation List (ISEL). Prz Psychol 2009;52(4):433–51.

Baumann M, Lurbe K, Leandro M-E, Chau N. Life satisfaction of two-year post-stroke survivors: effects of socio-economic factors, motor impairment, Newcastle stroke-specific quality of life measure and World Health Organization quality of life: bref of informal caregivers in Luxembourg and a rural area in Portugal. Cerebrovasc Dis 2012;33(3):219–30. CrossRefexternal icon PubMedexternal icon

Mendoza F, Bastardo Y. PIH68 quality of life and social support among college students in Venezuela. Value Health 2012;15(4):A204. CrossRefexternal icon

Moretti M, Simonelli A, Melloni M, Ronconi L. Interpersonal Support Evaluation List (ISEL): validation and application in an Italian sample. Psicol Soc 2012;(3):447–57. CrossRefexternal icon

Merz EL, Roesch SC, Malcarne VL, Penedo FJ, Llabre MM, Weitzman OB, et al. Validation of Interpersonal Support Evaluation List-12 (ISEL-12) scores among English- and Spanish-speaking Hispanics/Latinos from the HCHS/SOL Sociocultural Ancillary Study. Psychol Assess 2014;26(2):384–94. CrossRefexternal icon PubMedexternal icon

Sacco E, Bientinesi R, Marangi F, D’Addessi A, Racioppi M, Gulino G, et al. [Overactive bladder syndrome: the social and economic perspective]. Urologia 2011;78(4):241–56. Italian. CrossRefexternal icon PubMedexternal icon

Life Attitude Profile

Reker G, Peacock E. The Life Attitude Profile (LAP): a multidimensional instrument for assessing attitudes towards life. Can J Behav Sci 1981;13(3):264–73. CrossRefexternal icon

Anagnostopoulos F, Slater J, Fitzsimmons D, Kolokotroni P. Exploring global meaning in Greek breast cancer patients: validation of the Life Attitude Profile — Revised (LAP-R). Psychooncology 2011;20(4):419–27. CrossRefexternal icon PubMedexternal icon

Mental Toughness Questionnaire (MTQ48)

Clough P, Earle K, Strycharczyk D. Developing resilience through coaching: MTQ48. In: Passmore J, editor. Psychometrics in coaching: using psychological and psychometric tools for development. London (GB): Kogan Page; 2008. p. 208–23.

Gucciardi DF, Hanton S, Mallett CJ. Progressing measurement in mental toughness: a case example of the Mental Toughness Questionnaire 48. Sport Exerc Perform Psychol 2012;1(3):194–214. CrossRefexternal icon

Sheard M, Golby J, Van Wersch A. Progress toward construct validation of the Sports Mental Toughness Questionnaire (SMTQ). Eur J Psychol Assess 2009;25(3):186–93. CrossRefexternal icon

Perry JL, Clough PJ, Crust L, Earle K, Nicholls AR. Factorial validity of the mental toughness questionnaire-48. Pers Individ Dif 2013;54(5):587–92. CrossRefexternal icon

Norbeck Social Support Questionnaire

Norbeck JS, Lindsey AM, Carrieri VL. The development of an instrument to measure social support. Nurs Res 1981;30(5):264–9. CrossRefexternal icon PubMedexternal icon

La Roche MJ, Turner C, Kalick SM. Latina mothers and their toddlers’ behavioral difficulties. Hisp J Behav Sci 1995;17(3):375–84. CrossRefexternal icon

Post Traumatic Growth Inventory

Tedeschi RG, Calhoun LG. The Posttraumatic Growth Inventory: measuring the positive legacy of trauma. J Trauma Stress 1996;9(3):455–71. CrossRefexternal icon PubMedexternal icon

Mystakidou K, Tsilika E, Parpa E, Kyriakopoulos D, Malamos N, Damigos D. Personal growth and psychological distress in advanced breast cancer. Breast 2008;17(4):382–6. CrossRefexternal icon PubMedexternal icon

Leiva-Bianchi M, Araneda A. Confirmatory factor analysis of the Post-Traumatic Growth Inventory after the Chilean earthquake. J Loss Trauma 2015;20(4):297–305. CrossRefexternal icon

Mack J, Herrberg M, Hetzel A, Wallesch CW, Bengel J, Schulz M, et al. The factorial and discriminant validity of the German version of the Post-traumatic Growth Inventory in stroke patients. Neuropsychol Rehabil 2015;25(2):216–32. CrossRefexternal icon PubMedexternal icon

Saltzman BM, Frank JM, Slikker W, Fernandez JJ, Cohen MS, Wysocki RW. Clinical outcomes of proximal row carpectomy versus four-corner arthrodesis for post-traumatic wrist arthropathy: a systematic review. J Hand Surg Eur Vol 2015;40(5):450–7. CrossRefexternal icon PubMedexternal icon

Psychological Capital Questionnaire

Avey JB, Luthans F, Jensen SM. Psychological capital: a positive resource for combating employee stress and turnover. Hum Resour Manage 2009;48(5):677–93. CrossRefexternal icon

Luthans F, Youssef CM. Positive workplaces. Oxford handbook of positive psychology, 2nd edition. Oxford library of psychology. New York (NY): Oxford University Press; 2009. p. 579–88.

Wang Y, Chang Y, Fu J, Wang L. Work-family conflict and burnout among Chinese female nurses: the mediating effect of psychological capital. BMC Public Health 2012;12(1):915. CrossRefexternal icon PubMedexternal icon

Psychological Well-being Questionnaire

Ryff CD, Keyes CLM. The structure of psychological well-being revisited. J Pers Soc Psychol 1995;69(4):719–27. CrossRefexternal icon PubMedexternal icon

Resilience Scale for Adults

Friborg O, Hjemdal O, Rosenvinge JH, Martinussen M. A new rating scale for adult resilience: what are the central protective resources behind healthy adjustment? Int J Methods Psychiatr Res 2003;12(2):65–76. CrossRefexternal icon PubMedexternal icon

Friborg O, Barlaug D, Martinussen M, Rosenvinge JH, Hjemdal O. Resilience in relation to personality and intelligence. Int J Methods Psychiatr Res 2005;14(1):29–42. CrossRefexternal icon PubMedexternal icon

Friborg O, Martinussen M, Rosenvinge JH. Likert-based vs. semantic differential-based scorings of positive psychological constructs: a psychometric comparison of two versions of a scale measuring resilience. Pers Individ Dif 2006;40(5):873–84. CrossRefexternal icon

Jowkar B, Friborg O, Hjemdal O. Cross-cultural validation of the Resilience Scale for Adults (RSA) in Iran. Scand J Psychol 2010;51(5):418–25. CrossRefexternal icon PubMedexternal icon

Hjemdal O, Friborg O, Braun S, Kempenaers C, Linkowski P, Fossion P. The Resilience Scale for Adults: construct validity and measurement in a Belgian sample. Int J Test 2011;11(1):53–70. CrossRefexternal icon

Hilbig J, Viliūnienė R, Friborg O, Pakalniškienė V, Danilevičiūtė V. Resilience in a reborn nation: validation of the Lithuanian Resilience Scale for Adults (RSA). Compr Psychiatry 2015;60:126–33. CrossRefexternal icon PubMedexternal icon

Hjemdal O, Roazzi A, Dias MG, Friborg O. The cross-cultural validity of the Resilience Scale for Adults: a comparison between Norway and Brazil. BMC Psychol 2015;3(1):18. CrossRefexternal icon PubMedexternal icon

Resistance to Trauma Test

Urra Portillo J, Escorial Martín S, Martínez Arias R. Development and psychometric properties of the Resistance to Trauma Test (TRauma). Psicothema 2014;26(2):215–21. CrossRefexternal icon PubMedexternal icon

Response to Stressful Experiences Scale

Johnson DC, Polusny MA, Erbes CR, King D, King L, Litz BT, et al. Development and initial validation of the Response to Stressful Experiences Scale. Mil Med 2011;176(2):161–9. CrossRefexternal icon PubMedexternal icon

Sense of Coherence Scale

Eriksson M, Lindström B. Validity of Antonovsky’s sense of coherence scale: a systematic review. J Epidemiol Community Health 2005;59(6):460–6. CrossRefexternal icon PubMedexternal icon

Solution-Focused Inventory

Grant AM, Cavanagh MJ, Kleitman S, Spence G, Lakota M, Yu N. Development and validation of the Solution-Focused Inventory. J Posit Psychol 2012;7(4):334–48. CrossRefexternal icon

Yang H, Hai T. Reliability and validity of the Chinese version of the solution‐focused inventory in college students. J Multicult Couns Devel 2015;43(4):305–15. CrossRefexternal icon

Values in Action

Macdonald C, Bore M, Munro D. Values in action scale and the big 5: an empirical indication of structure. J Res Pers 2008;42(4):787–99. CrossRefexternal icon

Azañedo CM, Fernández-Abascal EG, Barraca J. Character strengths in Spain: validation of the Values in Action Inventory of Strengths (VIA-IS) in a Spanish sample. Clin Salud 2014;25(2):123–30. CrossRefexternal icon

Choubisa R, Singh K. Psychometrics encompassing VIA-IS: a comparative cross cultural analytical and referential reading. J Indian Acad Appl Psychol 2011;37(2):325–32.

Duan W, Bai Y, Tang X, Siu PY, Ho S. Virtues and positive mental health. Ment Health (Lond) 2012;38(2):1–8.

Duan W, Ho SM, Yu B, Tang X, Zhang Y, Li T, et al. Factor structure of the Chinese Virtues Questionnaire. Res Soc Work Pract 2012;22(6):680–8. CrossRefexternal icon

Khumalo IP, Wissing MP, Temane QM. Exploring the validity of the Values-In-Action Inventory of Strengths (VIA-IS) in an African context. J Psychol Afr 2008;18(1):133–42. CrossRefexternal icon

Littman-Ovadia H. The effect of client attachment style and counselor functioning on career exploration. J Vocat Behav 2008;73(3):434–9. CrossRefexternal icon

Otake K, Shimai S, Ikemi A, Utsuki N, Peterson C, Seligman ME. [Development of the Japanese version of the Values In Action Inventory of Strengths (VIA-IS)]. Shinrigaku Kenkyu 2005;76(5):461–7. CrossRefexternal icon PubMedexternal icon

Top