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/pcd18.200323.

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Appendix

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

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