Search

BackgroundPeople often search the internet to obtain health-related information not only for themselves but also for family members and, in particular, their children. However, for a minority of parents, such searches may become excessive and distressing. Little is known about excessive web-based searching by parents for information regarding their children’s health. ObjectiveThis study aimed to develop and validate an instrument designed to assess parents' web-based health information searching behavior, the Children’s Health Internet Research, Parental Inventory (CHIRPI). MethodsA pilot survey was used to establish the instrument (21 items). CHIRPI was validated online in a second sample (372/384, 96.9% mothers; mean age 32.7 years, SD 5.8). Item analyses, an exploratory factor analysis (EFA), and correlations with parents’ perception of their children’s health-related vulnerability (Child Vulnerability Scale, CVS), parental health anxiety (modified short Health Anxiety Inventory, mSHAI), and parental cyberchondria (Cyberchondria Severity Scale, CSS-15) were calculated. A subset of participants (n=73) provided retest data after 4 weeks. CHIRPI scores (total scores and subscale scores) of parents with a chronically ill child and parents who perceived their child to be vulnerable (CVS+; CVS>10) were compared with 2×2 analyses of variances (ANOVAs) with the factors Child’s Health Status (chronically ill vs healthy) and perceived vulnerability (CVS+ vs CVS−). ResultsCHIRPI’s internal consistency was standardized alpha=.89. The EFA identified three subscales: Symptom Focus (standardized alpha=.87), Implementing Advice (standardized alpha=.74) and Distress (standardized alpha=.89). The retest reliability of CHIRPI was measured as rtt=0.78. CHIRPI correlated strongly with CSS-15 (r=0.66) and mSHAI (r=0.39). The ANOVAs comparing the CHIRPI total score and the subscale scores for parents having a chronically ill child and parents perceiving their child as vulnerable revealed the main effects for perceiving one’s child as vulnerable but not for having a chronically ill child. No interactions were found. This pattern was observed for the CHIRPI total score (η2=0.053) and each subscale (Symptom Focus η2=0.012; Distress η2=0.113; and Implementing Advice η2=0.018). ConclusionsThe psychometric properties of CHIRPI are excellent. Correlations with mSHAI and CSS-15 indicate its validity. CHIRPI appears to be differentially sensitive to excessive searches owing to parents perceiving their child’s health to be vulnerable rather than to higher informational needs of parents with chronically ill children. Therefore, it may help to identify parents who search excessively for web-based health information. CHIRPI (and, in particular, the Distress subscale) seems to capture a pattern of factors related to anxious health-related cognitions, emotions, and behaviors of parents, which is also applied to their children.

BackgroundThe number of mobile health apps (MHAs), which are developed to promote healthy behaviors, prevent disease onset, manage and cure diseases, or assist with rehabilitation measures, has exploded. App store star ratings and descriptions usually provide insufficient or even false information about app quality, although they are popular among end users. A rigorous systematic approach to establish and evaluate the quality of MHAs is urgently needed. The Mobile App Rating Scale (MARS) is an assessment tool that facilitates the objective and systematic evaluation of the quality of MHAs. However, a German MARS is currently not available. ObjectiveThe aim of this study was to translate and validate a German version of the MARS (MARS-G). MethodsThe original 19-item MARS was forward and backward translated twice, and the MARS-G was created. App description items were extended, and 104 MHAs were rated twice by eight independent bilingual researchers, using the MARS-G and MARS. The internal consistency, validity, and reliability of both scales were assessed. Mokken scale analysis was used to investigate the scalability of the overall scores. ResultsThe retranslated scale showed excellent alignment with the original MARS. Additionally, the properties of the MARS-G were comparable to those of the original MARS. The internal consistency was good for all subscales (ie, omega ranged from 0.72 to 0.91). The correlation coefficients (r) between the dimensions of the MARS-G and MARS ranged from 0.93 to 0.98. The scalability of the MARS (H=0.50) and MARS-G (H=0.48) were good. ConclusionsThe MARS-G is a reliable and valid tool for experts and stakeholders to assess the quality of health apps in German-speaking populations. The overall score is a reliable quality indicator. However, further studies are needed to assess the factorial structure of the MARS and MARS-G.

Organizational implementation climate is an important construct in implementation research to describe to what extent implementation is expected, supported, and rewarded. Efforts in bridging the research-practice gap by implementing evidence-based practice (EBP) can benefit from consideration of implementation climate. The Implementation Climate Scale (ICS) is a psychometrically strong measure assessing employees' perceptions of the implementation climate. The present cross-sectional study aimed at providing a German translation and investigating its psychometric properties. The translation followed standard procedures for adapting psychometric instruments. German psychotherapists (N = 425) recruited online completed the ICS, the Evidence Based Practice Attitudes Scale (EBPAS-36D) and the Intention Scale for Providers (ISP). We conducted standard item and reliability analyses. Factorial validity was assessed by comparing an independent cluster model of Confirmatory Factorial Analysis (ICM-CFA), a Bifactor CFA, a Second-order CFA and an (Bifactor) Exploratory Structural Equation Model (ESEM). Measurement invariance was tested using multiple-group CFA and ESEM, convergent validity with correlation analysis between the ICS and the ISP subjective norms subscale (ISP-D-SN). The mean item difficulty was pi = .47, mean inter-item correlation r = .34, and mean item-total correlation ritc = .55. The total scale (ω = 0.91) and the subscales (ω = .79-.92) showed acceptable to high internal consistencies. The model fit indices were comparable and acceptable (Second-order CFA: RMSEA [90% CI] = .077 [.069; .085], SRMR = .078, CFI = .93). Multiple-group CFA and ESEM indicated scalar measurement invariance across gender and presence of a psychotherapy license. Psychotherapists in training reported higher educational support for EBP than licensed psychotherapists (T = 2.09, p = .037, d = 0.25). The expected high correlation between the ICS and the ISP-D-SN was found (r = .59, p

In this study, we investigated whether the use of smartphone games while reading a text reduces learning performance or reading speed. We also examined whether this is affected by push notifications. Ninety-three students were randomly assigned to three learning conditions. In the gaming group (G), participants played a game app for 20 s at 2-min intervals while reading. In one subgroup, the game app sent push notifications (GN+); in the other subgroup, no notifications (GN-) were sent. In the control group (C), participants did not play a game. After the reading, participants took a multiple-choice quiz. We compared quiz scores and reading times of the groups (G) and (C) and within the gaming group (GN+, GN-) and observed no differences. Since the statistical non-significance of these tests does not entail the absence of an effect, we conducted equivalence tests, which did not demonstrate equivalence either. The experiment ensured high internal validity, yet remained inconclusive. Reasons for the similarity of performance in all groups could be non-specific exercise effects (all participants owned a smartphone), low similarity between the tasks, low variance of participants' ability and motivation (high achieving, low ADHD scores) or low game complexity. Future research should address these questions.

Background: The ICD‐11 classification of chronic pain comprises seven categories, each further subdivided. In total, it contains over 100 diagnoses each based on 5–7 criteria. To increase diagnostic reliability, the Classification Algorithm for Chronic Pain in the ICD‐11 (CAL‐CP) was developed. The current study aimed to evaluate the CAL‐CP regarding the correctness of assigned diagnoses, utility and ease of use. Methods: In an international online study, n = 195 clinicians each diagnosed 4 out of 8 fictitious patients. The clinicians interacted via chat with the virtual patients to collect information and view medical histories and examination findings. The patient cases differed in complexity: simple patients had one chronic pain diagnosis; complex cases had two. In a 2 × 2 repeated‐measures design with the factors tool (algorithm/standard browser) and diagnostic complexity (simple/complex), clinicians used either the algorithm or the ICD‐11 browser for their diagnoses. After each case, clinicians indicated the pain diagnoses and rated the diagnostic process. The correctness of the assigned diagnoses and the ratings of the algorithm's utility and ease of use were analysed. Results: The use of the algorithm resulted in more correct diagnoses. This was true for chronic primary and secondary pain diagnoses. The clinicians preferred the algorithm over the ICD‐11 browser, rating it easier to work with and more useful. Especially novice users benefited from the algorithm. Conclusions: The use of the algorithm increases the correctness of the diagnoses for chronic pain and is well accepted by clinicians. The CAL‐CP's use should be considered in routine care and research contexts. Significance Statement: The ICD‐11 has come into effect in January 2022. Clinicians and researchers will soon begin using the new classification of chronic pain. To facilitate clinicians training and diagnostic accuracy, a classification algorithm was developed. The paper investigates whether clinicians using the algorithm—as opposed to the generic tools provided by the WHO—reach more correct diagnoses when they diagnose standardized patients and how they rate the comparative utility of the diagnostic instruments available. [ABSTRACT FROM AUTHOR]

Zusammenfassung: Hintergrund: Die Wahrnehmung des Klimawandels als Gefahr kann zu psychischer Belastung in Form von Öko-Angst führen. Erste Erkenntnisse weisen darauf hin, dass Öko-Angst im Zusammenhang mit weiteren psychischen Belastungen wie anderen Ängsten, Depression und Stress steht. Ziel dieser Studie war es, diesen Zusammenhang im deutschsprachigen Raum zu untersuchen. Material und Methoden: Eine deutsche Version der Hogg Eco-Anxiety Skala (HEAS-13) wurde in einem mehrstufigen Übersetzungsvorgehen erarbeitet und anhand einer deutschsprachigen Stichprobe (N = 256) validiert. Ergebnisse: Die vierfaktorielle Struktur des Originalfragebogens konnte in einer konfirmatorischen Faktorenanalyse als passendes Faktorenmodell bestätigt werden. Der Fragebogen zeigte eine hohe interne Konsistenz und eine gute Retest-Reliabilität sowie eine hohe diskriminante bzw. konvergente Validität. Die HEAS-13 korrelierte hoch mit einem Fragebogen zur Erfassung der Klimawandelangst (Climate Change Anxiety Skala), und in der Literatur beschriebene Zusammenhänge zwischen Öko-Angst und pro-ökologischen Werten, politischer Orientierung und Geschlecht konnten mit der deutschen HEAS-13 reproduziert werden. Öko-Angst korrelierte zudem mit Depressivität, Angst und Stresserleben. Ein allgemeiner Alterseffekt wurde nicht gefunden. Diskussion und Schlussfolgerung: Zusammenfassend kann festgestellt werden, dass die erarbeitete deutsche Version der HEAS-13 ein valides und reliables Messinstrument darstellt. Die Zusammenhänge zwischen Öko-Angst und Depression, anderen Ängsten und Stress zeigen die potentielle klinische Bedeutung von erhöhter Öko-Angst. Zukünftige Forschung sollte diesen Zusammenhang weiter untersuchen, um dessen Rolle bei der Entstehung und Aufrechterhaltung psychischer Belastungen zu verstehen. [ABSTRACT FROM AUTHOR]